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


1

MonteCarlo and Analytical Methods for Forced Outage Rate Calculations of Peaking Units  

E-Print Network [OSTI]

(unavailability) of such units. This thesis examines the representation of peaking units using a four-state model and performs the analytical calculations and Monte Carlo simulations to examine whether such a model does indeed represent the peaking units...

Rondla, Preethi 1988-

2012-10-26T23:59:59.000Z

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

Total and Peak Energy Consumption Minimization of Building HVAC Systems Using Model Predictive Control  

E-Print Network [OSTI]

combination of the total energy consumption and the peakalso reduces the total energy consumption of the occupancyTotal and Peak Energy Consumption Minimization of Building

Maasoumy, Mehdi; Sangiovanni-Vincentelli, Alberto

2012-01-01T23:59:59.000Z

4

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]

5

Refinery Outages: Fall 2014  

Reports and Publications (EIA)

This report examines refinery outages planned for Fall 2014 and the potential implications for available refinery capacity, petroleum product markets and supply of gasoline and middle distillate fuel oil (diesel, jet fuel, and heating oil). EIA believes that dissemination of such analyses can be beneficial to market participants who may otherwise be unable to access such information.

2014-01-01T23:59:59.000Z

6

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

7

FPL's Christmas 1991 transmission outages  

SciTech Connect (OSTI)

A record number of contamination related outages occurred on FPL transmission lines during Christmas of 1991 and resulted in an investigation of inservice insulator performance. The field investigation process used was enhanced by recent improvements in outage data recording. Also used in the analysis were weather information, the results of recently completed accelerated aging tests of polymers, and specially conducted tests on the effects of weathering steel stain on porcelain insulators. Specific insulator problems were identified and actions taken to reduce the possibility of recurrence.

Burnham, J.T.; Busch, D.W.; Renowden, J.D. (Florida Power Light Co., Juno Beach, FL (United States). Transmission Line Dept.)

1993-10-01T23:59:59.000Z

8

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

9

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

SciTech Connect (OSTI)

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

10

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

11

North American Electric Reliability Council Outage Announcement |  

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

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

12

GUIDELINES FOR IMPLEMENTATION OF AN ADVANCED OUTAGE CONTROL CENTER TO IMPROVE OUTAGE COORDINATION, PROBLEM RESOLUTION, AND OUTAGE RISK MANAGEMENT  

SciTech Connect (OSTI)

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 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 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. Managing NPP outages is a complex and difficult task due to the large number of maintenance and repair activities that are accomplished in a short period of time. 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. It is a difficult task to maintain current the information related to outage progress and discovered conditions. Several advanced communication and collaboration technologies have shown promise for facilitating the information flow into, across, and out of the OCC. The use of these technologies will allow information to be shared electronically, providing greater amounts of real-time information to the decision makers and allowing OCC coordinators to meet with supporting staff remotely. Passively monitoring status electronically through advances in the areas of mobile worker technologies, computer-based procedures, and automated work packages will reduce the current reliance on manually reporting progress. The use of these technologies will also improve the knowledge capture and management capabilities of the organization. The purpose of this research is to improve management of NPP outages through the development of an advanced outage control center (AOCC) that is specifically designed to maximize the usefulness of communication and collaboration technologies for outage coordination and problem resolution activities. This technical report for industry implementation outlines methods and considerations for the establishment of an AOCC. This report provides a process for implementation of a change management plan, evaluation of current outage processes, the selection of technology, and guidance for the implementation of the selected technology. Methods are presented for both adoption of technologies within an existing OCC and for a complete OCC replacement, including human factors considerations for OCC design and setup.

Shawn St. Germain; Ronald Farris; April M. Whaley; Heather Medema; David Gertman

2014-09-01T23:59:59.000Z

13

Systems and Services Outage Notification Policy  

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

14

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

15

August 14, 2003 Power Outages … Announcement  

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

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

16

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

17

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

18

Contingency Analysis of Cascading Line Outage Events  

SciTech Connect (OSTI)

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

19

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

20

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

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

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

22

Potomac River Project Outage Schedule Clarification | Department of Energy  

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

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

23

Peak Oil  

Science Journals Connector (OSTI)

Wissenschaftliche Voraussagen deuten auf Peak Oil, das Maximum globaler Erdlfrderung, in unserer ... der demokratischen Systeme fhren. Psychoanalytische Betrachtung darf Peak Oil fr die Zivilisation als e...

Dr. Manuel Haus; Dr. med. Christoph Biermann

2013-03-01T23:59:59.000Z

24

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

25

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

26

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

27

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

28

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

29

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

30

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

31

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

32

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

33

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

34

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

35

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

36

Potomac River Project Outage Schedule Clarification | Department of Energy  

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

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

37

North American Electric Reliability Council Power Outage Update |  

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

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

38

Outage management and health physics issue, 2006  

SciTech Connect (OSTI)

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

39

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

SciTech Connect (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 1980s. 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

40

RESOLVED: Projectb filesystem outage July 9, 2012  

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

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

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.

42

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

43

Outage Capacity and Code Design for Dying Channels  

E-Print Network [OSTI]

. The outage exponents are also studied to reveal how fast the outage probability improves over the number of sub-channels. Besides the information-theoretical results, we also study a practical coding scheme for the dying binary erasure channel (DBEC), which...

Zeng, Meng

2012-10-19T23:59:59.000Z

44

Outage Probability Analysis for Asynchronous Cognitive Radio Networks  

E-Print Network [OSTI]

and the secondary network co-exist. Solid lines and dashed lines represent the data transmissionOutage Probability Analysis for Asynchronous Cognitive Radio Networks Chulhee Jang and Jae Hong Lee network in a spectrum sharing asynchronous cognitive radio (CR) network. We analyze the outage probability

Lee, Jae Hong

45

Homeowners: Respond to Power Outages | Department of Energy  

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

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

46

Peak Oil  

Science Journals Connector (OSTI)

At the start of the new millennium, the expression Peak Oil was unknown. Nevertheless, a discussion about when the worlds rate of oil production would reach its maximum had already ... . King Hubbert presented...

Kjell Aleklett

2012-01-01T23:59:59.000Z

47

Technology Integration Initiative In Support of Outage Management  

SciTech Connect (OSTI)

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 1980s. 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

48

Economic Benefits of Increasing Electric Grid Resilience to Weather Outages  

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

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

49

SAMPLE RESULTS FROM MCU SOLIDS OUTAGE  

SciTech Connect (OSTI)

Savannah River National Laboratory (SRNL) has received several solid and liquid samples from MCU in an effort to understand and recover from the system outage starting on April 6, 2014. SRNL concludes that the presence of solids in the Salt Solution Feed Tank (SSFT) is the likely root cause for the outage, based upon the following discoveries ? A solids sample from the extraction contactor #1 proved to be mostly sodium oxalate ? A solids sample from the scrub contactor#1 proved to be mostly sodium oxalate ? A solids sample from the Salt Solution Feed Tank (SSFT) proved to be mostly sodium oxalate ? An archived sample from Tank 49H taken last year was shown to contain a fine precipitate of sodium oxalate ? A solids sample from the extraction contactor #1 drain pipe from extraction contactor#1 proved to be mostly sodium aluminosilicate ? A liquid sample from the SSFT was shown to have elevated levels of oxalate anion compared to the expected concentration in the feed Visual inspection of the SSFT indicated the presence of precipitated or transferred solids, which were likely also in the Salt Solution Receipt Tank (SSRT). The presence of the solids coupled with agitation performed to maintain feed temperature resulted in oxalate solids migration through the MCU system and caused hydraulic issues that resulted in unplanned phase carryover from the extraction into the scrub, and ultimately the strip contactors. Not only did this carryover result in the Strip Effluent (SE) being pushed out of waste acceptance specification, but it resulted in the deposition of solids into several of the contactors. At the same time, extensive deposits of aluminosilicates were found in the drain tube in the extraction contactor #1. However it is not known at this time how the aluminosilicate solids are related to the oxalate solids. The solids were successfully cleaned out of the MCU system. However, future consideration must be given to the exclusion of oxalate solids into the MCU system. There were 53 recommendations for improving operations recently identified. Some additional considerations or additional details are provided below as recommendations. ? From this point on, IC-Anions analyses of the DSSHT should be part of the monthly routine analysis in order to spot negative trends in the oxalate leaving the MCU system. Care must be taken to monitor the oxalate content to watch for sudden precipitation of oxalate salts in the system. ? Conduct a study to optimize the cleaning strategy at ARP-MCU through decreasing the concentration or entirely eliminating the oxalic acid. ? The contents of the SSFT should remain unagitated. Routine visual observation should be maintained to ensure there is not a large buildup of solids. As water with agitation provided sufficient removal of the solids in the feed tank, it should be considered as a good means for dissolving oxalate solids if they are found in the future. ? Conduct a study to improve prediction of oxalate solubility in salt batch feed materials. As titanium and mercury have been found in various solids in this report, evaluate if either element plays a role in oxalate solubility during processing. ? Salt batch characterization focuses primarily on characterization and testing of unaltered Tank 21H material; however, non-typical feeds are developed through cleaning, washing, and/or sump transfers. As these solutions are processed through MCU, they may precipitate solids or reduce performance. Salt batch characterization and testing should be expanded to encompass a broader range of feeds that may be processed through ARPMCU.

Peters, T.; Washington, A.; Oji, L.; Coleman, C.; Poirier, M.

2014-09-22T23:59:59.000Z

50

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

Broader source: Energy.gov [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...

51

Number and propagation of line outages in cascading events in electric power transmission systems  

E-Print Network [OSTI]

Number and propagation of line outages in cascading events in electric power transmission systems of transmission lines. We estimate from observed utility data how transmission line outages propagate, and obtain of transmission lines. The multiple mechanisms involved these cascading outages are many and varied, and the power

Dobson, Ian

52

The Approximation of Outage Probability and the Trade-off between Capacity and Diversity for the  

E-Print Network [OSTI]

line channel model in [5]) at high SNR, and give approximations of the outage probability at lowThe Approximation of Outage Probability and the Trade-off between Capacity and Diversity of the equivalent FIR channel filter. The error probability is bounded by the outage probability and the error

Scharf, Louis

53

On PMU Location Selection for Line Outage Detection in Wide-area Transmission Networks  

E-Print Network [OSTI]

1 On PMU Location Selection for Line Outage Detection in Wide-area Transmission Networks Yue Zhao locations to collect voltage phase angle measurements for detecting line outages in wide-area transmission measurements. Index Terms--Phasor measurement unit, location selection, outage detection, transmission networks

Zhao, Yue

54

Onsite Wastewater Treatment Systems: Responding to Power Outages and Floods  

E-Print Network [OSTI]

People and the environment can be harmed if a home's onsite wastewater treatment system does not work properly after a flood or power outage. This publication explains the steps to take after such an event to get the system back into service. 4 pp...

Lesikar, Bruce J.; Mechell, Justin; Alexander, Rachel

2008-10-23T23:59:59.000Z

55

Preventing power outages Power system contingency analysis on the GPU  

E-Print Network [OSTI]

problem. Moreover, the power system has to keep functioning properly even when a transmission line failsPreventing power outages Power system contingency analysis on the GPU To provide electricity generators, nuclear power plants, wind turbines, etc.) and a network of lines and cables to transmit

Vuik, Kees

56

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

SciTech Connect (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

57

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

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

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

58

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

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

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

59

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

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

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

60

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

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

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

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

HPSS Outage Tue Mar 19 - Fri Mar 22  

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

62

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

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

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.

63

Notification of Planned 230kV Outage at Potomac River Generating Station  

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

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.

64

Repair duration effects on distribution system reliability indices and customer outage costs.  

E-Print Network [OSTI]

??The distribution system is part of the electric power system that links the bulk transmission system and the individual customers. Approximately 80 percent of outages (more)

Shakya, Binendra

2013-01-01T23:59:59.000Z

65

Desert Peak EGS Project  

Broader source: Energy.gov [DOE]

Desert Peak EGS Project presentation at the April 2013 peer review meeting held in Denver, Colorado.

66

Annual Steam System Maintenance Outage (2014) Beginning on Sunday, June 8th  

E-Print Network [OSTI]

Annual Steam System Maintenance Outage (2014) Beginning on Sunday, June 8th at 12:00pm (Noon), the Central Utility Plant (CUP), which supplies steam service to over 100 buildings on the Newark campus, will be shut down for the annual Steam System Maintenance Outage. This effort is necessary each year to ensure

Firestone, Jeremy

67

Outage Detection in Power Distribution Networks with Optimally-Deployed Power Flow Sensors  

E-Print Network [OSTI]

Outage Detection in Power Distribution Networks with Optimally-Deployed Power Flow Sensors Yue Zhao deployed real-time power flow sensors and that of load estimates via Advanced Metering Infrastructure (AMI within each subtree only the sensors at its root and on its boundary are used. Outage detection

Zhao, Yue

68

Outage Detection via Real-time Social Stream Analysis: Leveraging the Power of Online Complaints  

E-Print Network [OSTI]

disruptions. Each is described below with their ac- companying defects. Internal monitoring systems. NetflixOutage Detection via Real-time Social Stream Analysis: Leveraging the Power of Online Complaints documents the design and development of an outage detection system for the online services provided

Dekhtyar, Alexander

69

Market Assessment of Planned Refinery Outages March … 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.

70

Microsoft Word - 112706 Final Outage Letter PUBLIC.doc  

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

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

71

Economics of Peak Oil  

Science Journals Connector (OSTI)

Abstract Peak oil refers to the future decline in world production of crude oil and the accompanying potentially calamitous effects. The peak oil literature typically rejects economic analysis. This article argues that economic analysis is indeed appropriate for analyzing oil scarcity because standard economic models can replicate the observed peaks in oil production. Moreover, the emphasis on peak oil is misplaced as peaking is not a good indicator of scarcity, peak oil techniques are overly simplistic, the catastrophes predicted by the peak oil literature are unlikely, and the literature does not contribute to correcting identified market failures. Efficiency of oil markets could be improved by instead focusing on remedying market failures such as excessive private discount rates, environmental externalities, market power, insufficient innovation incentives, incomplete futures markets, and insecure property rights.

S.P. Holland

2013-01-01T23:59:59.000Z

72

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

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

- 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

73

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

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

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

74

Saving Power at Peak Hours (LBNL Science at the Theater)  

ScienceCinema (OSTI)

California needs new, responsive, demand-side energy technologies to ensure that periods of tight electricity supply on the grid don't turn into power outages. Led by Berkeley Lab's Mary Ann Piette, the California Energy Commission (through its Public Interest Energy Research Program) has established a Demand Response Research Center that addresses two motivations for adopting demand responsiveness: reducing average electricity prices and preventing future electricity crises. The research seeks to understand factors that influence "what works" in Demand Response. Piette's team is investigating the two types of demand response, load response and price response, that may influence and reduce the use of peak electric power through automated controls, peak pricing, advanced communications, and other strategies.

Piette, Mary Ann

2011-04-28T23:59:59.000Z

75

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

E-Print Network [OSTI]

and their neighboring lines . . . . . . . . . . . . . . 96 IX Transmission lines and their thermal limits (in MVA value) . . . . . 104 X Top 6 line outages ranked by vulnerability index and margin index . 105 XI Top 6 line outages ranked by vulnerability index based...116 120 1 CHAPTER I INTRODUCTION A. Problem Statement Electric power system is one of the biggest and most complex man-made sys- tems. It is composed of thousands of generators, transformers, transmission lines, substations, loads and extensive...

Song, Hongbiao

2009-05-15T23:59:59.000Z

76

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

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

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.

77

Reliability models of wind farms considering wind speed correlation and WTG outage  

Science Journals Connector (OSTI)

Abstract Wind speed correlation and wind turbine generator (WTG) outage are two factors affecting the reliability model of wind farms, but they are not addressed simultaneously in the existing literature. Meanwhile, WTG outage is reported to be dependent with wind speed to some extent. Therefore, the extended reliability models of wind farms incorporating both of these two factors and the dependency between WTG outage and wind speed are proposed in this paper. To consider the uncertainties and dependencies of wind speed and WTG failure, Copula method is applied to simulate correlated random variables representing for wind speed and the number of failed WTG units. Moreover, the linear apportioning technique is used to create multistate reliability models of wind farms from hourly wind power models. A number of sensitivity analyses on the modified IEEE RTS with wind power are conducted to validate the proposed reliability models for generation adequacy assessment. Case studies show that the generation adequacy indices increase with the correlation of wind speed and WTG forced outage rate (FOR). It is meaningful to point out that the effect of dependency between wind speed and WTG FOR on generation adequacy is minimal when WTG outages are independent, but it will be substantially larger when WTG outages are highly dependent. The proposed multistate reliability models of wind farms provide foundation for the reliability assessment of power systems with wind power integrated.

Fan Chen; Fangxing Li; Zhinong Wei; Guoqiang Sun; Jun Li

2015-01-01T23:59:59.000Z

78

Peak power ratio generator  

DOE Patents [OSTI]

A peak power ratio generator is described for measuring, in combination with a conventional power meter, the peak power level of extremely narrow pulses in the gigahertz radio frequency bands. The present invention in a preferred embodiment utilizes a tunnel diode and a back diode combination in a detector circuit as the only high speed elements. The high speed tunnel diode provides a bistable signal and serves as a memory device of the input pulses for the remaining, slower components. A hybrid digital and analog loop maintains the peak power level of a reference channel at a known amount. Thus, by measuring the average power levels of the reference signal and the source signal, the peak power level of the source signal can be determined.

