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Note: This page contains sample records for the topic "model output location" 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.


1

Modeling Multi Output Filtering Effects in PCMOS  

E-Print Network [OSTI]

Modeling Multi Output Filtering Effects in PCMOS Anshul Singh*, Arindam Basu, Keck-Voon Ling, Nanyang Technological University (NTU), Singapore *NTU-Rice Institute of Sustainable and Applied Infodynamics (ISAID), NTU, Singapore $School of Computer Engineering, NTU, Singapore §School of ECE, Georgia

Mooney, Vincent

2

Community Climate System Model (CCSM) Experiments and Output Data  

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

The CCSM web makes the source code of various versions of the model freely available and provides access to experiments that have been run and the resulting output data.

3

Formalization of computer input and output: the Hadley model  

Science Journals Connector (OSTI)

Current digital evidence acquisition tools are effective, but are tested rather than formally proven correct. We assert that the forensics community will benefit in evidentiary ways and the scientific community will benefit in practical ways by moving beyond simple testing of systems to a formal model. To this end, we present a hierarchical model of peripheral input to and output from von Neumann computers, patterned after the Open Systems Interconnection model of networking. The Hadley model categorizes all components of peripheral input and output in terms of data flow; with constructive aspects concentrated in the data flow between primary memory and the computer sides of peripherals' interfaces. The constructive domain of Hadley is eventually expandable to all areas of the I/O hierarchy, allowing for a full view of peripheral input and output and enhancing the forensics community's capabilities to analyze, obtain, and give evidentiary force to data.

Matthew Gerber; John Leeson

2004-01-01T23:59:59.000Z

4

MODELING MULTI-OUTPUT FILTERING EFFECTS IN PCMOS Anshul Singh*  

E-Print Network [OSTI]

MODELING MULTI-OUTPUT FILTERING EFFECTS IN PCMOS Anshul Singh* , Arindam Basu , Keck-Voon Ling* and Vincent J. Mooney III*$§ Email: anshul.singh@research.iiit.ac.in, {arindam.basu, ekvling}@ntu, Nanyang Technological University (NTU), Singapore * NTU-Rice Institute of Sustainable and Applied

Mooney, Vincent

5

Interpreting and analyzing model output (A very cursory introduction) Here will talk briefly about using "ncview" and "matlab" to analyze output  

E-Print Network [OSTI]

using "ncview" and "matlab" to analyze output from your model. The model output is in netcdf format for the output. I use matlab to measure, plot, compute, etc.. Recall the the model output is stored in: /scratch shown at the top.) matlab I hope you have some experience with matlab. There are handy tutorials

Gerber, Edwin

6

Statistical post processing of model output from the air quality model LOTOS-EUROS  

E-Print Network [OSTI]

Statistical post processing of model output from the air quality model LOTOS-EUROS Annemiek processing of model output from the air quality model LOTOS-EUROS Author: Annemiek Pijnappel Supervisor summary Air quality forecasts are produced routinely, focusing on concentrations of polluting gases

Stoffelen, Ad

7

Measurement and Modeling of Solar and PV Output Variability: Preprint  

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

Measurement and Modeling of Measurement and Modeling of Solar and PV Output Variability Preprint M. Sengupta To be presented at SOLAR 2011 Raleigh, North Carolina May 17-21, 2011 Conference Paper NREL/CP-5500-51105 April 2011 NOTICE The submitted manuscript has been offered by an employee of the Alliance for Sustainable Energy, LLC (Alliance), a contractor of the US Government under Contract No. DE-AC36-08GO28308. Accordingly, the US Government and Alliance retain a nonexclusive royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for US Government purposes. This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty,

8

FORMALIZATION OF INPUT AND OUTPUT IN MODERN OPERATING SYSTEMS: THE HADLEY MODEL.  

E-Print Network [OSTI]

??We present the Hadley model, a formal descriptive model of input and output for modern computer operating systems. Our model is intentionally inspired by the (more)

Gerber, Matthew

2005-01-01T23:59:59.000Z

9

Addressing endogeneity in residential location models  

E-Print Network [OSTI]

Some empirical residential location choice models have reported dwelling-unit price estimated parameters that are small, not statistically significant, or even positive. This would imply that households are non-sensitive ...

Guevara-Cue, Cristin Angelo

2005-01-01T23:59:59.000Z

10

Linear model-based estimation of blood pressure and cardiac output for Normal and Paranoid cases  

Science Journals Connector (OSTI)

Provisioning a generic simple linear mathematical model for Paranoid and Healthy cases leading to auxiliary investigation of the neuroleptic drugs effect imposed on cardiac output (CO) and blood pressure (BP). Multi-input single output system identification ... Keywords: Blood pressure, Cardiac output, Heart rate, MISO transfer function, Stroke volume, System identification

Mohamed Abdelkader Aboamer, Ahmad Taher Azar, Khaled Wahba, Abdallah S. Mohamed

2014-11-01T23:59:59.000Z

11

An Advanced simulation Code for Modeling Inductive Output Tubes  

SciTech Connect (OSTI)

During the Phase I program, CCR completed several major building blocks for a 3D large signal, inductive output tube (IOT) code using modern computer language and programming techniques. These included a 3D, Helmholtz, time-harmonic, field solver with a fully functional graphical user interface (GUI), automeshing and adaptivity. Other building blocks included the improved electrostatic Poisson solver with temporal boundary conditions to provide temporal fields for the time-stepping particle pusher as well as the self electric field caused by time-varying space charge. The magnetostatic field solver was also updated to solve for the self magnetic field caused by time changing current density in the output cavity gap. The goal function to optimize an IOT cavity was also formulated, and the optimization methodologies were investigated.

Thuc Bui; R. Lawrence Ives

2012-04-27T23:59:59.000Z

12

Investigating Output Accuracy for a Discrete Event Simulation Model and an Agent Based Simulation Model  

E-Print Network [OSTI]

In this paper, we investigate output accuracy for a Discrete Event Simulation (DES) model and Agent Based Simulation (ABS) model. The purpose of this investigation is to find out which of these simulation techniques is the best one for modelling human reactive behaviour in the retail sector. In order to study the output accuracy in both models, we have carried out a validation experiment in which we compared the results from our simulation models to the performance of a real system. Our experiment was carried out using a large UK department store as a case study. We had to determine an efficient implementation of management policy in the store's fitting room using DES and ABS. Overall, we have found that both simulation models were a good representation of the real system when modelling human reactive behaviour.

Majid, Mazlina Abdul; Siebers, Peer-Olaf

2010-01-01T23:59:59.000Z

13

Design of fast output sampling feedback control for smart structure model  

Science Journals Connector (OSTI)

In this paper, the problem of modelling and output feedback control design for a smart structural system using piezoelectric material as a sensor/actuator is addressed. The model for a smart cantilever beam is developed by the finite element method. ... Keywords: output feedback, smart structure, vibration control

M. Umapathy; B. Bandyopadhyay

2007-01-01T23:59:59.000Z

14

Use of Advanced Meteorological Model Output for Coastal Ocean Modeling in Puget Sound  

SciTech Connect (OSTI)

It is a great challenge to specify meteorological forcing in estuarine and coastal circulation modeling using observed data because of the lack of complete datasets. As a result of this limitation, water temperature is often not simulated in estuarine and coastal modeling, with the assumption that density-induced currents are generally dominated by salinity gradients. However, in many situations, temperature gradients could be sufficiently large to influence the baroclinic motion. In this paper, we present an approach to simulate water temperature using outputs from advanced meteorological models. This modeling approach was applied to simulate annual variations of water temperatures of Puget Sound, a fjordal estuary in the Pacific Northwest of USA. Meteorological parameters from North American Region Re-analysis (NARR) model outputs were evaluated with comparisons to observed data at real-time meteorological stations. Model results demonstrated that NARR outputs can be used to drive coastal ocean models for realistic simulations of long-term water-temperature distributions in Puget Sound. Model results indicated that the net flux from NARR can be further improved with the additional information from real-time observations.

Yang, Zhaoqing; Khangaonkar, Tarang; Wang, Taiping

2011-06-01T23:59:59.000Z

15

Probabilistic Forecasts of Wind Speed: Ensemble Model Output Statistics  

E-Print Network [OSTI]

. Over the past two decades, ensembles of numerical weather prediction (NWP) models have been developed and phrases: Continuous ranked probability score; Density forecast; Ensem- ble system; Numerical weather prediction; Heteroskedastic censored regression; Tobit model; Wind energy. 1 #12;1 Introduction Accurate

Washington at Seattle, University of

16

Ensemble regression : using ensemble model output for atmospheric dynamics and prediction  

E-Print Network [OSTI]

Ensemble regression (ER) is a linear inversion technique that uses ensemble statistics from atmospheric model output to make dynamical inferences and forecasts. ER defines a multivariate regression operator using ensemble ...

Gombos, Daniel (Daniel Lawrence)

2009-01-01T23:59:59.000Z

17

Modelling power output at nuclear power plant by neural networks  

Science Journals Connector (OSTI)

In this paper, we propose two different neural network (NN) approaches for industrial process signal forecasting. Real data is available for this research from boiling water reactor type nuclear power reactors. NNs are widely used for time series prediction, ... Keywords: evaluation methods, model input selection, neural networks, nuclear power plant, one-step ahead prediction

Jaakko Talonen; Miki Sirola; Eimontas Augilius

2010-09-01T23:59:59.000Z

18

Neural Networks for Post-processing Model Output: Caren Marzban  

E-Print Network [OSTI]

variables to the neural network are: Forecast hour, model forecast temperature, relative humidity, wind direction and speed, mean sea level pressure, cloud cover, and precipitation rate and amount. The single to being able to approximate a large class of functions, they are less inclined to overfit data than some

Marzban, Caren

19

Effect of ignition location on the in-process removal of combustion deposits from the output window of a gas turbine laser ignition system  

Science Journals Connector (OSTI)

The effect of ignition location on the effectiveness of combustion deposit removal from the reverse side of an optical window in a laser ignition system for use in gas turbines is presented. Such deposits consist of carbon and other by-products which accumulate on the walls of the chamber as a result of incomplete combustion. In laser based ignition systems this accumulation of combustion deposits has the potential to reduce the transmissive properties of the output window required for transmission of the laser radiation into the combustion chamber, adversely affecting the likelihood of successful ignition. In this work, a full empirical study into the in-process removal of combustion deposits from the reverse side of the optical window in a laser ignition system using a Q-switched Nd:YAG laser is presented, with an emphasis on the effect of ignition location on the effectiveness of combustion deposit removal. In addition, the mechanism of deposit removal is discussed.

J. Griffiths; J. Lawrence; P. Fitzsimons

2013-01-01T23:59:59.000Z

20

Resampling of regional climate model output for the simulation of extreme river flows  

E-Print Network [OSTI]

for the simulation of extreme river flows. This is important to assess the impact of climate change on river flooding biases in the RCM data, the simulated extreme flood quantiles correspond quite well with those obtainedResampling of regional climate model output for the simulation of extreme river flows Robert

Haak, Hein

Note: This page contains sample records for the topic "model output location" 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

Probabilistic Forecasting of (Severe) Thunderstorms in the Netherlands Using Model Output Statistics  

E-Print Network [OSTI]

Probabilistic Forecasting of (Severe) Thunderstorms in the Netherlands Using Model Output Statistics MAURICE J. SCHMEITS, KEES J. KOK, AND DAAN H. P. VOGELEZANG Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands (Manuscript received 29 April 2004, in final form 7 September 2004

Schmeits, Maurice

22

Reliability Models for Facility Location: The Expected Failure Cost ...  

E-Print Network [OSTI]

Reliability Models for Facility Location: The Expected Failure Cost Case. Lawrence V. Snyder (larry.snyder ***at*** lehigh.edu) Mark S. Daskin (m-daskin *

Lawrence V. Snyder

23

Using Weather Data and Climate Model Output in Economic Analyses of Climate Change  

SciTech Connect (OSTI)

Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

Auffhammer, Maximilian [University of California at Berkeley; Hsiang, Solomon M. [Princeton University; Schlenker, Wolfram [Columbia University; Sobel, Adam H. [Columbia University

2013-06-28T23:59:59.000Z

24

A MODELING APPROACH FOR LOCATING LOGISTICS PLATFORMS FOR FAST PARCEL  

E-Print Network [OSTI]

1 29 A MODELING APPROACH FOR LOCATING LOGISTICS PLATFORMS FOR FAST PARCEL DELIVERY IN URBAN AREAS for optimizing, in a sustainable way (i.e. economical, eco-friendly and societal), the location of logistics has a logistics platform right in its centre (ARENC: 41362 m2 of warehouses and offices

Paris-Sud XI, Université de

25

Modeling human location data with mixtures of kernel densities  

Science Journals Connector (OSTI)

Location-based data is increasingly prevalent with the rapid increase and adoption of mobile devices. In this paper we address the problem of learning spatial density models, focusing specifically on individual-level data. Modeling and predicting a spatial ... Keywords: anomaly/novelty detection, kernel density estimation, probabilistic methods, social media, spatial, user modeling

Moshe Lichman, Padhraic Smyth

2014-08-01T23:59:59.000Z

26

Scaled Tests and Modeling of Effluent Stack Sampling Location Mixing  

SciTech Connect (OSTI)

The Pacific Northwest National Laboratory researchers used a computational fluid dynamics (CFD) computer code to evaluate the mixing at a sampling system location of a research and development facility. The facility requires continuous sampling for radioactive air emissions. Researchers sought to determine whether the location would meet the criteria for uniform air velocity and contaminant concentration as prescribed in the American National Standard Institute (ANSI) standard, Sampling and Monitoring Releases of Airborne Radioactive Substances from the Stacks and Ducts of Nuclear Facilities. Standard ANSI/HPS N13.1-1999 requires that the sampling location be well-mixed and stipulates specific tests (e.g., velocity, gas, and aerosol uniformity and cyclonic flow angle) to verify the extent of mixing.. The exhaust system for the Radiochemical Processing Laboratory was modeled with a CFD code to better understand the flow and contaminant mixing and to predict mixing test results. The CFD results were compared to actual measurements made at a scale-model stack and to the limited data set for the full-scale facility stack. Results indicated that the CFD code provides reasonably conservative predictions for velocity, gas, and aerosol uniformity. Cyclonic flow predicted by the code is less than that measured by the required methods. In expanding from small to full scale, the CFD predictions for full-scale measurements show similar trends as in the scale model and no unusual effects. This work indicates that a CFD code can be a cost-effective aid in design or retrofit of a facilitys stack sampling location that will be required to meet Standard ANSI/HPS N13.1-1999.

Recknagle, Kurtis P.; Yokuda, Satoru T.; Ballinger, Marcel Y.; Barnett, J. M.

2009-02-01T23:59:59.000Z

27

Cardiac output and stroke volume estimation using a hybrid of three models  

E-Print Network [OSTI]

Cardiac output (CO) and stroke volume (SV) are the key hemodynamic parameters to be monitored and assessed in ambulatory and critically ill patients. The purpose of this study was to introduce and validate a new algorithm ...

Arai, Tatsuya

28

Modelling Dynamic Constraints in Electricity Markets and the Costs of Uncertain Wind Output  

E-Print Network [OSTI]

shifts between periods. Finally, higher variable costs, incurred if power stations are operated below their optimal rating, are allocated to the locally lowest de- mand. For inflexible power stations like nuclear, combined cycle gas turbines or coal... the start of the station has to be decided several hours before delivering output. At the earlier time there is still uncertainty about the future demand, possible failures of power stations and predictions for wind-output. We represent the uncertainty...

Musgens, Felix; Neuhoff, Karsten

2006-03-14T23:59:59.000Z

29

Robust UAV Coordination for Target Tracking using Output-Feedback Model Predictive Control with Moving Horizon Estimation  

E-Print Network [OSTI]

Robust UAV Coordination for Target Tracking using Output-Feedback Model Predictive Control consider the control of two UAVs tracking an evasive moving ground vehicle. The UAVs are small fixed to maintain visibility. The control inputs to the UAVs are computed based on noisy measurements of the UAVs

Hespanha, João Pedro

30

Modeling study of deposition locations in the 291-Z plenum  

SciTech Connect (OSTI)

The TEMPEST (Trent and Eyler 1991) and PART5 computer codes were used to predict the probable locations of particle deposition in the suction-side plenum of the 291-Z building in the 200 Area of the Hanford Site, the exhaust fan building for the 234-5Z, 236-Z, and 232-Z buildings in the 200 Area of the Hanford Site. The Tempest code provided velocity fields for the airflow through the plenum. These velocity fields were then used with TEMPEST to provide modeling of near-floor particle concentrations without particle sticking (100% resuspension). The same velocity fields were also used with PART5 to provide modeling of particle deposition with sticking (0% resuspension). Some of the parameters whose importance was tested were particle size, point of injection and exhaust fan configuration.

Mahoney, L.A.; Glissmeyer, J.A.

1994-06-01T23:59:59.000Z

31

Output Analysis  

Science Journals Connector (OSTI)

Every discrete-event simulation experiment with random input generates random sample paths as output. Each path usually consists of a sequence of dependent observations that serve as the raw material for estim...

George S. Fishman

2001-01-01T23:59:59.000Z

32

Scalable extraction of error models from the output of error detection circuits  

E-Print Network [OSTI]

Accurate methods of assessing the performance of quantum gates are extremely important. Quantum process tomography and randomized benchmarking are the current favored methods. Quantum process tomography gives detailed information, but significant approximations must be made to reduce this information to a form quantum error correction simulations can use. Randomized benchmarking typically outputs just a single number, the fidelity, giving no information on the structure of errors during the gate. Neither method is optimized to assess gate performance within an error detection circuit, where gates will be actually used in a large-scale quantum computer. Specifically, the important issues of error composition and error propagation lie outside the scope of both methods. We present a fast, simple, and scalable method of obtaining exactly the information required to perform effective quantum error correction from the output of continuously running error detection circuits, enabling accurate prediction of large-scale behavior.

Austin G. Fowler; D. Sank; J. Kelly; R. Barends; John M. Martinis

2014-05-06T23:59:59.000Z

33

SAS Output  

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

B. Landfill Gas: Consumption for Useful Thermal Output, B. Landfill Gas: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Million Cubic Feet) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 993 0 116 0 876 2004 2,174 0 735 10 1,429 2005 1,923 0 965 435 522 2006 2,051 0 525 1,094 433 2007 1,988 0 386 1,102 501 2008 1,025 0 454 433 138 2009 793 0 545 176 72 2010 1,623 0 1,195 370 58 2011 3,195 0 2,753 351 91 2012 3,189 0 2,788 340 61 2010 January 118 0 83 30 5 February 110 0 79 27 5 March 132 0 94 32 6 April 131 0 93 33 6 May 132 0 92 34 6 June 139 0 104 30 5 July 140 0 102 33 5 August 132 0 95 32 5 September 148 0 113 30 5

34

SAS Output  

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

B. Petroleum Coke: Consumption for Useful Thermal Output, B. Petroleum Coke: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 517 0 111 6 399 2003 763 0 80 9 675 2004 1,043 0 237 8 798 2005 783 0 206 8 568 2006 1,259 0 195 9 1,055 2007 1,262 0 162 11 1,090 2008 897 0 119 9 769 2009 1,007 0 126 8 873 2010 1,059 0 98 11 950 2011 1,080 0 112 6 962 2012 1,346 0 113 11 1,222 2010 January 92 0 10 1 81 February 93 0 10 1 82 March 84 0 12 1 71 April 76 0 9 1 66 May 84 0 10 0 75 June 93 0 8 0 86 July 89 0 8 0 80 August 87 0 2 1 84 September 82 0 2 1 79

35

SAS Output  

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

F. Petroleum Coke: Consumption for Electricity Generation and Useful Thermal Output, F. Petroleum Coke: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 193,120 57,296 105,416 227 30,182 2003 197,827 69,695 92,384 309 35,440 2004 245,389 116,086 90,747 259 38,297 2005 256,441 115,727 111,098 260 29,356 2006 246,687 102,117 98,314 269 45,987 2007 208,198 77,941 81,845 348 48,064 2008 180,034 64,843 79,856 280 35,055 2009 166,449 77,919 52,428 245 35,856 2010 173,078 94,331 41,090 340 37,317 2011 176,349 99,257 40,167 173 36,752 2012 144,266 60,862 24,925 353 58,126 2010 January 14,949 7,995 3,716 38 3,199

36

SAS Output  

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

C. Coal: Consumption for Electricity Generation and Useful Thermal Output, C. Coal: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 1,005,144 767,803 209,703 1,405 26,232 2003 1,031,778 757,384 247,732 1,816 24,846 2004 1,044,798 772,224 244,044 1,917 26,613 2005 1,065,281 761,349 276,135 1,922 25,875 2006 1,053,783 753,390 273,246 1,886 25,262 2007 1,069,606 764,765 280,377 1,927 22,537 2008 1,064,503 760,326 280,254 2,021 21,902 2009 955,190 695,615 238,012 1,798 19,766 2010 1,001,411 721,431 253,621 1,720 24,638 2011 956,470 689,316 243,168 1,668 22,319 2012 845,066 615,467 208,085 1,450 20,065

37

SAS Output  

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

E. Landfill Gas: Consumption for Useful Thermal Output, E. Landfill Gas: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 500 0 61 0 439 2004 1,158 0 415 5 738 2005 994 0 519 212 263 2006 1,034 0 267 549 218 2007 985 0 226 532 228 2008 552 0 271 211 70 2009 440 0 313 91 37 2010 847 0 643 174 30 2011 1,635 0 1,422 165 48 2012 1,630 0 1,441 156 32 2010 January 61 0 44 14 3 February 58 0 42 13 3 March 67 0 49 15 3 April 67 0 49 15 3 May 68 0 49 16 3 June 73 0 56 14 3 July 73 0 55 16 2 August 69 0 52 15 3 September 79 0 62 14 3 October 75 0 59 14 2

38

SAS Output  

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

B. Coal: Consumption for Useful Thermal Output, B. Coal: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 17,561 0 2,255 929 14,377 2003 17,720 0 2,080 1,234 14,406 2004 24,275 0 3,809 1,540 18,926 2005 23,833 0 3,918 1,544 18,371 2006 23,227 0 3,834 1,539 17,854 2007 22,810 0 3,795 1,566 17,449 2008 22,168 0 3,689 1,652 16,827 2009 20,507 0 3,935 1,481 15,091 2010 21,727 0 3,808 1,406 16,513 2011 21,532 0 3,628 1,321 16,584 2012 19,333 0 2,790 1,143 15,400 2010 January 1,972 0 371 160 1,440 February 1,820 0 347 139 1,334 March 1,839 0 338 123 1,378 April 2,142 0 284 95 1,764

39

SAS Output  

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

E. Petroleum Liquids: Consumption for Useful Thermal Output, E. Petroleum Liquids: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 76,737 0 1,669 3,276 71,788 2003 85,488 0 6,963 3,176 75,349 2004 124,809 0 8,592 7,219 108,997 2005 125,689 0 8,134 6,145 111,410 2006 87,137 0 6,740 3,481 76,916 2007 82,768 0 7,602 2,754 72,412 2008 45,481 0 7,644 2,786 35,051 2009 48,912 0 7,557 1,802 39,552 2010 29,243 0 6,402 1,297 21,545 2011 22,799 0 5,927 1,039 15,833 2012 18,233 0 5,871 746 11,616 2010 January 3,648 0 614 190 2,843 February 3,027 0 422 157 2,447 March 2,015 0 272 43 1,699

40

SAS Output  

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

C. Petroleum Liquids: Consumption for Electricity Generation and Useful Thermal Output, C. Petroleum Liquids: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Barrels) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 146,643 88,595 39,320 1,210 17,517 2003 189,260 105,319 62,617 1,394 19,929 2004 185,761 103,793 57,843 1,963 22,162 2005 185,631 98,223 63,546 1,584 22,278 2006 87,898 53,529 18,332 886 15,150 2007 95,895 56,910 24,097 691 14,198 2008 61,379 38,995 14,463 621 7,300 2009 51,690 31,847 11,181 477 8,185 2010 44,968 30,806 9,364 376 4,422 2011 31,152 20,844 6,637 301 3,370 2012 25,702 17,521 5,102 394 2,685 2010 January 6,193 4,381 1,188 48 576

Note: This page contains sample records for the topic "model output location" 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

SAS Output  

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

E. Wood / Wood Waste Biomass: Consumption for Useful Thermal Output, E. Wood / Wood Waste Biomass: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 682,060 0 9,585 727 671,747 2003 746,375 0 10,893 762 734,720 2004 1,016,124 0 14,968 1,493 999,663 2005 997,331 0 19,193 1,028 977,111 2006 1,049,161 0 18,814 1,045 1,029,303 2007 982,486 0 21,435 1,756 959,296 2008 923,889 0 18,075 1,123 904,690 2009 816,285 0 19,587 1,135 795,563 2010 876,041 0 18,357 1,064 856,620 2011 893,314 0 16,577 1,022 875,716 2012 883,158 0 19,251 949 862,958 2010 January 73,418 0 1,677 91 71,651 February 67,994 0 1,689 81 66,224

42

SAS Output  

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

F. Landfill Gas: Consumption for Electricity Generation and Useful Thermal Output, F. Landfill Gas: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 66,270 3,930 59,149 1,753 1,438 2004 70,489 5,373 60,929 2,098 2,089 2005 68,897 5,650 59,144 2,571 1,532 2006 77,004 8,287 64,217 3,937 563 2007 80,697 8,620 68,657 2,875 544 2008 94,768 10,242 81,300 2,879 346 2009 100,261 9,748 87,086 3,089 337 2010 106,681 10,029 93,405 3,011 236 2011 114,173 11,146 91,279 11,497 251 2012 125,927 12,721 101,379 10,512 1,315 2010 January 8,502 853 7,379 251 19 February 7,882 830 6,823 209 20

43

SAS Output  

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

E. Other Waste Biomass: Consumption for Useful Thermal Output, E. Other Waste Biomass: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 29,854 0 10,655 757 18,442 2004 30,228 0 12,055 2,627 15,547 2005 38,010 0 10,275 2,086 25,649 2006 36,966 0 8,561 2,318 26,087 2007 41,757 0 10,294 2,643 28,820 2008 41,851 0 9,674 1,542 30,635 2009 41,810 0 10,355 1,638 29,817 2010 47,153 0 8,436 1,648 37,070 2011 43,483 0 6,460 1,566 35,458 2012 46,863 0 6,914 1,796 38,153 2010 January 4,885 0 1,088 137 3,661 February 4,105 0 943 137 3,025 March 4,398 0 845 136 3,417 April 4,224 0 399 138 3,688

44

SAS Output  

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

E. Petroleum Coke: Consumption for Useful Thermal Output, E. Petroleum Coke: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 14,395 0 3,192 179 11,024 2003 21,170 0 2,282 244 18,644 2004 29,342 0 6,768 226 22,347 2005 22,224 0 5,935 228 16,061 2006 38,169 0 5,672 236 32,262 2007 38,033 0 4,710 303 33,019 2008 27,100 0 3,441 243 23,416 2009 29,974 0 3,652 213 26,109 2010 31,303 0 2,855 296 28,152 2011 31,943 0 3,244 153 28,546 2012 38,777 0 3,281 315 35,181 2010 January 2,683 0 285 33 2,365 February 2,770 0 302 29 2,439 March 2,424 0 338 36 2,050 April 2,257 0 255 22 1,980

45

SAS Output  

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

F. Other Waste Biomass: Consumption for Electricity Generation and Useful Thermal Output, F. Other Waste Biomass: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 64,629 2,456 26,514 5,323 30,337 2004 49,443 2,014 21,294 6,935 19,201 2005 55,862 2,485 17,640 6,763 28,974 2006 54,693 2,611 16,348 6,755 28,980 2007 60,840 2,992 19,155 6,692 32,001 2008 66,139 3,409 22,419 5,227 35,085 2009 66,658 3,679 23,586 5,398 33,994 2010 77,150 3,668 22,884 5,438 45,159 2011 74,255 4,488 22,574 5,382 41,810 2012 77,205 4,191 22,654 5,812 44,548 2010 January 7,109 189 2,166 458 4,295 February 6,441 275 2,151 429 3,586

46

SAS Output  

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

F. Natural Gas: Consumption for Electricity Generation and Useful Thermal Output, F. Natural Gas: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 7,135,572 2,307,358 3,481,961 75,985 1,270,268 2003 6,498,549 1,809,003 3,450,177 60,662 1,178,707 2004 6,912,661 1,857,247 3,749,945 73,744 1,231,725 2005 7,220,520 2,198,098 3,837,717 69,682 1,115,023 2006 7,612,500 2,546,169 3,847,644 69,401 1,149,286 2007 8,181,986 2,808,500 4,219,827 71,560 1,082,099 2008 7,900,986 2,803,283 4,046,069 67,571 984,062 2009 8,138,385 2,981,285 4,062,633 77,077 1,017,390 2010 8,694,186 3,359,035 4,191,241 87,357 1,056,553

47

SAS Output  

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

B. Biogenic Municipal Solid Waste: Consumption for Useful Thermal Output, B. Biogenic Municipal Solid Waste: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 1,358 0 311 865 182 2004 2,743 0 651 1,628 464 2005 2,719 0 623 1,536 560 2006 2,840 0 725 1,595 520 2007 2,219 0 768 1,136 315 2008 2,328 0 806 1,514 8 2009 2,426 0 823 1,466 137 2010 2,287 0 819 1,316 152 2011 2,044 0 742 1,148 154 2012 1,986 0 522 1,273 190 2010 January 191 0 69 107 14 February 178 0 61 106 11 March 204 0 66 126 12 April 207 0 67 127 13 May 249 0 67 167 15 June 204 0 69 120 14 July 194 0 68 115 11

48

SAS Output  

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

C. Landfill Gas: Consumption for Electricity Generation and Useful Thermal Output, C. Landfill Gas: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Million Cubic Feet) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 137,414 9,168 122,100 3,280 2,865 2004 146,018 11,250 126,584 4,091 4,093 2005 143,822 11,490 124,030 5,232 3,070 2006 162,084 16,617 136,632 7,738 1,096 2007 168,762 17,442 144,490 5,699 1,131 2008 196,802 20,465 170,001 5,668 668 2009 207,585 19,583 181,234 6,106 661 2010 219,954 19,975 193,623 5,905 451 2011 235,990 22,086 183,609 29,820 474 2012 259,564 25,193 204,753 27,012 2,606 2010 January 17,649 1,715 15,406 491 37 February 16,300 1,653 14,198 410 38

49

SAS Output  

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

C. Petroleum Coke: Consumption for Electricity Generation and Useful Thermal Output, C. Petroleum Coke: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 7,353 2,125 3,691 8 1,529 2003 7,067 2,554 3,245 11 1,257 2004 8,721 4,150 3,223 9 1,339 2005 9,113 4,130 3,953 9 1,020 2006 8,622 3,619 3,482 10 1,511 2007 7,299 2,808 2,877 12 1,602 2008 6,314 2,296 2,823 10 1,184 2009 5,828 2,761 1,850 9 1,209 2010 6,053 3,325 1,452 12 1,264 2011 6,092 3,449 1,388 6 1,248 2012 5,021 2,105 869 13 2,034 2010 January 525 283 130 1 110 February 497 258 131 1 106 March 522 308 119 1 94

50

SAS Output  

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

E. Biogenic Municipal Solid Waste: Consumption for Useful Thermal Output, E. Biogenic Municipal Solid Waste: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 13,694 0 3,118 8,858 1,718 2004 19,991 0 4,746 12,295 2,950 2005 20,296 0 4,551 11,991 3,754 2006 21,729 0 5,347 12,654 3,728 2007 16,174 0 5,683 8,350 2,141 2008 18,272 0 6,039 12,174 59 2009 18,785 0 6,229 11,535 1,021 2010 17,502 0 6,031 10,333 1,138 2011 16,766 0 5,807 9,731 1,227 2012 16,310 0 4,180 10,615 1,515 2010 January 1,476 0 518 851 107 February 1,365 0 444 835 86 March 1,572 0 486 992 93 April 1,598 0 495 1,003 100

51

SAS Output  

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

B. Petroleum Liquids: Consumption for Useful Thermal Output, B. Petroleum Liquids: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Barrels) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 12,228 0 286 384 11,558 2003 14,124 0 1,197 512 12,414 2004 20,654 0 1,501 1,203 17,951 2005 20,494 0 1,392 1,004 18,097 2006 14,077 0 1,153 559 12,365 2007 13,462 0 1,303 441 11,718 2008 7,533 0 1,311 461 5,762 2009 8,128 0 1,301 293 6,534 2010 4,866 0 1,086 212 3,567 2011 3,826 0 1,004 168 2,654 2012 3,097 0 992 122 1,984 2010 January 606 0 105 31 470 February 504 0 78 26 401 March 335 0 46 7 281 April 355 0 86 9 260 May 340 0 93 14 232

52

SAS Output  

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

E. Natural Gas: Consumption for Useful Thermal Output, E. Natural Gas: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 885,987 0 267,675 45,359 572,953 2003 762,779 0 250,120 21,238 491,421 2004 1,085,191 0 398,476 40,122 646,593 2005 1,008,404 0 392,842 35,037 580,525 2006 968,574 0 339,047 33,928 595,599 2007 894,272 0 347,181 36,689 510,402 2008 813,794 0 333,197 33,434 447,163 2009 836,863 0 312,553 42,032 482,279 2010 841,521 0 308,246 47,001 486,274 2011 861,006 0 315,411 40,976 504,619 2012 909,087 0 330,354 48,944 529,788 2010 January 74,586 0 27,368 4,148 43,070 February 65,539 0 24,180 3,786 37,573

53

SAS Output  

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

2. Useful Thermal Output by Energy Source: Electric Power Sector Combined Heat and Power, 2002 - 2012 2. Useful Thermal Output by Energy Source: Electric Power Sector Combined Heat and Power, 2002 - 2012 (Billion Btus) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Renewable Sources Other Total Annual Totals 2002 40,020 1,319 2,550 214,137 5,961 12,550 4,732 281,269 2003 38,249 5,551 1,828 200,077 9,282 19,785 3,296 278,068 2004 39,014 5,731 2,486 239,416 18,200 17,347 3,822 326,017 2005 39,652 5,571 2,238 239,324 36,694 18,240 3,884 345,605 2006 38,133 4,812 2,253 207,095 22,567 17,284 4,435 296,579 2007 38,260 5,294 1,862 212,705 20,473 19,166 4,459 302,219 2008 37,220 5,479 1,353 204,167 22,109 17,052 4,854 292,234 2009 38,015 5,341 1,445 190,875 19,830 17,625 5,055 278,187

54

SAS Output  

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

3. Useful Thermal Output by Energy Source: Commerical Sector Combined Heat and Power, 2002 - 2012 3. Useful Thermal Output by Energy Source: Commerical Sector Combined Heat and Power, 2002 - 2012 (Billion Btus) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Renewable Sources Other Total Annual Totals 2002 18,477 2,600 143 36,265 0 6,902 4,801 69,188 2003 22,780 2,520 196 16,955 0 8,296 6,142 56,889 2004 22,450 4,118 165 21,851 0 8,936 6,350 63,871 2005 22,601 3,518 166 20,227 0 8,647 5,921 61,081 2006 22,186 2,092 172 19,370 0.22 9,359 6,242 59,422 2007 22,595 1,640 221 20,040 0 6,651 3,983 55,131 2008 22,991 1,822 177 20,183 0 8,863 6,054 60,091 2009 20,057 1,095 155 25,902 0 8,450 5,761 61,420 2010 19,216 845 216 29,791 13 7,917 5,333 63,330 2011 17,234 687 111 24,848 14 7,433 5,988 56,314

55

SAS Output  

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

F. Petroleum Liquids: Consumption for Electricity Generation and Useful Thermal Output, F. Petroleum Liquids: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 912,218 553,390 243,561 7,229 108,031 2003 1,174,795 658,868 387,341 8,534 120,051 2004 1,156,763 651,712 358,685 11,763 134,603 2005 1,160,733 618,811 395,489 9,614 136,820 2006 546,529 335,130 112,052 5,444 93,903 2007 595,191 355,999 147,579 4,259 87,354 2008 377,848 242,379 87,460 3,743 44,266 2009 315,420 196,346 66,834 2,903 49,336 2010 273,357 188,987 55,444 2,267 26,660 2011 186,753 125,755 39,093 1,840 20,066 2012 153,189 105,179 29,952 2,364 15,695

56

SAS Output  

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

B. Natural Gas: Consumption for Useful Thermal Output, B. Natural Gas: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Million Cubic Feet) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 860,024 0 263,619 41,435 554,970 2003 721,267 0 225,967 19,973 475,327 2004 1,052,100 0 388,424 39,233 624,443 2005 984,340 0 384,365 34,172 565,803 2006 942,817 0 330,878 33,112 578,828 2007 872,579 0 339,796 35,987 496,796 2008 793,537 0 326,048 32,813 434,676 2009 816,787 0 305,542 41,275 469,970 2010 821,775 0 301,769 46,324 473,683 2011 839,681 0 308,669 39,856 491,155 2012 886,103 0 322,607 47,883 515,613 2010 January 72,867 0 26,791 4,086 41,990

57

SAS Output  

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

E. Coal: Consumption for Useful Thermal Output, E. Coal: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 421,084 0 50,041 23,099 347,944 2003 416,700 0 47,817 28,479 340,405 2004 564,497 0 87,981 34,538 441,978 2005 548,666 0 88,364 34,616 425,685 2006 532,561 0 84,335 34,086 414,140 2007 521,717 0 83,838 34,690 403,189 2008 503,096 0 81,416 36,163 385,517 2009 462,674 0 90,867 32,651 339,156 2010 490,931 0 90,184 30,725 370,022 2011 479,822 0 84,855 28,056 366,911 2012 420,923 0 58,275 23,673 338,975 2010 January 44,514 0 8,627 3,445 32,442 February 40,887 0 8,041 3,024 29,823

58

SAS Output  

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

F. Wood / Wood Waste Biomass: Consumption for Electricity Generation and Useful Thermal Output, F. Wood / Wood Waste Biomass: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 1,287,114 10,659 139,532 1,196 1,135,727 2003 1,265,669 16,545 150,745 1,199 1,097,180 2004 1,360,258 19,973 145,216 1,661 1,193,408 2005 1,352,582 27,373 157,600 1,235 1,166,373 2006 1,399,235 27,455 154,360 1,314 1,216,106 2007 1,335,511 31,568 154,388 2,040 1,147,516 2008 1,262,675 29,150 148,198 1,410 1,083,917 2009 1,136,729 29,565 150,481 1,408 955,276 2010 1,225,571 40,167 155,429 1,338 1,028,637 2011 1,240,937 35,474 146,684 1,504 1,057,275

59

SAS Output  

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

1. Useful Thermal Output by Energy Source: Total Combined Heat and Power (All Sectors), 2002 - 2012 1. Useful Thermal Output by Energy Source: Total Combined Heat and Power (All Sectors), 2002 - 2012 (Billion Btus) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Renewable Sources Other Total Annual Totals 2002 336,848 61,313 11,513 708,738 117,513 571,509 48,263 1,855,697 2003 333,361 68,329 16,934 610,122 110,263 632,366 54,960 1,826,335 2004 351,871 80,824 16,659 654,242 126,157 667,341 45,456 1,942,550 2005 341,806 79,362 13,021 624,008 138,469 664,691 41,400 1,902,757 2006 332,548 54,224 24,009 603,288 126,049 689,549 49,308 1,878,973 2007 326,803 50,882 25,373 554,394 116,313 651,230 46,822 1,771,816 2008 315,244 29,554 18,263 509,330 110,680 610,131 23,729 1,616,931 2009 281,557 32,591 20,308 513,002 99,556 546,974 33,287 1,527,276

60

Assessing certainty and uncertainty in riparian habitat suitability models by identifying parameters with extreme outputs  

Science Journals Connector (OSTI)

The aim of this paper is to introduce a computationally efficient uncertainty assessment approach using an index-based habitat suitability model. The approach focuses on uncertainty in ecological knowledge regarding parameters of index curves and weights. ... Keywords: Habitat model, Riparian vegetation, Suitability index, Uncertainty

Baihua Fu, Joseph H. A. Guillaume

2014-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" 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

SAS Output  

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

F. Biogenic Municipal Solid Waste: Consumption for Electricity Generation and F. Biogenic Municipal Solid Waste: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 161,803 5,766 132,065 21,953 2,020 2004 161,567 3,705 129,562 25,204 3,096 2005 164,635 4,724 131,080 24,914 3,918 2006 168,716 4,078 135,127 25,618 3,893 2007 162,482 4,557 133,509 21,393 3,022 2008 166,723 4,476 136,080 26,108 59 2009 165,755 3,989 132,877 27,868 1,021 2010 162,436 3,322 130,467 27,509 1,138 2011 152,007 3,433 121,648 25,664 1,262 2012 152,045 3,910 117,598 28,923 1,614 2010 January 13,015 244 10,405 2,260 107

62

SAS Output  

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

1. Emissions from Energy Consumption at 1. Emissions from Energy Consumption at Conventional Power Plants and Combined-Heat-and-Power Plants 2002 through 2012 (Thousand Metric Tons) Year Carbon Dioxide (CO2) Sulfur Dioxide (SO2) Nitrogen Oxides (NOx) 2002 2,423,963 10,881 5,194 2003 2,445,094 10,646 4,532 2004 2,486,982 10,309 4,143 2005 2,543,838 10,340 3,961 2006 2,488,918 9,524 3,799 2007 2,547,032 9,042 3,650 2008 2,484,012 7,830 3,330 2009 2,269,508 5,970 2,395 2010 2,388,596 5,400 2,491 2011 2,287,071 4,845 2,406 2012 2,156,875 3,704 2,148 Notes: The emissions data presented include total emissions from both electricity generation and the production of useful thermal output. See Appendix A, Technical Notes, for a description of the sources and methodology used to develop the emissions estimates.

63

SAS Output  

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

C. Biogenic Municipal Solid Waste: Consumption for Electricity Generation and C. Biogenic Municipal Solid Waste: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 22,554 695 18,611 2,952 296 2004 22,330 444 17,959 3,439 488 2005 22,089 560 17,655 3,289 584 2006 22,469 500 18,068 3,356 545 2007 21,796 553 17,885 2,921 437 2008 22,134 509 18,294 3,323 8 2009 22,095 465 17,872 3,622 137 2010 21,725 402 17,621 3,549 152 2011 19,016 388 15,367 3,103 158 2012 18,954 418 14,757 3,577 203 2010 January 1,737 30 1,402 291 14 February 1,562 25 1,276 250 11 March 1,854 36 1,500 306 12

64

Optimal Location of Compressed Natural Gas (CNG) Refueling Station Using the Arc Demand Coverage Model  

Science Journals Connector (OSTI)

In this paper a model that locates Compressed Natural Gas (CNG) refueling stations to cover the full volume of vehicle flows is developed and applied. The model inputs consist of a road network include nodes and arcs, the volume of vehicle flows between ... Keywords: Compressed Natural Gas, Arc Demand Coverage Model, Optimal Location, Network

Abtin Boostani; Reza Ghodsi; Ali Kamali Miab

2010-05-01T23:59:59.000Z

65

Evaluation of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Populations  

E-Print Network [OSTI]

Evaluation of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Buster is a stochastic, spatially explicit simulation model of Aedes aegypti populations, designed of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Populations. PLoS ONE 6(7): e

Lloyd, Alun

66

A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling  

Science Journals Connector (OSTI)

...on a desktop computer. This is compared...features of the system. The important...resistance. The analysis also identified...and uncertainty analysis: applications to large-scale systems, vol. 2. Boca...for sensitivity analysis of large models...European Symp. on Computer Aided Process...

2012-01-01T23:59:59.000Z

67

A framework for interpreting climate model outputs Nadja A. Leith and Richard E. Chandler  

E-Print Network [OSTI]

to illustrate the methodology. Some key words: Climate change; Climate model uncertainty; Contemporaneous ARMA acknowledged that human activities have caused changes in the Earth's climate (Solomon et al., 2007). Indeed #12;the hydrological cycle (Solomon et al., 2007). To accommodate this possibility therefore, planners

Guillas, Serge

68

USE OF GENERAL CIRCULATION MODEL OUTPUT IN THE CREATION OF CLIMATE CHANGE SCENARIOS  

E-Print Network [OSTI]

, Sub-Saharan Africa and Venezuela, for use in biological effects models. By combining the general of Energy (MacCracken and Luther, 1985a, b; NRC, 1985; Trabalka, 1985; Strain and Cure, 1985; White, 1985, and possible solar variations, and all agree that surface air temperatures will rise, pre- cipitation patterns

Robock, Alan

69

Model Validation and Spatial Interpolation by Combining Observations with Outputs from Numerical  

E-Print Network [OSTI]

""r,c,rn The authors are for hel]JfuI #12;Abstract Constructing maps of pollution levels is vital for air quality concentrations. Key tlJords: air pollution, Ba~yesian inference, change of support, likelihood approaches, Matern Resolutions 2.5 Modeling a Nonstationary Covariance . 3 Estimation 3.1 Algorithm 4 Application: Air Pollution

Washington at Seattle, University of

70

SAS Output  

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

Coal Consumers in the Manufacturing and Coke Sectors, 2012" Coal Consumers in the Manufacturing and Coke Sectors, 2012" "Company Name","Plant Location" "Top Ten Manufacturers" "American Crystal Sugar Co","MN, ND" "Archer Daniels Midland","IA, IL, MN, ND, NE" "Carmeuse Lime Stone Inc","AL, IL, IN, KY, MI, OH, PA, TN, VA, WI" "Cemex Inc","AL, CA, CO, FL, GA, KY, OH, TN, TX" "Dakota Gasification Company","ND" "Eastman Chemical Company","TN" "Georgia-Pacific LLC","AL, GA, OK, VA, WI" "Holcim (US) Inc","AL, CO, MD, MO, MT, OK, SC, TX, UT" "NewPage Corporation","MD, MI, WI" "U S Steel Corporation","AL, IN, MI, MN"

71

Ecological-economic assessment of farms using multi-input multi-output models: life cycle assessment with multiple paired comparisons  

Science Journals Connector (OSTI)

A multi-input multi-output model is developed by extending the life cycle assessment framework for analysing the relationship between agricultural production and environmental impacts. The inputs include farmland and materials such as fertilisers, pesticides and animals. The outputs are of two types: one is agro-economic production, such as crop yields, and the other is environmental impacts, including greenhouse gas emissions. Additive and ratio models are defined for analysing the relationship between management intensity, land productivity and environmental impacts based on the farm model. After the framework of multiple paired comparisons is illustrated, the multi-input multi-output model is applied to rice farming in Japan. The results indicate that the additive and ratio models can be used for detecting the directions of changes. These models can be extended for analysing the land-use competition between food and energy production.

Kiyotada Hayashi

2014-01-01T23:59:59.000Z

72

OLAF _ A General Modeling System to Evaluate and Optimize the Location of an Air  

E-Print Network [OSTI]

OLAF _ A General Modeling System to Evaluate and Optimize the Location of an Air Polluting Facility Project Report J"org Fliege 13 2.1The Meteorological Preprocessor ..................13 2.2The Air Dispersion Model

Fliege, Jörg

73

An agent-based retail location model on a supply chain Arthur Huangand David Levinson  

E-Print Network [OSTI]

An agent-based retail location model on a supply chain network Arthur Huangand David Levinson of suppliers, retailers, and, consumers. Krugman (1996) argued that urban concentration involved a tension an agent-based model of retailers' location choice in a market of homogeneous products. In this game

Levinson, David M.

74

Reliable p-median facility location problem: two-stage robust models ...  

E-Print Network [OSTI]

plane method in the two-stage facility location problem and power system scheduling ... (ii) Because of the modeling advantages of two-stage RO, we consider real ...... Robust Unit Commitment Problem with Demand Response and Wind.

2012-12-18T23:59:59.000Z

75

Retail Location Choice with Complementary Goods: An Agent-Based Model  

E-Print Network [OSTI]

Retail Location Choice with Complementary Goods: An Agent-Based Model Arthur Huang and David 55455 {huang284,dlevinson}@umn.edu Abstract. This paper models the emergence of retail clusters on a supply chain network comprised of suppliers, retailers, and consumers. Firstly, an agent-based model

Levinson, David M.

76

Environmental Modelling & Software 15 (2000) 161167 www.elsevier.com/locate/envsoft  

E-Print Network [OSTI]

Environmental Modelling & Software 15 (2000) 161­167 www.elsevier.com/locate/envsoft A fuzzy model "contaminated", defined over the set of 70 sampling sites. The higher the concentration, the higher the degree contaminated sites. The proposed fuzzy model is easy to implement and the results are directly interpretable

Kuncheva, Ludmila I.

77

Object Oriented Modeling of a Multiple-Input Multiple-Output Flyback Converter in Nicholas D. Benavides and Patrick L.Chapman  

E-Print Network [OSTI]

Object Oriented Modeling of a Multiple-Input Multiple-Output Flyback Converter in Dymola Nicholas D not lend itself to many traditional circuit simulators such as SPICE. The state equations of a converter dependent on the states, and cannot be determined prior to simulation, requiring the use of an iterative

Chapman, Patrick

78

A Comparison of Simulated Cloud Radar Output from the Multiscale Modeling Framework Global Climate Model with CloudSat Cloud Radar Observations  

SciTech Connect (OSTI)

Over the last few years a new type of global climate model (GCM) has emerged in which a cloud-resolving model is embedded into each grid cell of a GCM. This new approach is frequently called a multiscale modeling framework (MMF) or superparameterization. In this article we present a comparison of MMF output with radar observations from the NASA CloudSat mission, which uses a near-nadir-pointing millimeter-wavelength radar to probe the vertical structure of clouds and precipitation. We account for radar detection limits by simulating the 94 GHz radar reflectivity that CloudSat would observe from the high-resolution cloud-resolving model output produced by the MMF. Overall, the MMF does a good job of reproducing the broad pattern of tropical convergence zones, subtropical belts, and midlatitude storm tracks, as well as their changes in position with the annual solar cycle. Nonetheless, the comparison also reveals a number of model shortfalls including (1) excessive hydrometeor coverage at all altitudes over many convectively active regions, (2) a lack of low-level hydrometeors over all subtropical oceanic basins, (3) excessive low-level hydrometeor coverage (principally precipitating hydrometeors) in the midlatitude storm tracks of both hemispheres during the summer season (in each hemisphere), and (4) a thin band of low-level hydrometeors in the Southern Hemisphere of the central (and at times eastern and western) Pacific in the MMF, which is not observed by CloudSat. This band resembles a second much weaker ITCZ but is restricted to low levels.

Marchand, Roger T.; Haynes, J. M.; Mace, Gerald G.; Ackerman, Thomas P.; Stephens, Graeme L.

2009-01-13T23:59:59.000Z

79

Training Quench Performance and Quench Location of the Short Superconducting Dipole Models for the LHC  

E-Print Network [OSTI]

The short model program, started in October 1995 to study and validate design variants and assembly of the main LHC dipoles, has achieved its last phase. The last models were focused on the validation of specific design choices to be implemented in the series production, and to the study of the training performance of the coil heads. This paper reports on the manufacturing features of the recent twin-aperture short models, reviews the results of the cold tests and presents a summary of the training quench performance and quench location.

Sanfilippo, S; Tommasini, D; Venturini-Delsolaro, W

2002-01-01T23:59:59.000Z

80

The feasibility of co-existence between conventional and genetically modified crops: Using machine learning to analyse the output of simulation models  

Science Journals Connector (OSTI)

Simulation models are a commonly used tool for the study of the co-existence of conventional and genetically modified (GM) crops. Among other things, they allow us to investigate the effects of using different crop varieties, cropping systems and farming practices on the levels of adventitious presence of GM material in conventional crops. We propose to use machine learning methods to analyse the output of simulation models to learn co-existence rules that directly link the above mentioned causes and effects. The outputs of the GENESYS model, designed to study the co-existence of conventional and GM oilseed rape crops, were analysed by using the machine learning methods of regression tree induction and relational decision tree induction. Co-existence and adventitious presence of GM material were studied in several contexts, including gene flow between pairs of fields, the interactions of this process with farming practices (cropping systems), and gene flow in the context of an entire field plan. Accurate models were learned, which also make use of the relational aspects of a field plan, using information on the neighboring fields of a field, and the farming practices applied in it. The use of relational decision tree induction to analyse the results of simulation models is a novel approach and holds the promise of learning more general co-existence rules by allowing us to vary the target field within a chosen field plan, as well as to consider completely different field plans at the same time.

Aneta Ivanovska; Celine Vens; Nathalie Colbach; Marko Debeljak; Sao Deroski

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" 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

Design science research toward designing/prototyping a repeatable model for testing location management (LM) algorithms for wireless networking.  