Moyer, Robert D. (Albuquerque, NM)

1985-01-01T23:59:59.000Z

79

Status Report on the Development of Micro-Scheduling Software for the Advanced Outage Control Center Project  

SciTech Connect (OSTI)

The long-term viability of existing nuclear power plants (NPPs) in the United States (U.S.) is dependent upon a number of factors, including maintaining high capacity factors, maintaining nuclear safety, and reducing operating costs, particularly those associated with refueling outages. Refueling outages typically take 20-30 days, and for existing light water NPPs in the U.S., the reactor cannot be in operation during the outage. Furthermore, given that many NPPs generate between $1-1.5 million/day in revenue when in operation, there is considerable interest in shortening the length of refueling outages. Yet, refueling outages are highly complex operations, involving multiple concurrent and dependent activities that are difficult to coordinate. Finding ways to improve refueling outage performance while maintaining nuclear safety has proven to be difficult. The Advanced Outage Control Center project is a research and development (R&D) demonstration activity under the Light Water Reactor Sustainability (LWRS) Program. LWRS is a R&D program which works with industry R&D programs to establish technical foundations for the licensing and managing of long-term, safe, and economical operation of current NPPs. The Advanced Outage Control Center project has the goal of improving the management of commercial NPP refueling outages. To accomplish this goal, this INL R&D project is developing an advanced outage control center (OCC) that is specifically designed to maximize the usefulness of communication and collaboration technologies for outage coordination and problem resolution activities. This report describes specific recent efforts to develop a capability called outage Micro-Scheduling. Micro-Scheduling is the ability to allocate and schedule outage support task resources on a sub-hour basis. Micro-Scheduling is the real-time fine-tuning of the outage schedule to react to the actual progress of the primary outage activities to ensure that support task resources are optimally deployed with the least amount of delay and unproductive use of resources. The remaining sections of this report describe in more detail the scheduling challenges that occur during outages, how a Micro-Scheduling capability helps address those challenges, and provides a status update on work accomplished to date and the path forward.

Shawn St. Germain; Kenneth Thomas; Ronald Farris; Jeffrey Joe

2014-09-01T23:59:59.000Z

80

Desert Peak EGS Project  

Broader source: Energy.gov [DOE]

Geothermal Technologies Program 2010 Peer Review Desert Peak EGS Project, for the Engineered Geothermal Systems Demonstration Projects and Innovative Exploration Technologies. Objective to stimulate permeability in tight well 27-15 and improve connection to rest of the field; improve overall productivity or injectivity. Successful stimulation yields more production and enables more power generation.

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

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

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

82

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

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

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

83

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 /

84

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

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

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

85

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS--II: EXPRESS BRIEFS, VOL. 55, NO. 9, SEPTEMBER 2008 927 Using Transmission Line Outage Data to  

E-Print Network [OSTI]

Using Transmission Line Outage Data to Estimate Cascading Failure Propagation in an Electric Power transmission line outages recorded over nine years in an electric power system with approx- imately 200 lines. The average amount of propagation of the line outages is estimated from the data. The distribution

Dobson, Ian

86

Copyright 2008 IEEE. Reprinted from Hui Ren, Student Member, IEEE and Ian Dobson, Fellow, IEEE; Using Transmission Line Outage Data to Estimate Cascading Failure Propagation in an  

E-Print Network [OSTI]

; Using Transmission Line Outage Data to Estimate Cascading Failure Propagation in an Electric Power ON CIRCUITS AND SYSTEMS--II: EXPRESS BRIEFS, VOL. 55, NO. 9, SEPTEMBER 2008 927 Using Transmission Line Outage, IEEE, and Ian Dobson, Fellow, IEEE Abstract--We study cascading transmission line outages recorded over

87

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

E-Print Network [OSTI]

! Draft!07"18"2011! 1 Turning the Tide on Outages1 What are the true costs of implementing!data!for!the!U.S.,!which!are!generally!available!from! several!sources,!including!from!the!U.S.!DOE's!Energy!University!of!Minnesota,!he!directed!all!Infrastructure!Security,!Grid! Operations/Planning,!and!Energy!Ma

Amin, S. Massoud

88

Steam turbine maintenance and repair technology: Reducing planned-outage costs  

SciTech Connect (OSTI)

The North American Electric Reliability Council (NAERC) reported that the average loss of equivalent availability per outage for a major fossil turbine overhaul is 323,000 MW-HR. The Electric Power Research Institute (EPRI) Generation and Storage Division, is in the first phase of a major research project to reduce the duration and/or frequency of steam turbine maintenance outages. This project consists of an assessment of the current state-of-the-art turbine maintenance and repair techniques and technologies. It is based on a review of current turbine maintenance practices of the US, European, Japanese, and Australian utility industries. Emphasized are maintenance and repair activities that have the most significant impact on outage duration or frequency. Twenty-six key turbine maintenance activities and the current best techniques were identified for use by utility maintenance personnel. Overall outage durations could be reduced if the duration of these activities were shortened or if they were performed more effectively. Recommended projects for development of advanced steam turbine maintenance technology were identified. 29 refs., 46 figs., 9 tabs.

Grace, H.P.; McClintock, M. (General Physics Corp., Columbia, MD (USA)); Lamping, G. (Southwest Research Inst., San Antonio, TX (USA))

1990-04-01T23:59:59.000Z

89

Confidence intervals for state probabilities of system capacity outages and for LOLP  

E-Print Network [OSTI]

CONFID"NC. , INTERVALS FO- S'TATE PROBABILITIES OF SYSTEM CAPACITY OUTAGES AND FOR LOLP A Thcsi. , bv ATHANASIOS STASINOS Submi. tted to the Graduate College of Texas A&M University in partial fulfillment of the requirement for the degree... of MASTER OF SCIENCE December 1974 Major Subject: Electrical Engineering CONFIDENCE INTERVALS FOR STA1'E PROBABILITIES OF STSTEM CAPACITY OVTAGES AND FOR LOLP A Thesis by ATHANASIOS STASINOS Approved as to style and content by: (Chairman...

Stasinos, Athanasios

1974-01-01T23:59:59.000Z

90

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

91

winter_peak_2005.xls  

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

2b . Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, 2005 and Projected 2006 through 2010 (Megawatts and 2005 Base Year)...

92

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

93

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 worlds total production of usable energy will reach a maximum value and then begin an inexorable decline. Ninety-two percent of the worlds energy is currently derived from the non-renewable sources (oil, coal...

Warner, Kevin 1987-

2012-11-28T23:59:59.000Z

94

MATCASC: A tool to analyse cascading line outages in power grids  

E-Print Network [OSTI]

Blackouts in power grids typically result from cascading failures. The key importance of the electric power grid to society encourages further research into sustaining power system reliability and developing new methods to manage the risks of cascading blackouts. Adequate software tools are required to better analyze, understand, and assess the consequences of the cascading failures. This paper presents MATCASC, an open source MATLAB based tool to analyse cascading failures in power grids. Cascading effects due to line overload outages are considered. The applicability of the MATCASC tool is demonstrated by assessing the robustness of IEEE test systems and real-world power grids with respect to cascading failures.

Ko, Yakup; Araujo, Nuno A M; Warnier, Martijn

2013-01-01T23:59:59.000Z

95

summer_peak_2004.xls  

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

(Megawatts and 2004 Base Year) Summer Noncoincident Peak Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year ECAR FRCC MAAC MAIN...

96

winter_peak_2003.xls  

Gasoline and Diesel Fuel Update (EIA)

and 2003 Base Year) Winter Noncoincident Peak Load Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year ECAR FRCC MAAC MAIN...

97

summer_peak_2003.xls  

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

(Megawatts and 2003 Base Year) Summer Noncoincident Peak Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year ECAR FRCC MAAC MAIN...

98

winter_peak_2004.xls  

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

and 2004 Base Year) Winter Noncoincident Peak Load Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year ECAR FRCC MAAC MAIN...

99

monthly_peak_2003.xls  

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

O Form EIA-411 for 2005 Released: February 7, 2008 Next Update: October 2007 Table 3a . January Monthly Peak Hour Demand, Actual and Projected by North American Electric...

100

Outage Log  

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

1814 4:45 PST 111814 10:18 PST Project Unavailable. 111214 0:22 PST - Hopper IDLMATLABMathematica unavailable on Hopper. 111214 0:22 PST - Edison IDLMATLABMathematica...

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

Economic vulnerability to Peak Oil  

Science Journals Connector (OSTI)

Abstract Peak Oil, which refers to the maximum possible global oil production rate, is increasingly gaining attention in both science and policy discourses. However, little is known about how this phenomenon will impact economies, despite its apparent imminence and potential dangers. In this paper, we construct a vulnerability map of the U.S. economy, combining two approaches for analyzing economic systems, i.e. inputoutput analysis and social network analysis (applied to economic data). Our approach reveals the relative importance of individual economic sectors, and how vulnerable they are to oil price shocks. As such, our dual-analysis helps identify which sectors, due to their strategic position, could put the entire U.S. economy at risk from Peak Oil. For the U.S., such sectors would include Iron Mills, Fertilizer Production and Transport by Air. Our findings thus provide early warnings to downstream companies about potential trouble in their supply chain, and inform policy action for Peak Oil. Although our analysis is embedded in a Peak Oil narrative, it is just as valid and useful in the context of developing a climate roadmap toward a low carbon economy.

Christian Kerschner; Christina Prell; Kuishuang Feng; Klaus Hubacek

2013-01-01T23:59:59.000Z

102

Resolving piping analysis issues to minimize impact on installation activities during refueling outage at nuclear power plants  

SciTech Connect (OSTI)

While it is required to maintain piping code compliance for all phases of installation activities during outages at a nuclear plant, it is equally essential to reduce challenges to the installation personnel on how plant modification work should be performed. Plant betterment activities that incorporate proposed design changes are continually implemented during the outages. Supporting analysis are performed to back these activities for operable systems. The goal is to reduce engineering and craft man-hours and minimize outage time. This paper outlines how plant modification process can be streamlined to facilitate construction teams to do their tasks that involve safety related piping. In this manner, installation can proceed by minimizing on the spot analytical effort and reduce downtime to support the proposed modifications. Examples are provided that permit performance of installation work in any sequence. Piping and hangers including the branch lines are prequalified and determined operable. The system is up front analyzed for all possible scenarios. The modification instructions in the work packages is flexible enough to permit any possible installation sequence. The benefit to this approach is large enough in the sense that valuable outage time is not extended and on site analytical work is not required.

Bhavnani, D. [Public Service Electric and Gas Co., Hancocks Bridge, NJ (United States)

1996-12-01T23:59:59.000Z

103

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

104

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

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

105

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

106

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

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

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

107

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

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

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

108

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

109

Silver Peak Innovative Exploration Project  

Broader source: Energy.gov [DOE]

DOE Geothermal Peer Review 2010 - Presentation. Project objectives: Reduce the high level of risk during the early stages of geothermal project development by conducting a multi-faceted and innovative exploration and drilling program at Silver Peak. Determine the combination of techniques that are most useful and cost-effective in identifying the geothermal resource through a detailed, post-project evaluation of the exploration and drilling program.

110

TOTAL Full-TOTAL Full-  

E-Print Network [OSTI]

Conducting - Orchestral 6 . . 6 5 1 . 6 5 . . 5 Conducting - Wind Ensemble 3 . . 3 2 . . 2 . 1 . 1 Early- X TOTAL Full- Part- X TOTAL Alternative Energy 6 . . 6 11 . . 11 13 2 . 15 Biomedical Engineering 52 English 71 . 4 75 70 . 4 74 72 . 3 75 Geosciences 9 . 1 10 15 . . 15 19 . . 19 History 37 1 2 40 28 3 3 34

Portman, Douglas

111

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.

112

Economic effects of peak oil  

Science Journals Connector (OSTI)

Assuming that global oil production peaked, this paper uses scenario analysis to show the economic effects of a possible supply shortage and corresponding rise in oil prices in the next decade on different sectors in Germany and other major economies such as the US, Japan, China, the OPEC or Russia. Due to the price-inelasticity of oil demand the supply shortage leads to a sharp increase in oil prices in the second scenario, with high effects on GDP comparable to the magnitude of the global financial crises in 2008/09. Oil exporting countries benefit from high oil prices, whereas oil importing countries are negatively affected. Generally, the effects in the third scenario are significantly smaller than in the second, showing that energy efficiency measures and the switch to renewable energy sources decreases the countries' dependence on oil imports and hence reduces their vulnerability to oil price shocks on the world market.

Christian Lutz; Ulrike Lehr; Kirsten S. Wiebe

2012-01-01T23:59:59.000Z

113

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

SciTech Connect (OSTI)

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

114

Peak load management: Potential options  

SciTech Connect (OSTI)

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

115

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

116

AUTOMATED CRITICAL PEAK PRICING FIELD TESTS  

E-Print Network [OSTI]

AUTOMATED CRITICAL PEAK PRICING FIELD TESTS: 2006 PROGRAM DESCRIPTION AND RESULTS APPENDICES.................................................................................... 5 B.2. DR Automation Server User Guide

117

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"

118

Solar Photovoltaic Power Systems: Will They Reduce Utility Peaking Requirements?  

Science Journals Connector (OSTI)

...and distri-bution line losses, reductions...electricity losses in transmission and distribution...load. The vertical lines de-fine the "breakpoints...intersection of these lines with the load duration...scheduled and forced outages and the cycle time...cost and operating data used in the analysis...

R. O. MUELLER; B. K. CHA; R. F. GIESE

1981-07-10T23:59:59.000Z

119

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":""}]}

120

Peak Treatment Systems | Open Energy Information  

Open Energy Info (EERE)

Agreement Partnership Year 1998 Link to project description http:www.nrel.govnewspress199804licns.html Peak Treatment Systems is a company located in Golden, CO....

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

Measured Peak Equipment Loads in Laboratories  

E-Print Network [OSTI]

of measured equipment load data for laboratories, designersmeasured peak equipment load data from 39 laboratory spacesmeasured equipment load data from various laboratory spaces

Mathew, Paul A.

2008-01-01T23:59:59.000Z

122

Monthly Generation System Peak (pbl/generation)  

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

Generation > Generation Hydro Power Wind Power Monthly GSP BPA White Book Dry Year Tools Firstgov Monthly Generation System Peak (GSP) This site is no longer maintained. Page last...

123

Preliminary Assumptions for Natural Gas Peaking  

E-Print Network [OSTI]

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

124

Storm Peak Lab Cloud Property Validation  

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

125

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

126

LNG production for peak shaving operations  

SciTech Connect (OSTI)

LNG production facilities are being developed as an alternative or in addition to underground storage throughout the US to provide gas supply during peak gas demand periods. These facilities typically involved a small liquefaction unit with a large LNG storage tank and gas sendout facilities capable of responding to peak loads during the winter. Black and Veatch is active in the development of LNG peak shaving projects for clients using a patented mixed refrigerant technology for efficient production of LNG at a low installed cost. The mixed refrigerant technology has been applied in a range of project sizes both with gas turbine and electric motor driven compression systems. This paper will cover peak shaving concepts as well as specific designs and projects which have been completed to meet this market need.

Price, B.C.

1999-07-01T23:59:59.000Z

127

Peak Oil Futures: Same Crisis, Different Responses  

Science Journals Connector (OSTI)

Peak oil theory predicts that global oil production will soon start a terminal decline. ... resource and technology will be available to replace oil as the backbone resource of industrial society. ... understand ...

Jrg Friedrichs

2012-01-01T23:59:59.000Z

128

A perspective on the CMB acoustic peak  

E-Print Network [OSTI]

CMB angular spectrum measurements suggest a flat universe. This paper clarifies the relation between geometry and the spherical harmonic index of the first acoustic peak ($\\ell_{peak}$). Numerical and analytic calculations show that $\\ell_{peak}$ is approximately a function of $\\Omega_K/\\Omega_M$ where $\\Omega_K$ and $\\Omega_M$ are the curvature ($\\Omega_K > 0$ implies an open geometry) and mass density today in units of critical density. Assuming $\\Omega_K/\\Omega_M \\ll 1$, one obtains a simple formula for $\\ell_{peak}$, the derivation of which gives another perspective on the widely-recognized $\\Omega_M$-$\\Omega_\\Lambda$ degeneracy in flat models. This formula for near-flat cosmogonies together with current angular spectrum data yields familiar parameter constraints.

T. A. Marriage

2002-03-11T23:59:59.000Z

129

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

130

Flow shop scheduling with peak power consumption constraints  

E-Print Network [OSTI]

Mar 29, 2012 ... Flow shop scheduling with peak power consumption constraints ... Keywords: scheduling, flow shop, energy, peak power consumption, integer...

K. Fang

2012-03-29T23:59:59.000Z

131

Barge Truck Total  

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

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...

132

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.

133

Total and Peak Energy Consumption Minimization of Building HVAC Systems Using Model Predictive Control  

E-Print Network [OSTI]

inputs. The idea of modeling building thermal behavior usingThe detail of building thermal modeling is pre- sented in [Modeling and optimal control algorithm design for hvac systems in energy efficient buildings,

Maasoumy, Mehdi; Sangiovanni-Vincentelli, Alberto

2012-01-01T23:59:59.000Z

134

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":""}]}

135

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":""}]}

136

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.

137

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":""}]}

138

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":""}]}

139

Vad r 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)

Wlimaa, Peter

2013-01-01T23:59:59.000Z

140

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":""}]}

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

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":""}]}

142

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":""}]}

143

Preliminary Assumptions for Natural Gas Peaking  

E-Print Network [OSTI]

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

144

Scott McPeak Research Statement  

E-Print Network [OSTI]

Scott McPeak Research Statement My main research interest is in tools and techniques to improve software quality. In this statement I describe my past involvement in several research projects whose goal and server proxy I co-wrote with Dan Bonachea.) Our group's efforts on CCured have made it more than a mere

California at Berkeley, University of

145

AUTOMATED CRITICAL PEAK PRICING FIELD TESTS  

E-Print Network [OSTI]

AUTOMATED CRITICAL PEAK PRICING FIELD TESTS: 2006 PROGRAM DESCRIPTION AND RESULTS) for development of the DR Automation Server System This project could not have been completed without extensive: Greg Watson and Mark Lott · C&C Building Automation: Mark Johnson and John Fiegel · Chabot Space

146

MODELING THE GLOBAL PEAKS AND COOLING SY  

E-Print Network [OSTI]

of assessed building energy consumption and indoor air temperature peaks. At last, the coupling of the urban energy consumption. Building uses are an important part of the global energy use thus a good conception until the year 2100 highlight a regular increase building energy consumption and indoor At last

Boyer, Edmond

147

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":""}]}

148

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

149

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]]

150

Central peaking of magnetized gas discharges  

SciTech Connect (OSTI)

Partially ionized gas discharges used in industry are often driven by radiofrequency (rf) power applied at the periphery of a cylinder. It is found that the plasma density n is usually flat or peaked on axis even if the skin depth of the rf field is thin compared with the chamber radius a. Previous attempts at explaining this did not account for the finite length of the discharge and the boundary conditions at the endplates. A simple 1D model is used to focus on the basic mechanism: the short-circuit effect. It is found that a strong electric field (E-field) scaled to electron temperature T{sub e}, drives the ions inward. The resulting density profile is peaked on axis and has a shape independent of pressure or discharge radius. This universal profile is not affected by a dc magnetic field (B-field) as long as the ion Larmor radius is larger than a.