E-Print Network [OSTI]

?? The purpose of this research effort was to develop a model that provides repeatable Location Management (LM) testing using a network simulation tool, QualNet (more)

Peacock, Christopher

2012-01-01T23:59:59.000Z

82

Computational modelling of T-cell formation kinetics: output regulated by initial proliferation-linked deferral of developmental competence  

Science Journals Connector (OSTI)

...marrow-derived progenitors enter the thymus of an adult...our models validate the search for its molecular basis...At time zero, n cells enter the DN1pre compartment...11) best models in terms of G, the number of generations...11) best models in terms of G, the number of generations...

2013-01-01T23:59:59.000Z

83

Comparing urban solid waste recycling from the viewpoint of urban metabolism based on physical input-output model: A case of Suzhou in China  

SciTech Connect (OSTI)

Highlights: Black-Right-Pointing-Pointer Impacts of solid waste recycling on Suzhou's urban metabolism in 2015 are analyzed. Black-Right-Pointing-Pointer Sludge recycling for biogas is regarded as an accepted method. Black-Right-Pointing-Pointer Technical levels of reusing scrap tires and food wastes should be improved. Black-Right-Pointing-Pointer Other fly ash utilization methods should be exploited. Black-Right-Pointing-Pointer Secondary wastes from reusing food wastes and sludge should be concerned. - Abstract: Investigating impacts of urban solid waste recycling on urban metabolism contributes to sustainable urban solid waste management and urban sustainability. Using a physical input-output model and scenario analysis, urban metabolism of Suzhou in 2015 is predicted and impacts of four categories of solid waste recycling on urban metabolism are illustrated: scrap tire recycling, food waste recycling, fly ash recycling and sludge recycling. Sludge recycling has positive effects on reducing all material flows. Thus, sludge recycling for biogas is regarded as an accepted method. Moreover, technical levels of scrap tire recycling and food waste recycling should be improved to produce positive effects on reducing more material flows. Fly ash recycling for cement production has negative effects on reducing all material flows except solid wastes. Thus, other fly ash utilization methods should be exploited. In addition, the utilization and treatment of secondary wastes from food waste recycling and sludge recycling should be concerned.

Liang Sai, E-mail: liangsai09@gmail.com [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); Zhang Tianzhu, E-mail: zhangtz@mail.tsinghua.edu.cn [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China)

2012-01-15T23:59:59.000Z

84

A multi-media planning model for assessing co-located energy and desalination plants  

Science Journals Connector (OSTI)

The co-location of desalination plants with existing or proposed power plants ... strain of power needed for the energy intensive desalination process increases these pollutants into the atmosphere. ... pollutant...

E. Annette Hernandez; Venkatesh Uddameri

2014-03-01T23:59:59.000Z

85

ON THE FORMATION LOCATION OF URANUS AND NEPTUNE AS CONSTRAINED BY DYNAMICAL AND CHEMICAL MODELS OF COMETS  

SciTech Connect (OSTI)

The D/H enrichment observed in Saturn's satellite Enceladus is remarkably similar to the values observed in the nearly-isotropic comets. Given the predicted strong variation of D/H with heliocentric distance in the solar nebula, this observation links the primordial source region of the nearly-isotropic comets with the formation location of Enceladus. That is, comets from the nearly-isotropic class were most likely fed into their current reservoir, the Oort cloud, from a source region near the formation location of Enceladus. Dynamical simulations of the formation of the Oort cloud indicate that Uranus and Neptune are, primarily, responsible for the delivery of material into the Oort cloud. In addition, Enceladus formed from material that condensed from the solar nebula near the location at which Saturn captured its gas envelope, most likely at or near Saturn's current location in the solar system. The coupling of these lines of evidence appears to require that Uranus and Neptune were, during the epoch of the formation of the Oort cloud, much closer to the current location of Saturn than they are currently. Such a configuration is consistent with the Nice model of the evolution of the outer solar system. Further measurements of the D/H enrichment in comets, particularly in ecliptic comets, will provide an excellent discriminator among various models of the formation of the outer solar system.

Kavelaars, J. J. [Herzberg Institute of Astrophysics, National Research Council of Canada, 5071 West Saanich Road, Victoria, BC V9E 2E7 (Canada); Mousis, Olivier; Petit, Jean-Marc [Institut UTINAM, CNRS-UMR 6213, Observatoire de Besancon, BP 1615, 25010 Besancon Cedex (France); Weaver, Harold A., E-mail: JJ.Kavelaars@nrc.gc.ca [Space Department, Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD 20723-6099 (United States)

2011-06-20T23:59:59.000Z

86

Seeing our signals: combining location traces and web-based models for personal discovery  

Science Journals Connector (OSTI)

Each of us has a complex and reciprocal relationship with our environment. Based on limited knowledge of this interwoven set of influences and consequences, we constantly make choices: where to live, how to go to work, what brands to buy, what to do ... Keywords: activity diary, location technology, mapmatching, personal exposure, personal impact

E. Agapie; G. Chen; D. Houston; E. Howard; J. Kim; M. Y. Mun; A. Mondschein; S. Reddy; R. Rosario; J. Ryder; A. Steiner; J. Burke; E. Estrin; M. Hansen; M. Rahimi

2008-02-01T23:59:59.000Z

87

A SpatioTemporal Placement Model for Caching Location Dependent Queries Anand Murugappan and Ling Liu  

E-Print Network [OSTI]

objects of the location queries are still ob- jects such as gas stations, restaurants, or moving objects is driving on the I85 North highway at 60 mph speed, and wants to find the nearest gas stations within certain range. If the query is asking for gas stations within 5 miles, then the spatial validity

Liu, Ling

88

Modelling locational price spreads in competitive electricity markets; applications for transmission rights valuation and replication  

Science Journals Connector (OSTI)

......price of fuel (oil, gas, and coal...feeds into the price of electricity...the emergence of heating and cooling degree...locational power price risk. Changes...derivatives (heating and cooling degree...supply side, the price of fuel for power...Futures contracts on oil and gas, both......

Petter Skantze; Marija Ilic; Andrej Gubina

2004-10-01T23:59:59.000Z

89

Environmental Modelling & Software 15 (2000) 681692 www.elsevier.com/locate/envsoft  

E-Print Network [OSTI]

-scale air pollution modelling using adaptive unstructured meshes A.S. Tomlin a,* , S. Ghorai a , G. Hart of Computer Studies, University of Leeds, Leeds LS2 9JT, UK Abstract High resolution models of air pollution but less so in meteorological and air pollution models. However, it is well known that grid resolution has

Utah, University of

90

A global 3D P-velocity model of the Earth's crust and mantle for improved event location.  

SciTech Connect (OSTI)

To test the hypothesis that high quality 3D Earth models will produce seismic event locations which are more accurate and more precise, we are developing a global 3D P wave velocity model of the Earth's crust and mantle using seismic tomography. In this paper, we present the most recent version of our model, SALSA3D (SAndia LoS Alamos) version 1.4, and demonstrate its ability to reduce mislocations for a large set of realizations derived from a carefully chosen set of globally-distributed ground truth events. Our model is derived from the latest version of the Ground Truth (GT) catalog of P and Pn travel time picks assembled by Los Alamos National Laboratory. To prevent over-weighting due to ray path redundancy and to reduce the computational burden, we cluster rays to produce representative rays. Reduction in the total number of ray paths is > 55%. The model is represented using the triangular tessellation system described by Ballard et al. (2009), which incorporates variable resolution in both the geographic and radial dimensions. For our starting model, we use a simplified two layer crustal model derived from the Crust 2.0 model over a uniform AK135 mantle. Sufficient damping is used to reduce velocity adjustments so that ray path changes between iterations are small. We obtain proper model smoothness by using progressive grid refinement, refining the grid only around areas with significant velocity changes from the starting model. At each grid refinement level except the last one we limit the number of iterations to prevent convergence thereby preserving aspects of broad features resolved at coarser resolutions. Our approach produces a smooth, multi-resolution model with node density appropriate to both ray coverage and the velocity gradients required by the data. This scheme is computationally expensive, so we use a distributed computing framework based on the Java Parallel Processing Framework, providing us with {approx}400 processors. Resolution of our model is assessed using a variation of the standard checkerboard method, as well as by directly estimating the diagonal of the model resolution matrix based on the technique developed by Bekas, et al. We compare the travel-time prediction and location capabilities of this model over standard 1D models. We perform location tests on a global, geographically-distributed event set with ground truth levels of 5 km or better. These events generally possess hundreds of Pn and P phases from which we can generate different realizations of station distributions, yielding a range of azimuthal coverage and proportions of teleseismic to regional arrivals, with which we test the robustness and quality of relocation. The SALSA3D model reduces mislocation over standard 1D ak135, especially with increasing azimuthal gap. The 3D model appears to perform better for locations based solely or dominantly on regional arrivals, which is not unexpected given that ak135 represents a global average and cannot therefore capture local and regional variations.

Ballard, Sanford; Encarnacao, Andre Villanova; Begnaud, Michael A. (Los Alamos National Laboratories); Rowe, Charlotte A. (Los Alamos National Laboratories); Lewis, Jennifer E.; Young, Christopher John; Chang, Marcus C.; Hipp, James Richard

2010-04-01T23:59:59.000Z

91

Title Slide "The broadband acoustic output of  

E-Print Network [OSTI]

Title Slide "The broadband acoustic output of marine seismic airgun sources" Les Hatton CISM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . #12;Seismic sources ­ marine airguns Introduction Modelling Marine Life Impact Where next Overview #12 Normal speed surface movie of airgun firing Courtesy IO limited #12;Seismic sources ­ marine airguns

Hatton, Les

92

A Robust Model Control for Dynamic Systems  

Science Journals Connector (OSTI)

Analytical methods of polynomial algebra, heuristic techniques, and digital modeling are used to study the robustness domain of linear dynamic systems with model inputoutput controllers as a function of the mutual locations of zeros ...

S. V. Tararykin; V. V. Tyutikov

2002-05-01T23:59:59.000Z

93

Environmental Modelling & Software 19 (2004) 285304 www.elsevier.com/locate/envsoft  

E-Print Network [OSTI]

Water Management District, Everglades Department, PO Box 24680, West Palm Beach, Florida 33416-4680, USA for Ecological Economics, University of Vermont, 590 Main Street, Burlington, VT 05405-0088, USA b South Florida are formulated as STELLA models, which adds to transparency and helps reuse. Spatial transport processes

Vermont, University of

94

Enhanced performance CCD output amplifier  

DOE Patents [OSTI]

A low-noise FET amplifier is connected to amplify output charge from a che coupled device (CCD). The FET has its gate connected to the CCD in common source configuration for receiving the output charge signal from the CCD and output an intermediate signal at a drain of the FET. An intermediate amplifier is connected to the drain of the FET for receiving the intermediate signal and outputting a low-noise signal functionally related to the output charge signal from the CCD. The amplifier is preferably connected as a virtual ground to the FET drain. The inherent shunt capacitance of the FET is selected to be at least equal to the sum of the remaining capacitances.

Dunham, Mark E. (Los Alamos, NM); Morley, David W. (Santa Fe, NM)

1996-01-01T23:59:59.000Z

95

A computer model for optimizing the location of natural gas fueling stations  

Science Journals Connector (OSTI)

Abstract High levels of fine particulate matter and ozone in many major cities are causing increased respiratory problems, increased asthma attacks and premature death. Natural gas vehicles have been reported to emit up to 95% less particulate matter than diesel powered vehicles and up to 90% less ozone-producing carbon monoxide and reactive hydrocarbons. The adoption of natural gas vehicles, therefore, could play a large role in improving air quality in many cities. Because of the many costs associated with the introduction of a new fueling infrastructure, optimum distribution of fueling stations will play a major role in widespread use of natural gas vehicles, especially in the early stages of market penetration. A model was developed that can be used to optimize fueling station placement-based on traffic volume using a Monte Carlo algorithm. In particular, the Monte Carlo method allows for the placement of the fueling stations based upon their proximity to high volume traffic flow and the placement of all the fueling stations are optimized simultaneously. Traffic volume data from Pittsburgh, PA was used in the model simulations.

T.L. Kerzmann; G.A. Buxton; J. Preisser

2014-01-01T23:59:59.000Z

96

Sparse Convolved Gaussian Processes for Multi-output Regression  

E-Print Network [OSTI]

the concentration of different heavy metal pollutants [5]. Modelling multiple output variables is a challenge as we methodology for synthetic data and real world applications on pollution prediction and a sensor network. 1

Rattray, Magnus

97

Inflation uncertainty, growth uncertainty, oil prices, and output growth in the UK  

Science Journals Connector (OSTI)

This study examines the transmission and response of inflation uncertainty and output uncertainty on inflation and output growth in the UK using a bi-variate EGARCH model. Results suggest that inflation uncertain...

Ramprasad Bhar; Girijasankar Mallik

2013-12-01T23:59:59.000Z

98

A Framework to Determine the Probability Density Function for the Output Power of Wind Farms  

E-Print Network [OSTI]

A Framework to Determine the Probability Density Function for the Output Power of Wind Farms Sairaj to the power output of a wind farm while factoring in the availability of the wind turbines in the farm availability model for the wind turbines, we propose a method to determine the wind-farm power output pdf

Liberzon, Daniel

99

Simulation of one-minute power output from utility-scale photovoltaic generation systems.  

SciTech Connect (OSTI)

We present an approach to simulate time-synchronized, one-minute power output from large photovoltaic (PV) generation plants in locations where only hourly irradiance estimates are available from satellite sources. The approach uses one-minute irradiance measurements from ground sensors in a climatically and geographically similar area. Irradiance is translated to power using the Sandia Array Performance Model. Power output is generated for 2007 in southern Nevada are being used for a Solar PV Grid Integration Study to estimate the integration costs associated with various utility-scale PV generation levels. Plant designs considered include both fixed-tilt thin-film, and single-axis-tracked polycrystalline Si systems ranging in size from 5 to 300 MW{sub AC}. Simulated power output profiles at one-minute intervals were generated for five scenarios defined by total PV capacity (149.5 MW, 222 WM, 292 MW, 492 MW, and 892 MW) each comprising as many as 10 geographically separated PV plants.

Stein, Joshua S.; Ellis, Abraham; Hansen, Clifford W.

2011-08-01T23:59:59.000Z

100

SALSA3D : a global 3D p-velocity model of the Earth's crust and mantle for improved event location.  

SciTech Connect (OSTI)

To test the hypothesis that high quality 3D Earth models will produce seismic event locations which are more accurate and more precise, we are developing a global 3D P wave velocity model of the Earth's crust and mantle using seismic tomography. In this paper, we present the most recent version of our model, SALSA3D version 1.5, and demonstrate its ability to reduce mislocations for a large set of realizations derived from a carefully chosen set of globally-distributed ground truth events. Our model is derived from the latest version of the Ground Truth (GT) catalog of P and Pn travel time picks assembled by Los Alamos National Laboratory. To prevent over-weighting due to ray path redundancy and to reduce the computational burden, we cluster rays to produce representative rays. Reduction in the total number of ray paths is {approx}50%. The model is represented using the triangular tessellation system described by Ballard et al. (2009), which incorporates variable resolution in both the geographic and radial dimensions. For our starting model, we use a simplified two layer crustal model derived from the Crust 2.0 model over a uniform AK135 mantle. Sufficient damping is used to reduce velocity adjustments so that ray path changes between iterations are small. We obtain proper model smoothness by using progressive grid refinement, refining the grid only around areas with significant velocity changes from the starting model. At each grid refinement level except the last one we limit the number of iterations to prevent convergence thereby preserving aspects of broad features resolved at coarser resolutions. Our approach produces a smooth, multi-resolution model with node density appropriate to both ray coverage and the velocity gradients required by the data. This scheme is computationally expensive, so we use a distributed computing framework based on the Java Parallel Processing Framework, providing us with {approx}400 processors. Resolution of our model is assessed using a variation of the standard checkerboard method. We compare the travel-time prediction and location capabilities of SALSA3D to standard 1D models via location tests on a global event set with GT of 5 km or better. These events generally possess hundreds of Pn and P picks from which we generate different realizations of station distributions, yielding a range of azimuthal coverage and ratios of teleseismic to regional arrivals, with which we test the robustness and quality of relocation. The SALSA3D model reduces mislocation over standard 1D ak135 regardless of Pn to P ratio, with the improvement being most pronounced at higher azimuthal gaps.

Encarnacao, Andre Villanova; Begnaud, Michael A. (Los Alamos National Laboratories); Rowe, Charlotte A. (Los Alamos National Laboratories); Young, Christopher John; Chang, Marcus C.; Ballard, Sally C.; Hipp, James Richard

2010-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" 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

A global 3D P-velocity model of the Earth's crust and mantle for improved event location : SALSA3D.  

SciTech Connect (OSTI)

To test the hypothesis that high quality 3D Earth models will produce seismic event locations which are more accurate and more precise, we are developing a global 3D P wave velocity model of the Earth's crust and mantle using seismic tomography. In this paper, we present the most recent version of our model, SALSA3D version 1.5, and demonstrate its ability to reduce mislocations for a large set of realizations derived from a carefully chosen set of globally-distributed ground truth events. Our model is derived from the latest version of the Ground Truth (GT) catalog of P and Pn travel time picks assembled by Los Alamos National Laboratory. To prevent over-weighting due to ray path redundancy and to reduce the computational burden, we cluster rays to produce representative rays. Reduction in the total number of ray paths is {approx}50%. The model is represented using the triangular tessellation system described by Ballard et al. (2009), which incorporates variable resolution in both the geographic and radial dimensions. For our starting model, we use a simplified two layer crustal model derived from the Crust 2.0 model over a uniform AK135 mantle. Sufficient damping is used to reduce velocity adjustments so that ray path changes between iterations are small. We obtain proper model smoothness by using progressive grid refinement, refining the grid only around areas with significant velocity changes from the starting model. At each grid refinement level except the last one we limit the number of iterations to prevent convergence thereby preserving aspects of broad features resolved at coarser resolutions. Our approach produces a smooth, multi-resolution model with node density appropriate to both ray coverage and the velocity gradients required by the data. This scheme is computationally expensive, so we use a distributed computing framework based on the Java Parallel Processing Framework, providing us with {approx}400 processors. Resolution of our model is assessed using a variation of the standard checkerboard method. We compare the travel-time prediction and location capabilities of SALSA3D to standard 1D models via location tests on a global event set with GT of 5 km or better. These events generally possess hundreds of Pn and P picks from which we generate different realizations of station distributions, yielding a range of azimuthal coverage and ratios of teleseismic to regional arrivals, with which we test the robustness and quality of relocation. The SALSA3D model reduces mislocation over standard 1D ak135 regardless of Pn to P ratio, with the improvement being most pronounced at higher azimuthal gaps.

Young, Christopher John; Steck, Lee K. (Los Alamos National Laboratory); Phillips, William Scott (Los Alamos National Laboratory); Ballard, Sanford; Chang, Marcus C.; Rowe, Charlotte A. (Los Alamos National Laboratory); Encarnacao, Andre Villanova; Begnaud, Michael A. (Los Alamos National Laboratory); Hipp, James Richard

2010-07-01T23:59:59.000Z

102

Evaluating Solar Radiation Attenuation Models to Assess the Effects of Climate and Geographical Location on the Heliostat Field Efficiency in Brazil  

Science Journals Connector (OSTI)

Abstract Most of the solar power plants using a central receiver which are currently in operation are installed in the Sun Belt region, specifically above the Tropic of Cancer. These plants are located in regions characterized by a dry summers and a yearly sum of Direct Normal Irradiation (DNI) of over 2300 kWh/m2. These regions include the Mojave Desert (semi-arid climate) and Andaluca in southern Spain (Mediterranean and semi-arid climate). Potential locations for installing such plants in Brazil, identified in previous studies, are the So Francisco river basin and the Sobradinho area in the Northeast Region of the country. These locations are characterized by high humidity levels and yearly DNI values ranging from 1800 to 2300 kWh/m2, which is in clear contrast with the dry and desert climates where the solar tower projects currently in operation are located. Besides the combined effects of climate and the inter-tropicalization of the site, based on the solar angles and atmospheric attenuation, the potential locations in Brazil provide a small variation between the monthly averages DNI values. In this paper, the effects of these particularities on the performance of a heliostat field are assessed. For instance, the effects of the atmospheric water vapor and aerosol concentration on the optical performance of the heliostat field are analyzed. The results suggest that, for the same DNI level, the heliostat field in Brazil should be 4% larger due to the effect of the water vapor concentration in the atmosphere. This is an important finding, which shows that the current models for calculating the attenuation between the heliostat and the receiver need to be reviewed and compared with experimental observations and validated for the conditions prevailing at potential locations in Brazil.

JM Cardemil; AR Starke; VK Scariot; IL. Grams; S Colle

2014-01-01T23:59:59.000Z

103

Energy Input Output Calculator | Open Energy Information  

Open Energy Info (EERE)

Input Output Calculator Input Output Calculator Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Energy Input-Output Calculator Agency/Company /Organization: Department of Energy Sector: Energy Focus Area: Energy Efficiency Resource Type: Online calculator User Interface: Website Website: www2.eere.energy.gov/analysis/iocalc/Default.aspx Web Application Link: www2.eere.energy.gov/analysis/iocalc/Default.aspx OpenEI Keyword(s): Energy Efficiency and Renewable Energy (EERE) Tools Language: English References: EERE Energy Input-Output Calculator[1] The Energy Input-Output Calculator (IO Calculator) allows users to estimate the economic development impacts from investments in alternate electricity generating technologies. About the Calculator The Energy Input-Output Calculator (IO Calculator) allows users to estimate

104

A global 3D P-Velocity model of the Earth%3CU%2B2019%3Es crust and mantle for improved event location.  

SciTech Connect (OSTI)

To test the hypothesis that high quality 3D Earth models will produce seismic event locations which are more accurate and more precise, we are developing a global 3D P wave velocity model of the Earth's crust and mantle using seismic tomography. In this paper, we present the most recent version of our model, SALSA3D (SAndia LoS Alamos) version 1.4, and demonstrate its ability to reduce mislocations for a large set of realizations derived from a carefully chosen set of globally-distributed ground truth events. Our model is derived from the latest version of the Ground Truth (GT) catalog of P and Pn travel time picks assembled by Los Alamos National Laboratory. To prevent over-weighting due to ray path redundancy and to reduce the computational burden, we cluster rays to produce representative rays. Reduction in the total number of ray paths is > 55%. The model is represented using the triangular tessellation system described by Ballard et al. (2009), which incorporates variable resolution in both the geographic and radial dimensions. For our starting model, we use a simplified two layer crustal model derived from the Crust 2.0 model over a uniform AK135 mantle. Sufficient damping is used to reduce velocity adjustments so that ray path changes between iterations are small. We obtain proper model smoothness by using progressive grid refinement, refining the grid only around areas with significant velocity changes from the starting model. At each grid refinement level except the last one we limit the number of iterations to prevent convergence thereby preserving aspects of broad features resolved at coarser resolutions. Our approach produces a smooth, multi-resolution model with node density appropriate to both ray coverage and the velocity gradients required by the data. This scheme is computationally expensive, so we use a distributed computing framework based on the Java Parallel Processing Framework, providing us with {approx}400 processors. Resolution of our model is assessed using a variation of the standard checkerboard method, as well as by directly estimating the diagonal of the model resolution matrix based on the technique developed by Bekas, et al. We compare the travel-time prediction and location capabilities of this model over standard 1D models. We perform location tests on a global, geographically-distributed event set with ground truth levels of 5 km or better. These events generally possess hundreds of Pn and P phases from which we can generate different realizations of station distributions, yielding a range of azimuthal coverage and proportions of teleseismic to regional arrivals, with which we test the robustness and quality of relocation. The SALSA3D model reduces mislocation over standard 1D ak135, especially with increasing azimuthal gap. The 3D model appears to perform better for locations based solely or dominantly on regional arrivals, which is not unexpected given that ak135 represents a global average and cannot therefore capture local and regional variations.

Ballard, Sanford; Encarnacao, Andre Villanova; Begnaud, Michael A. (Los Alamos National Laboratories); Rowe, Charlotte A. (Los Alamos National Laboratories); Lewis, Jennifer E.; Young, Christopher John; Chang, Marcus C.; Hipp, James Richard

2010-05-01T23:59:59.000Z

105

Extreme wind climate modeling of some locations in India for the specification of the design wind speed of structures  

Science Journals Connector (OSTI)

The wind load on a structure is proportional to the square of the wind speed. Extreme wind climate modeling should be required for specifying the design wind speed of structures. Extreme wind speeds for a storm t...

Arnab Sarkar; Navneet Kumar; Debojyoti Mitra

2014-06-01T23:59:59.000Z

106

Multivariate process control for detection and cause identification of location shifts  

Science Journals Connector (OSTI)

Most processes involve more than one process/product output variable, multiple process input/regulatory variables, and a category of noise variables, which consists of factors not considered in the model, or those external to the process. Since output variables are not necessarily independent of each other, an adequate approach involves multivariate process control for monitoring of the process. It is of practical value to determine possible causes in the event of a change in the process location, which is detected through a multivariate control chart. In this paper, for cause identification, one of the methods uses information from only the process input variables, while the other uses a generalised measure, based on the residuals, that incorporates the process input and output variables. A simulation approach is adopted to investigate the performance of the proposed estimators as well as the traditional estimator that incorporates only the process/product output variables. Based on a selected performance measure of the average run length of the time to first detection, when the location parameter has changed, the proposed methods perform favourably compared to the traditional estimator.

Amitava Mitra; Mark M. Clark

2014-01-01T23:59:59.000Z

107

Waveguide submillimetre laser with a uniform output beam  

SciTech Connect (OSTI)

A method for producing non-Gaussian light beams with a uniform intensity profile is described. The method is based on the use of a combined waveguide quasi-optical resonator containing a generalised confocal resonator with an inhomogeneous mirror with absorbing inhomogeneities discretely located on its surface and a hollow dielectric waveguide whose size satisfies the conditions of self-imaging of a uniform field in it. The existence of quasi-homogeneous beams at the output of an optically pumped 0.1188-mm waveguide CH{sub 3}OH laser with a amplitude-stepped mirror is confirmed theoretically and experimentally. (lasers)

Volodenko, A V; Gurin, O V; Degtyarev, A V; Maslov, Vyacheslav A; Svich, V A; Topkov, A N [V.N. Karazin Kharkiv National University, Kharkiv (Ukraine)

2007-01-31T23:59:59.000Z

108

X-ray source assembly having enhanced output stability, and fluid stream analysis applications thereof  

DOE Patents [OSTI]

An x-ray source assembly and method of operation are provided having enhanced output stability. The assembly includes an anode having a source spot upon which electrons impinge and a control system for controlling position of the anode source spot relative to an output structure. The control system can maintain the anode source spot location relative to the output structure notwithstanding a change in one or more operating conditions of the x-ray source assembly. One aspect of the disclosed invention is most amenable to the analysis of sulfur in petroleum-based fuels.