Chen, Francis F. [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States)] [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States); Curreli, Davide [Department of Nuclear, Plasma and Radiological Engineering, University of Illinois at Urbana Champaign, Urbana, Illinois 61801 (United States)] [Department of Nuclear, Plasma and Radiological Engineering, University of Illinois at Urbana Champaign, Urbana, Illinois 61801 (United States)

2013-05-15T23:59:59.000Z

151

Eyesight and the solar Wien peak  

Science Journals Connector (OSTI)

It is sometimes said that humans see best at yellowgreen wavelengths because they have evolved under a Sun whose blackbody spectrum has a Wien peak in the green part of the spectrum. However as a function of frequency the solar blackbody spectrum peaks in the infrared. Why did human vision not evolve toward a peak sensitivity in this range if the eye is an efficient quantum detector of photons? The puzzle is resolved if we assume that natural selection acted in such a way as to maximize the amount of energy that can be detected by the retina across a range of wavelengths (whose upper and lower limits are fixed by biological constraints). It is then found that our eyes are indeed perfectly adapted to life under a class G2 star. Extending this reasoning allows educated guesses to be made about the kind of eyesight that might have evolved in extrasolar planetary systems such as that of the red dwarf Gliese 876.

James M. Overduin

2003-01-01T23:59:59.000Z

152

Emerging WiFi Direct technique in home area networks for Smart Grid: Power consumption and outage performance  

Science Journals Connector (OSTI)

Abstract Considering the power saving potential of the emerging WiFi Direct technique, we evaluate the performance of WiFi Direct technique in Home Area Networks (HANs) for Smart Grid communication from two aspects: power consumption and downlink outage performance. By modeling the traffic intensity and the number of working devices in a dynamic HAN as a Markov chain, the power consumption of the dynamic HAN with Power Saving Mechanism (PSM) and the conventional static HAN with Continuous Active Mode (CAM) are evaluated and compared. On the other hand, the probability density function (PDF) of the signal to interference and noise ratio (SINR) for the active user connected in the HAN is derived from the amplitude distribution property of the classical indoor SalehValenzuela (SV) channel. The numerical results show that WiFi Direct technique not only improves the power saving in the HAN for Smart Grid, but also enhances the reliability of HAN communications for Smart Grid.

Zhuo Li; Qilian Liang; Xiuzhen Cheng

2014-01-01T23:59:59.000Z

153

Mean and peak wind loads on heliostats  

SciTech Connect (OSTI)

Mean and peak wind loads on flat rectangular or circular heliostats were measured on models in a boundary layer wind tunnel which included an atmospheric surface layer simulation. Horizontal and vertical forces, moments about horizontal axes at the ground level and at the centerline of the heliostat, and the moment about the vertical axis through the heliostat center were measured. Results showed that loads are higher than predicted from results obtained in a uniform, low-turbulence flow due to the presence of turbulence. Reduced wind loads were demonstrated for heliostats within a field of heliostats and upper bound curves were developed to provide preliminary design coefficients.

Peterka, J.A.; Tan, Z.; Cermak, J.E.; Bienkiewicz, B.

1989-05-01T23:59:59.000Z

154

Rank Name Peak Date Peak Location Bomb Peak Gradient Min Depth (Hr-Dy-Mn-Yr) (Lat, Lon) (Bergeron) (hPa/1000km) (hPa)  

E-Print Network [OSTI]

Rank Name Peak Date Peak Location Bomb Peak Gradient Min Depth (Hr-Dy-Mn-Yr) (Lat, Lon) (Bergeron, and northwest europe (Cambride Univ. Pr.). 1 #12;Figure S1(a): Evolution of 'Daria' (the top ranked storm arrow is approximately 50 m s-1). 2 #12;Figure S1(b): As for Figure S1(a) but for the storm ranked

Caballero, Rodrigo

155

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":""}]}

156

Oil hills, ridges, peaks, cliffs and ravines  

Science Journals Connector (OSTI)

In an earlier paper Tanner and Berry (1985) considered the decay of a disturbance to an otherwise uniform thin oil film. This was followed analytically using the Navier-Stokes equation, and optically by interferometry. Solutions were obtained in the form of a series of three-dimensional hills and of two-dimensional ridges, decaying with time in a self-similar manner. The present work extends this in several ways. By better control of the applied disturbance, more of the original series are produced and illustrated. The original hill series is extended to a doubly-infinite one, providing the possibility, as with the ridges, of different time decay rates for each azimuthal structure. Negative j values, giving either vertical growth or static vertical heights, are considered and in a few cases produced experimentally. Finally nonlinear peaks, cliffs and ravines having self-similar scaling properties are studied. In all cases, good agreement between theory and experiment is obtained.

L H Tanner

1986-01-01T23:59:59.000Z

157

Gamow peak approximation near strong resonances  

E-Print Network [OSTI]

We discuss the most effective energy range for charged particle induced reactions in a plasma environment at a given plasma temperature. The correspondence between the plasma temperature and the most effective energy should be modified from the one given by the Gamow peak energy, in the presence of a significant incident-energy dependence in the astrophysical S-factor as in the case of resonant reactions. The suggested modification of the effective energy range is important not only in thermonuclear reactions at high temperature in the stellar environment, e.g., in advanced burning stages of massive stars and in explosive stellar environment, as it has been already claimed, but also in the application of the nuclear reactions driven by ultra-intense laser pulse irradiations.

Kimura, Sachie

2013-01-01T23:59:59.000Z

158

Variations of Total Domination  

Science Journals Connector (OSTI)

The study of locatingdominating sets in graphs was pioneered by Slater[186, 187...], and this concept was later extended to total domination in graphs. A locatingtotal dominating set, abbreviated LTD-set, in G

Michael A. Henning; Anders Yeo

2013-01-01T23:59:59.000Z

159

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

160

BroadPeak: a novel algorithm for identifying broad peaks in dif-fuse ChIP-seq datasets  

E-Print Network [OSTI]

1 BroadPeak: a novel algorithm for identifying broad peaks in dif- fuse ChIP-seq datasets JianrongIP-seq datasets. We show that BroadPeak is a linear time algorithm that requires only two parame- ters, and we validate its performance on real and simulated histone modification ChIP-seq datasets. BroadPeak calls

Jordan, King

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

Total Space Heat-  

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

Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration...

162

Refinery Outages: Fall 2014  

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

well- supplied with middle distillate fuel oil, not only from Europe but also from Russia, India and the Middle East. As a result, planned maintenance this fall at Eastern...

163

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...

164

A Multimethod analysis of the Phenomenon of Peak-Oil.  

E-Print Network [OSTI]

??El concepto de Peak-Oil (el cnit del petrleo) es complejo y a menudo malentendido. Despus de aclarar que el Peak-Oil es tanto un problema de (more)

Kerschner, Christian

2012-01-01T23:59:59.000Z

165

THE COMPACT STEEP SPECTRUM AND GHZ PEAKED SPECTRUM RADIO SOURCES  

E-Print Network [OSTI]

THE COMPACT STEEP SPECTRUM AND GHZ PEAKED SPECTRUM RADIO SOURCES Christopher P. O'Dea Space@stsci.edu ABSTRACT I review the radio to X­ray properties of GHz Peaked Spectrum (GPS) and Compact Steep Spectrum The GHz Peaked Spectrum (GPS) and Compact Steep Spectrum (CSS) radio sources make up significant fractions

166

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

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

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

167

Computing plasma focus pinch current from total current measurement  

Science Journals Connector (OSTI)

The total current I total waveform in a plasma focus discharge is the most commonly measured quantity contrasting with the difficult measurement of I pinch . However yield laws should be scaled to focus pinch current I pinch rather than the peak I total . This paper describes how I pinch may be computed from the I total trace by fitting a computed current trace to the measured current trace using the Lee model. The method is applied to an experiment in which both the I total trace and the plasma sheath current trace were measured. The result shows good agreement between the values of computed and measured I pinch .

S. Lee; S. H. Saw; P. C. K. Lee; R. S. Rawat; H. Schmidt

2008-01-01T23:59:59.000Z

168

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

SciTech Connect (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

169

Flexible Coal: An Example Evolution from Baseload to Peaking Plant (Presentation)  

SciTech Connect (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.

2014-05-01T23:59:59.000Z

170

Flexible Coal: An Example Evolution from Baseload to Peaking Plant (Presentation)  

SciTech Connect (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.

2014-08-01T23:59:59.000Z

171

On peaked solitary waves of Camassa-Holm equation  

E-Print Network [OSTI]

Unlike the Boussinesq, KdV and BBM equations, the celebrated Casamma-Holm (CH) equation can model both phenomena of soliton interaction and wave breaking. Especially, it has peaked solitary waves in case of omega=0. Besides, in case of omega > 0, its solitary wave "becomes $C^\\infty$ and there is no derivative discontinuity at its peak", as mentioned by Camassa and Holm in 1993 (PRL). However, it is found in this article that the CH equation has peaked solitary waves even in case of omega > 0. Especially, all of these peaked solitary waves have an unusual property: their phase speeds have nothing to do with the height of peakons or anti-peakons. Therefore, in contrast to the traditional view-points, the peaked solitary waves are a common property of the CH equation: in fact, all mainstream models of shallow water waves admit such kind of peaked solitary waves

Liao, Shijun

2012-01-01T23:59:59.000Z

172

21 briefing pages total  

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

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

173

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

Open Energy Info (EERE)

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

174

,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...  

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

and 2007 Base Year)" ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid",,,," " ,"Projected Year...

175

,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...  

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

and 2008 Base Year)" ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid",,,," " ,"Projected Year...

176

,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...  

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

and 2003 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,"Texas Power Grid","Western Power Grid" ,"Projected Year...

177

,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...  

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

and 2009 Base Year)" ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid",,,," " ,"Projected Year...

178

,"Table 2a. Noncoincident Summer Peak Load, Actual and Projected...  

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

Base Year)",,,," " ,"Summer Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,"Texas Power Grid","Western Power Grid" ,"Projected Year...

179

,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...  

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

and 2004 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,"Texas Power Grid","Western Power Grid" ,"Projected Year...

180

,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...  

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

January 23, 2008" ,"Next Update: October 2007" ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, " ,"2005...

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

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 (more)

Tuckerman, Samantha Lynn

2012-01-01T23:59:59.000Z

182

Peak Oil, Energiesicherheit und die Grenzen des Marktes  

Science Journals Connector (OSTI)

Der lpreis wird von zahlreichen Faktoren beeinflusst. Die OPEC spielt bei der Preisbildung derzeit nur eine geringe Rolle. Ein Peak Oil wird die lpreise stark beeinflussen und zahlreiche...

Dr. Nikolaus Supersberger

2009-04-01T23:59:59.000Z

183

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

184

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

Open Energy Info (EERE)

2007) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Gas Flux Sampling At Desert Peak Area (Lechler And Coolbaugh, 2007) Exploration Activity...

185

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

186

Summary Max Total Units  

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

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

187

Total Precipitable Water  

SciTech Connect (OSTI)

The simulation was performed on 64K cores of Intrepid, running at 0.25 simulated-years-per-day and taking 25 million core-hours. This is the first simulation using both the CAM5 physics and the highly scalable spectral element dynamical core. The animation of Total Precipitable Water clearly shows hurricanes developing in the Atlantic and Pacific.

None

2012-01-01T23:59:59.000Z

188

Total Sustainability Humber College  

E-Print Network [OSTI]

1 Total Sustainability Management Humber College November, 2012 SUSTAINABILITY SYMPOSIUM Green An Impending Global Disaster #12;3 Sustainability is NOT Climate Remediation #12;Our Premises "We cannot, you cannot improve it" (Lord Kelvin) "First rule of sustainability is to align with natural forces

Thompson, Michael

189

Peak Oil and REMI PI+: State Fiscal Implications  

E-Print Network [OSTI]

, nation, and states) · Shale oil not included ­ Shale oil reserve estimates 2.0 Trillion bbls in USPeak Oil and REMI PI+: State Fiscal Implications Jim Peach Arrowhead Center Prosper Project is peak oil? · Why peak oil (and gas) matters ­ (In energy and non-energy states) ­ National Real GDP

Johnson, Eric E.

190

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

191

On Transforming Spectral Peaks in Voice Conversion Elizabeth Godoy 1  

E-Print Network [OSTI]

On Transforming Spectral Peaks in Voice Conversion Elizabeth Godoy 1 , Olivier Rosec1 , Thierry.chonavel@telecom-bretagne.eu Abstract This paper explores the benefits of transforming spectral peaks in voice conversion. First, in examining classic GMM- based transformation with cepstral coefficients, we show that the lack of transformed

Paris-Sud XI, Université de

192

Total isomerization gains flexibility  

SciTech Connect (OSTI)

Isomerization extends refinery flexibility to meet changing markets. TIP (Total Isomerization Process) allows conversion of paraffin fractions in the gasoline boiling region including straight run naptha, light reformate, aromatic unit raffinate, and hydrocrackate. The hysomer isomerization is compared to catalytic reforming. Isomerization routes are graphed. Cost estimates and suggestions on the use of other feedstocks are given. TIP can maximize gas production, reduce crude runs, and complement cat reforming. In four examples, TIP reduces reformer severity and increases reformer yield.

Symoniak, M.F.; Holcombe, T.C.

1983-05-01T23:59:59.000Z

193

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":""}]}

194

Geographies of peak oil: The other carbon problem  

Science Journals Connector (OSTI)

This extended editorial introduction to a themed issue of Geoforum on geographies of peak oil has three objectives. First, it provides a concise account of the peak oil claim, identifying the key protagonists in the debate, and outlining different stances with regard to the timing, shape and composition (conventional vs. non-conventional hydrocarbons) of the peak. Second, after briefly characterising the limited engagement with peak oil by human geographers, it offers a provisional set of claims about what a geographical analysis of peak oil might yield. Finally, it introduces each of the papers and, in doing so, makes the case for a fuller and more sustained engagement by geography with this other carbon problem.

Gavin Bridge

2010-01-01T23:59:59.000Z

195

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

196

A model of peak production in oil fields  

Science Journals Connector (OSTI)

We developed a model for oil production on the basis of simple physical considerations. The model provides a basic understanding of Hubberts empirical observation that the production rate for an oil-producing region reaches its maximum when approximately half the recoverable oil has been produced. According to the model the oil production rate at a large field must peak before drilling peaks. We use the model to investigate the effects of several drilling strategies on oil production. Despite the models simplicity predictions for the timing and magnitude of peak production match data on oil production from major oil fields throughout the world.

Daniel M. Abrams; Richard J. Wiener

2010-01-01T23:59:59.000Z

197

Determination of Total Solids in Biomass and Total Dissolved...  

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

Total Solids in Biomass and Total Dissolved Solids in Liquid Process Samples Laboratory Analytical Procedure (LAP) Issue Date: 3312008 A. Sluiter, B. Hames, D. Hyman, C. Payne,...

198

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

SciTech Connect (OSTI)

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

199

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

200

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

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

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.


201

EA-1921: Silver Peak Area Geothermal Exploration Project Environmental  

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

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

202

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"

203

EA-1921: Silver Peak Area Geothermal Exploration Project Environmental  

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

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

204

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:

205

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...

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

1987-01-01T23:59:59.000Z

206

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

207

Potential Peak Load Reductions From Residential Energy Efficient Upgrades  

E-Print Network [OSTI]

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...

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

2002-01-01T23:59:59.000Z

208

,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...  

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

and 2009 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"FRCC",...

209

,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...  

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

and 2007 Base Year)" ,"Winter Noncoincident Peak Load",,"Contiguous U.S. ","Eastern Power Grid",,,,,,"Texas Power Grid","Western Power Grid" ,"Projected Year Base","Year",,"FRCC",...

210

Robust powder auto-indexing using many peaks  

Science Journals Connector (OSTI)

A new algorithm, CONOGRAPH, carries out exhaustive powder auto-indexing in a short time, even if the q values of many peaks are used for robust powder auto-indexing. Some results from CONOGRAPH are presented.

Oishi-Tomiyasu, R.

2014-03-11T23:59:59.000Z

211

Optimization of Demand Response Through Peak Shaving , D. Craigie  

E-Print Network [OSTI]

Optimization of Demand Response Through Peak Shaving G. Zakeri , D. Craigie , A. Philpott , M. Todd for the demand response of such a consumer. We will establish a monotonicity result that indicates fuel supply

Todd, Michael J.

212

The peak of oil productionTimings and market recognition  

Science Journals Connector (OSTI)

Energy is essential for present societies. In particular, transportation systems depend on petroleum-based fuels. That world oil production is set to pass a peak is now a reasonably accepted concept, although its date is far from consensual. In this work, we analyze the true expectations of the oil market participants about the future availability of this fundamental energy source. We study the evolution through time of the curves of crude oil futures prices, and we conclude that the market participants, among them the crude oil producers, already expect a near-term peak of oil production. This agrees with many technical predictions for the date of peak production, including our own, that point to peak dates around the end of the present decade. If this scenario is confirmed, it can cause serious social and economical problems because societies will have little time to perform the necessary adjustments.

Pedro de Almeida; Pedro D. Silva

2009-01-01T23:59:59.000Z

213

Peak Oil and the Arctic National Wildlife Refuge  

Science Journals Connector (OSTI)

When Peak Oil is reached, oil production is slated to decline. If the ... worlds economic engine is still running on oil, there is potential for instability in the global economy as oil becomes scarcer and more ...

Peter Van Tuyn

2014-01-01T23:59:59.000Z

214

High Energy Density Science with High Peak Power Light Sources  

Science Journals Connector (OSTI)

High energy density (HED) science is a growing sub-field of plasma and condensed matter physics. I will examine how recent technological developments in high peak power, petawatt-class...

Ditmire, Todd

215

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

216

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":[]}

217

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":""}]}

218

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":""}]}

219

Peak oil: The four stages of a new idea  

Science Journals Connector (OSTI)

The present paper reviews the reactions and the path of acceptance of the theory known as peak oil. The theory was proposed for the first time by M.K. Hubbert in the 1950s as a way to describe the production pattern of crude oil. According to Hubbert, the production curve is bell shaped and approximately symmetric. Hubbert's theory was verified with good approximation for the case of oil production in the United States that peaked in 1971, and is now being applied to the worldwide oil production. It is generally believed that the global peak of oil production (peak oil) will take place during the first decade of the 21st century, and some analysts believe that it has already occurred in 2005 or 2006. The theory and its consequences have unpleasant social and economical implications. The present paper is not aimed at assessing the peak date but offers a discussion on the factors that affect the acceptance and the diffusion of the concept of peak oil with experts and with the general public. The discussion is based on a subdivision of four stages of acceptance, loosely patterned after a sentence by Thomas Huxley.

Ugo Bardi

2009-01-01T23:59:59.000Z

220

Gaussian Approximation of Peak Values in the Integrated Sachs-Wolfe Effect  

E-Print Network [OSTI]

The accelerating expansion of the universe at recent epochs is encoded in the cosmic microwave background: a few percent of the total temperature fluctuations are generated by evolving gravitational potentials which trace the large-scale structures in the universe. This signature of dark energy, the Integrated Sachs-Wolfe Effect, has been detected by averaging temperatures in the WMAP sky maps corresponding to the directions of superstructures in the Sloan Digital Sky Survey data release 6. We model the maximum average peak signal expected in the standard $\\Lambda$CDM cosmological model, using Gaussian random realizations of the microwave sky, including correlations between different physical contributions to the temperature fluctuations and between different redshift ranges of the evolving gravitational potentials. We find good agreement with the mean temperature peak amplitude from previous theoretical estimates based on large-scale structure simulations, but with larger statistical uncertainties. We apply ...

Aiola, Simone; Wang, Bingjie

2014-01-01T23:59:59.000Z

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.


221

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

222

Scenarios for a South African CSP Peaking System in the Short Term  

Science Journals Connector (OSTI)

Abstract The South African Integrated Resource Plan is a policy document, which by law allocates the energy resources that will be built to meet the future electricity needs of South Africa. The current Integrated Resource Plan indicates the electricity generation types that will be built from 2010 to 2030. It states that most of the future peak load will be met by Open Cycle Gas Turbines which operate using diesel and represents an allocation of 4,930M W. Further, the Integrated Resource Plan does not identify CSP as a potential peaking solution and allocates 1,200M W of capacity to CSP. This represents less than 2% of total capacity in 2030. This paper investigates the feasibility of utilizing CSP Plants as peaking plants in the short to medium term based on a proposition that under certain scenarios, a fleet of unsubsidized CSP peaking plants could drop the LCOE of the current Integrated Resource Plan. This is done by modeling a contemporary CSP tower system with Thermal Energy Storage. The Gemasolar CSP plant is used as the reference plant in order to obtain operating parameters. Our analysis suggests that at current fuels costs, diesel powered Open Cycle Gas Turbines produce electricity in excess of 5.08 ZAR/kWh (?0.63 US$/kWh), significantly above current CSP energy generating costs. This is the context that informed the undertaking of this study, to influence policy and provide technical evidence that CSP can guarantee and deliver energy at competitive costs in the short term. Two alternate scenarios show a lower LCOE for providing peak power. The most promising is a combined distributed CSP system wit h diesel powered Open Cycle Gas Turbine system as backup. The LCOE for this system is 2.78 ZAR (?0.34 $/kWh) or a drop of 45% when no fuel price inflation is considered. This system also increases security of supply due to a lower dependence on fuel prices.

C. Silinga; P. Gauch

2014-01-01T23:59:59.000Z

223

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

SciTech Connect (OSTI)

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

224

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

225

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

226

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

227

Achieving sustainable urban transport mobility in post peak oil era  

Science Journals Connector (OSTI)

Peak oil is the term used to describe the point at which global oil production will peak and thereafter start to decline. Recognising that transport uses a significant portion of global energy, the shortage of fossil fuel in post peak oil era will pose a global challenge in the transport sector. The paper presents an assessment of international research to illustrate the possible time frame of peak oil. It investigates the key implications of the oil shortage that threaten to render the urban transport system of Australia ineffective. Synthesis of documented research evidence suggests three major implications in the urban transport sector: (1) a reduction of mobility for individuals, (2) an increase of transport disadvantage, and (3) a disruption of urban freight movement. In addition, the paper explores strategies to cope with the devastating effects of the shortage of the fossil fuel in the post peak oil era. A number of strategies to achieve sustainable mobility in the future urban transport system are presented. These strategies are summarised into three main themes: (1) a mode shift to alternate transport modes, (2) an integration of land use and transport planning, and (3) a global technical effort for alternate fuels and vehicles. It is expected that a concerted global effort in this regard can have a far-reaching effect in achieving sustainability in urban transport mobility.

Md Aftabuzzaman; Ehsan Mazloumi

2011-01-01T23:59:59.000Z

228

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma  

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

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

229

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":""}]}

230

Price Server System for Automated Critical Peak Pricing  

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

231

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

232

The Peak/Dip Picture of the Cosmic Web  

E-Print Network [OSTI]

The initial shear field plays a central role in the formation of large-scale structures, and in shaping the geometry, morphology, and topology of the cosmic web. We discuss a recent theoretical framework for the shear tensor, termed the `peak/dip picture', which accounts for the fact that halos/voids may form from local extrema of the density field - rather than from random spatial positions; the standard Doroshkevich's formalism is generalized, to include correlations between the density Hessian and shear field at special points in space around which halos/voids may form. We then present the `peak/dip excursion-set-based' algorithm, along with its most recent applications - merging peaks theory with the standard excursion set approach.

Rossi, Graziano

2014-01-01T23:59:59.000Z

233

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":""}]}

234

An Energy and Peak Loads Analysis of the TYC/TRC Building Final Report  

E-Print Network [OSTI]

with the ASHRAE standards and (iii) modifying the building to comply with the California standards. These options not only reduce the peak loads but also reduce the total energy use. The energy consumption of the TYC/TRC Building was compared with the energy... consumption of the building modified to comply with the ASHRAE and California standards. A net reduction of 38% and 44% was obtained using the ASHRAE and California standards, respectively. The California standards are more stringent and are a better choice...

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

1987-01-01T23:59:59.000Z

235

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... havior of the ratio of total quanta to total energy (Q : W) within the spectral region of photosynthetic ..... For blue-green waters, where hRmax lies.

2000-01-02T23:59:59.000Z

236

Scenario Analysis of Peak Demand Savings for Commercial Buildings with  

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

237

Silver Peak Innovative Exploration Project (Ram Power Inc.)  

SciTech Connect (OSTI)

Data generated from the Silver Peak Innovative Exploration Project, in Esmeralda County, Nevada, encompasses a deep-circulation (amagmatic) meteoric-geothermal system circulating beneath basin-fill sediments locally blanketed with travertine in western Clayton Valley (lithium-rich brines from which have been mined for several decades). Spring- and shallow-borehole thermal-water geochemistry and geothermometry suggest that a Silver Peak geothermal reservoir is very likely to attain the temperature range 260- 300oF (~125-150oC), and may reach 300-340oF (~150-170oC) or higher (GeothermEx, Inc., 2006). Results of detailed geologic mapping, structural analysis, and conceptual modeling of the prospect (1) support the GeothermEx (op. cit.) assertion that the Silver Peak prospect has good potential for geothermal-power production; and (2) provide a theoretical geologic framework for further exploration and development of the resource. The Silver Peak prospect is situated in the transtensional (regional shearing coupled with extension) Walker Lane structural belt, and squarely within the late Miocene to Pliocene (11 Ma to ~5 Ma) Silver Peak-Lone Mountain metamorphic core complex (SPCC), a feature that accommodated initial displacement transfer between major right-lateral strike- slip fault zones on opposite sides of the Walker Lane. The SPCC consists essentially of a ductiley-deformed lower plate, or core, of Proterozoic metamorphic tectonites and tectonized Mesozoic granitoids separated by a regionally extensive, low-angle detachment fault from an upper plate of severely stretched and fractured structural slices of brittle, Proterozoic to Miocene-age lithologies. From a geothermal perspective, the detachment fault itself and some of the upper-plate structural sheets could function as important, if secondary, subhorizontal thermal-fluid aquifers in a Silver Peak hydrothermal system.

Miller, Clay

2010-01-01T23:59:59.000Z

238

Injection Solvent Effect on Peak Height in Ion Exchange HPLC  

Science Journals Connector (OSTI)

......2. To further evaluate the effect of the injection volume only...injection volume were varied. Effect of weak injection solvent There...same eluent ion strength. The effect of eluent ion strength. Figure...nitrate in the mobile phase. 418 ship of the peak height of phenylacetate......

Hyunjoo Kim Lee; Norman E. Hoffman

1992-10-01T23:59:59.000Z

239

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

240

Scalable Scheduling of Building Control Systems for Peak Demand Reduction  

E-Print Network [OSTI]

Behl, Rahul Mangharam and George J. Pappas Department of Electrical and Systems Engineering University operation of sub- systems such as heating, ventilating, air conditioning and refrigeration (HVAC&R) systems is fundamental for their efficient behavior, especially in elec- trical systems and the electric grid [1]. Peak

Pappas, George J.

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

Providing Regulation Services and Managing Data Center Peak Power Budgets  

E-Print Network [OSTI]

-based peak shaving. However, none of these publications consider the feasibility of using the energy storage AND RELATED WORK Substantial integration of electric vehicles and renewable energy sources into the electric utility companies use to ensure stability. It includes multiple mechanisms, such as demand-response (DR

Simunic, Tajana

242

Why Military and Intelligence Agencies Are Peeking at Peak Oil  

Science Journals Connector (OSTI)

In the spring of 2003 I received a telephone call that was, to me, astonishing. A lady introduced herself and told me that she worked for MUST. She and a colleague wanted to come to Uppsala to discuss Peak Oil wi...

Kjell Aleklett

2012-01-01T23:59:59.000Z

243

Green Scheduling: Scheduling of Control Systems for Peak Power Reduction  

E-Print Network [OSTI]

approach to fine-grained coordination of energy demand by scheduling energy consuming control systems of the system variables only, control system execution (i.e. when energy is supplied to the system-Scheduling; Energy Systems; Peak Power Reduction; Load Balancing; I. INTRODUCTION During a major sporting event

Pappas, George J.

244

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

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

245

Mujeres Hombres Total Hombres Total 16 5 21 0 10  

E-Print Network [OSTI]

Julio de 2011 Tipo de Discapacidad Sexo CENTRO 5-Distribución del estudiantado con discapacidad por centro, tipo de discapacidad, sexo y totales. #12;

Autonoma de Madrid, Universidad

246

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... ment of the total energy and vice versa. From a measurement of spectral irradi- ance ... unit energy (for the wavelength region specified).

2000-01-02T23:59:59.000Z

247

Categorical Exclusion for Pinnacle Peak Substation PCB contaminated Electrical  

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

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

248

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

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

249

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

250

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

251

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

252

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

253

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

254

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

255

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

256

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

257

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

258

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

259

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

260

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

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

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

262

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

263

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

264

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

265

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

266

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

267

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

268

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

269

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

270

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

271

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

272

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

273

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

274

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)

275

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

276

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

277

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)...........................

278

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

279

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

280

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

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

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

Gasoline and Diesel Fuel Update (EIA)

... 2.8 0.7 0.5 0.2 Million U.S. Housing Units Home Electronics Usage Indicators Table HC12.12 Home Electronics Usage Indicators by Midwest Census Region,...

282

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

Gasoline and Diesel Fuel Update (EIA)

... 13.2 1.8 1.2 0.5 Table HC11.10 Home Appliances Usage Indicators by Northeast Census Region, 2005 Million U.S. Housing Units Home Appliances...

283

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

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

... 2.8 1.1 0.7 Q 0.4 Million U.S. Housing Units Home Electronics Usage Indicators Table HC13.12 Home Electronics Usage Indicators by South Census Region,...

284

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

Gasoline and Diesel Fuel Update (EIA)

... 13.2 3.1 1.0 2.2 Table HC14.10 Home Appliances Usage Indicators by West Census Region, 2005 Million U.S. Housing Units Home Appliances...

285

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

Gasoline and Diesel Fuel Update (EIA)

States New York Florida Texas California Million U.S. Housing Units Home Electronics Usage Indicators Table HC15.12 Home Electronics Usage Indicators by Four Most Populated...

286

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

Gasoline and Diesel Fuel Update (EIA)

... 13.2 2.7 3.5 2.2 1.3 3.5 1.3 3.8 Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line Eligible for Federal...

287

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

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

... 13.2 3.4 2.0 1.4 Table HC12.10 Home Appliances Usage Indicators by Midwest Census Region, 2005 Million U.S. Housing Units Home Appliances...

288

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

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

Census Region Northeast Midwest South West Million U.S. Housing Units Home Electronics Usage Indicators Table HC10.12 Home Electronics Usage Indicators by U.S. Census Region, 2005...

289

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

Gasoline and Diesel Fuel Update (EIA)

(as Self-Reported) City Town Suburbs Rural Million U.S. Housing Units Home Electronics Usage Indicators Table HC8.12 Home Electronics Usage Indicators by UrbanRural Location,...

290

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

Gasoline and Diesel Fuel Update (EIA)

... 13.2 4.4 2.5 3.0 3.4 Table HC8.10 Home Appliances Usage Indicators by UrbanRural Location, 2005 Million U.S. Housing Units UrbanRural...

291

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

Gasoline and Diesel Fuel Update (EIA)

... 2.8 0.6 Q 0.5 Million U.S. Housing Units Home Electronics Usage Indicators Table HC14.12 Home Electronics Usage Indicators by West Census Region, 2005...

292

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

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

... 13.2 4.9 2.3 1.1 1.5 Table HC13.10 Home Appliances Usage Indicators by South Census Region, 2005 Million U.S. Housing Units South Census Region...

293

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

Gasoline and Diesel Fuel Update (EIA)

... 51.9 7.0 4.8 2.2 Not Asked (Mobile Homes or Apartment in Buildings with 5 or More Units)... 23.7...

294

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

Gasoline and Diesel Fuel Update (EIA)

Housing Units Living Space Characteristics Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Single-Family Units Detached...

295

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

Gasoline and Diesel Fuel Update (EIA)

0.7 21.7 6.9 12.1 Do Not Have Space Heating Equipment... 1.2 Q Q N Q Have Main Space Heating Equipment... 109.8 40.3 21.4 6.9 12.0 Use Main Space Heating...

296

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...

297

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...

298

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

299

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

300

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

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

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

302

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

303

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

304

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

305

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

306

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

307

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

308

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

309

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

310

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

311

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

312

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":""}]}

313

Deconvolution of mixed gamma emitters using peak parameters  

SciTech Connect (OSTI)

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

314

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":""}]}

315

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

316

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

Open Energy Info (EERE)

Silver Peak Area (Henkle, Et Al., 2005) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Soil Sampling At Silver Peak Area (Henkle, Et Al., 2005)...

317

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

318

Transverse Polarization for Energy Calibration at the Z peak  

E-Print Network [OSTI]

In this paper we deal with aspects of transverse polarization for the purpose of energy calibration of proposed circular colliders like the FCC-ee and the CEPC. The main issues of such a measurement will be discussed. The possibility of using this method to accurately determine the energy at the WW threshold as well as the Z peak will be addressed. The use of wigglers for reducing long polarization times will be discussed and a possible strategy will be presented for minimising the energy uncertainty error in these large machines.

Koratzinos, M

2015-01-01T23:59:59.000Z

319

Peak oil supply or oil not for sale?  

Science Journals Connector (OSTI)

Abstract The restrictions imposed by climate change are inevitable and will be exerted either via precautionary mitigation of (mainly energy-related) CO2 emissions or via irreversible impacts on ecosystems and on human habitats. Either way, oil markets are bound to incur drastic shrinking. Concern over peak oil supply will crumble when the irrevocable peak oil demand is created. Replacing oil in the world's energy economies requires redirected market forces, notably in the form of steadily increasing oil end-use prices. Yet, thus far, crude oil prices have obeyed the market fundamentals of expanding-contracting demand and oligopolistic supply. A hockey stick supply curve supports high sales prices, providing large rents to submarginal sources. Cutting oil demand and maintaining high prices implies reducing the supply hockey stick's length by curtailing some oil producers. In such a scenario, the alliances, goals, and tactics of oil geopolitics are set to change. We identify a distribution over friendly and hostile oil suppliers, with others drifting in between the two sides. Conflicts and warfare are less aimed at conquering oil fields for exploitation than at paralyzing production capabilities of opponents or of unreliable transient sources. Covert warfare and instigation of internal conflicts are likely tactics to exhaust hostile opponents.

Aviel Verbruggen; Thijs Van de Graaf

2013-01-01T23:59:59.000Z

320

Total Sky Imager (TSI) Handbook  

SciTech Connect (OSTI)

The total sky imager (TSI) provides time series of hemispheric sky images during daylight hours and retrievals of fractional sky cover for periods when the solar elevation is greater than 10 degrees.

Morris, VR

2005-06-01T23:59:59.000Z

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.


321

Origin of the narrow, single peak in the fission-fragment mass distribution for 258Fm  

SciTech Connect (OSTI)

We discuss the origin of the narrowness of the single peak at mass-symmetric division in the fragment mass-yield curve for spontaneous fission of {sup 258}Fm. For this purpose, we employ the macroscopic-microscopic model and calculate a potential-energy curve at the mass-symmetric compact scission configuration, as a function of the fragment mass number, which is obtained from the single-particle wave-function densities. In the calculations, we minimize total energies by varying the deformations of the two fragments, with constraints on the mass quadrupole moment, and by keeping the neck radius zero. The energies thus become functions of mass asymmetry. Using the obtained potential, we solve the one-dimensional Schroedinger equation with a microscopic coordinate-dependent inertial mass to calculate the fragment mass-yield curve. The calculated mass yield, expressed in terms of the microscopic mass density, is consistent with the extremely narrow experimental mass distribution.