Radley, Ian (Glenmont, NY); Bievenue, Thomas J. (Delmar, NY); Burdett, John H. (Charlton, NY); Gallagher, Brian W. (Guilderland, NY); Shakshober, Stuart M. (Hudson, NY); Chen, Zewu (Schenectady, NY); Moore, Michael D. (Alplaus, NY)

2008-06-08T23:59:59.000Z

109

Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs  

E-Print Network [OSTI]

Anisotropic gridadaptive strategies are presented for viscous flow simulations in which the accurate prediction of multiple aerodynamic outputs (such as the lift, drag, and moment coefficients) is required from a single ...

Venditti, David A.

110

Optimization on Solar Panels: Finding the Optimal Output Brian Y. Lu  

E-Print Network [OSTI]

Optimization on Solar Panels: Finding the Optimal Output Brian Y. Lu January 1, 2013 1 Introduction of solar panel: Routing the configuration between solar cells with a switch matrix. However, their result models and control policies for the optimal output of solar panels. The smallest unit on a solar panel

Lavaei, Javad

111

Library Locations Locations other than Main Library  

E-Print Network [OSTI]

Library Locations Locations other than Main Library Example: Feminist Studies HQ1410 .U54 2009 University of California, Santa Barbara Library www.library.ucsb.edu Updated 3-2014 A - B.......................................6 Central M - N..................................................Arts Library (Music Building) P

112

STANDARD OPERATING PROCEDURE Location(s): ___________________________________________________  

E-Print Network [OSTI]

of as hazardous waste. 8. Decontamination: Specific instructions: For light contamination of small areas or items12.1 STANDARD OPERATING PROCEDURE for PHENOL Location(s): ___________________________________________________ Chemical(s): Phenol Specific Hazards: May be fatal if inhaled. Harmful if absorbed through skin. Harmful

Pawlowski, Wojtek

113

NAO Climatology: ROMS output is saved once every 3 days and written to an output file  

E-Print Network [OSTI]

NAO Climatology: ROMS output is saved once every 3 days and written to an output file every 6 days Output after 30 days in 6th file. The Starting Month = July Example: roms_low_his_levts0570dg.0120.nc.gz : July 3 roms_low_his_levts0570dg.0122.nc.gz : July 6 and July 9 roms_low_his_levts0570dg.0124.nc

Gangopadhyay, Avijit

114

Boosting America's Hydropower Output | Department of Energy  

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

Boosting America's Hydropower Output Boosting America's Hydropower Output Boosting America's Hydropower Output October 9, 2012 - 2:10pm Addthis The Boulder Canyon Hydroelectric Facility's new, highly-efficient turbine. | Photo courtesy of the city of Boulder, Colorado. The Boulder Canyon Hydroelectric Facility's new, highly-efficient turbine. | Photo courtesy of the city of Boulder, Colorado. City of Boulder employees celebrate the completion of the Boulder Canyon Hydroelectric Modernization project. | Photo courtesy of the city of Boulder, Colorado. City of Boulder employees celebrate the completion of the Boulder Canyon Hydroelectric Modernization project. | Photo courtesy of the city of Boulder, Colorado. The Boulder Canyon Hydroelectric Facility's new, highly-efficient turbine. | Photo courtesy of the city of Boulder, Colorado.

115

PV output smoothing with energy storage.  

SciTech Connect (OSTI)

This report describes an algorithm, implemented in Matlab/Simulink, designed to reduce the variability of photovoltaic (PV) power output by using a battery. The purpose of the battery is to add power to the PV output (or subtract) to smooth out the high frequency components of the PV power that that occur during periods with transient cloud shadows on the PV array. The control system is challenged with the task of reducing short-term PV output variability while avoiding overworking the battery both in terms of capacity and ramp capability. The algorithm proposed by Sandia is purposely very simple to facilitate implementation in a real-time controller. The control structure has two additional inputs to which the battery can respond. For example, the battery could respond to PV variability, load variability or area control error (ACE) or a combination of the three.

Ellis, Abraham; Schoenwald, David Alan

2012-03-01T23:59:59.000Z

116

Predicting the Energy Output of Wind Farms Based on Weather Data: Important Variables and their Correlation  

E-Print Network [OSTI]

Wind energy plays an increasing role in the supply of energy world-wide. The energy output of a wind farm is highly dependent on the weather condition present at the wind farm. If the output can be predicted more accurately, energy suppliers can coordinate the collaborative production of different energy sources more efficiently to avoid costly overproductions. With this paper, we take a computer science perspective on energy prediction based on weather data and analyze the important parameters as well as their correlation on the energy output. To deal with the interaction of the different parameters we use symbolic regression based on the genetic programming tool DataModeler. Our studies are carried out on publicly available weather and energy data for a wind farm in Australia. We reveal the correlation of the different variables for the energy output. The model obtained for energy prediction gives a very reliable prediction of the energy output for newly given weather data.

Vladislavleva, Katya; Neumann, Frank; Wagner, Markus

2011-01-01T23:59:59.000Z

117

Gesture output: eyes-free output using a force feedback touch surface  

Science Journals Connector (OSTI)

We propose using spatial gestures not only for input but also for output. Analogous to gesture input, the proposed gesture output moves the user's finger in a gesture, which the user then recognizes. We use our concept in a mobile scenario where a motion ... Keywords: eyes free, force feedback, gestures, touch

Anne Roudaut; Andreas Rau; Christoph Sterz; Max Plauth; Pedro Lopes; Patrick Baudisch

2013-04-01T23:59:59.000Z

118

Single Inductor Dual Output Buck Converter  

E-Print Network [OSTI]

of value 3V. The main focus areas are low cross regulation between the outputs and supply of completely independent load current levels while maintaining desired values (1.2V,1.5 V) within well controlled ripple levels. Dynamic hysteresis control is used...

Eachempatti, Haritha

2010-07-14T23:59:59.000Z

119

Bioenergy technology balancing energy output with environmental  

E-Print Network [OSTI]

E2.3 Bioenergy technology ­ balancing energy output with environmental benefitsbenefits John standards #12;Is it right to grow bioenergy? Or How much bioenergy production is right? #12;Historical bioenergy Farmers historically used 25% land for horse feed #12;Energy crops are `solar panels' Solar energy

Levi, Ran

120

Automated detection and location of indications in eddy current signals  

DOE Patents [OSTI]

A computer implemented information extraction process that locates and identifies eddy current signal features in digital point-ordered signals, signals representing data from inspection of test materials, by enhancing the signal features relative to signal noise, detecting features of the signals, verifying the location of the signal features that can be known in advance, and outputting information about the identity and location of all detected signal features.

Brudnoy, David M. (Albany, NY); Oppenlander, Jane E. (Burnt Hills, NY); Levy, Arthur J. (Schenectady, NY)

2000-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" 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

Stochastic p-Robust Location Problems  

E-Print Network [OSTI]

We present p-robust models based on two classical facility location problems, ... University, Department of Industrial Engineering and Management Sciences,...

2004-08-03T23:59:59.000Z

122

Administrator Ready Reference Guide Customizing an Output Style  

E-Print Network [OSTI]

may be in various sections of the instructions. Some things to look for: - line spacing Preview Utility (Tools, Preview Output Styles) or by simply opening the Output Style Editor (Bibliography, Edit button -- to the right of the output style drop- down). The Output Style Preview Utility

University of Technology, Sydney

123

Generalized Input-Output Inequality Systems  

SciTech Connect (OSTI)

In this paper two types of generalized Leontief input-output inequality systems are introduced. The minimax properties for a class of functions associated with the inequalities are studied. Sufficient and necessary conditions for the inequality systems to have solutions are obtained in terms of the minimax value. Stability analysis for the solution set is provided in terms of upper semi-continuity and hemi-continuity of set-valued maps.

Liu Yingfan [Department of Mathematics, Nanjing University of Post and Telecommunications, Nanjing 210009 (China)], E-mail: yingfanliu@hotmail.com; Zhang Qinghong [Department of Mathematics and Computer Science, Northern Michigan University, Marquette, MI 49855 (United States)], E-mail: qzhang@nmu.edu

2006-09-15T23:59:59.000Z

124

Characterizing detonator output using dynamic witness plates  

SciTech Connect (OSTI)

A sub-microsecond, time-resolved micro-particle-image velocimetry (PIV) system is developed to investigate the output of explosive detonators. Detonator output is directed into a transparent solid that serves as a dynamic witness plate and instantaneous shock and material velocities are measured in a two-dimensional plane cutting through the shock wave as it propagates through the solid. For the case of unloaded initiators (e.g. exploding bridge wires, exploding foil initiators, etc.) the witness plate serves as a surrogate for the explosive material that would normally be detonated. The velocity-field measurements quantify the velocity of the shocked material and visualize the geometry of the shocked region. Furthermore, the time-evolution of the velocity-field can be measured at intervals as small as 10 ns using the PIV system. Current experimental results of unloaded exploding bridge wire output in polydimethylsiloxane (PDMS) witness plates demonstrate 20 MHz velocity-field sampling just 300 ns after initiation of the wire.

Murphy, Michael John [Los Alamos National Laboratory; Adrian, Ronald J [Los Alamos National Laboratory

2009-01-01T23:59:59.000Z

125

ARM - Instrument Location Table  

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

govInstrumentsLocation Table govInstrumentsLocation Table Instruments Location Table Contacts Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Instrument Locations Site abbreviations explained in the key. Instrument Name Abbreviation NSA SGP TWP AMF C1 C2 EF BF CF EF IF C1 C2 C3 EF IF Aerosol Chemical Speciation Monitor ACSM Atmospheric Emitted Radiance Interferometer AERI Aethalometer AETH Ameriflux Measurement Component AMC Aerosol Observing System AOS Meteorological Measurements associated with the Aerosol Observing System AOSMET Broadband Radiometer Station BRS

126

Reversible micromachining locator  

DOE Patents [OSTI]

This invention provides a device which includes a locator, a kinematic mount positioned on a conventional tooling machine, a part carrier disposed on the locator and a retainer ring. The locator has disposed therein a plurality of steel balls, placed in an equidistant position circumferentially around the locator. The kinematic mount includes a plurality of magnets which are in registry with the steel balls on the locator. In operation, a blank part to be machined is placed between a surface of a locator and the retainer ring (fitting within the part carrier). When the locator (with a blank part to be machined) is coupled to the kinematic mount, the part is thus exposed for the desired machining process. Because the locator is removably attachable to the kinematic mount, it can easily be removed from the mount, reversed, and reinserted onto the mount for additional machining. Further, the locator can likewise be removed from the mount and placed onto another tooling machine having a properly aligned kinematic mount. Because of the unique design and use of magnetic forces of the present invention, positioning errors of less than 0.25 micrometer for each machining process can be achieved. 7 figs.

Salzer, L.J.; Foreman, L.R.

1999-08-31T23:59:59.000Z

127

Location-specific weather predictions for Sriharikota (13.72N, 80.22E) through numerical atmospheric models during satellite launch campaigns  

Science Journals Connector (OSTI)

Accurate knowledge of different meteorological parameters over a launch site is very crucial for efficient management of satellite launch operations. Local weather over the Indian satellite launch site located at...

D. Bala Subrahamanyam; Radhika Ramachandran; S. Indira Rani

2012-04-01T23:59:59.000Z

128

Off-set stabilizer for comparator output  

DOE Patents [OSTI]

A stabilized off-set voltage is input as the reference voltage to a comparator. In application to a time-interval meter, the comparator output generates a timing interval which is independent of drift in the initial voltage across the timing capacitor. A precision resistor and operational amplifier charge a capacitor to a voltage which is precisely offset from the initial voltage. The capacitance of the reference capacitor is selected so that substantially no voltage drop is obtained in the reference voltage applied to the comparator during the interval to be measured.

Lunsford, James S. (Los Alamos, NM)

1991-01-01T23:59:59.000Z

129

Entrance Maze Locations  

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

Entrance Maze Locations Entrance Maze Locations for the Storage Ring Tunnel Martin Knott LS-83 2/17/87 The Purpose of this note is to document the locations and decision rationale of the entrance mazes for the APS storage ring. There are a total of seven entrance mazes, four on the infield side and three on the operating floor side of the ring. Three of the infield mazes are associated with infield buildings, one in the Extraction Building and one each in the two RF Buildings. These three were located to provide convenient passage between the technical buildings and the storage ring components associated with those buildings. The Extraction Building maze allows passage between the positron beam transfer area and the storage ring two sectors upstream of the injection

130

Reading Room Locations  

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

FOIA Offices and Reading Rooms FOIA Offices and Reading Rooms FOIA Office Locations Our FOIA Officers are located at various sites throughout the DOE complex, each with responsibility for records located at or under the jurisdiction of the site. We recommend that you send your request directly to that specific site. This will shorten the processing time. However, if you do not know which location has responsive records, you may either call the Headquarters FOIA office at (202) 586-5955 to determine the appropriate office, or mail the request to the Headquarters FOIA office. Other records are publicly available in the facilities listed below: Headquarters U.S. Department of Energy FOIA/Privacy Act Group 1000 Independence Avenue, SW Washington, D.C. 20585 Phone: 202-586-5955 Fax: 202-586-0575

131

Location linked information  

E-Print Network [OSTI]

This work builds an infrastructure called Location Linked Information that offers a means to associate digital information with public, physical places. This connection creates a hybrid virtual/physical space, called glean ...

Mankins, Matthew William David, 1975-

2003-01-01T23:59:59.000Z

132

International land rig locator  

SciTech Connect (OSTI)

Mechanical specifications, ratings, locations, and status are listed for each of the 5,000 contract rotary drilling rigs operated by the more than 700 independent drilling contractors throughout the Free World.

Not Available

1984-03-01T23:59:59.000Z

133

International land rig locator  

SciTech Connect (OSTI)

Mechanical specifications, ratings, locations, and status are listed for each of the 5,000 contract rotary drilling rigs operated by more than 700 independent drilling contractors throughout the Free World.

Not Available

1983-09-01T23:59:59.000Z

134

A numerical method for calculation of power output from ducted vertical axis hydro-current turbines  

Science Journals Connector (OSTI)

Abstract This paper investigates effects of ducting on power output from vertical axis hydro-current turbines. A numerical two-dimensional method based on the potential flow theory is developed for calculation of non-dimensional power output from these turbines. In this method, the blades are represented by vortex filaments. The vortex shedding from the blades is modeled by discrete vortices. A boundary element method is used to incorporate the duct shape which is represented by a series of panels with constant distributions of sources and doublets. The aerodynamic loading on the blades are calculated using a quasi-steady modeling. A time-marching scheme is used for implementation of the numerical method. The results of this method are compared with experimental results for a turbine model. A good correlation between the numerical and experimental results is obtained for tip speed ratios equal and higher than 2.25. However due to a lack of dynamic stall modeling, the numerical method is not able to predict power output accurately at lower tip speed ratios wherein effects of dynamic stall are significant. Both numerical and experimental results also showed that the power output from a turbine can increase significantly when it is enclosed within a well-designed duct. The maximum power output of the turbine model investigated in this paper showed a 74% increase when the turbine is operating within the duct relative to the case it is in free-stream conditions.

Mahmoud Alidadi; Sander Calisal

2014-01-01T23:59:59.000Z

135

Application of computer voice input/output  

SciTech Connect (OSTI)

The advent of microprocessors and other large-scale integration (LSI) circuits is making voice input and output for computers and instruments practical; specialized LSI chips for speech processing are appearing on the market. Voice can be used to input data or to issue instrument commands; this allows the operator to engage in other tasks, move about, and to use standard data entry systems. Voice synthesizers can generate audible, easily understood instructions. Using voice characteristics, a control system can verify speaker identity for security purposes. Two simple voice-controlled systems have been designed at Los Alamos for nuclear safeguards applicaations. Each can easily be expanded as time allows. The first system is for instrument control that accepts voice commands and issues audible operator prompts. The second system is for access control. The speaker's voice is used to verify his identity and to actuate external devices.

Ford, W.; Shirk, D.G.

1981-01-01T23:59:59.000Z

136

New Research Center to Increase Safety and Power Output of U.S. Nuclear  

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

New Research Center to Increase Safety and Power Output of U.S. New Research Center to Increase Safety and Power Output of U.S. Nuclear Reactors New Research Center to Increase Safety and Power Output of U.S. Nuclear Reactors May 3, 2011 - 3:41pm Addthis Oak Ridge, Tenn. - Today the Department of Energy dedicated the Consortium for Advanced Simulation of Light Water Reactors (CASL), an advanced research facility that will accelerate the advancement of nuclear reactor technology. CASL researchers are using supercomputers to study the performance of light water reactors and to develop highly sophisticated modeling that will help accelerate upgrades at existing U.S. nuclear plants. These upgrades could improve the energy output of our existing reactor fleet by as much as seven reactors' worth at a fraction of the cost of building new reactors, while providing continued improvements in

137

Coordinated Output Regulation of Multiple Heterogeneous Linear Systems  

E-Print Network [OSTI]

, the generalizations of coordination of multiple linear dynamic systems to the cooperative output regulation problemCoordinated Output Regulation of Multiple Heterogeneous Linear Systems Ziyang Meng, Tao Yang, Dimos V. Dimarogonas, and Karl H. Johansson Abstract-- The coordinated output regulation problem

Dimarogonas, Dimos

138

a r r i o r BUILDING# NAME LOCATION BUILDING# NAME LOCATION OTHER BUILDINGS LOCATION SORORITIES LOCATION  

E-Print Network [OSTI]

Admissions Parking Palmer Lake B l a c k W a r r i o r R i v e r BUILDING# NAME LOCATION BUILDING# NAME LOCATION OTHER BUILDINGS LOCATION SORORITIES LOCATION 7046 70127012 1155 10331033 1150 1039 1038

Carver, Jeffrey C.

139

location | OpenEI  

Open Energy Info (EERE)

location location Dataset Summary Description No description given. Source Oak Ridge National Laboratory Date Released November 30th, 2009 (5 years ago) Date Updated Unknown Keywords biodiesel ethanol location production capacity transportation Data application/zip icon Biorefineries.zip (zip, 7 MiB) Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage Frequency Time Period License License Other or unspecified, see optional comment below Comment Rate this dataset Usefulness of the metadata Average vote Your vote Usefulness of the dataset Average vote Your vote Ease of access Average vote Your vote Overall rating Average vote Your vote Comments Login or register to post comments If you rate this dataset, your published comment will include your rating.

140

Pine Tree Growth Locations  

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

Pine Tree Growth Locations Pine Tree Growth Locations Name: Amielee Location: N/A Country: N/A Date: N/A Question: Why do pine trees not grow south of the equator? Replies: Dear Amielee, The natural distribution of the pines is the northern hemisphere: http://phylogeny.arizona.edu/tree/eukaryotes/green_plants/embryophytes/conif ers/pinaceae/pinus/pinus.html However, pines have become introduced into the southern hemisphere through cultivation: http://www.woodweb.com/~treetalk/Radiata_Pine/wowhome.html Sincerely, Anthony R. Brach, Ph.D. Hi Amielee Some pine trees do live south of the equator but we (I live in Australia) do not have the huge forests of native conifers that you have in the northern hemisphere. Even in the northern hemisphere conifers are only found in two forest types: 1. Tiaga

Note: This page contains sample records for the topic "model output location" 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

University Location Project Description  

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

Location Project Description Location Project Description Boise State University Boise, Idaho Boise State University has undertaken a study of the structural setting and geothermal potential at Neal Hot Springs that will integrate geology, geochemistry, and geophysics to analyze the site on the western Snake River plain. Boise State will determine if Neal Hot Springs sustains the necessary rock dilation and conduit pathways for hydrothermal fluid flow and successful geothermal development. The result will be new data acquisition, including a deep geophysical survey and fault surface data. Colorado School of Mines Golden, Colorado Colorado School of Mines will conduct an investigation near Homedale, Idaho, an area that straddles volcanic rock and unconsolidated sediments.

142

The effect of small field output factor measurements on IMRT dosimetry  

SciTech Connect (OSTI)

Purpose: To evaluate how changes in the measured small field output factors affect the doses in intensity-modulated treatment planning. Methods: IMRT plans were created using Philips Pinnacle treatment planning system. The plans were optimized to treat a cylindrical target 2 cm in diameter and 2 cm in length. Output factors for 2 Multiplication-Sign 2 and 3 Multiplication-Sign 3 cm{sup 2} field sizes were changed by {+-}5%, {+-}10%, and {+-}20% increments from the baseline measurements and entered into the planning system. The treatment units were recommissioned in the treatment planning system after each modification of the output factors and treatment plans were reoptimized. All plans were delivered to a solid water phantom and dose measurements were made using an ionization chamber. The percentage differences between measured and computed doses were calculated. An Elekta Synergy and a Varian 2300CD linear accelerator were separately evaluated. Results: For the Elekta unit, decreasing the output factors resulted in higher measured than computed doses by 0.8% for -5%, 3.6% for -10%, and 8.7% for -20% steps. Increasing the output factors resulted in lower doses by 2.9% for +5%, 5.4% for +10%, and 8.3% for +20% steps. For the Varian unit no changes were observed for either increased or decreased output factors. Conclusions: The measurement accuracy of small field output factors are of importance especially when the treatment plan consists of small segments as in IMRT. The method proposed here could be used to verify the accuracy of the measured small field output factors for certain linear accelerators as well as to test the beam model. The Pinnacle treatment planning system model uses output factors as a function of jaw setting. Consequently, plans using the Elekta unit, which conforms the jaws to the segments, are sensitive to small field measurement accuracy. On the other hand, for the Varian unit, jaws are fixed and segments are modeled as blocked fields hence, the impact of small field output factors on IMRT monitor unit calculation is not evaluable by this method.

Azimi, Rezvan; Alaei, Parham; Higgins, Patrick [Department of Therapeutic Radiology-Radiation Oncology, University of Minnesota, Minneapolis, Minnesota 55455 (United States)

2012-08-15T23:59:59.000Z

143

Computer Lab Information Location  

E-Print Network [OSTI]

M340 Computer Lab Information · Location: The computer labs accessible to you are Weber 205 it is recommended that you save your files on a floppy when you are finished. · There is another directory, g:\\m340 to the saved files you have to add the directory to the Matlab path. To do this type addpath g:\\m340

Dangelmayr, Gerhard

144

Evaluation of solar energy resources by establishing empirical models for diffuse solar radiation on tilted surface and analysis for optimum tilt angle for a prospective location in southern region of Sindh, Pakistan  

Science Journals Connector (OSTI)

Abstract Diffuse solar radiation data is very important and is required for solar energy system implementations. The main purpose of the present study is to evaluate solar energy resources by establishing diffuse solar radiation models and obtaining optimum tilt angle fora prospective location is southern region of Sindh, Pakistan. Due to the unavailability of measured diffuse solar radiation data, nine new models, based on available data from local agency and values obtain from existing models, to predict diffuse solar radiation on tilted surface has been established. The best model was chosen based on test results from statistical indicators. The optimum tilt angle for monthly, seasonally, half-yearly and yearly adjustment was determined. The optimum tilt angle varies from 0 in May, June and July to 49 in December. The yearly optimum tilt angle was found as 23, which is close to latitude of investigated location (2507?N). The monthly average total, beam and diffuse solar radiations were calculated for optimum and vertical tilted surfaces and were compared with those obtain for horizontal surfaces. The half-yearly adjustment of optimum tilt angle is recommended for the investigated location because very small difference in annual solar energy gains in comparison with monthly or seasonal adjustment. The total annual energy for completer year and for four seasons of the year was calculated and found that maximum total annual energy is obtained at optimum tilt angle.

Shahnawaz Farhan Khahro; Kavita Tabbassum; Shahnawaz Talpur; Mohammad Bux Alvi; Xiaozhong Liao; Lei Dong

2015-01-01T23:59:59.000Z

145

Numerical modelling of the energy balance and the englacial temperature of the Greenland Ice Sheet. Calculations for the ETH-Camp location (West Greenland, 1155 m a.s.l.)  

Science Journals Connector (OSTI)

In the present work, a numerical model that calculates the surface energy blance, mass balance and temperature in the uppermost 25 m of ice at a single location on a glacier is presented. The model is forced by five basic meteorological elements: air temperature and humidity, wind speed, cloud amount and precipitation. The model was developed for studies of the Greenland Ice Sheet. Parameterizations of the surface energy fluxes were optimised with data mainly from the ETH Camp, West Greenland (1155 m a.s.l.). The model was tested on data collected during the summer of 1990 in the ETH Camp. In this case measurements of the radiative fluxes could be used. A reasonable fit between measurements and calculations of mass balance and englacial temperature could be obtained. The energy balance of this summer is discussed. In a second application, the annual cycle of the energy and mass balance and the englacial temperature at the location of the ETH Camp was simulated. In this case long term average values of the input variables were estimated from measurements at other locations and the radiative fluxes were computed with the parameterizations. The effect of model uncertainties on the calculated mass balance and 10 m ice temperature is discussed. The energy balance and the relation between air and ice temperature are analysed. The uncertainty in the calculated ablation is so large (5001000 mm w.e./yr) that the contribution of ablation on the Greenland Ice Sheet to sea-level rise cannot be calculated with sufficient accuracy (i.e. 60 mm w.e./yr) with this kind of model. However, the model should be appropriate for the determination of the sensitivity of ablation to climate change. It is predicted that at the ETH Camp the mass balance will decrease by 610 mm w.e./yr after a temperature increase of 1C.

Wouter Greuell; Thomas Konzelmann

1994-01-01T23:59:59.000Z

146

Effect of the block-spin configuration on the location of ?c in two-dimensional Ising modelsin two-dimensional Ising models  

Science Journals Connector (OSTI)

We consider the nearest neighbor Ising model on the 2D square lattice and...? c ...is close to 1, which, compared to the original nearest neighbor Ising? ...