Moller, Peter [Los Alamos National Laboratory; Ickhikawa, Takatoshi [RIKEN; Iwamoto, Akira [JAEA

2008-01-01T23:59:59.000Z

322

Measurement of a Peak in the Cosmic Microwave Background Power  

Science Journals Connector (OSTI)

We describe a measurement of the angular power spectrum of anisotropies in the cosmic microwave background (CMB) at scales of 03 to 5 from the North American test flight of the Boomerang experiment. Boomerang is a balloon-borne telescope with a bolometric receiver designed to map CMB anisotropies on a long-duration balloon flight. During a 6 hr test flight of a prototype system in 1997, we mapped more than 200 deg2 at high Galactic latitudes in two bands centered at 90 and 150 GHz with a resolution of 26' and 165 FWHM, respectively. Analysis of the maps gives a power spectrum with a peak at angular scales of 1 with an amplitude 70 ?KCMB.

P. D. Mauskopf; P. A. R. Ade; P. de Bernardis; J. J. Bock; J. Borrill; A. Boscaleri; B. P. Crill; G. DeGasperis; G. De Troia; P. Farese; P. G. Ferreira; K. Ganga; M. Giacometti; S. Hanany; V. V. Hristov; A. Iacoangeli; A. H. Jaffe; A. E. Lange; A. T. Lee; S. Masi; A. Melchiorri; F. Melchiorri; L. Miglio; T. Montroy; C. B. Netterfield; E. Pascale; F. Piacentini; P. L. Richards; G. Romeo; J. E. Ruhl; E. Scannapieco; F. Scaramuzzi; R. Stompor; N. Vittorio

2000-01-01T23:59:59.000Z

323

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.

324

Logistic curves, extraction costs and effective peak oil  

Science Journals Connector (OSTI)

Debates about the possibility of a near-term maximum in world oil production have become increasingly prominent over the past decade, with the focus often being on the quantification of geologically available and technologically recoverable amounts of oil in the ground. Economically, the important parameter is not a physical limit to resources in the ground, but whether market price signals and costs of extraction will indicate the efficiency of extracting conventional or nonconventional resources as opposed to making substitutions over time for other fuels and technologies. We present a hybrid approach to the peak-oil question with two models in which the use of logistic curves for cumulative production are supplemented with data on projected extraction costs and historical rates of capacity increase. While not denying the presence of large quantities of oil in the ground, even with foresight, rates of production of new nonconventional resources are unlikely to be sufficient to make up for declines in availability of conventional oil. Furthermore we show how the logistic-curve approach helps to naturally explain high oil prices even when there are significant quantities of low-cost oil yet to be extracted.

Robert J. Brecha

2012-01-01T23:59:59.000Z

325

Performance Period Total Fee Paid  

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

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:

326

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"

327

ARM - Measurement - Total cloud water  

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

328

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

329

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

330

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 (OSTI)

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

331

ON THERMALIZATION IN GAMMA-RAY BURST JETS AND THE PEAK ENERGIES OF PHOTOSPHERIC SPECTRA  

SciTech Connect (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}< 20, is obtained if synchrotron emission acts as the photon source. This requires, however, a non-thermal acceleration deep below the Thomson photosphere transferring a significant fraction of the flow energy to relativistic electrons with Lorentz factors between 10 and 100. Other processes require bulk flow Lorentz factors of order of a few for typical 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

332

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

333

Signal Peak-Tracker based on the Teager-Kaiser Energy (TKE) Operator  

E-Print Network [OSTI]

Described is a modification of the TKE operator from its usual `energy form'. The resulting `peak-tracker' (or peak-detector) is especially useful in studies that involve the frequency domain.

Randall D. Peters

2010-10-25T23:59:59.000Z

334

The evolution and present status of the study on peak oil in China  

Science Journals Connector (OSTI)

Peak oil theory is a theory concerning long-term oil reserves and the rate of oil production. Peak oil refers to the maximum rate of the production of oil or gas in any area under consideration. ... from three as...

Xiongqi Pang; Lin Zhao; Lianyong Feng; Qingyang Meng; Xu Tang

2009-06-01T23:59:59.000Z

335

Two kinds of peaked solitary waves of the KdV, BBM and Boussinesq equations  

Science Journals Connector (OSTI)

It is well-known that the celebrated Camassa-Holm equation has the peaked solitary waves, which have ... solutions of peaked solitary waves of the KdV equation, the BBM equation and the Boussinesq equation are gi...

ShiJun Liao

2012-12-01T23:59:59.000Z

336

THE ROLE OF BUILDING TECHNOLOGIES IN REDUCING AND CONTROLLING PEAK ELECTRICITY DEMAND  

E-Print Network [OSTI]

LBNL-49947 THE ROLE OF BUILDING TECHNOLOGIES IN REDUCING AND CONTROLLING PEAK ELECTRICITY DEMAND? ..................................... 8 What are the seasonal aspects of electric peak demand?............................ 9 What because of the California electricity crisis (Borenstein 2001). Uncertainties surrounding the reliability

337

The suppression of fluorescence peaks in energy-dispersive X-ray diffraction  

Science Journals Connector (OSTI)

It is shown experimentally that diffraction peaks which are normally obscured by fluorescence peaks in energy-dispersive X-ray diffraction can be revealed by tuning of the X-ray tube excitation voltage in order to suppress the fluorescence peaks.

Hansford, G.M.

2014-09-30T23:59:59.000Z

338

Polyribosomes in Rat Tissues: IV. On the Abnormal Dimer Peak in Hepatomas  

Science Journals Connector (OSTI)

...previously (11) that the dimer peak which is present in both the...between the monomer and dimer peaks. Also only slight changes are...height of the monomer and dimer peaks when the Novikoff hepatoma was...in an equal volume of mineral oil 12 hr before removal of the...

Thomas E. Webb and Van R. Potter

1966-05-01T23:59:59.000Z

339

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

340

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

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

Solar total energy project Shenandoah  

SciTech Connect (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

342

Grantee Total Number of Homes  

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

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

343

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:

344

Total quality management implementation guidelines  

SciTech Connect (OSTI)

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

345

Total Heart Transplant: A Modern Overview  

E-Print Network [OSTI]

use of the total artificial heart. New England Journal ofJ. (1997). Artificial heart transplants. British medicala total artificial heart as a bridge to transplantation. New

Lingampalli, Nithya

2014-01-01T23:59:59.000Z

346

Detection of point sources on two-dimensional images based on peaks  

E-Print Network [OSTI]

This article considers the detection of point sources in two dimensional astronomical images. The detection scheme we propose is based on peak statistics. We discuss the example of the detection of far galaxies in Cosmic Microwave Background experiments throughout the paper, although the method we present is totally general and can be used in many other fields of data analysis. We assume sources with a Gaussian profile --that is a fair approximation of the profile of a point source convolved with the detector beam in microwave experiments-- on a background modeled by a homogeneous and isotropic Gaussian random field characterized by a scale-free power spectrum. Point sources are enhanced with respect to the background by means of linear filters. After filtering, we identify local maxima and apply our detection scheme, a Neyman-Pearson detector that defines our region of acceptance based on the a priori pdf of the sources and the ratio of number densities. We study the different performances of some linear fil...

Lopez-Caniego, M; Sanz, J L; Barreiro, R B

2005-01-01T23:59:59.000Z

347

Detection of point sources on two-dimensional images based on peaks  

E-Print Network [OSTI]

This article considers the detection of point sources in two dimensional astronomical images. The detection scheme we propose is based on peak statistics. We discuss the example of the detection of far galaxies in Cosmic Microwave Background experiments throughout the paper, although the method we present is totally general and can be used in many other fields of data analysis. We assume sources with a Gaussian profile --that is a fair approximation of the profile of a point source convolved with the detector beam in microwave experiments-- on a background modeled by a homogeneous and isotropic Gaussian random field characterized by a scale-free power spectrum. Point sources are enhanced with respect to the background by means of linear filters. After filtering, we identify local maxima and apply our detection scheme, a Neyman-Pearson detector that defines our region of acceptance based on the a priori pdf of the sources and the ratio of number densities. We study the different performances of some linear filters that have been used in this context in the literature: the Mexican Hat wavelet, the matched filter and the scale-adaptive filter. We consider as well an extension to two dimensions of the biparametric scale adaptive filter (BSAF). The BSAF depends on two parameters which are determined by maximizing the number density of real detections while fixing the number density of spurious detections. For our detection criterion the BSAF outperforms the other filters in the interesting case of white noise.

M. Lopez-Caniego; D. Herranz; J. L. Sanz; R. B. Barreiro

2005-03-07T23:59:59.000Z

348

Total Imports of Residual Fuel  

Gasoline and Diesel Fuel Update (EIA)

May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 View May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 View History U.S. Total 5,752 5,180 7,707 9,056 6,880 6,008 1936-2013 PAD District 1 1,677 1,689 2,008 3,074 2,135 2,814 1981-2013 Connecticut 1995-2009 Delaware 1995-2012 Florida 359 410 439 392 704 824 1995-2013 Georgia 324 354 434 364 298 391 1995-2013 Maine 65 1995-2013 Maryland 1995-2013 Massachusetts 1995-2012 New Hampshire 1995-2010 New Jersey 903 756 948 1,148 1,008 1,206 1995-2013 New York 21 15 14 771 8 180 1995-2013 North Carolina 1995-2011 Pennsylvania 1995-2013 Rhode Island 1995-2013 South Carolina 150 137 194 209 1995-2013 Vermont 5 4 4 5 4 4 1995-2013 Virginia 32 200 113 1995-2013 PAD District 2 217 183 235 207 247 179 1981-2013 Illinois 1995-2013

349

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Noyes, MN Warroad, MN Babb, MT Port of Del Bonita, MT Port of Morgan, MT Sweetgrass, MT Whitlash, MT Portal, ND Sherwood, ND Pittsburg, NH Champlain, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Highgate 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 from Canada Highgate Springs, VT LNG Imports from Egypt Cameron, LA Elba Island, GA Freeport, TX Gulf LNG, MS LNG Imports from Equatorial Guinea LNG Imports from Indonesia LNG Imports from Malaysia LNG Imports from Nigeria Cove Point, MD LNG Imports from Norway Cove Point, MD Freeport, TX Sabine Pass, LA LNG Imports from Oman LNG Imports from Peru Cameron, LA Freeport, TX LNG Imports from Qatar Elba Island, GA Golden Pass, TX Sabine Pass, LA LNG Imports from Trinidad/Tobago Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf LNG, MS Lake Charles, LA Sabine Pass, LA LNG Imports from United Arab Emirates LNG Imports from Yemen Everett, MA Freeport, TX Sabine Pass, LA LNG Imports from Other Countries Period: Monthly Annual

350

Natural Gas Total Liquids Extracted  

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

Thousand Barrels) Thousand Barrels) Data Series: Natural Gas Processed Total Liquids Extracted NGPL Production, Gaseous Equivalent Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2007 2008 2009 2010 2011 2012 View History U.S. 658,291 673,677 720,612 749,095 792,481 873,563 1983-2012 Alabama 13,381 11,753 11,667 13,065 1983-2010 Alaska 22,419 20,779 19,542 17,798 18,314 18,339 1983-2012 Arkansas 126 103 125 160 212 336 1983-2012 California 11,388 11,179 11,042 10,400 9,831 9,923 1983-2012 Colorado 27,447 37,804 47,705 57,924 1983-2010 Florida 103 16 1983-2008 Illinois 38 33 24 231 705 0 1983-2012

351

Hurricane Sandy Situation Report # 19 November 6, 2012 (3:00 PM EST)  

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

9 9 November 6, 2012 (3:00 PM EST) http://www.oe.netl.doe.gov/emergency_sit_rpt.aspx Highlights: At 8:00 pm EDT October 29, the National Hurricane Center reported Sandy made landfall near Atlantic City, NJ as a post tropical cyclone. As of 2:00 pm EST November 6, there are 930,783 customers without power in the affected States. 7,580,468 customers have been restored out of the 8,511,251 combined total peak outages reported in the Situation Reports for all 21 States affected. Restoration estimates and efforts by electric utilities are reported below. Summary Impacted State Current Customer Outages Percentage of Customers Without Power Peak Outages Reported in DOE SitReps Customers Restored Since Peak Connecticut 7,371 < 1% 626,559 619,188 Maryland

352

Hurricane Sandy Situation Report # 14 November 4, 2012 (10:00 AM EST)  

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

4 4 November 4, 2012 (10:00 AM EST) http://www.oe.netl.doe.gov/emergency_sit_rpt.aspx Highlights: At 8:00 pm EDT October 29, the National Hurricane Center reported Sandy made landfall near Atlantic City, NJ as a post tropical cyclone. As of 9:00 am EST November 4 there are 1,923,169 customers without power in the affected States. 6,558,082 customers have been restored out of the 8,511,251 combined total peak outages reported in the Situation Reports for all 21 States affected. Restoration estimates and efforts by electric utilities are reported below. Summary Impacted State Current Customer Outages Percentage of Customers Without Power Peak Outages Reported in DOE SitReps Customers Restored Since Peak Connecticut 75,289 5% 626,559 551,270 Maryland

353

Hurricane Sandy Situation Report # 12 November 3, 2012 (10:00 AM EDT)  

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

2 2 November 3, 2012 (10:00 AM EDT) http://www.oe.netl.doe.gov/emergency_sit_rpt.aspx Highlights: At 8:00 pm EDT October 29, the National Hurricane Center reported Sandy made landfall near Atlantic City, NJ as a post tropical cyclone. As of 9:00 am EDT November 3 there are 2,576,101 customers without power in the affected States. 5,935,150 customers have been restored out of the 8,511,251 combined total peak outages reported in the Situation Reports for all 21 States affected. Restoration estimates and efforts by electric utilities are reported below. Summary Impacted State Current Customer Outages Percentage of Customers Without Power Peak Outages Reported in DOE SitReps Customers Restored Since Peak Connecticut 144,678 7% 626,559 481,881 Maryland

354

Hurricane Sandy Situation Report # 16 November 5, 2012 (10:00 AM EST)  

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

6 6 November 5, 2012 (10:00 AM EST) http://www.oe.netl.doe.gov/emergency_sit_rpt.aspx Highlights: At 8:00 pm EDT October 29, the National Hurricane Center reported Sandy made landfall near Atlantic City, NJ as a post tropical cyclone. As of 9:00 am EST November 5, there are 1,374,676 customers without power in the affected States. 7,136,575 customers have been restored out of the 8,511,251 combined total peak outages reported in the Situation Reports for all 21 States affected. Restoration estimates and efforts by electric utilities are reported below. Summary Impacted State Current Customer Outages Percentage of Customers Without Power Peak Outages Reported in DOE SitReps Customers Restored Since Peak Connecticut 33,868 2% 626,559 592,691 Maryland

355

Hurricane Sandy Situation Report # 17 November 5, 2012 (3:00 PM EST)  

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

7 7 November 5, 2012 (3:00 PM EST) http://www.oe.netl.doe.gov/emergency_sit_rpt.aspx Highlights: At 8:00 pm EDT October 29, the National Hurricane Center reported Sandy made landfall near Atlantic City, NJ as a post tropical cyclone. As of 2:00 pm EST November 5, there are 1,351,683 customers without power in the affected States. 7,159,568 customers have been restored out of the 8,511,251 combined total peak outages reported in the Situation Reports for all 21 States affected. Restoration estimates and efforts by electric utilities are reported below. Summary Impacted State Current Customer Outages Percentage of Customers Without Power Peak Outages Reported in DOE SitReps Customers Restored Since Peak Connecticut 30,608 2% 626,559 595,951 Maryland

356

Hurricane Sandy Situation Report # 15 November 4, 2012 (3:00 PM EST)  

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

5 5 November 4, 2012 (3:00 PM EST) http://www.oe.netl.doe.gov/emergency_sit_rpt.aspx Highlights: At 8:00 pm EDT October 29, the National Hurricane Center reported Sandy made landfall near Atlantic City, NJ as a post tropical cyclone. As of 2:00 pm EST November 4, there are 1,855,958 customers without power in the affected States. 6,655,293 customers have been restored out of the 8,511,251 combined total peak outages reported in the Situation Reports for all 21 States affected. Restoration estimates and efforts by electric utilities are reported below. Summary Impacted State Current Customer Outages Percentage of Customers Without Power Peak Outages Reported in DOE SitReps Customers Restored Since Peak Connecticut 64,955 4% 626,559 561,604 Maryland

357

Hurricane Sandy Situation Report # 18 November 6, 2012 (10:00 AM EST)  

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

8 8 November 6, 2012 (10:00 AM EST) http://www.oe.netl.doe.gov/emergency_sit_rpt.aspx Highlights: At 8:00 pm EDT October 29, the National Hurricane Center reported Sandy made landfall near Atlantic City, NJ as a post tropical cyclone. As of 9:00 am EST November 6, there are 973,759 customers without power in the affected States. 7,537,492 customers have been restored out of the 8,511,251 combined total peak outages reported in the Situation Reports for all 21 States affected. Restoration estimates and efforts by electric utilities are reported below. Summary Impacted State Current Customer Outages Percentage of Customers Without Power Peak Outages Reported in DOE SitReps Customers Restored Since Peak Connecticut 9,864 < 1% 626,559 616,695 Maryland

358

Hurricane Sandy Situation Report # 13 November 3, 2012 (3:00 PM EDT)  

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

3 3 November 3, 2012 (3:00 PM EDT) http://www.oe.netl.doe.gov/emergency_sit_rpt.aspx Highlights: At 8:00 pm EDT October 29, the National Hurricane Center reported Sandy made landfall near Atlantic City, NJ as a post tropical cyclone. As of 2:00 pm EDT November 3 there are 2,497,421 customers without power in the affected States. 6,013,830 customers have been restored out of the 8,511,251 combined total peak outages reported in the Situation Reports for all 21 States affected. Restoration estimates and efforts by electric utilities are reported below. Summary Impacted State Current Customer Outages Percentage of Customers Without Power Peak Outages Reported in DOE SitReps Customers Restored Since Peak Connecticut 132,805 6% 626,559 493,754 Maryland

359

Total Petroleum Systems and Assessment Units (AU)  

E-Print Network [OSTI]

Total Petroleum Systems (TPS) and Assessment Units (AU) Field type Surface water Groundwater X X X X X X X X AU 00000003 Oil/ Gas X X X X X X X X Total X X X X X X X Total Petroleum Systems (TPS) and Assessment Units (AU) Field type Total undiscovered petroleum (MMBO or BCFG) Water per oil

Torgersen, Christian

360

Locating and total dominating sets in trees  

Science Journals Connector (OSTI)

A set S of vertices in a graph G = ( V , E ) is a total dominating set of G if every vertex of V is adjacent to a vertex in S. We consider total dominating sets of minimum cardinality which have the additional property that distinct vertices of V are totally dominated by distinct subsets of the total dominating set.

Teresa W. Haynes; Michael A. Henning; Jamie Howard

2006-01-01T23:59:59.000Z

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

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

362

Locating-total domination in graphs  

Science Journals Connector (OSTI)

In this paper, we continue the study of locating-total domination in graphs. A set S of vertices in a graph G is a total dominating set in G if every vertex of G is adjacent to a vertex in S . We consider total dominating sets S which have the additional property that distinct vertices in V ( G ) ? S are totally dominated by distinct subsets of the total dominating set. Such a set S is called a locating-total dominating set in G , and the locating-total domination number of G is the minimum cardinality of a locating-total dominating set in G . We obtain new lower and upper bounds on the locating-total domination number of a graph. Interpolation results are established, and the locating-total domination number in special families of graphs, including cubic graphs and grid graphs, is investigated.

Michael A. Henning; Nader Jafari Rad

2012-01-01T23:59:59.000Z

363

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

364

E-Print Network 3.0 - annihilation coincidence peak Sample Search...  

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

peak is seen at 3375 keV with 6000... . the annihilation spectra from the polyethylene and gold tar- ... Source: Golovchenko, Jene A. - Department of Physics, Harvard...

365

RESCHEDULED: Webinar on Material Handling Fuel Cells for Building Electric Peak Shaving Applications  

Broader source: Energy.gov [DOE]

The Fuel Cell Technologies Office will present a live webinar entitled "Material Handling Fuel Cells for Building Electric Peak Shaving Applications".

366

The origin of brucite in hydrothermally altered limestone near Devil Peak, Nevada.  

E-Print Network [OSTI]

??Open-space brucite was identified in veins crosscutting hydrothermally altered limestone near the Devil Peak rhyolite plug in southern Nevada. The brucite occurs with serpentine, calcite, (more)

Knupp, Rhonda L.

1999-01-01T23:59:59.000Z

367

E-Print Network 3.0 - artificial extra peaks Sample Search Results  

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

A L . 2004 American Meteorological Society Summary: with theory, extratropical stochastic wind forces a decadal spectral peak in the tropical and eastern boundary... forcing, with...

368

E-Print Network 3.0 - adduct peak elimination Sample Search Results  

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

in 1,2-eliminations observed for HF loss... peak could be the CF3 + adduct of acrolein ... Source: Morton, Thomas Hellman - Department of Chemistry, University of...

369

Konsekvenser av Peak Oil i relation till fysisk planering - En fallstudie av Vxj kommun.  

E-Print Network [OSTI]

??Arbetets syfte r att uppmrksamma den problematik som r kopplad till Peak Oil, samt genom att exemplifiera med Vxj kommun, underska p vilket stt fysisk (more)

Edholm, Hedvig

2012-01-01T23:59:59.000Z

370

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

371

2-M Probe At Desert Peak Area (Sladek, Et Al., 2007) | Open Energy...  

Open Energy Info (EERE)

Sladek, Et Al., 2007) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: 2-M Probe At Desert Peak Area (Sladek, Et Al., 2007) Exploration Activity...

372

U.S. Total Exports  

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

International Falls, MN Noyes, MN Warroad, MN Babb, MT Havre, MT Port of Del Bonita, MT Port of Morgan, MT Sweetgrass, MT Whitlash, MT Portal, ND Sherwood, ND Pittsburg, NH Champlain, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Highgate Springs, VT North Troy, VT LNG Imports into Cameron, LA LNG Imports into Cove Point, MD LNG Imports into Elba Island, GA LNG Imports into Everett, MA LNG Imports into Freeport, TX LNG Imports into Golden Pass, TX LNG Imports into Gulf Gateway, LA LNG Imports into Gulf LNG, MS LNG Imports into Lake Charles, LA LNG Imports into Neptune Deepwater Port LNG Imports into Northeast Gateway LNG Imports into Sabine Pass, LA U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Alamo, TX El Paso, TX Galvan Ranch, TX Hidalgo, TX McAllen, TX Penitas, TX LNG Imports from Algeria Cove Point, MD Everett, MA Lake Charles, LA LNG Imports from Australia Everett, MA Lake Charles, LA LNG Imports from Brunei Lake Charles, LA LNG Imports from Canada Highgate Springs, VT LNG Imports from Egypt Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf LNG, MS Lake Charles, LA Northeast Gateway Sabine Pass, LA LNG Imports from Equatorial Guinea Elba Island, GA Lake Charles, LA LNG Imports from Indonesia Lake Charles, LA LNG Imports from Malaysia Gulf Gateway, LA Lake Charles, LA LNG Imports from Nigeria Cove Point, MD Elba Island, GA Freeport, TX Gulf Gateway, LA Lake Charles, LA Sabine Pass, LA LNG Imports from Norway Cove Point, MD Sabine Pass, LA LNG Imports from Oman Lake Charles, LA LNG Imports from Peru Cameron, LA Freeport, TX Sabine Pass, LA LNG Imports from Qatar Cameron, LA Elba Island, GA Golden Pass, TX Gulf Gateway, LA Lake Charles, LA Northeast Gateway Sabine Pass, LA LNG Imports from Trinidad/Tobago Cameron, LA Cove Point, MD Elba Island, GA Everett, MA Freeport, TX Gulf Gateway, LA Gulf LNG, MS Lake Charles, LA Neptune Deepwater Port Northeast Gateway Sabine Pass, LA LNG Imports from United Arab Emirates Lake Charles, LA LNG Imports from Yemen Everett, MA Freeport, TX Neptune Deepwater Port Sabine Pass, LA LNG Imports from Other Countries Lake Charles, LA Period: Monthly Annual

373

Evaluation of potential severe accidents during low power and shutdown operations at Grand Gulf, Unit 1. Volume 2, Part 1C: Analysis of core damage frequency from internal events for plant operational State 5 during a refueling outage, Main report (Sections 11--14)  

SciTech Connect (OSTI)

This document contains the accident sequence analysis of internally initiated events for Grand Gulf, Unit 1 as it operates in the Low Power and Shutdown Plant Operational State 5 during a refueling outage. The report documents the methodology used during the analysis, describes the results from the application of the methodology, and compares the results with the results from two full power analyses performed on Grand Gulf.

Whitehead, D. [Sandia National Labs., Albuquerque, NM (United States); Darby, J. [Science and Engineering Associates, Inc., Albuquerque, NM (United States); Yakle, J. [Science Applications International Corp., Albuquerque, NM (United States)] [and others

1994-06-01T23:59:59.000Z

374

Plasmonic Nature of the Terahertz Conductivity Peak in Single-Wall Carbon Nanotubes  

E-Print Network [OSTI]

Plasmonic Nature of the Terahertz Conductivity Peak in Single-Wall Carbon Nanotubes Qi Zhang, Erik resonance is expected to occur in metallic and doped semiconducting carbon nanotubes in the terahertz conductivity peak commonly observed for carbon nanotube ensembles remains controversial. Here we present

Kono, Junichiro

375

Distributed Battery Control to Improve Peak Power Shaving Efficiency in Data Centers  

E-Print Network [OSTI]

Rack PDU BackupMain Bus-type power network Utility Diesel Generator ATS PDU Server Rack Server RackDistributed Battery Control to Improve Peak Power Shaving Efficiency in Data Centers Baris Aksanli, Eddie Pettis and Tajana S. Rosing UCSD, Google Stored energy in batteries can be used to cap peak power

Simunic, Tajana

376

20 th International Sacramento Peak Summer Workshop Advanced Solar Polarimetry -Theory, Observation, and Instrumentation  

E-Print Network [OSTI]

in the Quiet Sun Alexei A. Pevtsov National Solar Observatory/Sacramento Peak, PO Box 62, Sunspot, New Mexico20 th International Sacramento Peak Summer Workshop Advanced Solar Polarimetry - Theory in the solar activity on all spatial scales. It is believed that the strong magnetic #12;eld (active regions

Pevtsov, Alexei A.

377

An Approximate Method to Assess the Peaking Capability of the NW Hydroelectric System  

E-Print Network [OSTI]

DRAFT 1 An Approximate Method to Assess the Peaking Capability of the NW Hydroelectric System September 26, 2005 The best way to assess the hydroelectric system's peaking capability is to simulate its. This model simulates the operation of the major hydroelectric projects over a one-week (168 hour) period

378

State Residential Commercial Industrial Transportation Total  

Gasoline and Diesel Fuel Update (EIA)

schedules 4A-D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total 2012 Total Electric Industry- Average Retail Price (centskWh) (Data from...

379

Total cost model for making sourcing decisions  

E-Print Network [OSTI]

This thesis develops a total cost model based on the work done during a six month internship with ABB. In order to help ABB better focus on low cost country sourcing, a total cost model was developed for sourcing decisions. ...

Morita, Mark, M.B.A. Massachusetts Institute of Technology

2007-01-01T23:59:59.000Z

380

InSAR At Desert Peak Area (Laney, 2005) | Open Energy Information  

Open Energy Info (EERE)

InSAR At Desert Peak Area (Laney, 2005) InSAR At Desert Peak Area (Laney, 2005) Exploration Activity Details Location Desert Peak Area Exploration Technique InSAR Activity Date Usefulness not indicated DOE-funding Unknown Notes InSAR Ground Displacement Analysis, Gary Oppliger and Mark Coolbaugh. This project supports increased utilization of geothermal resources in the Western United States by developing basic measurements and interpretations that will assist reservoir management and expansion at Bradys, Desert Peak and the Desert Peak EGS study area (80 km NE of Reno, Nevada) and will serve as a technology template for other geothermal fields. Raw format European Space Agency (ESA) ERS 1/2 satellite synthetic Aperture Radar (SAR) radar scenes acquired from 1992 through 2002 are being processed to

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

On the portents of peak oil (and other indicators of resource scarcity)  

Science Journals Connector (OSTI)

Economists have studied various indicators of resource scarcity but largely ignored the phenomenon of peaking due to its connection to non-economic (physical) theories of resource exhaustion. I consider peaking from the economic point of view, where economic forces determine the shape of the equilibrium extraction path. Within that framework, I ask whether the timing of peak production reveals anything useful about scarcity. I find peaking to be an ambiguous indicator. If someone announced the peak would arrive earlier than expected, and you believed them, you would not know whether the news was good or bad. However, I also show that the traditional economic indicators of resource scarcity (price, cost, and rent) fare no better, and argue that previous studies have misconstrued the connection between changes in underlying scarcity and movements in these traditional indicators.

James L. Smith

2012-01-01T23:59:59.000Z

382

Team Total Points Beta Theta Pi 2271  

E-Print Network [OSTI]

Bubbles 40 Upset City 30 Team Success 30 #12;Team Total Points Sly Tye 16 Barringer 15 Fire Stinespring 15

Buehrer, R. Michael

383

Million Cu. Feet Percent of National Total  

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

38 38 Nevada - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S30. Summary statistics for natural gas - Nevada, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 4 4 4 3 4 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 4 4 4 3 4

384

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Idaho - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S14. Summary statistics for natural gas - Idaho, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

385

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Washington - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S49. Summary statistics for natural gas - Washington, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

386

Million Cu. Feet Percent of National Total  

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

0 0 Maine - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S21. Summary statistics for natural gas - Maine, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0

387

Million Cu. Feet Percent of National Total  

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

8 8 Minnesota - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S25. Summary statistics for natural gas - Minnesota, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

388

Million Cu. Feet Percent of National Total  

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

2 2 South Carolina - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S42. Summary statistics for natural gas - South Carolina, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

389

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 North Carolina - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S35. Summary statistics for natural gas - North Carolina, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

390

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Iowa - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S17. Summary statistics for natural gas - Iowa, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0

391

Million Cu. Feet Percent of National Total  

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

4 4 Massachusetts - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S23. Summary statistics for natural gas - Massachusetts, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

392

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Minnesota - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S25. Summary statistics for natural gas - Minnesota, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

393

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 New Jersey - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S32. Summary statistics for natural gas - New Jersey, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

394

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Vermont - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S47. Summary statistics for natural gas - Vermont, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

395

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Wisconsin - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S51. Summary statistics for natural gas - Wisconsin, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0 0 0

396

Million Cu. Feet Percent of National Total  

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

8 8 North Carolina - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S35. Summary statistics for natural gas - North Carolina, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

397

Million Cu. Feet Percent of National Total  

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

2 2 New Jersey - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S32. Summary statistics for natural gas - New Jersey, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

398

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Maryland - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S22. Summary statistics for natural gas - Maryland, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 7 7 7 7 8 Production (million cubic feet) Gross Withdrawals From Gas Wells 35 28 43 43 34 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 35

399

Million Cu. Feet Percent of National Total  

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

0 0 New Hampshire - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S31. Summary statistics for natural gas - New Hampshire, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

400

Million Cu. Feet Percent of National Total  

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

2 2 Maryland - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S22. Summary statistics for natural gas - Maryland, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 7 7 7 8 9 Production (million cubic feet) Gross Withdrawals From Gas Wells 28 43 43 34 44 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 28

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

Million Cu. Feet Percent of National Total  

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

2 2 Missouri - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S27. Summary statistics for natural gas - Missouri, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 53 100 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

402

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Massachusetts - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S23. Summary statistics for natural gas - Massachusetts, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

403

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 South Carolina - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S42. Summary statistics for natural gas - South Carolina, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

404

Million Cu. Feet Percent of National Total  

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

0 0 Rhode Island - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S41. Summary statistics for natural gas - Rhode Island, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0 Total 0

405

Peak Oil  

Science Journals Connector (OSTI)

Between 2000 and 2010, world oil prices advanced from approximately $25 per barrel to more than $100 per barrel. The price appreciation of oil over the decade was around ten times the rate of inflation.

Robert Rapier

2012-01-01T23:59:59.000Z

406

Compare All CBECS Activities: Total Energy Use  

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

Total Energy Use Total Energy Use Compare Activities by ... Total Energy Use Total Major Fuel Consumption by Building Type Commercial buildings in the U.S. used a total of approximately 5.7 quadrillion Btu of all major fuels (electricity, natural gas, fuel oil, and district steam or hot water) in 1999. Office buildings used the most total energy of all the building types, which was not a surprise since they were the most common commercial building type and had an above average energy intensity. Figure showing total major fuel consumption by building type. If you need assistance viewing this page, please call 202-586-8800. Major Fuel Consumption per Building by Building Type Because there were relatively few inpatient health care buildings and they tend to be large, energy intensive buildings, their energy consumption per building was far above that of any other building type.

407

TotalView Parallel Debugger at NERSC  

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

Totalview Totalview Totalview Description TotalView from Rogue Wave Software is a parallel debugging tool that can be run with up to 512 processors. It provides both X Windows-based Graphical User Interface (GUI) and command line interface (CLI) environments for debugging. The performance of the GUI can be greatly improved if used in conjunction with free NX software. The TotalView documentation web page is a good resource for learning more about some of the advanced TotalView features. Accessing Totalview at NERSC To use TotalView at NERSC, first load the TotalView modulefile to set the correct environment settings with the following command: % module load totalview Compiling Code to Run with TotalView In order to use TotalView, code must be compiled with the -g option. We

408

First versus subsequent return-stroke current and field peaks in negative cloud-to-ground lightning discharges  

E-Print Network [OSTI]

First versus subsequent return-stroke current and field peaks in negative cloud-to-ground lightning examine relative magnitudes of electric field peaks of first and subsequent return strokes in negative, the electric field peak of the first stroke is appreciably, 1.7 to 2.4 times, larger than the field peak

Florida, University of

409

Decarbonization and the time-delay between peak CO2 emissions and concentrations  

E-Print Network [OSTI]

Carbon-dioxide (CO2) is the main contributor to anthropogenic global warming, and the timing of its peak concentration in the atmosphere is likely to govern the timing of maximum radiative forcing. While dynamics of atmospheric CO2 is governed by multiple time-constants, we idealize this by a single time-constant to consider some of the factors describing the time-delay between peaks in CO2 emissions and concentrations. This time-delay can be understood as the time required to bring CO2 emissions down from its peak to a small value, and is governed by the rate of decarbonizaton of economic activity. This decarbonization rate affects how rapidly emissions decline after having achieved their peak, and a rapid decline in emissions is essential for limiting peak radiative forcing. Long-term mitigation goals for CO2 should therefore consider not only the timing of peak emissions, but also the rate of decarbonization. We discuss implications for mitigation of the fact that the emissions peak corresponds to small bu...

Seshadri, Ashwin K

2015-01-01T23:59:59.000Z

410

Development of oil formation theories and their importance for peak oil  

Science Journals Connector (OSTI)

This paper reviews the historical development of both biogenic and non-biogenic petroleum formation. It also examines the recent claim that the so-called abiotic oil formation theory undermines the concept of peak oil, i.e. the notion that world oil production is destined to reach a maximum that will be followed by an irreversible decline. We show that peak oil is first and foremost a matter of production flows. Consequently, the mechanism of oil formation does not strongly affect depletion. We would need to revise the theory beyond peak oil only for the extreme and unlikely hypothesis of abiotic petroleum formation.

Mikael Hk; Ugo Bardi; Lianyong Feng; Xiongqi Pang

2010-01-01T23:59:59.000Z

411

Higher-order pair-conversion peaks in heavy-ion collisions  

Science Journals Connector (OSTI)

We analyze quantum electrodynamic pair creation from vibrating nuclear quasimolecules which may occur in collisions of heavy ions. We find that higher-order processes, which can be phenomenologically relevant for sufficiently long lived systems, can result in coincident narrow peaks even for subcritical systems. The Z dependence of the energy of the peaks can be much softer than that predicted for positrons from sparking of the vacuum. Our results may be relevant to peaks which have been observed at the Gesellschaft fr Schwerionenforschung (GSI).