Mohamed Ould-Lemrabott

1997-03-01T23:59:59.000Z

147

Transportation Networks and Location A Geometric Approach  

E-Print Network [OSTI]

Transportation Networks and Location A Geometric Approach Belén Palop1,2 1Departamento de March 2009 Florida State University #12;Belén Palop, UVa, SUNY Outline Transportation Network Model;Transportation Network Model Belén Palop, UVa, SUNY Outline Transportation Network Model Network placement

Palop del Río, Belén

148

Compact waveguide power divider with multiple isolated outputs  

DOE Patents [OSTI]

A waveguide power divider (10) for splitting electromagnetic microwave power and directionally coupling the divided power includes an input waveguide (21) and reduced height output waveguides (23) interconnected by axial slots (22) and matched loads (25) and (26) positioned at the unused ends of input and output guides (21) and (23) respectively. The axial slots are of a length such that the wave in the input waveguide (21) is directionally coupled to the output waveguides (23). The widths of input guide (21) and output guides (23) are equal and the width of axial slots (22) is one half of the width of the input guide (21).

Moeller, Charles P. (Del Mar, CA)

1987-01-01T23:59:59.000Z

149

An examination of the relationship between energy consumption and performance of transportation sector in Malaysia: output multipliers approach  

Science Journals Connector (OSTI)

The objective of the current study is to investigate the energy consumption and the performance of Malaysia's transportation sector. It applied output multiplier approach which is based on input-output model. Three input-output tables of Malaysia covering the 1991, 2000 and 2005 periods were used. The results indicate significant changes in the output multipliers of the transportation sector for the (1991-2005) period. Also, the transportation-to-energy subsector multipliers were found to increase over time. The increasing importance of transportation sector to the development of Malaysian economy resulted in a noticeable increase in the consumption of each energy subsector's output especially 'petrol and coal industries' products. Based on the research findings, several policy implications were suggested for the betterment of both sectors' performance and generally for the improvement of Malaysian economy.

Hussain Ali Bekhet; Azlina Abdullah

2013-01-01T23:59:59.000Z

150

GAMS program used to estimate capacity output using a distance function with both good and bad output, variable returns to scale and weak disposability of the bad outputs.  

E-Print Network [OSTI]

." VIMS Marine resource Report N. 2007-6. August 2007. Author: John B. Walden NMFS/NEFSC 166 Water St(obs) weights ; POSITIVE Variable weight, lambda; EQUATIONS CONSTR1(GOUTPUT, OBS) DEA constraint for each output

151

Clean Cities: Coalition Locations  

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

Locations Locations Clean Cities coalitions are primarily located in major metropolitan areas throughout the United States. Select the dots on the map for information about individual coalitions. See also the list of coalitions by designation date. United States map showing Clean Cities Coalition locations. Philadelphia State of Delaware Capitol Clean Cities of Connecticut Connecticut Southwestern Area New Haven Norwich Red River Valley (Grand Forks, Winnipeg, Manitoba, Canada) Silicon Valley (San Jose) East Bay (Oakland) San Francisco Sacramento Granite State State of Vermont Northeast Ohio Clean Transportation (Cleveland) Detroit Clean Communities of Western New York (Buffalo) Central New York (Syracuse) Capital District (Albany) Empire Clean Cities State of Maryland Washington DC Metropolitan South Shore Western Riverside County Southern California Association of Governments (SCAG) Atlanta Alabama Denver Philadelphia State of Delaware Las Vegas Washington DC Metropolitan Massachusetts Clean Cities Lone Star Clean Fuels Alliance (Austin) Southeast Florida Chicago Land of Enchantment Wisconsin-Southeast Area Southern Colorado Clean Cities Coalition Long Beach Antelope Valley Utah Clean Cities State of Maryland Kentucky Clean Cities Partnership Coalition Rogue Valley State of West Virginia San Joaquin Valley San Francisco Columbia-Willamette St. Louis Central New York (Syracuse) Dallas/Ft. Worth Honolulu Central Arkansas Pittsburgh Southern California Association of Governments (SCAG) Los Angeles Coachella Valley Region Northern Colorado Central Oklahoma (Oklahoma City) Virginia Clean Cities Coalition San Diego Regional Clean Cities Coalition Greater Long Island Maine Clean Communities Tulsa Valley of the Sun (Phoenix) Western Riverside County New Jersey Genesee Region (Rochester) Western Washington Clean Cities (Seattle) Ocean State Connecticut Connecticut2 Kansas City Regional Coalition Greater Indiana Clean Cities Coalition Capital District (Albany) Tucson Central Florida Clean Cities Coalition Alamo Area (San Antonio) Greater Baton Rouge Clean Cities Coalition Triangle (Raleigh, Durham, Chapel Hill) Twin Cities Clean Fuels Ohio Yellowstone-Teton Clean Energy Coalition Greater Lansing Palmetto State Houston-Galveston Middle Tennessee East Tennessee Clean Fuels Coalition Centralina Clean Fuels Coalition State of Iowa Treasure Valley Central Coast Southeast Louisiana Clean Fuels Partnership Land of Sky Coalition

152

Clean Cities: Coalition Locations  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Locations Locations Clean Cities coalitions are primarily located in major metropolitan areas throughout the United States. Select the dots on the map for information about individual coalitions. See also the list of coalitions by designation date. United States map showing Clean Cities Coalition locations. Philadelphia State of Delaware Capitol Clean Cities of Connecticut Connecticut Southwestern Area New Haven Norwich Red River Valley (Grand Forks, Winnipeg, Manitoba, Canada) Silicon Valley (San Jose) East Bay (Oakland) San Francisco Sacramento Granite State State of Vermont Northeast Ohio Clean Transportation (Cleveland) Detroit Clean Communities of Western New York (Buffalo) Central New York (Syracuse) Capital District (Albany) Empire Clean Cities State of Maryland Washington DC Metropolitan South Shore Western Riverside County Southern California Association of Governments (SCAG) Atlanta Alabama Denver Philadelphia State of Delaware Las Vegas Washington DC Metropolitan Massachusetts Clean Cities Lone Star Clean Fuels Alliance (Austin) Southeast Florida Chicago Land of Enchantment Wisconsin-Southeast Area Southern Colorado Clean Cities Coalition Long Beach Antelope Valley Utah Clean Cities State of Maryland Kentucky Clean Cities Partnership Coalition Rogue Valley State of West Virginia San Joaquin Valley San Francisco Columbia-Willamette St. Louis Central New York (Syracuse) Dallas/Ft. Worth Honolulu Central Arkansas Pittsburgh Southern California Association of Governments (SCAG) Los Angeles Coachella Valley Region Northern Colorado Central Oklahoma (Oklahoma City) Virginia Clean Cities Coalition San Diego Regional Clean Cities Coalition Greater Long Island Maine Clean Communities Tulsa Valley of the Sun (Phoenix) Western Riverside County New Jersey Genesee Region (Rochester) Western Washington Clean Cities (Seattle) Ocean State Connecticut Connecticut2 Kansas City Regional Coalition Greater Indiana Clean Cities Coalition Capital District (Albany) Tucson Central Florida Clean Cities Coalition Alamo Area (San Antonio) Greater Baton Rouge Clean Cities Coalition Triangle (Raleigh, Durham, Chapel Hill) Twin Cities Clean Fuels Ohio Yellowstone-Teton Clean Energy Coalition Greater Lansing Palmetto State Houston-Galveston Middle Tennessee East Tennessee Clean Fuels Coalition Centralina Clean Fuels Coalition State of Iowa Treasure Valley Central Coast Southeast Louisiana Clean Fuels Partnership Land of Sky Coalition

153

TRIPLE OUTPUT POWER SUPPLY Agilent MODEL E3630A  

E-Print Network [OSTI]

, manufacture, and intended use of the instrument. Agilent Technologies assumes no liability for the customer, the instrument chassis and cabinet must be connected to an electrical ground. The instrument must be connected to the ac power supply mains through a three-conductor power cable, with the third wire firmly connected

Ravikumar, B.

154

Modelling Power Output at Nuclear Power Plant by Neural Networks  

Science Journals Connector (OSTI)

In this paper, we propose two different neural network (NN) approaches for industrial process signal forecasting. Real data is available for this research from boiling water reactor type nuclear power reactors. N...

Jaakko Talonen; Miki Sirola; Eimontas Augilius

2010-01-01T23:59:59.000Z

155

Analytical input-output and supply chain study of China's coke and steel sectors  

E-Print Network [OSTI]

I design an input-output model to investigate the energy supply chain of coal-coke-steel in China. To study the demand, supply, and energy-intensity issues for coal and coke from a macroeconomic perspective, I apply the ...

Li, Yu, 1976-

2004-01-01T23:59:59.000Z

156

A metaheuristic approach for location of gas stations in a metropolitan area  

Science Journals Connector (OSTI)

The paper presents a metaheuristic model, which is developed to determine the location of gas stations in the state of Kuwait. The variables of this study cover requirements to high demand areas such as commercial areas, businesses as well as safety and environmental factors translated into minimum distances to sensitive entities and receptors. The developed methodology combines GIS with analytic hierarchy process (AHP) to weigh and overlay layers of interest on the base map of urban and suburban areas in Kuwait. The output on this process is a suitability map that contains feasible locations for future gas stations sites. Feasible locations are then fed into an optimisation routine to obtain the optimal sites. The methodology includes international and national standards and regulation including minimum allowable distance to existing gas stations, natural gas distributors, fire stations, educational institutions, governmental agencies and ministries, airport, residential areas, commercial areas, industrial areas, road network and others. 199 feasible locations were obtained in the State of Kuwait that abide with all regulation while satisfying demand of businesses and residents. The optimum was obtained from these feasible solutions by using an optimisation routine.

Esra Aleisa; Mehmet Savsar; Mohammed M. Al-Mashaan; Abrar Al-Jadi; Sarah A. Al-Sabah

2014-01-01T23:59:59.000Z

157

Constellation Shaping for Communication Channels with Quantized Outputs  

E-Print Network [OSTI]

average energy are selected more frequently than constellations with higher energy. However, the resultsConstellation Shaping for Communication Channels with Quantized Outputs Chandana Nannapaneni signal constellation and the output is quantized by a uniform scalar quantizer. The goal is to jointly

Valenti, Matthew C.

158

ANALOG-DIGITAL INPUT OUTPUT SYSTEM FOR APPLE CO  

E-Print Network [OSTI]

ADIOS ANALOG-DIGITAL INPUT OUTPUT SYSTEM FOR APPLE CO NATIONAL RADIO ASTRONOMY OBSERVATORY TABLES ADIOS - ANALOG-DIGITAL INPUT OUTPUT SYSTEM FOR APPLE COMPUTER TABLE FOR CONTENTS Page I Module and Apple Card (Photograph) Figure 3 Complete Apple/ADIOS System (Photograph) Figure 4 Analog

Groppi, Christopher

159

Most efficient quantum thermoelectric at finite power output  

E-Print Network [OSTI]

Machines are only Carnot efficient if they are reversible, but then their power output is vanishingly small. Here we ask, what is the maximum efficiency of an irreversible device with finite power output? We use a nonlinear scattering theory to answer this question for thermoelectric quantum systems; heat engines or refrigerators consisting of nanostructures or molecules that exhibit a Peltier effect. We find that quantum mechanics places an upper bound on both power output, and on the efficiency at any finite power. The upper bound on efficiency equals Carnot efficiency at zero power output, but decays with increasing power output. It is intrinsically quantum (wavelength dependent), unlike Carnot efficiency. This maximum efficiency occurs when the system lets through all particles in a certain energy window, but none at other energies. A physical implementation of this is discussed, as is the suppression of efficiency by a phonon heat flow.

Robert S. Whitney

2014-03-13T23:59:59.000Z

160

Test Cell Location  

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

Mazda 3 i-Stop Mazda 3 i-Stop Test Cell Location APRF- 4WD Vehicle Setup Information Downloadable Dynamometer Database (D 3 )- Test Summary Sheet Vehicle Architecture Conventional- Start Stop Vehicle Dynamometer Input Document Date 11/20/2012 Advanced Powertrain Research Facility Test weight [lb] 3250 Vehicle Dynamometer Input Document Date 11/20/2012 Revision Number 1 Advanced Powertrain Research Facility Test weight [lb] Target A [lb] 3250 31.2 Target B [lb/mph] Target C [lb/mph^2] 0.462 0.014 Test Fuel Information - Vehicle equipped with with i-Stop package - Manual Transmission - All tests completed in ECO mode - EPA shift schedule modified based on vehicle shift light activity Revision Number 1 Notes: Fuel type EPA Tier II EEE Gasoline Test Fuel Information - Vehicle equipped with with i-Stop package

Note: This page contains sample records for the topic "model output location" 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

Property:Event/Location | Open Energy Information  

Open Energy Info (EERE)

Location Location Jump to: navigation, search Property Name Event/Location Property Type String Description The location in which an event will occur. Examples: 'Golden, Colorado' or 'Prestigious Hotel: 11 Rue Leroy, Paris, France'. Pages using the property "Event/Location" Showing 25 pages using this property. (previous 25) (next 25) 1 11th Annual Workshop on Greenhouse Gas Emission Trading + Paris, France + 11th Annual Workshop on Greenhouse Gas Emission Trading Day 2 + Paris, France + 15th International Business Forum: Low Carbon High Growth - Business Models for a Changing Climate + Pretoria, South Africa + 18th Africa Partnership Forum + Paris, France + 2 2012 Bonn Climate Change Conference + Bonn, Germany + 7 7th Asia Clean Energy Forum + Manila, Philippines +

162

Locations Everyone: Lights, Camera, Action!  

Science Journals Connector (OSTI)

Locations Everyone: Lights, Camera, Action! ... Harvard Institute of Proteomics Harvard Medical School ...

Robert F. Murphy; Joshua LaBaer

2008-12-05T23:59:59.000Z

163

Relationship Among Efficiency and Output Power of Heat Energy Converters  

E-Print Network [OSTI]

Relationship among efficiency and output power of heat-electric energy converters as well as of any converters for transforming of heat energy into any other kind of energy is considered. It is shown, that the parameter efficiency does not determine univocally the output power of a converter. It is proposed to use another parameter for determination of working ability of heat energy converters. It is shown, that high output power can not be achieved by any kind of Stirling-type converters in spite of their high efficiency.

Alexander Luchinskiy

2004-09-02T23:59:59.000Z

164

Impurity-doped optical shock, detonation and damage location sensor  

DOE Patents [OSTI]

A shock, detonation, and damage location sensor providing continuous fiber-optic means of measuring shock speed and damage location, and could be designed through proper cabling to have virtually any desired crush pressure. The sensor has one or a plurality of parallel multimode optical fibers, or a singlemode fiber core, surrounded by an elongated cladding, doped along their entire length with impurities to fluoresce in response to light at a different wavelength entering one end of the fiber(s). The length of a fiber would be continuously shorted as it is progressively destroyed by a shock wave traveling parallel to its axis. The resulting backscattered and shifted light would eventually enter a detector and be converted into a proportional electrical signals which would be evaluated to determine shock velocity and damage location. The corresponding reduction in output, because of the shortening of the optical fibers, is used as it is received to determine the velocity and position of the shock front as a function of time. As a damage location sensor the sensor fiber cracks along with the structure to which it is mounted. The size of the resulting drop in detector output is indicative of the location of the crack.

Weiss, Jonathan D. (Albuquerque, NM)

1995-01-01T23:59:59.000Z

165

Impurity-doped optical shock, detonation and damage location sensor  

DOE Patents [OSTI]

A shock, detonation, and damage location sensor providing continuous fiber-optic means of measuring shock speed and damage location, and could be designed through proper cabling to have virtually any desired crush pressure. The sensor has one or a plurality of parallel multimode optical fibers, or a singlemode fiber core, surrounded by an elongated cladding, doped along their entire length with impurities to fluoresce in response to light at a different wavelength entering one end of the fiber(s). The length of a fiber would be continuously shorted as it is progressively destroyed by a shock wave traveling parallel to its axis. The resulting backscattered and shifted light would eventually enter a detector and be converted into a proportional electrical signals which would be evaluated to determine shock velocity and damage location. The corresponding reduction in output, because of the shortening of the optical fibers, is used as it is received to determine the velocity and position of the shock front as a function of time. As a damage location sensor the sensor fiber cracks along with the structure to which it is mounted. The size of the resulting drop in detector output is indicative of the location of the crack. 8 figs.

Weiss, J.D.

1995-02-07T23:59:59.000Z

166

Output, efficiency, emissions improved with Cat's 3500 series B engine  

SciTech Connect (OSTI)

Like most technologies, engine developments tend to follow evolutionary paths. And it's a given that the longer an engine's been around and the more successful it's been, the more likely it is that any changes made would be incremental. On the surface, such is the case with the Caterpillar 3500 Series B diesel engine, recently introduced in Europe and the United States. Based on the well-proven 3500 engine first introduced in 1980 and upgraded with a Phase II program five years later, most of the changes appear incremental. But taken as a whole, they provide a level of performance and durability that Caterpillar anticipates will make this engine an even stronger contender in power generation and marine applications for years to come. It's not hard to see why. Output has been increased between 17% and 30% on some models; fuel consumption is improved by as much as 15%; and with the new aftertreatment system introduced with the engines, emissions as low as 1.3 g/kWh NO[sub x] are said to be achieveable. This paper outlines the design, specifications, and highlights of the improvements in performance of these new engines. 3 figs.

Brezonick, M.

1995-03-01T23:59:59.000Z

167

Test Cell Location  

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

Chrysler 300 Chrysler 300 Test Cell Location 2WD Vehicle Setup Information Downloadable Dynamometer Database (D 3 )- Test Summary Sheet Vehicle Architecture Conventional Vehicle Dynamometer Input Document Date 8/7/2013 Advanced Powertrain Research Facility Test weight [lb] Target A [lb] 4250 38.61 Target B [lb/mph] Target C [lb/mph^2] 0.8894 0.01105 3.6L VVT Port-injected V-6 8 speed Transmission Revision Number 3 Notes: Test Fuel Information 3.6L VVT Port-injected V-6 8 speed Transmission Fuel type Tier II EEE HF437 3.6L VVT Port-injected V-6 8 speed Transmission Fuel density [g/ml] Fuel Net HV [BTU/lbm] 0.743 18490 T e s t I D [ # ] C y c l e C o l d s t a r t ( C S t ) H o t s t a r t [ H S t ] D a t e T e s t C e l l T e m p [ C ] T e s t C e l l R H [ % ] T e s t C e l l B a r o [ i n / H g ] V e h i c l e c o o l i n g f a n s p e e d : S p e e d M a t c h [ S M ] o r c o n s t a n t s p e e d [ C S ] S

168

Computability in Anonymous Networks: Revocable vs. Irrecovable Outputs  

E-Print Network [OSTI]

Computability in Anonymous Networks: Revocable vs. Irrecovable Outputs Yuval Emek1 , Jochen Seidel2, and leader election. 1 Introduction We study computability in networks, referred to hereafter as distributed

169

Failure mode and effects analysis outputs: are they valid?  

Science Journals Connector (OSTI)

Failure Mode and Effects Analysis (FMEA) is a prospective risk assessment tool that ... this study was to explore the validity of FMEA outputs within a hospital setting in the...

Nada Atef Shebl; Bryony Dean Franklin; Nick Barber

2012-06-01T23:59:59.000Z

170

Grid adaptation for functional outputs of compressible flow simulations  

E-Print Network [OSTI]

An error correction and grid adaptive method is presented for improving the accuracy of functional outputs of compressible flow simulations. The procedure is based on an adjoint formulation in which the estimated error in ...

Venditti, David Anthony, 1973-

2002-01-01T23:59:59.000Z

171

Reliable Gas Turbine Output: Attaining Temperature Independent Performance  

E-Print Network [OSTI]

of availability, it is the major option for future power generation. One inherent disadvantage of gas turbines is the degradation of output as the ambient air temperature increases. This reduction in output during times of peak load create a reliability..., power generation for offshore platforms, utility peak load 58 ESL-IE-92-04-10 Proceedings from the 14th National Industrial Energy Technology Conference, Houston, TX, April 22-23, 1992 power generation, emergency power, ship propulsion, and private...

Neeley, J. E.; Patton, S.; Holder, F.

172

Guide to the Library Locations  

E-Print Network [OSTI]

Guide to the Libraries #12;Library Locations W.E.B. DU BOIS LIBRARY www.library.umass.edu 154 Hicks Way (413) 545-0150, (413) 545-2622 The Du Bois Library is the primary location for resources machine, and a fax machine. Quiet study space is located on Floors 2 and 3 and throughout the upper floors

Massachusetts at Amherst, University of

173

Spring loaded locator pin assembly  

DOE Patents [OSTI]

This invention deals with spring loaded locator pins. Locator pins are sometimes referred to as captured pins. This is a mechanism which locks two items together with the pin that is spring loaded so that it drops into a locator hole on the work piece.

Groll, Todd A. (Idaho Falls, ID); White, James P. (Pocatelo, ID)

1998-01-01T23:59:59.000Z

174

Spring loaded locator pin assembly  

DOE Patents [OSTI]

This invention deals with spring loaded locator pins. Locator pins are sometimes referred to as captured pins. This is a mechanism which locks two items together with the pin that is spring loaded so that it drops into a locator hole on the work piece. 5 figs.

Groll, T.A.; White, J.P.

1998-03-03T23:59:59.000Z

175

Ota City : characterizing output variability from 553 homes with residential PV systems on a distribution feeder.  

SciTech Connect (OSTI)

This report describes in-depth analysis of photovoltaic (PV) output variability in a high-penetration residential PV installation in the Pal Town neighborhood of Ota City, Japan. Pal Town is a unique test bed of high-penetration PV deployment. A total of 553 homes (approximately 80% of the neighborhood) have grid-connected PV totaling over 2 MW, and all are on a common distribution line. Power output at each house and irradiance at several locations were measured once per second in 2006 and 2007. Analysis of the Ota City data allowed for detailed characterization of distributed PV output variability and a better understanding of how variability scales spatially and temporally. For a highly variable test day, extreme power ramp rates (defined as the 99th percentile) were found to initially decrease with an increase in the number of houses at all timescales, but the reduction became negligible after a certain number of houses. Wavelet analysis resolved the variability reduction due to geographic diversity at various timescales, and the effect of geographic smoothing was found to be much more significant at shorter timescales.

Stein, Joshua S.; Miyamoto, Yusuke (Kandenko, Ibaraki, Japan); Nakashima, Eichi (Kandenko, Ibaraki, Japan); Lave, Matthew

2011-11-01T23:59:59.000Z

176

Determining Optimal Locations for New Wind Energy Development in Iowa.  

E-Print Network [OSTI]

??The purpose of this research is to generate the most accurate model possible for predicting locations most suitable for new wind energy development using a (more)

Mann, David

2011-01-01T23:59:59.000Z

177

GIS and Location Theory Based Bioenergy Systems Planning.  

E-Print Network [OSTI]

??This research is concerned with bioenergy systems planning and optimization modelling in the context of locating biomass power plants and allocating available biomass feedstock to (more)

Dong, Jingyuan

2008-01-01T23:59:59.000Z

178

Mobile Alternative Fueling Station Locator  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Alternative Fueling Station Locator Alternative Fueling Station Locator Fuel Type Biodiesel (B20 and above) Compressed Natural Gas Electric Ethanol (E85) Hydrogen Liquefied Natural Gas (LNG) Liquefied Petroleum Gas (Propane) Location Enter a city, postal code, or address Include private stations Not all stations are open to the public. Choose this option to also search private fueling stations. Search Caution: The AFDC recommends that users verify that stations are open, available to the public, and have the fuel prior to making a trip to that location. Some stations in our database have addresses that could not be located by the Station Locator application. This may result in the station appearing in the center of the zip code area instead of the actual location. If you're having difficulty, please contact the technical response team at

179

Location-based Sponsored Search Advertising George Trimponias1  

E-Print Network [OSTI]

Location-based Sponsored Search Advertising George Trimponias1 , Ilaria Bartolini2 , Dimitris unprecedented opportunities for location-based advertising. In this work, we provide models and investigate the market for location-based sponsored search, where advertisers pay the search engine to be displayed

Papadias, Dimitris

180

Analysis of Temporal and Spatial Characteristics on Output of Wind Farms with Doubly Fed Induction Generator Wind Turbines  

Science Journals Connector (OSTI)

Due to the large number of wind turbines and covering too large area in a large wind farm, wake effects among wind turbines and wind speed time delays will have a greater impact of wind farms models. Taking wind farms with doubly fed induction generator(DFIG) ... Keywords: wind farm, modeling, temporal and spatial characteristics, DFIG, output characteristics

Shupo Bu; Xunwen Su

2012-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" 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

Categorical Exclusion Determinations: Other Location | Department of Energy  

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

Other Location Other Location Categorical Exclusion Determinations: Other Location Location Categorical Exclusion Determinations issued for actions in other locations. DOCUMENTS AVAILABLE FOR DOWNLOAD September 24, 2013 CX-010914: Categorical Exclusion Determination Pilot Testing of a Highly Efficient Pre-Combustion Sorbent-Based Carbon Capture System (SUMMARY Categorical Exclusion (CX)) CX(s) Applied: A9, A11, B3.6 Date: 09/24/2013 Location(s): Multiple States, China, Canada Offices(s): National Energy Technology Laboratory August 21, 2013 CX-010781: Categorical Exclusion Determination A Geomechanical Model for Gas Shales Based on Integration of Stress CX(s) Applied: A9, A11, B3.6 Date: 08/21/2013 Location(s): Pennsylvania Offices(s): National Energy Technology Laboratory August 16, 2013

182

Estimation of annual energy output from a tidal barrage using two different methods  

Science Journals Connector (OSTI)

In recent years, there have been growing international challenges relating to climate change and global warming, with a conflict developing between the need to create a low-carbon economy and rapid depleting reserves of fossil fuels. In addition to these challenges there continues to be the added complexity of a significant global increase in energy demand. Marine renewable energy from tidal barrages is carbon-free and has the potential to make a significant contribution to energy supplies now and in the future. Therefore, it is appropriate to evaluate the total energy that can be extracted from such barrages. In this study two different methods are proposed to estimate the total annual energy output from a barrage, including a theoretical estimation based on the principle associated with tidal hydrodynamics, and a numerical estimation based on the solutions obtained from a 2D hydrodynamic model. The proposed Severn Barrage in the UK was taken as a case study, and these two methods were applied to estimate the potential annual energy output from the barrage. The predicted results obtained using the two methods indicate that the magnitude of the annual energy output would range from 13 to 16TWh, which is similar to the value of 15.6TWh reported by the Department of Energy and Climate Change, in the UK. Further investigations show that the total annual energy output would increase by about 15% if a higher discharge coefficient were to be adopted for the sluice gates, or if the turbine performance were to be improved. However, the estimated annual energy output could exceed the value of 16TWh if future technological advances in both sluice gate construction and turbine performance are included.