Denis Carrier and Lawrence M. Krauss

1988-09-01T23:59:59.000Z

412

OFFICE OF ELECTRICITY DELIVERY AND ENERGY RELIABILITY (OE)  

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

Isaac Situation Report # 14 Isaac Situation Report # 14 September 5, 2012 (3:00 PM EDT) http://www.oe.netl.doe.gov/emergency_sit_rpt.aspx Highlights: Hurricane Isaac made its first landfall on Tuesday, August 28 at 7:45 pm EDT in Plaquemines Parish, LA. Isaac made a second landfall along the coast of southeast Louisiana, just west of Port Fourchon, at 3:15 am EDT on Wednesday, August 29. Summary Impacted State Current Customer Outages Percentage of Customers Without Power Peak Outages Reported in DOE SitReps Customers Restored Since Peak Louisiana 13,884 < 1% 889,517 875,633 TOTAL: 13,884 Amount % Capacity Out* 680,749 49.33% 1,156.9 25.71% 247,000 NA Natural Gas Production Shut-in (mmcf/d) Refinery Capacity Shut down (b/d) Electric Outages by State Crude Oil Production Shut-In (b/d)

413

EA-1863: Vegetation Management on the Glen Canyon-Pinnacle Peak  

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

63: Vegetation Management on the Glen Canyon-Pinnacle Peak 63: Vegetation Management on the Glen Canyon-Pinnacle Peak Transmission Lines Spanning the Coconino National Forest, Coconino County, Arizona EA-1863: Vegetation Management on the Glen Canyon-Pinnacle Peak Transmission Lines Spanning the Coconino National Forest, Coconino County, Arizona Summary DOE's Western Area Power Administration is preparing this EA to evaluate the environmental impacts of updating the vegetation management and right-of-way maintenance program for Western's Glen Canyon to Pinnacle Peak 345-kV transmission lines, which cross the Coconino National Forest, Coconino County, Arizona. For more information on this EA, contact: Ms. Linette King at: lking@wapa.gov. Public Comment Opportunities No public comment opportunities available at this time.

414

EA-1863: Vegetation Management on the Glen Canyon-Pinnacle Peak  

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

3: Vegetation Management on the Glen Canyon-Pinnacle Peak 3: Vegetation Management on the Glen Canyon-Pinnacle Peak Transmission Lines Spanning the Coconino National Forest, Coconino County, Arizona EA-1863: Vegetation Management on the Glen Canyon-Pinnacle Peak Transmission Lines Spanning the Coconino National Forest, Coconino County, Arizona Summary DOE's Western Area Power Administration is preparing this EA to evaluate the environmental impacts of updating the vegetation management and right-of-way maintenance program for Western's Glen Canyon to Pinnacle Peak 345-kV transmission lines, which cross the Coconino National Forest, Coconino County, Arizona. For more information on this EA, contact: Ms. Linette King at: lking@wapa.gov. Public Comment Opportunities No public comment opportunities available at this time.

415

New Methods In Exploration At The Socorro Peak Kgra- A Gred Iii Project |  

Open Energy Info (EERE)

Methods In Exploration At The Socorro Peak Kgra- A Gred Iii Project Methods In Exploration At The Socorro Peak Kgra- A Gred Iii Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Conference Paper: New Methods In Exploration At The Socorro Peak Kgra- A Gred Iii Project Details Activities (6) Areas (1) Regions (0) Abstract: New Mexico Institute of Mining and Technology is investigating a Known Geothermal Resource Area in Socorro NM in attempts at locating a low temperature (65-100 °C) geothermal reservoir for direct-use heating on campus. The KGRA is positioned near the Socorro Peak mountain block, a Basin and Range normal-fault terrain superimposed by an Oligocene caldera margin. Preexisting evidence of this geothermal resource includes heat gradients upwards of 490mW/m2 from thermal-gradient wells, tepid spring

416

Peak Power Reduction Strategies for the Lighting Systems in Government Buildings  

E-Print Network [OSTI]

presents an approach developed to reduce the peak power demand in the lighting. The approach included optimum use of daylight, time of day control and delamping. The implementation of this approach for eight government buildings with occupancy of between 7...

Al-Nakib, D.; Al-Mulla, A. A.; Maheshwari, G. P.

2010-01-01T23:59:59.000Z

417

Univariate time-series forecasting of monthly peak demand of electricity in northern India  

Science Journals Connector (OSTI)

This study forecasts the monthly peak demand of electricity in the northern region of India using univariate time-series techniques namely Multiplicative Seasonal Autoregressive Integrated Moving Average (MSARIMA) and Holt-Winters Multiplicative Exponential Smoothing (ES) for seasonally unadjusted monthly data spanning from April 2000 to February 2007. In-sample forecasting reveals that the MSARIMA model outperforms the ES model in terms of lower root mean square error, mean absolute error and mean absolute percent error criteria. It has been found that ARIMA (2, 0, 0) (0, 1, 1)12 is the best fitted model to explain the monthly peak demand of electricity, which has been used to forecast the monthly peak demand of electricity in northern India, 15 months ahead from February 2007. This will help Northern Regional Load Dispatch Centre to make necessary arrangements a priori to meet the future peak demand.

Sajal Ghosh

2008-01-01T23:59:59.000Z

418

Redesigning experimental equipment for determining peak pressure in a simulated tank car transfer line  

E-Print Network [OSTI]

When liquids are transported from storage tanks to tank cars, improper order of valve openings can cause pressure surges in the transfer line. To model this phenomenon and predict the peak pressures in such a transfer line, ...

Diaz, Richard A

2007-01-01T23:59:59.000Z

419

On The Portents of Peak Oil (And Other Indicators of Resource Scarcity)  

E-Print Network [OSTI]

Although economists have studied various indicators of resource scarcity (e.g., unit cost, resource rent, and market price), the phenomenon of peaking has largely been ignored due to its connection to non-economic theories ...

Smith, James L.

420

Demand response: a strategy to address residential air-conditioning peak load in Australia  

Science Journals Connector (OSTI)

Rapid growth in electricity network peak demand is increasing pressure for new investment which may be used for only a few hours a year. Residential air-conditioning is widely believed to be the prime cause of...

Robert Smith; Ke Meng; Zhaoyang Dong

2013-12-01T23:59:59.000Z

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.


421

Discovery and geology of the Desert Peak geothermal field: a case history. Bulletin 97  

SciTech Connect (OSTI)

A case history of the exploration, development (through 1980), and geology of the Desert Peak geothermal field is presented. Sections on geochemistry, geophysics, and temperature-gradient drilling are included.

Benoit, W.R.; Hiner, J.E.; Forest, R.T.

1982-09-01T23:59:59.000Z

422

E-Print Network 3.0 - ag peaks disappear Sample Search Results  

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

The Journal of Physical Chemistry C is published by the American Chemical Summary: to the formation of oxide species for Pt and Ag. However, after several cycles, this peak...

423

Response of Professional Societies and Conservation Organizations to Peak Oil and Economic Growth  

Science Journals Connector (OSTI)

Peaking of the worlds oil supply is resulting in economic, social, ... way to live and is utterly dependent on oil. Addressing current environmental problems is already a ... up their efforts to address global i...

David L. Trauger; Rhonda D. Jackson

2014-01-01T23:59:59.000Z

424

The Formation of ASPO and the Growing Influence of the Peak Oil Community  

Science Journals Connector (OSTI)

The first question to be asked is why nobodly noticed the peak oil issue before? Well, in fact, people ... students Al-Jarri and Al-Fattah who plotted oil and gas production of every country using ... past decade...

Charles A. S. Hall; Carlos A. Ramrez-Pascualli

2013-01-01T23:59:59.000Z

425

Changes in measured lightning return stroke peak current after the 1994 National Lightning Detection Network upgrade  

E-Print Network [OSTI]

Since a comprehensive upgrade of the US National Lightning Detection Network (NLDN) in 1994, the mean peak current of detected cloud-to-ground (CG) lightning flashes has decreased, the number of detected flashes has increased, and the percentage...

Wacker, Robert Scott

2012-06-07T23:59:59.000Z

426

Using Compressed Air Efficiency Projects to Reduce Peak Industrial Electric Demands: Lessons Learned  

E-Print Network [OSTI]

"To help customers respond to the wildly fluctuating energy markets in California, Pacific Gas & Electric (PG&E) initiated an emergency electric demand reduction program in October 2000 to cut electric use during peak periods. One component...

Skelton, J.

427

Phase-Change Frame Walls (PCFWs) for Peak Demand Reduction, Load Shifting, Energy Conservation and Comfort  

E-Print Network [OSTI]

) for lowering peak heat transfer rates across walls of residential and small commercial buildings. A PCFW is a typical wall in which phase change materials (PCMs) have been incorporated via macroencapsulation to enhance the energy storage capabilities...

Medina, M.; Stewart, R.

428

Webinar February 17: Material Handling Fuel Cells for Building Electric Peak Shaving Applications  

Broader source: Energy.gov [DOE]

The Fuel Cell Technologies Office will present a live webinar entitled "Material Handling Fuel Cells for Building Electric Peak Shaving Applications" on Tuesday, February 17, from 12 to 1 p.m. Eastern Standard Time.

429

College of Engineering Fall 2010 PEAK Local Situational Awareness (LSA) System for Department  

E-Print Network [OSTI]

PENNSTATE College of Engineering Fall 2010 PEAK Local Situational Awareness (LSA) System and create a working prototype that has the ability to retrieve text, audio, still photos and videos

Demirel, Melik C.

430

Million Cu. Feet Percent of National Total  

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

6 6 Tennessee - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S44. Summary statistics for natural gas - Tennessee, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 285 310 230 210 212 Production (million cubic feet) Gross Withdrawals From Gas Wells 4,700 5,478 5,144 4,851 5,825 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

431

Million Cu. Feet Percent of National Total  

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

2 2 Connecticut - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S7. Summary statistics for natural gas - Connecticut, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

432

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Oregon - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S39. Summary statistics for natural gas - Oregon, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 18 21 24 26 24 Production (million cubic feet) Gross Withdrawals From Gas Wells 409 778 821 1,407 1,344 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

433

Million Cu. Feet Percent of National Total  

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

6 6 District of Columbia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S9. Summary statistics for natural gas - District of Columbia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

434

Million Cu. Feet Percent of National Total  

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

6 6 Oregon - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S39. Summary statistics for natural gas - Oregon, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 21 24 26 24 27 Production (million cubic feet) Gross Withdrawals From Gas Wells 778 821 1,407 1,344 770 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

435

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Georgia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S11. Summary statistics for natural gas - Georgia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

436

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Delaware - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S8. Summary statistics for natural gas - Delaware, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

437

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 District of Columbia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S9. Summary statistics for natural gas - District of Columbia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

438

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Tennessee - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S44. Summary statistics for natural gas - Tennessee, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 305 285 310 230 210 Production (million cubic feet) Gross Withdrawals From Gas Wells NA 4,700 5,478 5,144 4,851 From Oil Wells 3,942 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

439

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Nebraska - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S29. Summary statistics for natural gas - Nebraska, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 186 322 285 276 322 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,331 2,862 2,734 2,092 1,854 From Oil Wells 228 221 182 163 126 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

440

Million Cu. Feet Percent of National Total  

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

0 0 Georgia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S11. Summary statistics for natural gas - Georgia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

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

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Connecticut - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S7. Summary statistics for natural gas - Connecticut, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

442

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Florida - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S10. Summary statistics for natural gas - Florida, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 2,000 2,742 290 13,938 17,129 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

443

Million Cu. Feet Percent of National Total  

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

4 4 Delaware - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S8. Summary statistics for natural gas - Delaware, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 0 0 0 0 0 Production (million cubic feet) Gross Withdrawals From Gas Wells 0 0 0 0 0 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0 0 0 0 0

444

ARM - Measurement - Shortwave spectral total downwelling irradiance  

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

Shadowband Spectroradiometer SPEC-TOTDN : Shortwave Total Downwelling Spectrometer UAV-EGRETT : UAV-Egrett Value-Added Products VISST : Minnis Cloud Products Using Visst...

445

,"New York Natural Gas Total Consumption (MMcf)"  

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

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Total Consumption (MMcf)",1,"Annual",2013 ,"Release Date:","12312014"...

446

Total Supplemental Supply of Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Product: Total Supplemental Supply Synthetic Propane-Air Refinery Gas Biomass Other Period: Monthly Annual Download Series History Download Series History Definitions, Sources &...

447

Total Natural Gas Gross Withdrawals (Summary)  

Gasoline and Diesel Fuel Update (EIA)

Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to...

448

Million Cu. Feet Percent of National Total  

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

0 0 Indiana - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S16. Summary statistics for natural gas - Indiana, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 525 563 620 914 819 Production (million cubic feet) Gross Withdrawals From Gas Wells 4,701 4,927 6,802 9,075 8,814 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

449

Temperature evolution of the spectral peak in high-temperature superconductors  

Science Journals Connector (OSTI)

Recent photoemission data in the high-temperature cuprate superconductor Bi2212 have been interpreted in terms of a sharp spectral peak with a temperature-independent lifetime, whose weight strongly decreases upon heating. By a detailed analysis of the data, we are able to extract the temperature dependence of the electron self-energy, and demonstrate that this interpretation is misleading. Rather, the spectral peak loses its integrity above Tc due to a large reduction in the electron lifetime.

M. R. Norman; A. Kaminski; J. Mesot; J. C. Campuzano

2001-03-22T23:59:59.000Z

450

Determination of a peak benzene exposure to consumers at typical self-service gasoline stations  

E-Print Network [OSTI]

DETERMINATION OF A PEAK BENZENE EXPOSURE TO CONSUMERS AT TYPICAL SELF-SERVICE GASOLINE STATIONS A Thesis by TED CARAPEZZA Submitted to the Graduate College of Texas A8M University in Partial fulfillment of the requirement for the degree... of MASTER OF SCIENCE December 1977 Major Subject: Industrial Hygiene DETERMINATION OF A PEAK BENZENE EXPOSURE TO CONSUMERS AT TYPICAL SELF-SERVICE GASOLINE STATIONS A Thesis by TED CARAPEZZA Approved as to style and content by: (. (iL, &? Chairman...

Carapezza, Ted

2012-06-07T23:59:59.000Z

451

On the reliability of peak-flux distributions, with an application to solar flares  

E-Print Network [OSTI]

Narrow-band radio spikes have been recorded during a solar flare with unprecedented resolution. This unique example allows to study the effect of low resolution in previously published peak-flux distributions of radio spikes. We give a general, analytical expression for how an actual peak-flux distribution is changed in shape if the peaks are determined with low temporal and/or frequency resolution. It turns out that, generally, low resolution tends to cause an exponential behavior at large flux values if the actual distribution is of power-law shape. The distribution may be severely altered if the burst-duration depends on the peak-flux. The derived expression is applicable also to peak-flux distributions derived at other wavelengths (e.g. soft and hard X-rays, EUV). We show that for the analyzed spike-event the resolution was sufficient for a reliable peak flux distribution. It can be fitted by generalized power-laws or by an exponential.

H. Isliker; A. O. Benz

2001-06-08T23:59:59.000Z

452

Total Synthesis of Irciniastatin A (Psymberin)  

E-Print Network [OSTI]

Total Synthesis of Irciniastatin A (Psymberin) Michael T. Crimmins,* Jason M. Stevens, and Gregory, North Carolina 27599 crimmins@email.unc.edu Received July 21, 2009 ABSTRACT The total synthesis of a hemiaminal and acid chloride to complete the synthesis. In 2004, Pettit and Crews independently reported

453

TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION  

E-Print Network [OSTI]

TOTAL REFLUX OPERATION OF MULTIVESSEL BATCH DISTILLATION BERND WITTGENS, RAJAB LITTO, EVA S RENSEN a generalization of previously proposed batch distillation schemes. A simple feedback control strategy for total re verify the simulations. INTRODUCTION Although batch distillation generally is less energy e cient than

Skogestad, Sigurd

454

GAMMA-RAY LOUDNESS, SYNCHROTRON PEAK FREQUENCY, AND PARSEC-SCALE PROPERTIES OF BLAZARS DETECTED BY THE FERMI LARGE AREA TELESCOPE  

SciTech Connect (OSTI)

The parsec-scale radio properties of 232 active galactic nuclei, most of which are blazars, detected by the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope have been observed contemporaneously by the Very Long Baseline Array (VLBA) at 5 GHz. Data from both the first 11 months (1FGL) and the first 2 years (2FGL) of the Fermi mission were used to investigate these sources' {gamma}-ray properties. We use the ratio of the {gamma}-ray-to-radio luminosity as a measure of {gamma}-ray loudness. We investigate the relationship of several radio properties to {gamma}-ray loudness and to the synchrotron peak frequency. There is a tentative correlation between {gamma}-ray loudness and synchrotron peak frequency for BL Lac objects in both 1FGL and 2FGL, and for flat-spectrum radio quasars (FSRQs) in 2FGL. We find that the apparent opening angle tentatively correlates with {gamma}-ray loudness for FSRQs, but only when we use the 2FGL data. We also find that the total VLBA flux density correlates with the synchrotron peak frequency for BL Lac objects and FSRQs. The core brightness temperature also correlates with synchrotron peak frequency, but only for the BL Lac objects. The low-synchrotron-peaked (LSP) BL Lac object sample shows indications of contamination by FSRQs which happen to have undetectable emission lines. There is evidence that the LSP BL Lac objects are more strongly beamed than the rest of the BL Lac object population.

Linford, J. D.; Taylor, G. B.; Schinzel, F. K., E-mail: jlinford@unm.edu [Department of Physics and Astronomy, University of New Mexico, MSC07 4220, Albuquerque, NM 87131-0001 (United States)

2012-09-20T23:59:59.000Z

455

The Fermi blazars' divide based on the diagnostic of the SEDs peak frequencies  

E-Print Network [OSTI]

We have studied the quasi-simultaneous Spectral Energy Distributions (SED) of 48 LBAS blazars, detected within the three months of the LAT Bright AGN Sample (LBAS) data taking period, combining Fermi and Swift data with radio NIR-Optical and hard-X/gamma-ray data. Using these quasi-simultaneous SEDs, sampling both the low and the high energy peak of the blazars broad band emission, we were able to apply a diagnostic tool based on the estimate of the peak frequencies of the synchrotron (S) and Inverse Compton (IC) components. Our analysis shows a Fermi blazars' divide based on the peak frequencies of the SED. The robust result is that the Synchrotron Self Compton (SSC) region divides in two the plane were we plot the peak frequency of the synchrotron SED vs the typical Lorentz factor of the electrons most contributing to the synchrotron emission and to the inverse Compton process. Objects within or below this region, radiating likely via the SSC process, are high-frequency-peaked BL Lac object (HBL), or low/in...