Junqiang Xia; Roger A. Falconer; Binliang Lin; Guangming Tan

2012-01-01T23:59:59.000Z

183

LOCATION: Johnson County Sheriff's Office  

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

LOCATION: Johnson County Sheriff's Office Criminalistics Laboratory 11890 Sunset Drive Olathe, Kansas 66061 DATE: JULY 15TH - JULY 18TH, 2013 TUITION: MAFS MEMBERS: 550 Non-MAFS...

184

Carbon Capture, Transport and Storage Regulatory Test Exercise: Output  

Open Energy Info (EERE)

Carbon Capture, Transport and Storage Regulatory Test Exercise: Output Carbon Capture, Transport and Storage Regulatory Test Exercise: Output Report Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Carbon Capture, Transport and Storage Regulatory Test Exercise: Output Report Focus Area: Clean Fossil Energy Topics: Market Analysis Website: cdn.globalccsinstitute.com/sites/default/files/publications/7326/carbo Equivalent URI: cleanenergysolutions.org/content/carbon-capture-transport-and-storage- Policies: Regulations Regulations: Emissions Mitigation Scheme The Scottish Government published this report to identify regulatory gaps or overlaps in the nation's framework for regulating carbon capture and storage (CCS). The report aims to streamline and better manage CCS regulation. It focuses on evaluating the risks, barriers, information gaps,

185

OECD Input-Output Tables | Open Energy Information  

Open Energy Info (EERE)

OECD Input-Output Tables OECD Input-Output Tables Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Input-Output Tables Agency/Company /Organization: Organisation for Economic Co-Operation and Development Topics: Co-benefits assessment, Market analysis, Co-benefits assessment, Pathways analysis Resource Type: Dataset Website: www.oecd.org/document/3/0,3343,en_2649_34445_38071427_1_1_1_1,00.html Country: Sweden, Finland, Japan, South Korea, Argentina, Australia, China, Israel, United Kingdom, Portugal, Romania, Greece, Poland, Slovakia, Chile, India, Canada, New Zealand, United States, Denmark, Norway, Spain, Austria, Italy, Netherlands, Ireland, France, Belgium, Brazil, Czech Republic, Estonia, Germany, Hungary, Luxembourg, Mexico, Slovenia, South Africa, Turkey, Indonesia, Switzerland, Taiwan, Russia

186

Mobile Alternative Fueling Station Locator  

SciTech Connect (OSTI)

The Department of Energy's Alternative Fueling Station Locator is available on-the-go via cell phones, BlackBerrys, or other personal handheld devices. The mobile locator allows users to find the five closest biodiesel, electricity, E85, hydrogen, natural gas, and propane fueling sites using Google technology.

Not Available

2009-04-01T23:59:59.000Z

187

Open neighborhood locatingdominating in trees  

Science Journals Connector (OSTI)

For a graph G that models a facility or a multiprocessor network, detection devices can be placed at the vertices so as to identify the location of an intruder such as a thief or saboteur or a faulty processor. Open neighborhood locatingdominating sets are of interest when the intruder/fault at a vertex precludes its detection at that location. The parameter OLD ( G ) denotes the minimum cardinality of a vertex set S ? V ( G ) such that for each vertex v in V ( G ) its open neighborhood N ( v ) has a unique non-empty intersection with S . For a tree T n of order n we have ? n / 2 ? + 1 ? OLD ( T n ) ? n ? 1 . We characterize the trees that achieve these extremal values.

Suk J. Seo; Peter J. Slater

2011-01-01T23:59:59.000Z

188

Development of a 402.5 MHz 140 kW Inductive Output Tube  

SciTech Connect (OSTI)

This report contains the results of Phase I of an SBIR to develop a Pulsed Inductive Output Tube (IOT) with 140 kW at 400 MHz for powering H-proton beams. A number of sources, including single beam and multiple beam klystrons, can provide this power, but the IOT provides higher efficiency. Efficiencies exceeding 70% are routinely achieved. The gain is typically limited to approximately 24 dB; however, the availability of highly efficient, solid state drivers reduces the significance of this limitation, particularly at lower frequencies. This program initially focused on developing a 402 MHz IOT; however, the DOE requirement for this device was terminated during the program. The SBIR effort was refocused on improving the IOT design codes to more accurately simulate the time dependent behavior of the input cavity, electron gun, output cavity, and collector. Significant improvement was achieved in modeling capability and simulation accuracy.

R. Lawrence Ives; Michael Read, Robert Jackson

2012-05-09T23:59:59.000Z

189

Output power characteristics and performance of TOPAZ II Thermionic Fuel Element No. 24  

SciTech Connect (OSTI)

A final report on the output power characteristics and capabilities of single cell TOPAZ II Thermionic Fuel Element (TFE) No. 24 is presented. Thermal power tests were conducted for over 3000 hours to investigate converter performance under normal and adverse operating conditions. Experiments conducted include low power testing, high power testing, air introduction to the interelectrode gap, collector temperature optimization, thermal modeling, and output power characteristic measurements. During testing, no unexpected degradation in converter performance was observed. The TFE has been removed from the test stand and returned to Scientific Industrial Association {open_quote}{open_quote}LUCH{close_quote}{close_quote} for materials analysis and report. This research was conducted at the Thermionic System Evaluation Test (TSET) Facility at the New Mexico Engineering Research Institute (NMERI) as a part of the Topaz International Program (TIP) by the Air Force Phillips Laboratory (PL). {copyright} {ital 1996 American Institute of Physics.}

Luchau, D.W.; Bruns, D.R. [Team Specialty Services, Inc., TOPAZ International Program, 901 University Blvd., SE, Albuquerque, New Mexico 87106 (United States); Izhvanov, O.; Androsov, V. [JV INERTEK, Scientific Industrial Association ``Luch``, 24 Zheleznodorozhnaya, Podolsk, (Russia) 142100

1996-03-01T23:59:59.000Z

190

An input-output approach to analyze the ways to increase total output of energy sectors: The case of Japan  

Science Journals Connector (OSTI)

The purpose of this study is to analyze the ways to increase total output of Japanese energy sectors in future time. In this study, Input-Output (IO) analysis is employed as a tool of analysis. This study focuses on petroleum refinery products and non-ferrous metals as analyzed sectors. The results show that positive impact observed in export and outside households consumption modifications while opposite impact is given by modification of import. The recommendations suggested based on these results are Japanese government should make breakthroughs so analyzed sector's export activities can increase and they have to careful in conducting import activities related to these sectors.

Ubaidillah Zuhdi

2014-01-01T23:59:59.000Z

191

Output-Based Regulations: A Handbook for Air Regulators (U.S. EPA), August 2004  

Broader source: Energy.gov [DOE]

Handbook providing practical information to help regulators decide if they want to use output-based regulations and explains how to develop an output-based emission standard

192

Output-Sensitive Algorithms for Tukey Depth and Related Problems  

E-Print Network [OSTI]

Output-Sensitive Algorithms for Tukey Depth and Related Problems David Bremner University of New de Bruxelles Pat Morin Carleton University Abstract The Tukey depth (Tukey 1975) of a point p halfspace that contains p. Algorithms for computing the Tukey depth of a point in various dimensions

Morin, Pat

193

Soft-Input Soft-Output Sphere Decoding Christoph Studer  

E-Print Network [OSTI]

Soft-Input Soft-Output Sphere Decoding Christoph Studer Integrated Systems Laboratory ETH Zurich Laboratory ETH Zurich, 8092 Zurich, Switzerland Email: boelcskei@nari.ee.ethz.ch Abstract--Soft-input soft, 8092 Zurich, Switzerland Email: studer@iis.ee.ethz.ch Helmut Bölcskei Communication Technology

194

Maximizing output from oil reservoirs without water breakthrough  

E-Print Network [OSTI]

Maximizing output from oil reservoirs without water breakthrough S.K. Lucas School of Mathematics, revised May 2003, published 45(3), 2004, 401­422 Abstract Often in oil reservoirs a layer of water lies, for example, Muskat [8], Bear [1]). When oil is removed from the reservoir by an oil well, it will generate

Lucas, Stephen

195

Model Development Development of a system emulating the global carbon cycle in Earth system models  

E-Print Network [OSTI]

developed a loosely coupled model (LCM) which can represent the outputs of a GCMbased Earth system model

K. Tachiiri; J. C. Hargreaves; J. D. Annan; A. Oka; A. Abe-ouchi; M. Kawamiya

2010-01-01T23:59:59.000Z

196

Effect of local government expenditure on the ratio of output to capital: Evidence from panel data at Chinas provincial level  

Science Journals Connector (OSTI)

This paper divides the expenditure of local government into the productive and nonproductive expenditure for revealing the effect of local governments expenditure on output-capital efficiency through model and e...

Tao Jin; Jianhui Zhang

2011-06-01T23:59:59.000Z

197

Location theory and the location of industry along an interstate highway  

E-Print Network [OSTI]

identified in theory will provide a basis for the "empirical" model or system of classification to be used in tabulating the response to the survey. Of particular interest is the theoretical development of the ms]or forces in plant location; i. e, , cost... identified in theory will provide a basis for the "empirical" model or system of classification to be used in tabulating the response to the survey. Of particular interest is the theoretical development of the ms]or forces in plant location; i. e, , cost...

Miller, James Patterson

2012-06-07T23:59:59.000Z

198

Location-aware active signage  

E-Print Network [OSTI]

Three-dimensional route maps, which depict a path from one location to another, can be powerful tools for visualizing and communicating directions. This thesis presents a client-server architecture for generating and ...

Nichols, Patrick James, 1981-

2004-01-01T23:59:59.000Z

199

Mask locations in the SLC final focus region  

SciTech Connect (OSTI)

The location of four sets of masks needed to shield against background in the final focus region of the SLC is shown. The main point of this note is to update the results of Miller and Sens taking into account the recent changes that have been made in the optics of the SLC beams. For the latest beam design we use the TRANSPORT output dated 5-13-83. This design assumes that the final bends will form an S about the interaction point and that the final quadrupoles will be superconducting and will be placed about 8 feet from the interaction point.

Cence, R.J.

1983-07-05T23:59:59.000Z

200

A CMOS contact imager for locating individual Honghao Ji, David Sander, Alfred Haas, Pamela A. Abshire  

E-Print Network [OSTI]

to the background illumination. The imager is capable of locating dark objects in a bright background or bright objects in a dark background. The loca- tions of recognized cells are generated as outputs to alleviate of intracel- lular processes, drug development, medical diagnostics, and the development of cell-based sensors

Maryland at College Park, University of

Note: This page contains sample records for the topic "model output location" 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

Clock-controlled generators with large period output sequences  

Science Journals Connector (OSTI)

Clock-controlled generators are a kind of pseudo-random number generators (PRNG). Recently, some clock-controlled generators based on jumping Linear Finite State Machines (LFSMs) have been proposed, such as Pomaranch and MICKEY. The period and the linear complexity of their output sequences need to be large enough to provide security against linear attacks. In this paper, a new condition for the period to reach its maximal value is presented. The condition is better than the previous one. Further, some clock-controlled generators are considered, including a new generator which uses a Feedback with Carry Shift Register (FCSR) as the control register. How to maximise the period of their output sequences is investigated.

Zhiqiang Lin

2014-01-01T23:59:59.000Z

202

Control of XeF laser output by pulse injecton  

SciTech Connect (OSTI)

Injection locking is investigated as a means for control of optical pulse duration and polarization in a XeF laser. Intense short-pulse generation in the ultraviolet is achieved by injection of a low-level 1-ns optical pulse into a XeF oscillator. Control of laser output polarization by injection locking is demonstrated and studied as a function of injected signal level. Enhancement of XeF electric-discharge laser efficiency by injection pulse ''priming'' is observed.

Pacala, T.J.; Christensen, C.P.

1980-04-15T23:59:59.000Z

203

State-space model identification and feedback control of unsteady aerodynamic forces  

E-Print Network [OSTI]

Unsteady aerodynamic models are necessary to accurately simulate forces and develop feedback controllers for wings in agile motion; however, these models are often high dimensional or incompatible with modern control techniques. Recently, reduced-order unsteady aerodynamic models have been developed for a pitching and plunging airfoil by linearizing the discretized Navier-Stokes equation with lift-force output. In this work, we extend these reduced-order models to include multiple inputs (pitch, plunge, and surge) and explicit parameterization by the pitch-axis location, inspired by Theodorsen's model. Next, we investigate the na\\"{\\i}ve application of system identification techniques to input--output data and the resulting pitfalls, such as unstable or inaccurate models. Finally, robust feedback controllers are constructed based on these low-dimensional state-space models for simulations of a rigid flat plate at Reynolds number 100. Various controllers are implemented for models linearized at base angles of ...

Brunton, Steven L; Rowley, Clarence W

2014-01-01T23:59:59.000Z

204

Output power characteristics of the neutral xenon long laser  

SciTech Connect (OSTI)

Lasers which oscillate within inhomogeneously broadened gain media exhibit spectral hole burning and concomitant reduction in output power compared with equivalent homogeneously-broadened laser gain media. By increasing the cavity length, it may be possible to demonstrate at least a partial transition from an inhomogeneous laser cavity mode spectrum to a homogeneous spectrum. There are a number of high gain laser lines which are inhomogeneously-broadened transitions in electric discharges of neutral xenon. In neutral xenon lasers, as in the cases of many other gas lasers, the inhomogeneous spectral broadening mechanism arises from Doppler shifts, {Delta}{nu}{sub D}, of individual atoms in thermal motion within the electric discharge comprising the laser gain medium. Optical transitions corresponding to these noble gas atoms have natural linewidths, {Delta}{nu}{sub n}{lt}{Delta}{nu}{sub D}. Simulations of the output power characteristics of the xenon laser were carried out as a function of laser cavity parameters, including the cavity length, L. These calculations showed that when the intracavity mode spacing frequency, c/2L{lt}{Delta}{nu}{sub n}, the inhomogeneously broadened xenon mode spectrum converted to a homogeneously broadened oscillation spectrum with an increase in output power. These simulations are compared with experimental results obtained for the long laser oscillation characteristics of the (5d[5/2]{degree}{sub 2}{r_arrow}6p[3/2]{sub 1}) transition corresponding to the strong, high-gain 3.508 {mu} line in xenon.

Linford, G.J. [TRW Space and Electronics Group, Redondo Beach, CA (United States). Space and Technology Div.

1994-12-31T23:59:59.000Z

205

Location logistics of industrial facilities  

E-Print Network [OSTI]

is not growing rapidly or 1s very small, they may not carry a staff from wh1ch the necessary people for a 25 s1te selection team can be drawn. Also, quite possibly, a company may not be involved in the site selection process for expansion. Instead, they may... location and site selection. This data was gathered through library research, atten- dance of various industr1al development conferences, sol1citation of mater1als from individuals currently involved with industrial facil1ties location, and various...

Hammack, William Eugene

2012-06-07T23:59:59.000Z

206

Major DOE Biofuels Project Locations  

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

Biofuels Project Locations Biofuels Project Locations BlueFire Ethanol Biochemical Municipal Solid Waste (Mecca, CA) Poet Biochemical Corn Cob/Corn Fiber (Emmetsburg, IA) Lignol Biochemical Woody Biomass- Ag Residues (Grand Junction, CO) ICM Biochemical Switchgrass, Forage Sorghum, Stover (St. Joseph, MO) Abengoa Biochemica Agricultural Residue (Hugoton, KS) DOE Joint Bioenergy Institute (Berkeley, CA) DOE Great Lakes Bioenergy Research Center (Madison, WI) DOE Bioenergy Science Center (Oak Ridge, TN) NewPage Thermochemical Woody Biomass - Mill Residues (Wisconsin Rapids, WI) Range Fuels Thermochemical Woody Waste (Soperton, GA) DSM Innovation Center Biochemical Various (Parsippany, NJ) Novozymes Biochemical Various (Davis, CA) Genencor Biochemical Various (Palo Alto, CA) Verenium Corp Biochemical Various (San Diego, CA)

207

Analysis of photovoltaic module energy output under operating conditions in South Africa  

SciTech Connect (OSTI)

South Africa does not have any industry standard methodology to evaluate photovoltaic (PV) modules for energy production. The aim of this study is to characterize the energy production of PV modules deployed outdoors at the University of Port Elizabeth (UPE), Summerstrand, South Africa with the view of facilitating such a standard. The system developed for this study was designed to monitor the energy production of seven PV modules under normal operating conditions. An analysis of energy production of three of the PV modules under test, while operating under prevailing outdoor conditions, is given. Measured energy output is also compared with that predicted using an energy model.

Dyk, E.E. van; Meyer, E.L.; Scott, B.J.; O`Connor, D.A.; Wessels, J.B. [Univ. of Port Elizabeth (South Africa). Dept. of Physics

1997-12-31T23:59:59.000Z

208

WORKING PAPER N 2009 -11 Regulatory policy and the location  

E-Print Network [OSTI]

Pamina Koenig Megan MacGarvie JEL Codes: F23, I18 Keywords: Pharmaceutical industry, location choices: pharmaceutical industry, location choices, price regulations, discrete choice model This paper was prepared plants. The pharmaceutical industry is one example of this type of industry. The pharmaceutical industry

Paris-Sud XI, Université de

209

Inferring human mobility patterns from taxicab location traces  

Science Journals Connector (OSTI)

Taxicabs equipped with real-time location sensing devices are increasingly becoming popular. Such location traces are a rich source of information and can be used for congestion pricing, taxicab placement, and improved city planning. An important problem ... Keywords: hidden markov models, human mobility patterns, taxi cab occupancy, trajectory analysis

Raghu Ganti; Mudhakar Srivatsa; Anand Ranganathan; Jiawei Han

2013-09-01T23:59:59.000Z

210

Predicting Debris-Slide Locations in Northwestern California1  

E-Print Network [OSTI]

Predicting Debris-Slide Locations in Northwestern California1 Mark E. Reid,2 Stephen D. Ellen,3 tested four topographic models for predicting locations of debris-slide sources: 1) slope; 2) proximity to stream; 3) SHALSTAB with "standard" parameters; and 4) debris-slide-prone landforms, which delineates

Standiford, Richard B.

211

Efficient data IO for a Parallel Global Cloud Resolving Model  

SciTech Connect (OSTI)

Execution of a Global Cloud Resolving Model (GCRM) at target resolutions of 2-4 km will generate, at a minimum, 10s of Gigabytes of data per variable per snapshot. Writing this data to disk without creating a serious bottleneck in the execution of the GCRM code while also supporting efficient post-execution data analysis is a significant challenge. This paper discusses an Input/Output (IO) application programmer interface (API) for the GCRM that efficiently moves data from the model to disk while maintaining support for community standard formats, avoiding the creation of very large numbers of files, and supporting efficient analysis. Several aspects of the API will be discussed in detail. First, we discuss the output data layout which linearizes the data in a consistent way that is independent of the number of processors used to run the simulation and provides a convenient format for subsequent analyses of the data. Second, we discuss the flexible API interface that enables modelers to easily add variables to the output stream by specifying where in the GCRM code these variables are located and to flexibly configure the choice of outputs and distribution of data across files. The flexibility of the API is designed to allow model developers to add new data fields to the output as the model develops and new physics is added and also provides a mechanism for allowing users of the GCRM code itself to adjust the output frequency and the number of fields written depending on the needs of individual calculations. Third, we describe the mapping to the NetCDF data model with an emphasis on the grid description. Fourth, we describe our messaging algorithms and IO aggregation strategies that are used to achieve high bandwidth while simultaneously writing concurrently from many processors to shared files. We conclude with initial performance results.

Palmer, Bruce J.; Koontz, Annette S.; Schuchardt, Karen L.; Heikes, Ross P.; Randall, David A.

2011-11-26T23:59:59.000Z

212

Building Address Locations -Assumes entire  

E-Print Network [OSTI]

Housman Building 80 E. Concord St R BU School of Medicine, Instructional Building 80 E. Concord St L BU JBuilding Address Locations - Assumes entire building unless noted Designation Submit through* 560, 4 BU Crosstown Center 801 Massachusetts Ave Floor 1, 2 BMC BCD Building 800 Harrison Avenue BCD BMC

Guenther, Frank

213

NCPART: management of ICEMDDN output for numerical control users  

SciTech Connect (OSTI)

NCPART is a procedure developed by the Numerical Control Department at Bendix Kansas City Division to handle the entry to and exit from ICEMDDN, and process all of the local files output by ICEMDDN. The NCPART procedure is menu driven, and provides automatic access to ICEMDDN and any files necessary to process information with ICEM for numerical Control users. Basically, the procedure handles all of the ICEMDDN operations that involve operating system commands, and frees the NC programmer to concentrate on his/her work as a programmer.

Rossini, B.F.

1986-04-01T23:59:59.000Z

214

Optimization of Storage Location Assignment for Fixed Rack Systems  

Science Journals Connector (OSTI)

A multi-objective mathematical model and an improved Genetic Algorithm (GA) are formulated for storage location assignment of the fixed rack system. According to the assignment rules, ... efficiency and to keep t...

Qinghong Wu; Ying Zhang; Zongmin Ma

2010-01-01T23:59:59.000Z

215

station locations | OpenEI  

Open Energy Info (EERE)

00 00 Varnish cache server Browse Upload data GDR 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2142288500 Varnish cache server station locations Dataset Summary Description Alternative fueling stations are located throughout the United States and their availability continues to grow. The Alternative Fuels Data Center (AFDC) maintains a website where you can find alternative fuels stations near you or on a route, obtain counts of alternative fuels stations by state, Source Alternative Fuels Data Center Date Released December 13th, 2010 (4 years ago) Date Updated December 13th, 2010 (4 years ago) Keywords alt fuel alternative fuels alternative fuels stations biodiesel CNG compressed natural gas E85 Electricity ethanol

216

Method and system for managing an electrical output of a turbogenerator  

DOE Patents [OSTI]

The system and method manages an electrical output of a turbogenerator in accordance with multiple modes. In a first mode, a direct current (DC) bus receives power from a turbogenerator output via a rectifier where turbogenerator revolutions per unit time (e.g., revolutions per minute (RPM)) or an electrical output level of a turbogenerator output meet or exceed a minimum threshold. In a second mode, if the turbogenerator revolutions per unit time or electrical output level of a turbogenerator output are less than the minimum threshold, the electric drive motor or a generator mechanically powered by the engine provides electrical energy to the direct current bus.

Stahlhut, Ronnie Dean (Bettendorf, IA); Vuk, Carl Thomas (Denver, IA)

2010-08-24T23:59:59.000Z

217

A survey of computational location privacy  

Science Journals Connector (OSTI)

This is a literature survey of computational location privacy, meaning computation-based privacy mechanisms that treat location data as geometric information. This definition includes privacy-preserving algorithms like anonymity and obfuscation as well ... Keywords: Context, Location, Privacy

John Krumm

2009-08-01T23:59:59.000Z

218

Location and Hours | ornl.gov  

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

Location and Hours Location The ORNL Research Library is located off the central corridor of Bldg. 4500N on the main ORNL campus. Hours The library is open 24 hours, seven days a...

219

Regulatory Reform to Promote Clean Energy: The Potential of Output-Based Emissions Standards  

SciTech Connect (OSTI)

Barriers to industrial energy-efficient technologies hinder their use. A number of EPA analyses and industrial experts have found that the utilization of input-based emissions standards (measured in parts-per-million or pounds/MMBtu) in the Clean Air Act creates a regulatory barrier to the installation and deployment of technologies that emit fewer criteria pollutants and use energy more efficiently. Changing emission management strategies to an output-based emissions standard (measured in tons of pollutant emitted) is a way to ameliorate some of these barriers. Combined heat and power (CHP) is one of the key technologies that would see increased industrial application if the emissions standards were modified. Many states have made this change since the EPA first approved it in 2000, although direction from the Federal government could speed implementation modifications. To analyze the national impact of accelerated state adoption of output-based standards on CHP technologies, this paper uses detailed National Energy Modeling System (NEMS) and spreadsheet analysis illustrating two phased-in adoption scenarios for output-based emissions standards in the industrial sector. Benefit/cost metrics are calculated from a private and public perspective, and also a social perspective that considers the criteria and carbon air pollution emissions. These scenarios are compared to the reference case of AEO 2010 and are quite favorable, with a social benefit-cost ratio of 16.0 for a five-year phase-in scenario. In addition, the appropriateness of the Federal role, applicability, technology readiness, and administrative feasibility are discussed.

Cox, Matthew [Georgia Institute of Technology] [Georgia Institute of Technology; Brown, Dr. Marilyn Ann [Georgia Institute of Technology] [Georgia Institute of Technology; Jackson, Roderick K [ORNL] [ORNL

2011-01-01T23:59:59.000Z

220

Vacuum State/Refiner/Location  

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

Vacuum Vacuum State/Refiner/Location Barrels per Atmospheric Crude Oil Distillation Capacity Barrels per Operating Idle Operating Idle Downstream Charge Capacity Thermal Cracking Delayed Fluid Coking Visbreaking Other/Gas Calendar Day Stream Day Distillation Coking Oil Table 3. Capacity of Operable Petroleum Refineries by State as of January 1, 2013 (Barrels per Stream Day, Except Where Noted) ......................................................... Alabama 120,100 0 130,000 0 48,000 32,000 0 0 0 Goodway Refining LLC 4,100 0 5,000 0 0 0 0 0 0 ....................................................................................................................................................................................................

Note: This page contains sample records for the topic "model output location" 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

Mobile Truck Stop Electrification Site Locator  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Mobile Truck Stop Electrification Site Locator Location Enter a city, postal code, or address Search Caution: The AFDC recommends that users verify that sites are open prior to...

222

Energy Department Launches Alternative Fueling Station Locator...  

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

Launches Alternative Fueling Station Locator App Energy Department Launches Alternative Fueling Station Locator App November 7, 2013 - 11:16am Addthis As part of the Obama...

223

Quantum teleportation scheme by selecting one of multiple output ports  

E-Print Network [OSTI]

The scheme of quantum teleportation, where Bob has multiple (N) output ports and obtains the teleported state by simply selecting one of the N ports, is thoroughly studied. We consider both deterministic version and probabilistic version of the teleportation scheme aiming to teleport an unknown state of a qubit. Moreover, we consider two cases for each version: (i) the state employed for the teleportation is fixed to a maximally entangled state, and (ii) the state is also optimized as well as Alice's measurement. We analytically determine the optimal protocols for all the four cases, and show the corresponding optimal fidelity or optimal success probability. All these protocols can achieve the perfect teleportation in the asymptotic limit of $N\\to\\infty$. The entanglement properties of the teleportation scheme are also discussed.