Tramacere, A; Giommi, P; Mazziotta, N; Monte, C

2010-01-01T23:59:59.000Z

456

Views on peak oil and its relation to climate change policy  

Science Journals Connector (OSTI)

Definitions of fossil fuel reserves and resources and assessed stock data are reviewed and clarified. Semantics explain a large stake of conflict between advocate and critical voices on peak oil. From a holistic sourcessinks perspective, limited carrying capacity of atmospheric sinks, not absolute scarcity in oil resources, will impose tight constraints on oil use. Eventually observed peaks in oil production in nearby years will result from politically imposed limits on carbon emissions, and not be caused by physical lack of oil resources. Peak-oil belief induces passive climate policy attitudes when suggesting carbon dioxide emissions will peak naturally linked to dwindling oil supplies. Active policies for reducing emissions and use of fossil fuels will also encompass higher energy end-use prices. Revenues obtained from higher levies on oil use can support financing energy efficiency and renewable energy options. But when oil producers charge the higher prices they can pump new oil for many decades, postponing peak oil to occur while extending carbon lock-in.

Aviel Verbruggen; Mohamed Al Marchohi

2010-01-01T23:59:59.000Z

457

A physical model for active galactic nuclei with double-peaked broad emission lines  

E-Print Network [OSTI]

The double-peaked broad emission lines are usually thought to be linked to accretion disks, however, the local viscous heating in the line-emitting disk portion is usually insufficient for the observed double-peaked broad-line luminosity in most sources. Our calculations show that only a small fraction (line-emitting disk portion, because the solid angle of the outer disk portion subtended to the inner region of the RIAF is too small. We propose that only those AGNs with sufficient matter above the disk (slowly moving jets or outflows) can scatter enough photons radiated from the inner disk region to the outer line-emitting disk portion. Our model predicts a power-law r-dependent line emissivity with an index ~2.5, which is consistent with \\beta~2-3 required by the model fittings for double-peaked line profiles. Using a sample of radio-loud double-peaked line emitters, we show that the outer disk regions can be efficiently illuminated by the photons scattered from the electron-positron jets with \\gamma_jline is present in strong radio quasars with relativistic jets. For radio-quiet counterparts, slow outflows with Thomson scattering depth ~0.2 can scatter sufficient photons to the line-emitting regions. This model can therefore solve the energy budget problem for double-peaked line emitters.

Xinwu Cao; Ting-Gui Wang

2006-07-19T23:59:59.000Z

458

Peak Oil Netherlands Foundation (PONL) was founded in May 2005 by a group of citizens who are concerned about the effects of a premature peak in oil and other fossil fuels production. The main aims of  

E-Print Network [OSTI]

#12;Peak Oil Netherlands Foundation (PONL) was founded in May 2005 by a group of citizens who are concerned about the effects of a premature peak in oil and other fossil fuels production. The main aims of this report, the other people in the Peak Oil Netherlands Foundation for their work, peakoil.com & the oildrum

Keeling, Stephen L.

459

Million Cu. Feet Percent of National Total  

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

8 8 Illinois - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S15. Summary statistics for natural gas - Illinois, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 45 51 50 40 40 Production (million cubic feet) Gross Withdrawals From Gas Wells E 1,188 E 1,438 E 1,697 2,114 2,125 From Oil Wells E 5 E 5 E 5 7 0 From Coalbed Wells E 0 E 0 0 0 0 From Shale Gas Wells 0

460

Million Cu. Feet Percent of National Total  

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

50 50 North Dakota - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S36. Summary statistics for natural gas - North Dakota, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 194 196 188 239 211 Production (million cubic feet) Gross Withdrawals From Gas Wells 13,738 11,263 10,501 14,287 22,261 From Oil Wells 54,896 45,776 38,306 27,739 17,434 From Coalbed Wells 0

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

Million Cu. Feet Percent of National Total  

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

0 0 Mississippi - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S26. Summary statistics for natural gas - Mississippi, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 2,343 2,320 1,979 5,732 1,669 Production (million cubic feet) Gross Withdrawals From Gas Wells 331,673 337,168 387,026 429,829 404,457 From Oil Wells 7,542 8,934 8,714 8,159 43,421 From Coalbed Wells 7,250

462

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Virginia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S48. Summary statistics for natural gas - Virginia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 5,735 6,426 7,303 7,470 7,903 Production (million cubic feet) Gross Withdrawals From Gas Wells R 6,681 R 7,419 R 16,046 R 23,086 20,375 From Oil Wells 0 0 0 0 0 From Coalbed Wells R 86,275 R 101,567

463

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Michigan - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S24. Summary statistics for natural gas - Michigan, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 9,712 9,995 10,600 10,100 11,100 Production (million cubic feet) Gross Withdrawals From Gas Wells R 80,090 R 16,959 R 20,867 R 7,345 18,470 From Oil Wells 54,114 10,716 12,919 9,453 11,620 From Coalbed Wells 0

464

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Montana - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S28. Summary statistics for natural gas - Montana, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 6,925 7,095 7,031 6,059 6,477 Production (million cubic feet) Gross Withdrawals From Gas Wells R 69,741 R 67,399 R 57,396 R 51,117 37,937 From Oil Wells 23,092 22,995 21,522 19,292 21,777 From Coalbed Wells

465

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Mississippi - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S26. Summary statistics for natural gas - Mississippi, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 2,315 2,343 2,320 1,979 5,732 Production (million cubic feet) Gross Withdrawals From Gas Wells R 259,001 R 331,673 R 337,168 R 387,026 429,829 From Oil Wells 6,203 7,542 8,934 8,714 8,159 From Coalbed Wells

466

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Indiana - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S16. Summary statistics for natural gas - Indiana, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 2,350 525 563 620 914 Production (million cubic feet) Gross Withdrawals From Gas Wells 3,606 4,701 4,927 6,802 9,075 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0 0 0 0 0 From Shale Gas Wells 0

467

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 New York - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S34. Summary statistics for natural gas - New York, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 6,680 6,675 6,628 6,736 6,157 Production (million cubic feet) Gross Withdrawals From Gas Wells 54,232 49,607 44,273 35,163 30,495 From Oil Wells 710 714 576 650 629 From Coalbed Wells 0

468

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Texas - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S45. Summary statistics for natural gas - Texas, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 76,436 87,556 93,507 95,014 100,966 Production (million cubic feet) Gross Withdrawals From Gas Wells R 4,992,042 R 5,285,458 R 4,860,377 R 4,441,188 3,794,952 From Oil Wells 704,092 745,587 774,821 849,560 1,073,301

469

Million Cu. Feet Percent of National Total  

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

2 2 Ohio - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S37. Summary statistics for natural gas - Ohio, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 34,416 34,963 34,931 46,717 35,104 Production (million cubic feet) Gross Withdrawals From Gas Wells 79,769 83,511 73,459 30,655 65,025 From Oil Wells 5,072 5,301 4,651 45,663 6,684 From Coalbed Wells 0

470

Million Cu. Feet Percent of National Total  

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

0 0 Colorado - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S6. Summary statistics for natural gas - Colorado, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 25,716 27,021 28,813 30,101 32,000 Production (million cubic feet) Gross Withdrawals From Gas Wells 496,374 459,509 526,077 563,750 1,036,572 From Oil Wells 199,725 327,619 338,565

471

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 South Dakota - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S43. Summary statistics for natural gas - South Dakota, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 71 71 89 102 100 Production (million cubic feet) Gross Withdrawals From Gas Wells 422 R 1,098 R 1,561 1,300 933 From Oil Wells 11,458 10,909 11,366 11,240 11,516 From Coalbed Wells 0 0

472

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Illinois - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S15. Summary statistics for natural gas - Illinois, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 43 45 51 50 40 Production (million cubic feet) Gross Withdrawals From Gas Wells RE 1,389 RE 1,188 RE 1,438 RE 1,697 2,114 From Oil Wells E 5 E 5 E 5 E 5 7 From Coalbed Wells RE 0 RE

473

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Colorado - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S6. Summary statistics for natural gas - Colorado, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 22,949 25,716 27,021 28,813 30,101 Production (million cubic feet) Gross Withdrawals From Gas Wells R 436,330 R 496,374 R 459,509 R 526,077 563,750 From Oil Wells 160,833 199,725 327,619

474

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Alaska - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S2. Summary statistics for natural gas - Alaska, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 239 261 261 269 277 Production (million cubic feet) Gross Withdrawals From Gas Wells 165,624 150,483 137,639 127,417 112,268 From Oil Wells 3,313,666 3,265,401 3,174,747 3,069,683 3,050,654

475

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

0 0 Ohio - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S37. Summary statistics for natural gas - Ohio, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 34,416 34,416 34,963 34,931 46,717 Production (million cubic feet) Gross Withdrawals From Gas Wells R 82,812 R 79,769 R 83,511 R 73,459 30,655 From Oil Wells 5,268 5,072 5,301 4,651 45,663 From Coalbed Wells

476

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

4 4 Kentucky - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S19. Summary statistics for natural gas - Kentucky, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 16,563 16,290 17,152 17,670 14,632 Production (million cubic feet) Gross Withdrawals From Gas Wells 95,437 R 112,587 R 111,782 133,521 122,578 From Oil Wells 0 1,529 1,518 1,809 1,665 From Coalbed Wells 0

477

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

8 8 Utah - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S46. Summary statistics for natural gas - Utah, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 5,197 5,578 5,774 6,075 6,469 Production (million cubic feet) Gross Withdrawals From Gas Wells R 271,890 R 331,143 R 340,224 R 328,135 351,168 From Oil Wells 35,104 36,056 36,795 42,526 49,947 From Coalbed Wells

478

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 California - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S5. Summary statistics for natural gas - California, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 1,540 1,645 1,643 1,580 1,308 Production (million cubic feet) Gross Withdrawals From Gas Wells 93,249 91,460 82,288 73,017 63,902 From Oil Wells R 116,652 R 122,345 R 121,949 R 151,369 120,880

479

Million Cu. Feet Percent of National Total  

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

0 0 Utah - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S46. Summary statistics for natural gas - Utah, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 5,578 5,774 6,075 6,469 6,900 Production (million cubic feet) Gross Withdrawals From Gas Wells 331,143 340,224 328,135 351,168 402,899 From Oil Wells 36,056 36,795 42,526 49,947 31,440 From Coalbed Wells 74,399

480

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Louisiana - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S20. Summary statistics for natural gas - Louisiana, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 18,145 19,213 18,860 19,137 21,235 Production (million cubic feet) Gross Withdrawals From Gas Wells R 1,261,539 R 1,288,559 R 1,100,007 R 911,967 883,712 From Oil Wells 106,303 61,663 58,037 63,638 68,505

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481

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 Oklahoma - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S38. Summary statistics for natural gas - Oklahoma, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 38,364 41,921 43,600 44,000 41,238 Production (million cubic feet) Gross Withdrawals From Gas Wells R 1,583,356 R 1,452,148 R 1,413,759 R 1,140,111 1,281,794 From Oil Wells 35,186 153,227 92,467 210,492 104,703

482

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

2 2 New Mexico - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S33. Summary statistics for natural gas - New Mexico, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 42,644 44,241 44,784 44,748 32,302 Production (million cubic feet) Gross Withdrawals From Gas Wells R 657,593 R 732,483 R 682,334 R 616,134 556,024 From Oil Wells 227,352 211,496 223,493 238,580 252,326

483

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 West Virginia - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S50. Summary statistics for natural gas - West Virginia, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 48,215 49,364 50,602 52,498 56,813 Production (million cubic feet) Gross Withdrawals From Gas Wells R 189,968 R 191,444 R 192,896 R 151,401 167,113 From Oil Wells 701 0 0 0 0 From Coalbed Wells

484

Million Cu. Feet Percent of National Total  

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

6 6 Michigan - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S24. Summary statistics for natural gas - Michigan, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 9,995 10,600 10,100 11,100 10,900 Production (million cubic feet) Gross Withdrawals From Gas Wells 16,959 20,867 7,345 18,470 17,041 From Oil Wells 10,716 12,919 9,453 11,620 4,470 From Coalbed Wells 0

485

Million Cu. Feet Percent of National Total  

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

8 8 West Virginia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S50. Summary statistics for natural gas - West Virginia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 49,364 50,602 52,498 56,813 50,700 Production (million cubic feet) Gross Withdrawals From Gas Wells 191,444 192,896 151,401 167,113 397,313 From Oil Wells 0 0 0 0 1,477 From Coalbed Wells 0

486

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

80 80 Wyoming - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S52. Summary statistics for natural gas - Wyoming, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 27,350 28,969 25,710 26,124 26,180 Production (million cubic feet) Gross Withdrawals From Gas Wells R 1,649,284 R 1,764,084 R 1,806,807 R 1,787,599 1,709,218 From Oil Wells 159,039 156,133 135,269 151,871 152,589

487

Million Cu. Feet Percent of National Total  

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

6 6 New York - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S34. Summary statistics for natural gas - New York, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6,675 6,628 6,736 6,157 7,176 Production (million cubic feet) Gross Withdrawals From Gas Wells 49,607 44,273 35,163 30,495 25,985 From Oil Wells 714 576 650 629 439 From Coalbed Wells 0

488

Million Cu. Feet Percent of National Total  

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

2 2 Wyoming - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S52. Summary statistics for natural gas - Wyoming, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 28,969 25,710 26,124 26,180 22,171 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,764,084 1,806,807 1,787,599 1,709,218 1,762,095 From Oil Wells 156,133 135,269 151,871 152,589 24,544

489

Million Cu. Feet Percent of National Total  

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

4 4 Virginia - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S48. Summary statistics for natural gas - Virginia, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6,426 7,303 7,470 7,903 7,843 Production (million cubic feet) Gross Withdrawals From Gas Wells 7,419 16,046 23,086 20,375 21,802 From Oil Wells 0 0 0 0 9 From Coalbed Wells 101,567 106,408

490

Million Cu. Feet Percent of National Total  

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

6 6 Kentucky - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S19. Summary statistics for natural gas - Kentucky, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 16,290 17,152 17,670 14,632 17,936 Production (million cubic feet) Gross Withdrawals From Gas Wells 112,587 111,782 133,521 122,578 106,122 From Oil Wells 1,529 1,518 1,809 1,665 0 From Coalbed Wells 0

491

Million Cu. Feet Percent of National Total  

Gasoline and Diesel Fuel Update (EIA)

6 6 Pennsylvania - Natural Gas 2011 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S40. Summary statistics for natural gas - Pennsylvania, 2007-2011 2007 2008 2009 2010 2011 Number of Producing Gas Wells at End of Year 52,700 55,631 57,356 44,500 54,347 Production (million cubic feet) Gross Withdrawals From Gas Wells 182,277 R 188,538 R 184,795 R 173,450 242,305 From Oil Wells 0 0 0 0 0 From Coalbed Wells 0

492

Total synthesis and study of myrmicarin alkaloids  

E-Print Network [OSTI]

I. Enantioselective Total Synthesis of Tricyclic Myrmicarin Alkaloids An enantioselective gram-scale synthesis of a key dihydroindolizine intermediate for the preparation of myrmicarin alkaloids is described. Key transformations ...

Ondrus, Alison Evelynn, 1981-

2009-01-01T23:59:59.000Z

493

Total synthesis of cyclotryptamine and diketopiperazine alkaloids  

E-Print Network [OSTI]

I. Total Synthesis of the (+)-12,12'-Dideoxyverticillin A The fungal metabolite (+)-12,12'-dideoxyverticillin A, a cytotoxic alkaloid isolated from a marine Penicillium sp., belongs to a fascinating family of densely ...

Kim, Justin, Ph. D. Massachusetts Institute of Technology

2013-01-01T23:59:59.000Z

494

Provides Total Tuition Charge to Source Contribution  

E-Print Network [OSTI]

,262 1,938 TGR 4-20 0-3 2,871 2,871 - % of time appointed Hours of Work/Week Units TAL Provides Total

Kay, Mark A.

495

Enantioselective Total Synthesis of (?)-Acylfulvene and (?)- Irofulven  

E-Print Network [OSTI]

We report our full account of the enantioselective total synthesis of (?)-acylfulvene (1) and (?)-irofulven (2), which features metathesis reactions for the rapid assembly of the molecular framework of these antitumor ...

Movassaghi, Mohammad

496

A GENUINELY HIGH ORDER TOTAL VARIATION DIMINISHING ...  

E-Print Network [OSTI]

(TVD) schemes solving one-dimensional scalar conservation laws degenerate to first order .... where the total variation is measured by the standard bounded variation ..... interval Ij and into the jump discontinuities at cell interfaces, see [12].

497

Million Cu. Feet Percent of National Total  

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

8 8 Texas - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S45. Summary statistics for natural gas - Texas, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 87,556 93,507 95,014 100,966 96,617 Production (million cubic feet) Gross Withdrawals From Gas Wells 5,285,458 4,860,377 4,441,188 3,794,952 3,619,901 From Oil Wells 745,587 774,821 849,560 1,073,301 860,675

498

Million Cu. Feet Percent of National Total  

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

0 0 Alabama - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S1. Summary statistics for natural gas - Alabama, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 6,860 6,913 7,026 7,063 6,327 Production (million cubic feet) Gross Withdrawals From Gas Wells 158,964 142,509 131,448 116,872 114,407 From Oil Wells 6,368 5,758 6,195 5,975 10,978

499

Million Cu. Feet Percent of National Total  

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

8 8 Louisiana - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S20. Summary statistics for natural gas - Louisiana, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 19,213 18,860 19,137 21,235 19,792 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,288,559 1,100,007 911,967 883,712 775,506 From Oil Wells 61,663 58,037 63,638 68,505 49,380

500

Million Cu. Feet Percent of National Total  

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

4 4 South Dakota - Natural Gas 2012 Million Cu. Feet Percent of National Total Million Cu. Feet Percent of National Total Total Net Movements: - Industrial: Dry Production: Vehicle Fuel: Deliveries to Consumers: Residential: Electric Power: Commercial: Total Delivered: Table S43. Summary statistics for natural gas - South Dakota, 2008-2012 2008 2009 2010 2011 2012 Number of Producing Gas Wells at End of Year 71 89 102 100 95 Production (million cubic feet) Gross Withdrawals From Gas Wells 1,098 1,561 1,300 933 14,396 From Oil Wells 10,909 11,366 11,240 11,516 689 From Coalbed Wells 0 0 0 0 0