Satoshi Ishizaka; Tohya Hiroshima

2009-04-06T23:59:59.000Z

224

GAMS program used to estimate capacity output using a distance function with both desirable and undesirable outputs, and weak disposability for the undesirable outputs.  

E-Print Network [OSTI]

." VIMS Marine resource Report N. 2007-6. August 2007. Author: John B. Walden NMFS/NEFSC 166 Water St(obs,var) variuable input utilization rate weight(obs) weights ; POSITIVE Variable weight, lambda; EQUATIONS CONSTR1 /dd_res_crs.txt/ MODEL CAP /ALL/; /*Use all the equations. Alternatively, the model could be solved

225

A H-infinity Fault Detection and Diagnosis Scheme for Discrete Nonlinear System Using Output Probability Density Estimation  

SciTech Connect (OSTI)

In this paper, a H-infinity fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic space-time dynamic model including nonlinearities, uncertainties. A weighting mean value is given as an integral function of the square root PDF along space direction, which leads a function only about time and can be used to construct residual signal. Thus, the classical nonlinear filter approach can be used to detect and diagnose the fault in system. A feasible detection criterion is obtained at first, and a new H-infinity adaptive fault diagnosis algorithm is further investigated to estimate the fault. Simulation example is given to demonstrate the effectiveness of the proposed approaches.

Zhang Yumin; Lum, Kai-Yew [Temasek Laboratories, National University of Singapore, Singapore 117508 (Singapore); Wang Qingguo [Depa. Electrical and Computer Engineering, National University of Singapore, Singapore 117576 (Singapore)

2009-03-05T23:59:59.000Z

226

Effects of collector radius and chimney height on power output of a solar chimney power plant with turbines  

Science Journals Connector (OSTI)

A comprehensive theoretical model is proposed for the performance evaluation of a solar chimney power plant (SCPP), and has been verified by the experimental data of the Spanish prototype. This model takes account of the effects of flow and heat losses, and the temperature lapse rates inside and outside the chimney. There is a maximum power output for a certain SCPP under a given solar radiation condition, due to flow and heat losses and the installation of the turbines. In addition, the design flow rate of the turbine in the SCPP system is found beneficial for power output when it is lower than that at themaximum power point. Furthermore, a limitation on the maximum collector radius exists for the maximum attainable power of the SCPP; whereas, no such limitation exists for chimney height in terms of contemporary construction technology.

Jing-yin Li; Peng-hua Guo; Yuan Wang

2012-01-01T23:59:59.000Z

227

Major DOE Biofuels Project Locations  

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

Biofuels Biofuels Project Locations Pacific Ethanol (Boardman, OR) BlueFire Ethanol (Corona, CA) POET (Emmetsburg, IA) Lignol Innovations (Commerce City, CO) ICM (St. Joseph, MO) Abengoa (Hugoton, KS) DOE Joint Bioenergy Institute (Berkeley, CA) DOE Great Lakes Bioenergy Research Center (Madison, WI) DOE Bioenergy Science Center (Oak Ridge, TN) NewPage (Wisconsin Rapids, WI) Range Fuels (Soperton, GA) DSM Innovation Center (Parsippany, NJ) Novozymes (Davis, CA) Genencor (Palo Alto, CA) Verenium Corp (San Diego, CA) Dupont (Wilmington, DE) Mascoma (Lebanon, NH) Cargill Inc (Minneapolis, MN) Regional Partnerships South Dakota State University, Brookings, SD Cornell University, Ithaca, NY University of Tennessee, Knoxville, TN Oklahoma State University, Stillwater, OK Oregon State University, Corvallis, OR

228

Robust Characterization of Model Physics Uncertainty for Simulations of Deep Moist Convection  

Science Journals Connector (OSTI)

This study explores the functional relationship between model physics parameters and model output variables for the purpose of 1) characterizing the sensitivity of the simulation output to the model formulation and 2) understanding model ...

Derek J. Posselt; Tomislava Vukicevic

2010-05-01T23:59:59.000Z

229

Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by  

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

2: August 13, 2: August 13, 2007 Refinery Output by World Region to someone by E-mail Share Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by World Region on Facebook Tweet about Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by World Region on Twitter Bookmark Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by World Region on Google Bookmark Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by World Region on Delicious Rank Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by World Region on Digg Find More places to share Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by World Region on AddThis.com... Fact #482: August 13, 2007

230

Sandia National Laboratories: simulating solar-power-plant output...  

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

Energy, Modeling & Analysis, News, News & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource...

231

NordhausGaddum bounds for locating domination  

Science Journals Connector (OSTI)

Abstract A dominating set S of graph G is called metric-locatingdominating if it is also locating, that is, if every vertex v is uniquely determined by its vector of distances to the vertices in S . If moreover, every vertex v not in S is also uniquely determined by the set of neighbors of v belonging to S , then it is said to be locatingdominating. Locating, metric-locatingdominating and locatingdominating sets of minimum cardinality are called ? -codes, ? -codes and ? -codes, respectively. A NordhausGaddum bound is a tight lower or upper bound on the sum or product of a parameter of a graph G and its complement G . In this paper, we present some NordhausGaddum bounds for the location number ? , the metric-locationdomination number ? and the locationdomination number ? . Moreover, in each case, the graph family attaining the corresponding bound is fully characterized.

C. Hernando; M. Mora; I.M. Pelayo

2014-01-01T23:59:59.000Z

232

An empirical model for ramp analysis of utility-scale solar PV power  

Science Journals Connector (OSTI)

Abstract Short-term variability in the power generated by utility-scale solar photovoltaic (PV) plants is a cause for concern for power system operators. Without quantitative insights into such variability, system operators will have difficulty in exploiting grid integrated solar power without negatively impacting power quality and grid reliability. In this paper, we describe a statistical method to empirically model the ramping behavior of utility-scale solar PV power output for short time-scales. The general validity of the model is confirmed through the analysis of power output data from a MW-scale solar PV plant located in the state of Karnataka, India. The empirical parameters of the model are investigated for different time-intervals and solar datasets. The proposed model is able to satisfactorily approximate the actual distribution of PV ramp events and can be an effective tool in smartly planning additional resources for PV ramp control.

Bishal Madhab Mazumdar; Mohd. Saquib; Abhik Kumar Das

2014-01-01T23:59:59.000Z

233

LOCATION OF THUNDERSTORMS BY RADIO METHODS  

Science Journals Connector (OSTI)

... systems are well known, and the exact location can be determined when the line or substation is afterwards inspected. Thus power supply system statistics provide reliable evidence of the location ...

1943-03-06T23:59:59.000Z

234

Process and Intermediate Calculations User AccessInputs Outputs  

E-Print Network [OSTI]

density, canopy base height, fuel moisture) · Weather · Fire History · Ignition History Analytic Models Behavior · DEM (Elevation, slope, aspect) · Vegetation (Fuel models, crown cover, stand height, bulk Smoke Analysis Management of Unplanned Ignitions: Each cell is evaluated using a probabilistic footprint

235

Combining frequency and time domain approaches to systems with multiple spike train input and output  

E-Print Network [OSTI]

between neuronal spike trains. Prog Biophys Mol Biol Vapnikto systems with multiple spike train input and output D. R.Keywords Multiple spike trains Neural coding Maximum

Brillinger, D. R.; Lindsay, K. A.; Rosenberg, J. R.

2009-01-01T23:59:59.000Z

236

On using transputers to design the header and output processors for the PSi architecture  

E-Print Network [OSTI]

the complexity associatecl with general soft ware. From Upper Layer Needer Processor From Lower Leyei' Input Bus Concoction Processor Connection Processor 256 CP's Output Bus To Upper Layer Output Processor To Lower Layer Fig. 2. d. Block... yer From Lower Layer T2 T3 To Input Bus of CP's From Output Bus of CF's From Output Bus of Cfes Fig, 4. 1. e. Block diagram of Design I transputers has its own private memory. Tl acts as the header processor. Two of its serial links...

Manickam, Muralidhar

2012-06-07T23:59:59.000Z

237

A CSP Timed Input-Output Relation and a Strategy for Mechanised Conformance Verification  

Science Journals Connector (OSTI)

Here we propose a timed input-output conformance relation (named CSPTIO) based on the process algebra CSP. In contrast to other relations, CSPTIO...

Gustavo Carvalho; Augusto Sampaio

2013-01-01T23:59:59.000Z

238

Cavity dumping versus stationary output coupling in repetitively Q-switched solid-state lasers  

Science Journals Connector (OSTI)

A comparative theoretical analysis of continuously pumped actively Q-switched solid-state lasers differing in output coupling methods (cavity dumping versus a partially transmitting...

Grishin, Mikhail

2011-01-01T23:59:59.000Z

239

Analysis of the AirTouch automatic vehicle location system's ability to locate moving vehicles  

E-Print Network [OSTI]

Automatic vehicle location systems are becoming more prevalent in diverse transportation applications. Their ability to locate vehicles can assist in locating emergency and public transit vehicles for better real-time dispatching as well...

Henry, Tracy Lynn

2012-06-07T23:59:59.000Z

240

High beach temperatures increased female-biased primary sex ratios but reduced output of female hatchlings in the leatherback turtle  

Science Journals Connector (OSTI)

Abstract Sex of offspring in most turtles is determined by temperature-dependent sex determination (TSD). In sea turtles, higher incubation temperatures produce female hatchlings and primary sex ratios are often highly female-biased. Because of the current rate of climate warming, highly female-biased sex ratios have raised concern among scientists and managers because populations might become too female biased for genetic viability. We tested the effects of higher incubation temperatures on embryo and hatchling mortality and on sex ratios in a population of leatherback turtles (Dermochelys coriacea) in the eastern Pacific. The long-term study provided a large sample size in a location influenced by El Nio Southern Oscillation that resulted in highly variable climatic conditions between seasons. High temperatures reduced emergence success. Output of female hatchlings increased with incubation temperature as it reached the upper end of the transitional range (range of temperatures that produce both sexes) (30C) and decreased afterwards because high temperatures increased mortality of female clutches. Effect of temperature on female hatchling output lessened female-biased sex ratios from 85% female primary sex ratios to 79% secondary sex ratios (sex ratios of total number of hatchlings emerged). If male turtles reproduce more often than females, operational sex ratios will be closer to 1:1. Female-biased primary sex ratios should not raise concerns by default, but climate change may still threaten populations by reducing hatchling output and increasing frequency of seasons with 100% female production. Clutch relocation to cooler conditions may alter sex ratios and should be used cautiously unless temperatures are so high that no hatchlings survive. In addition, it is unknown what differential survival of male versus female hatchlings may have on the eventual adult sex ratio after they enter the ocean and disperse.

Pilar Santidrin Tomillo; Daniel Oro; Frank V. Paladino; Rotney Piedra; Annette E. Sieg; James R. Spotila

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" 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

Alternative Fueling Station Locator | Open Energy Information  

Open Energy Info (EERE)

Alternative Fueling Station Locator Alternative Fueling Station Locator Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Alternative Fueling Station Locator Agency/Company /Organization: United States Department of Energy Partner: National Renewable Energy Laboratory Sector: Energy Focus Area: Fuels & Efficiency, Transportation Phase: Evaluate Options, Prepare a Plan Topics: Datasets Resource Type: Online calculator User Interface: Website Website: www.afdc.energy.gov/afdc/locator/stations/ Web Application Link: www.afdc.energy.gov/afdc/locator/stations/ Cost: Free OpenEI Keyword(s): Featured References: National Renewable Energy Laboratory Advanced Vehicles and Fuels Research: Data and Resources[1] Logo: Alternative Fueling Station Locator The alternative fuel station locator uses an address based search to find

242

Wind Technology Modeling Within the System Advisor Model (SAM...  

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

P. Gilman, J. Whitmore* National Renewable Energy Laboratory * Golden, Colorado OFFSHORE WINDPOWER 2014, Las Vegas, May 58, 2014 Model Basics Outputs and Advanced Analysis...

243

HSPICE and WaveView Tutorial Hspice is used for circuit simulation and WaveView is used to view output waveforms.  

E-Print Network [OSTI]

NNano-E Hs Electron Sc San Fr S spice Q Mich Hamid nics & C chool of rancisco San Fra Spr Quick By be downloaded from the following website: http://ptm.asu.edu/ Click on the latest models and download 16nm PTM "hspice job aborted". In that case, please open the output file (inv.out) and search for error to see

Mahmoodi, Hamid

244

Major DOE Biofuels Project Locations | Department of Energy  

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

Major DOE Biofuels Project Locations Major DOE Biofuels Project Locations Major DOE Biofuels Project Locations More Documents & Publications Major DOE Biofuels Project Locations...

245

Advanced Condenser Boosts Geothermal Power Plant Output (Fact Sheet), The Spectrum of Clean Energy Innovation, NREL (National Renewable Energy Laboratory)  

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

Geothermal resources-the steam and water that lie below the earth's surface-have the Geothermal resources-the steam and water that lie below the earth's surface-have the potential to supply vast amounts of clean energy. But continuing to produce geothermal power efficiently and inexpensively can require innovative adjustments to the technology used to process it. Located in the Mayacamas Mountains of northern California, The Geysers is the world's larg- est geothermal complex. Encompassing 45 square miles along the Sonoma and Lake County border, the complex harnesses natural steam reservoirs to create clean renewable energy that accounts for one-fifth of the green power produced in California. In the late 1990s, the pressure of geothermal steam at The Geysers was falling, reducing the output of its power plants. NREL teamed with Pacific

246

Estimating Solar PV Output Using Modern Space/Time Geostatistics (Presentation)  

SciTech Connect (OSTI)

This presentation describes a project that uses mapping techniques to predict solar output at subhourly resolution at any spatial point, develop a methodology that is applicable to natural resources in general, and demonstrate capability of geostatistical techniques to predict the output of a potential solar plant.

Lee, S. J.; George, R.; Bush, B.

2009-04-29T23:59:59.000Z

247

PWM Inverter Output Filter Cost to Losses Trade Off and Optimal Design  

E-Print Network [OSTI]

PWM Inverter Output Filter Cost to Losses Trade Off and Optimal Design Robert J. Pasterczyk Jean--This paper describes how to design the output filter of a PWM inverter used in a Uninterruptible Power SupplyVA 3-ph. PWM inverter is taken as example. B. Design Constraints Uninterruptible Power Supply (UPS

Paris-Sud XI, Université de

248

Quality assurance of solar thermal systems with the ISFH-Input/Output-Procedure  

E-Print Network [OSTI]

. Supplementary sensors may be necessary for some special solar systems (e. g. solar systems with several storagesQuality assurance of solar thermal systems with the ISFH- Input/Output-Procedure Peter Paerisch/Output-Controllers for in situ and automatic function control of solar thermal systems that were developed within the research

249

A Method of Decreasing Power Output Fluctuation of Solar Chimney Power Generating Systems  

Science Journals Connector (OSTI)

Severe fluctuation of power output is a common problem in the various generating systems of renewable energies. The hybrid energy storage system with water and soil is adopted to decrease the fluctuation of solar chimney power generating systems in the ... Keywords: Solar chimney power generating system, power output fluctuation, hybrid energy storage layer, collector, chimney

Meng Fanlong; Ming Tingzhen; Pan Yuan

2011-01-01T23:59:59.000Z

250

Optimizing the Output of a Human-Powered Energy Harvesting System with Miniaturization and Integrated Control  

E-Print Network [OSTI]

1 Optimizing the Output of a Human-Powered Energy Harvesting System with Miniaturization mechanical energy from human foot-strikes and explore its configuration and control towards optimized energy output. Dielectric Elastomers (DEs) are high-energy density, soft, rubber-like material

Potkonjak, Miodrag

251

Table S1. Mixed-model ANOVA and Tukey's HSD results for the diversity of co-occurring ant species in plots. Sites were locations within 5 different forest stands within  

E-Print Network [OSTI]

Table S1. Mixed-model ANOVA and Tukey's HSD results for the diversity of co- occurring ant species.64 0.0385 year*site*ground*ant 4 0.08581728 0.02145432 0.20 0.9400 Tukey's Studentized Range (HSD) Tests for Number of species. Means with the same letter are not significantly different. Tukey Grouping

252

Method for leveling the power output of an electromechanical battery as a function of speed  

DOE Patents [OSTI]

The invention is a method of leveling the power output of an electromechanical battery during its discharge, while at the same time maximizing its power output into a given load. The method employs the concept of series resonance, employing a capacitor the parameters of which are chosen optimally to achieve the desired near-flatness of power output over any chosen charged-discharged speed ratio. Capacitors are inserted in series with each phase of the windings to introduce capacitative reactances that act to compensate the inductive reactance of these windings. This compensating effect both increases the power that can be drawn from the generator before inductive voltage drops in the windings become dominant and acts to flatten the power output over a chosen speed range. The values of the capacitors are chosen so as to optimally flatten the output of the generator over the chosen speed range. 3 figs.

Post, R.F.

1999-03-16T23:59:59.000Z

253

Our Locations | National Nuclear Security Administration  

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

Locations | National Nuclear Security Administration Locations | National Nuclear Security Administration Our Mission Managing the Stockpile Preventing Proliferation Powering the Nuclear Navy Emergency Response Recapitalizing Our Infrastructure Continuing Management Reform Countering Nuclear Terrorism About Us Our Programs Our History Who We Are Our Leadership Our Locations Budget Our Operations Media Room Congressional Testimony Fact Sheets Newsletters Press Releases Speeches Events Social Media Video Gallery Photo Gallery NNSA Archive Federal Employment Apply for Our Jobs Our Jobs Working at NNSA Blog Our Locations Home > About Us > Our Locations Our Locations The NNSA's nuclear security enterprise spans eight sites, including three national laboratories, with more than six decades of cutting-edge nuclear security experience. That history and technical expertise enables NNSA to

254

Our Locations | National Nuclear Security Administration  

National Nuclear Security Administration (NNSA)

Locations | National Nuclear Security Administration Locations | National Nuclear Security Administration Our Mission Managing the Stockpile Preventing Proliferation Powering the Nuclear Navy Emergency Response Recapitalizing Our Infrastructure Continuing Management Reform Countering Nuclear Terrorism About Us Our Programs Our History Who We Are Our Leadership Our Locations Budget Our Operations Media Room Congressional Testimony Fact Sheets Newsletters Press Releases Speeches Events Social Media Video Gallery Photo Gallery NNSA Archive Federal Employment Apply for Our Jobs Our Jobs Working at NNSA Blog Our Locations Home > About Us > Our Locations Our Locations The NNSA's nuclear security enterprise spans eight sites, including three national laboratories, with more than six decades of cutting-edge nuclear security experience. That history and technical expertise enables NNSA to

255

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

256

Community Detection from Location-Tagged Networks  

E-Print Network [OSTI]

Many real world systems or web services can be represented as a network such as social networks and transportation networks. In the past decade, many algorithms have been developed to detect the communities in a network using connections between nodes. However in many real world networks, the locations of nodes have great influence on the community structure. For example, in a social network, more connections are established between geographically proximate users. The impact of locations on community has not been fully investigated by the research literature. In this paper, we propose a community detection method which takes locations of nodes into consideration. The goal is to detect communities with both geographic proximity and network closeness. We analyze the distribution of the distances between connected and unconnected nodes to measure the influence of location on the network structure on two real location-tagged social networks. We propose a method to determine if a location-based community detection...

Liu, Zhi

2015-01-01T23:59:59.000Z

257

Helicopter magnetic survey conducted to locate wells  

SciTech Connect (OSTI)

A helicopter magnetic survey was conducted in August 2007 over 15.6 sq mi at the Naval Petroleum Reserve No. 3s (NPR-3) Teapot Dome Field near Casper, Wyoming. The surveys purpose was to accurately locate wells drilled there during more than 90 years of continuous oilfield operation. The survey was conducted at low altitude and with closely spaced flight lines to improve the detection of wells with weak magnetic response and to increase the resolution of closely spaced wells. The survey was in preparation for a planned CO2 flood for EOR, which requires a complete well inventory with accurate locations for all existing wells. The magnetic survey was intended to locate wells missing from the well database and to provide accurate locations for all wells. The ability of the helicopter magnetic survey to accurately locate wells was accomplished by comparing airborne well picks with well locations from an intense ground search of a small test area.

Veloski, G.A.; Hammack, R.W.; Stamp, V. (Rocky Mountain Oilfield Testing Center); Hall, R. (Rocky Mountain Oilfield Testing Center); Colina, K. (Rocky Mountain Oilfield Testing Center)

2008-07-01T23:59:59.000Z

258

Location-dependent communications using quantum entanglement  

SciTech Connect (OSTI)

The ability to unconditionally verify the location of a communication receiver would lead to a wide range of new security paradigms. However, it is known that unconditional location verification in classical communication systems is impossible. In this work we show how unconditional location verification can be achieved with the use of quantum communication channels. Our verification remains unconditional irrespective of the number of receivers, computational capacity, or any other physical resource held by an adversary. Quantum location verification represents an application of quantum entanglement that delivers a feat not possible in the classical-only channel. It gives us the ability to deliver real-time communications viable only at specified geographical coordinates.

Malaney, Robert A. [School of Electrical Engineering and Telecommunications, University of New South Wales, New South Wales 2052 (Australia)

2010-04-15T23:59:59.000Z

259

Implementing Rational Surface Locations Measured From Thomson...  

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

Rational Surface Locations Measured From Thomson Scattering Into MSTfit by Curtis A. Johnson Senior Thesis (Physics) at the University of Wisconsin-Madison 2014 i Abstract...

260

Regenerator Location Problem in Flexible Optical Networks  

E-Print Network [OSTI]

Nov 22, 2014 ... Abstract: In this study we introduce the regenerator location problem in flexible optical networks (RLP-FON). With a given traffic demand,...

BARIS YILDIZ

2014-11-22T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" 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

Procurement Information by Location | Department of Energy  

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

Procurement Information by Location Procurement Information by Location Procurement Information by Location As part of our Small Business Opportunity Tool, we are offering information about historical procurement by location. Find historical procurement data by state - check out the list of states below, and click on the state's name to learn more about their current programs and past procurement needs. Click on the state to learn more about our current procurement activity: California Colorado District of Columbia Georgia Idaho Illinois Iowa Louisana Maryland Missouri Nevada New Jersey New Mexico New York Ohio Oklahoma Oregon Pennsylvania South Carolina Tennessee Texas Virginia West Virginia Washington Wyoming

262

Optimization Online - Public Facility Location Using Dispersion ...  

E-Print Network [OSTI]

Jan 27, 2013 ... Our results show close collaboration with the p-median solution when decision makers restrict location to demand points, and use parameter...

Rajan Batta

2013-01-27T23:59:59.000Z

263

Sinusoidal self-modulation in the output of a CO/sub 2/ laser with an intracavity saturable absorber  

SciTech Connect (OSTI)

Conditions under which a sinusoidally modulated laser output occurs in a CO/sub 2/ laser with a saturable absorber were studied experimentally and theoretically for a wide range of laser operating parameters. A novel type of transition between stability and instability appears in the high-pressure range of the saturable absorber. Through the rate-equation analysis based on the three-level (the gain medium): two-level (the loss medium) model, the observed pulse shapes and the features of transitions in the phase diagram are reproducible. The conditions of saturable absorbers to obtain the sinusoidal are clarified from the analysis.

Tanii, K.; Tachikawa, M.; Kajita, M.; Shimizu, T.

1988-01-01T23:59:59.000Z

264

RECYCLING PROGRAM TYPE LOCATION ALLOWED NOT ALLOWED  

E-Print Network [OSTI]

RECYCLING PROGRAM TYPE LOCATION ALLOWED NOT ALLOWED Batteries, toner, ink cartridges & cell phones and recycling is an important part of that effort. Below is a guide to on-campus recycling at RSMAS: Visit http://www.rsmas.miami.edu/msgso/ for map of recycling bin locations. NOTE: This is not an exhaustive list. If unauthorized items are found

Miami, University of

265

Wind direction modelling using multiple observation points  

Science Journals Connector (OSTI)

...gains in the produced output power. chaos engineering|wind forecasting|multiple measurements...realized that the modelling of power output in wind turbines needs to be performed...region; in region 3, for high winds, the power output is subject to a threshold...

2008-01-01T23:59:59.000Z

266

Finding the quantum thermoelectric with maximal efficiency and minimal entropy production at given power output  

E-Print Network [OSTI]

We investigate the nonlinear scattering theory for quantum systems with strong Seebeck and Peltier effects, and consider their use as heat-engines and refrigerators with finite power outputs. This article gives detailed derivations of the results summarized in Phys. Rev. Lett. 112, 130601 (2014). It shows how to use the scattering theory to find (i) the quantum thermoelectric with maximum possible power output, and (ii) the quantum thermoelectric with maximum efficiency at given power output. The latter corresponds to a minimal entropy production at that power output. These quantities are of quantum origin since they depend on system size over electronic wavelength, and so have no analogue in classical thermodynamics. The maximal efficiency coincides with Carnot efficiency at zero power output, but decreases with increasing power output. This gives a fundamental lower bound on entropy production, which means that reversibility (in the thermodynamic sense) is impossible for finite power output. The suppression of efficiency by (nonlinear) phonon and photon effects is addressed in detail; when these effects are strong, maximum efficiency coincides with maximum power. Finally, we show in particular limits (typically without magnetic fields) that relaxation within the quantum system does not allow the system to exceed the bounds derived for relaxation-free systems, however a general proof of this remains elusive.

Robert S. Whitney

2015-01-28T23:59:59.000Z

267

Property:UtilityLocation | Open Energy Information  

Open Energy Info (EERE)

UtilityLocation UtilityLocation Jump to: navigation, search Property Name UtilityLocation Property Type Boolean Description Indicates this is the "mailing" location of the Utility. Usually is Yes if the information from EIA Form 861 File1_a is on the page. Pages using the property "UtilityLocation" Showing 25 pages using this property. (previous 25) (next 25) 3 3 Phases Energy Services + true + 4 4-County Electric Power Assn + true + A A & N Electric Coop (Virginia) + true + AEP Generating Company + true + AEP Texas Central Company + true + AEP Texas North Company + true + AES Eastern Energy LP + true + AGC Division of APG Inc + true + AP Holdings LLC + true + APN Starfirst, L.P. + true + APNA Energy + true + Accent Energy Holdings, LLC + true +

268

Analytical protostellar disk models 1: the effect of internal dissipation and surface irradiation on the structure of disks and the location of the snow line around Sun-like stars  

E-Print Network [OSTI]

We construct a new set of self-consistent analytical disk models by taking into account both viscous and radiative sources of thermal energy. We analyze the non-isothermal structure of the disk across the mid-plane for optically thick disks, and use the standard two-temperature model in the case of optically thin disks. We deduce a set of general formula for the relationship between the mass accretion rate and the surface density profile. Our results recover those of Chiang & Goldreich in the optically thin regions, but extend their work for the opaque regions of the disk. For the purpose of illustration, we apply our theory in this paper to determine the structure of protostellar disks around T Tauri stars under a state of steady accretion and derive the corresponding radial distribution function of various disk properties such as surface density and temperature near the mid-plane. We calculate the position of the snow line around a sun-like T Tauri star, and deduce that it can evolve from well outside 10 AU during FU Orionis outbursts, to about 4 AU during passive accretion phase, to the present-day orbital radius of Venus and finally re-expand to over 2.2 AU during the protostellar- to-debris disk transition. This non-monotonous evolution of the snow line may provide some novel and deterministic explanation for the total water content and its isotopic composition of both Venus and the Earth. In the optically thin, outermost regions of the disk we find that the surface density profile of the dust varies roughly as 1/r, which is consistent with mm observations of spatially resolved disk of Mundy et al. (2000).

Pascale Garaud; Douglas N. C. Lin

2006-05-03T23:59:59.000Z

269

Optimization of the output and efficiency of a high power cascaded arc hydrogen plasma source  

SciTech Connect (OSTI)

The operation of a cascaded arc hydrogen plasma source was experimentally investigated to provide an empirical basis for the scaling of this source to higher plasma fluxes and efficiencies. The flux and efficiency were determined as a function of the input power, discharge channel diameter, and hydrogen gas flow rate. Measurements of the pressure in the arc channel show that the flow is well described by Poiseuille flow and that the effective heavy particle temperature is approximately 0.8 eV. Interpretation of the measured I-V data in terms of a one-parameter model shows that the plasma production is proportional to the input power, to the square root of the hydrogen flow rate, and is independent of the channel diameter. The observed scaling shows that the dominant power loss mechanism inside the arc channel is one that scales with the effective volume of the plasma in the discharge channel. Measurements on the plasma output with Thomson scattering confirm the linear dependence of the plasma production on the input power. Extrapolation of these results shows that (without a magnetic field) an improvement in the plasma production by a factor of 10 over where it was in van Rooij et al. [Appl. Phys. Lett. 90, 121501 (2007)] should be possible.

Vijvers, W. A. J.; Gils, C. A. J. van; Goedheer, W. J.; Meiden, H. J. van der; Veremiyenko, V. P.; Westerhout, J.; Lopes Cardozo, N. J.; Rooij, G. J. van [FOM-Institute for Plasma Physics Rijnhuizen, Association EURATOM-FOM, Trilateral Euregio Cluster, P.O. Box 1207, 3430 BE Nieuwegein (Netherlands); Schram, D. C. [Department of Applied Physics, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands)

2008-09-15T23:59:59.000Z

270

Primate Motor Cortex: Individual and Ensemble Neuron-Muscle Output Relationships  

E-Print Network [OSTI]

The specific aims of this study were to: 1) investigate the encoding of forelimb muscle activity timing and magnitude by corticomotoneuronal (CM) cells, 2) test the stability of primary motor cortex (M1) output to forelimb ...

Griffin, Darcy Michelle

2008-07-30T23:59:59.000Z

271

Augmentation of Power Output of Axisymmetric Ducted Wind Turbines by Porous Trailing Edge Disks  

E-Print Network [OSTI]

This paper presents analytical and experimental results that demonstrated that the power output from a ducted wind turbine can be dramatically increased by the addition of a trailing edge device such as a porous disk. In ...

widnall, sheila

2014-06-30T23:59:59.000Z

272

A Hardware Implementation of the Soft Output Viterbi Algorithm for Serially Concatenated Convolutional Codes  

E-Print Network [OSTI]

This thesis outlines the hardware design of a soft output Viterbi algorithm decoder for use in a serially concatenated convolutional code system. Convolutional codes and their related structures are described, as well as the algorithms used...

Werling, Brett William

2010-06-28T23:59:59.000Z

273

Code design for multiple-input multiple-output broadcast channels  

E-Print Network [OSTI]

Recent information theoretical results indicate that dirty-paper coding (DPC) achieves the entire capacity region of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). This thesis presents practical code designs for Gaussian...

Uppal, Momin Ayub

2009-06-02T23:59:59.000Z

274

Power output enhancement of a vibration-driven electret generator for wireless sensor applications  

Science Journals Connector (OSTI)

We developed a compact vibration-driven electret generator that excelled at a power output. It succeeded in the operation of wireless sensor modules only on electricity from electret generators. This electret generator can supply enough power to operate a wireless sensor module without an external power source. It was necessary for enabling this operation to enhance the power output of the electret generator. We enhanced the power output by decreasing the parasitic capacitance. To decrease the parasitic capacitance, we fabricated a collector substrate using concave electrodes. We decreased it from 25 to 17 pF. As a result, the power output from our generator was enhanced from 40 to 100 W considerably at an acceleration of 0.15 g (1.47 m s?2) and a resonance frequency of 30 Hz.

Tatsuakira Masaki; Kenji Sakurai; Toru Yokoyama; Masayo Ikuta; Hiroshi Sameshima; Masashi Doi; Tomonori Seki; Masatoshi Oba

2011-01-01T23:59:59.000Z

275

Variable-Speed Wind Generator System with Maximum Output Power Control  

Science Journals Connector (OSTI)

To achieve maximum output power from wind generator systems, the rotational speed of wind generators should be adjusted in real time according to natural wind speed. This chapter pays attention to an optimum rota...

Yoko Amano

2013-01-01T23:59:59.000Z

276

Total Pollution Effect and Total Energy Cost per Output of Different Products for Polish Industrial System  

Science Journals Connector (OSTI)

For many years a broad use has been made of the indices of total energy requirements in the whole large production system corresponding to unit output of particular goods (Boustead I., Hancock G.F., 1979). The...

Henryk W. Balandynowicz

1988-01-01T23:59:59.000Z

277

Imprinting a complete information about a quantum channel on its output state  

E-Print Network [OSTI]

We introduce a novel property of bipartite quantum states, which we call "faithfulness", and we say that a state is faithful when acting with a channel on one of the two quantum systems, the output state carries a complete information about the channel. The concept of faithfulness can also be extended to sets of states, when the output states patched together carry a complete imprinting of the channel.

Giacomo Mauro D'Ariano; Paoloplacido Lo Presti

2002-11-20T23:59:59.000Z

278

Export.gov - Export.gov - Locations  

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

Locations Locations Print | E-mail Page Locations 800.872.8723 Domestic Offices International Offices Locations 800.872.8723 Call: 800.872.8723 (1-800-USA-TRAD(E)) Email: tic@trade.gov between 8:30 AM and 6 PM EST to receive immediate answers to your exporting questions on: Tariff and Tax Information Country-specific General Export Information Region-specific Export Information (Middle East, China, Latin America, EU, etc.) International Documentation, Regulations and Standards Logistics and Finance (HS/Schedule B numbers, Freight Forwarders, partners) Free Trade Agreements (qualifying products for FTA benefits, Certificates of origin.) Trade Data Export-related information offered by federal, state and local entities Export-related information related to other USG agencies Note for Importers: Please contact U.S. Customs at 877.227.5511

279

Location privacy in mobile computing environments  

Science Journals Connector (OSTI)

In general, privacy can be viewed as the right to be left alone when desired (solitude), the right to remain anonymous (anonymity), and the right to confidentiality (secrecy of information). More specifically, location privacy is the ability to ...

John P. Baugh; Jinhua Guo

2006-09-01T23:59:59.000Z

280

Data semantics in location-based services  

Science Journals Connector (OSTI)

As location-based applications become part of our everyday life, ranging from traffic prediction systems to services over mobile phones providing us with information about our surroundings, the call for more semantics and accurate services is emerging. ...

Nectaria Tryfona; Dieter Pfoser

2005-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" 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

Russian Locations | National Nuclear Security Administration  

National Nuclear Security Administration (NNSA)

Locations | National Nuclear Security Administration Locations | National Nuclear Security Administration Our Mission Managing the Stockpile Preventing Proliferation Powering the Nuclear Navy Emergency Response Recapitalizing Our Infrastructure Continuing Management Reform Countering Nuclear Terrorism About Us Our Programs Our History Who We Are Our Leadership Our Locations Budget Our Operations Media Room Congressional Testimony Fact Sheets Newsletters Press Releases Speeches Events Social Media Video Gallery Photo Gallery NNSA Archive Federal Employment Apply for Our Jobs Our Jobs Working at NNSA Blog The National Nuclear Security Administration Russian Locations Home > About Us > Our Programs > Defense Programs > Future Science & Technology Programs > Office of Advanced Simulation and Computing and Institutional R&D Programs > Russia Tri-Lab S&T Collaborations > Travel

282

Alternative Fueling Station Locator | Department of Energy  

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

Alternative Fueling Station Locator Alternative Fueling Station Locator Alternative Fueling Station Locator Find Stations Plan a Route Location: Go Start: End: Go Fuel: All Fuels Biodiesel (B20 and above) Compressed Natural Gas Electric Ethanol (E85) Hydrogen Liquefied Natural Gas (LNG) Liquefied Petroleum Gas (Propane) more search options close × More Search Options Include private stations Include planned stations Owner All Private Federal State Local Utility Payment All American Express Discover MasterCard VISA Cash Checks CFN Clean Energy Fuel Man Gas Card PHH Services Voyager WEX Electric charger types Include level 1 Include level 2 Include DC fast Include legacy chargers Limit results to within 5 miles Limit results to within 5 miles 12,782 alternative fuel stations in the United States Excluding private stations

283

Location-Aware Instant Search Ruicheng Zhong  

E-Print Network [OSTI]

to find a gas station nearby, she can issue a keyword query "gas station" to a LBS system, which returns the relevant gas stations by considering the user's location and keywords. Traditional spatial keyword search

Li, Guoliang

284

Locating and identifying codes in circulant networks  

Science Journals Connector (OSTI)

A set S of vertices of a graph G is a dominating set of G if every vertex u of G is either in S or it has a neighbour in S. In other words, S is dominating if the sets S@?N[u] where u@?V(G) and N[u] denotes the closed neighbourhood of u in G, are all ... Keywords: Circulant network, Domination, Identifying code, Locating code, Locating-dominating set

M. Ghebleh; L. Niepel

2013-09-01T23:59:59.000Z

285

Personal Digital Assistant PDA ----Location Based  

E-Print Network [OSTI]

, xur],[ ybl, yur ]) k k=100 K k k- AminAmin kLk k Amax TmaxTmax kAminLocation Anonymization ConstraintsAmax TmaxLocation Service Quality Constraints 3.3 3.3.1 id, loc, query id loc (x,y)query GPS / l- l- k- l- k l- l l- l- m-invariant 2 29 #12;[22] A B C D E F R1 R2 R3 6 Outlier 6

286

Final_Tech_Session_Schedule_and_Location.xls  

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

Modeling Critical Leakage Pathways in Modeling Critical Leakage Pathways in a Risk Assessment Framework: Representation of Abandoned Wells Michael A. Celia 1 , Stefan Bachu 2 , Jan M. Nordbotten 3 , Dmitri Kavetski 1 , and Sarah E. Gasda 1 1 Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544 USA (celia@princeton.edu, kavetski@princeton.edu, sgasda@princeton.edu) 2 Alberta Energy and Utilities Board, Edmonton, Alberta, T6B 2X3, Canada (Stefan.Bachu@gov.ab.ca) 3 Department of Mathematics, University of Bergen, Bergen 5020, Norway (janmn@mi.uib.no) CONFERENCE PROCEEDINGS Abstract In many locations in North America, likely injection sites for CO 2 storage in deep geological formation are located in mature sedimentary basins. These basins have a century-long history of oil and gas exploration and

287

Analytical Modeling Linking the FASTSim and ADOPT Software Tools  

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

Model Petroleum Impact Optimize for market share 6 Approach: Vehicle Powertrain Modeling Fuel Economy Inputs Vehicle Price Acceleration Outputs Component Sizes and Vehicle...

288

The Value of Flexibility in Robust Location-Transportation Problem  

E-Print Network [OSTI]

production and distribution of products can be delayed until actual orders are ... such as hub locations, supplier locations, air freight hub locations, railway station

2014-11-24T23:59:59.000Z

289

The effect of performance-based research funding on output of R&D results in the Czech Republic  

Science Journals Connector (OSTI)

We have studied the effects of performance-based research funding introduced to the Czech (CZ) R&D system in 2008 on outputs of R&D results. We have analyzed annual changes in number of various types of publications and applications including ... Keywords: Bibliometrics, Citation analysis, Patent output, Performance-based research funding, R&D results output

Jiri Vanecek

2014-01-01T23:59:59.000Z

290

Stochastic Model Output Statistics for Bias Correcting and Downscaling Precipitation Including Extremes  

Science Journals Connector (OSTI)

Precipitation is highly variable in space and time; hence, rain gauge time series generally exhibit additional random small-scale variability compared to area averages. Therefore, differences between daily precipitation statistics simulated by ...

Geraldine Wong; Douglas Maraun; Mathieu Vrac; Martin Widmann; Jonathan M. Eden; Thomas Kent

2014-09-01T23:59:59.000Z

291

Distributed quantitative precipitation forecasts combining information from radar and numerical weather prediction model outputs  

E-Print Network [OSTI]

Applications of distributed Quantitative Precipitation Forecasts (QPF) range from flood forecasting to transportation. Obtaining QPF is acknowledged to be one of the most challenging areas in hydrology and meteorology. ...

Ganguly, Auroop Ratan

2002-01-01T23:59:59.000Z

292

Statistical post-processing of High-Resolution Regional Climate Model Output  

Science Journals Connector (OSTI)

Statistical post-processing techniques have become essential tools for downscaling large scale information to the point scale, and also for providing a better probabilistic characterization of hydrometeorological variables in simulation and ...

Pablo A. Mendoza; Balaji Rajagopalan; Martyn P. Clark; Kyoko Ikeda; Roy Rasmussen

293

Sensitivity of Carbon Anode Baking Model Outputs to Kinetic Parameters Describing Pitch Pyrolysis  

Science Journals Connector (OSTI)

During the preheating, they will release volatiles (H2, CH4, tar) that will burn in the flue. ... The combustion of volatiles accounts for approximately 4050% of the required heating, the rest being provided by natural gas; see burner ramps on Figure 1. ... Figure 2. Schematic representation of the pit and the flue wall. ...

Franois Grgoire; Louis Gosselin; Houshang Alamdari

2013-02-20T23:59:59.000Z

294

Multiregional InputOutput Model for the Evaluation of Spanish Water Flows  

Science Journals Connector (OSTI)

Halfway through the first decade of the 21st century water withdrawals in Spain have been slightly less than 40 km3 per year (own estimations from ref 2), being around 60% abstracted by agriculture, 14.5% by the water distribution sector (distributed to industries and households), 16% by the energy and gas sectors, and 4% by industries. ... We also relate these water flows and demands with the regional water availability, in order to offer insights on the Spanish water stress, defined as volume of water consumed/availability per capita. ... Total WF to GDP ratio (SI Table SI2) is on average higher for Spain than for EU and lower than for the RW (the opposite for the last ratios of WF per capita). ...

Ignacio Cazcarro; Rosa Duarte; Julio Snchez Chliz

2013-09-12T23:59:59.000Z

295

Dissemination of Climate Model Output to the Public and Commercial Sector  

SciTech Connect (OSTI)

Climate is defined by the Glossary of Meteorology as the mean of atmospheric variables over a period of time ranging from as short as a few months to multiple years and longer. Although the term climate is often used to refer to long-term weather statistics, the broader definition of climate is the time evolution of a system consisting of the atmosphere, hydrosphere, lithosphere, and biosphere. Physical, chemical, and biological processes are involved in interactions among the components of the climate system. Vegetation, soil moisture, and glaciers are part of the climate system in addition to the usually considered temperature and precipitation (Pielke, 2008). Climate change refers to any systematic change in the long-term statistics of climate elements (such as temperature, pressure, or winds) sustained over several decades or longer. Climate change can be initiated by external forces, such as cyclical variations in the Earth's solar orbit that are thought to have caused glacial and interglacial periods within the last 2 million years (Milankovitch, 1941). However, a linear response to astronomical forcing does not explain many other observed glacial and interglacial cycles (Petit et al., 1999). It is now understood that climate is influenced by the interaction of solar radiation with atmospheric greenhouse gasses (e.g., carbon dioxide, chlorofluorocarbons, methane, nitrous oxide, etc.), aerosols (airborne particles), and Earth's surface. A significant aspect of climate are the interannual cycles, such as the El Nino La Nina cycle which profoundly affects the weather in North America but is outside the scope of weather forecasts. Some of the most significant advances in understanding climate change have evolved from the recognition of the influence of ocean circulations upon the atmosphere (IPCC, 2007). Human activity can affect the climate system through increasing concentrations of atmospheric greenhouse gases, air pollution, increasing concentrations of aerosol, and land alteration. A particular concern is that atmospheric levels of CO{sub 2} may be rising faster than at any time in Earth's history, except possibly following rare events like impacts from large extraterrestrial objects (AMS, 2007). Atmospheric CO{sub 2} concentrations have increased since the mid-1700s through fossil fuel burning and changes in land use, with more than 80% of this increase occurring since 1900. The increased levels of CO{sub 2} will remain in the atmosphere for hundreds to thousands of years. The complexity of the climate system makes it difficult to predict specific aspects of human-induced climate change, such as exactly how and where changes will occur, and their magnitude. The Intergovernmental Panel for Climate Change (IPCC) was established by World Meteorological Organization (WMO) and the United Nations in 1988. The IPCC was tasked with assessing the scientific, technical and socioeconomic information needed to understand the risk of human-induced climate change, its observed and projected impacts, and options for adaptation and mitigation. The IPCC concluded in its Fourth Assessment Report (AR4) that warming of the climate system is unequivocal, and that most of the observed increase in globally averaged temperatures since the mid-20th century is very likely due to the observed increased in anthropogenic greenhouse gas concentrations (IPCC, 2007).

Robert Stockwell, PhD

2010-09-23T23:59:59.000Z

296

Scaling analyses of forcings and outputs of a simplified Last1 Millennium climate model2  

E-Print Network [OSTI]

its responses with those of multiproxies and the NASA GISS-ER2 GCM. 22 became too weak at 27 longer scales. At small scales, the GISS ER2

Lovejoy, Shaun

297

Alternative Fueling Station Locations | OpenEI  

Open Energy Info (EERE)

Alternative Fueling Station Locations Alternative Fueling Station Locations Dataset Summary Description Alternative fueling stations are located throughout the United States and their availability continues to grow. The Alternative Fuels Data Center (AFDC) maintains a website where you can find alternative fuels stations near you or on a route, obtain counts of alternative fuels stations by state, view U.S. maps, and more. Access up-to-date fuel station data here: http://www.afdc.energy.gov/afdc/data_download The dataset available for download here provides a "snapshot" of the alternative fueling station information for: compressed natural gas (CNG), E85 (85% ethanol, 15% gasoline), propane/liquefied petroleum gas (LPG), biodiesel, electricity, hydrogen, and liquefied natural gas

298

Earthquake locations and seismic velocity models for Southern California  

E-Print Network [OSTI]

135 The Imperial Valley Region . . . . . . . . . . .for the Imperial Valley region . . . . . . . . . . . . .refraction survey of the imperial valley region, california.

Lin, Guoqing

2007-01-01T23:59:59.000Z

299

Economic impacts and challenges of Chinas petroleum industry: An inputoutput analysis  

Science Journals Connector (OSTI)

It is generally acknowledged that the petroleum industry plays an important role in Chinas national economic and social development. The direct, indirect, and induced impacts of Chinas petroleum industry are analyzed in this study by using the InputOutput approach. The study also considers the main challenges that Chinas economy might face in the future. The research results suggest the following: (1) The total economic impacts coefficients on output, given each unit of final demands change in extraction of petroleum and processing of petroleum, are 1.9180 and 3.2747 respectively, and the corresponding economic impacts coefficients on GDP are 1.0872 and 0.9001 respectively; (2) Extraction of petroleum has a more direct impact on GDP, while processing of petroleum has a greater effect on the total output; (3) Extraction of petroleums total economic impacts coefficients on both output and GDP have remained stable in recent years after a period of long decline; processing of petroleums total economic impacts coefficient on output is steadily increasing; (4) Import uncertainty, the likelihood of rising oil prices, and net oil exports caused by items manufactured with petroleum products (i.e. Made in China goods) are the main challenges the petroleum industry will cause for Chinas overall economy.

Tang Xu; Zhang Baosheng; Feng Lianyong; Marwan Masri; Afshin Honarvar

2011-01-01T23:59:59.000Z

300

The pipeline and valve location problem  

Science Journals Connector (OSTI)

This paper, proposes an exact algorithm for the problem of locating a pipeline between two points of a network, as well as a set of safety valves which help control the damage caused by possible spills along the pipeline. A labelling approach is developed to determine simultaneously the optimal pipeline and valve locations, with the objective of optimising an impact measure that depends on the average number of accidents and their cost. Computational experiments on grid and random instances are presented in order to evaluate the algorithm's performance and to compare its results to the solutions provided by sequential approaches. [Received 11 May 2010; Revised 10 October 2010; Accepted 21 November 2010

Gilbert Laporte; Marta M.B. Pascoal

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" 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
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301

Driver expectancy in locating automotive controls  

E-Print Network [OSTI]

to determine if any of these factors had any effect on the distributions of control locations. In the final phase of the study McGrath measured response time and errors in locating controls in two cars, one was a 1973 Toyota and the other a 1973 Buick..., Chrysler, and Dodge. Also included were the following far eastern car makes: Toyota, Honda, Mazda, Hyundai, Isuzu, Nissan, and Geo. The automobiles were divided into six groups: 14 1. Foreign-make, small, mid-size, and sports cars. 2. Foreign...

Francis, Dawn Suzette

1990-01-01T23:59:59.000Z

302

SAS Output  

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

4. Existing Capacity by Producer Type, 2012 (Megawatts) 4. Existing Capacity by Producer Type, 2012 (Megawatts) Producer Type Number of Generators Generator Nameplate Capacity Net Summer Capacity Net Winter Capacity Electric Power Sector Electric Utilities 9,624 680,592 621,785 644,358 Independent Power Producers, Non-Combined Heat and Power Plants 6,148 412,045 374,964 389,349 Independent Power Producers, Combined Heat and Power Plants 609 39,916 35,266 38,023 Total 16,381 1,132,554 1,032,015 1,071,729 Commercial and Industrial Sectors Commercial Sector 962 3,610 3,223 3,349 Industrial Sector 1,680 31,832 27,795 29,381 Total 2,642 35,442 31,018 32,730 All Sectors Total 19,023 1,167,995 1,063,033 1,104,459 Notes: In 2011, EIA corrected the NAICS codes of several plants which resulted in a net capacity shift from the electric utility sector to the commercial sector.

303

SAS Output  

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

B. U.S. Transformer Sustained Automatic Outage Counts B. U.S. Transformer Sustained Automatic Outage Counts and Hours by High-Voltage Size and NERC Region, 2012 Sustained Automatic Outage Counts High-Side Voltage (kV) Eastern Interconnection TRE WECC Contiguous U.S. 100-199 -- -- -- -- 200-299 -- -- 1.00 1.00 300-399 2.00 -- 4.00 6.00 400-599 14.00 -- 11.00 25.00 600+ -- -- -- -- Grand Total 16.00 -- 16.00 32.00 Sustained Automatic Outage Hours High-Side Voltage (kV) Eastern Interconnection TRE WECC Contiguous U.S. 100-199 -- -- -- -- 200-299 -- -- 27.58 27.58 300-399 153.25 -- 15.87 169.12 400-599 3,070.88 -- 258.37 3,329.25 600+ -- -- -- -- Grand Total 3,224.13 -- 301.82 3,525.95 Outage Hours per Outage Incident Eastern Interconnection TRE WECC Contiguous U.S.

304

SAS Output  

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

6. Coal Consumption at Commercial and Institutional Users by Census Division and State" 6. Coal Consumption at Commercial and Institutional Users by Census Division and State" "(thousand short tons)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "Middle Atlantic",20,52,24,73,83,-12.4 " Pennsylvania",20,52,24,73,83,-12.4 "East North Central",112,197,127,309,331,-6.8 " Illinois",34,45,29,79,66,18.9 " Indiana","w","w","w","w","w","w" " Michigan","w","w","w","w","w","w"

305

SAS Output  

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

Number of Employees at Underground and Surface Mines by State and Mine Production Range, 2012" Number of Employees at Underground and Surface Mines by State and Mine Production Range, 2012" ,"Mine Production Range (thousand short tons)" "Coal-Producing State, Region1","Above 1,000","Above 500","Above 200","Above 100","Above 50","Above 10","Above 0","Zero2","Total Number" "and Mine Type",,"to 1,000","to 500","to 200","to 100","to 50","to 10",,"of Employees" "Alabama",3415,97,655,317,160,224,54,105,5041 " Underground",2981,"-","-","-",36,88,"-",81,3190 " Surface",434,97,655,317,124,136,54,24,1851

306

SAS Output  

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

8. Average Sales Price of Coal by State and Mine Type, 2012 and 2011" 8. Average Sales Price of Coal by State and Mine Type, 2012 and 2011" "(dollars per short ton)" ,2012,,,2011,,,"Percent Change" "Coal-Producing","Underground","Surface","Total","Underground","Surface","Total","Underground","Surface","Total" "State" "Alabama",107.73,104.51,106.57,100.17,108.71,102.69,7.6,-3.9,3.8 "Alaska","-","w","w","-","w","w","-","w","w" "Arizona","-","w","w","-","w","w","-","w","w" "Arkansas","w","-","w","w","-","w","w","-","w"

307

SAS Output  

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

Underground Coal Production by State and Mining Method, 2012" Underground Coal Production by State and Mining Method, 2012" "(thousand short tons)" "Coal-Producing State and Region1","Continuous2","Conventional and","Longwall4","Total" ,,"Other3" "Alabama",139,20,12410,12570 "Arkansas",96,"-","-",96 "Colorado",757,"-",22889,23646 "Illinois",18969,"-",23868,42837 "Indiana",15565,"-","-",15565 "Kentucky Total",56179,2018,"-",58198 " Kentucky (East)",22090,2010,"-",24100 " Kentucky (West)",34089,9,"-",34098 "Maryland",797,"-","-",797 "Montana","-","-",5708,5708

308

SAS Output  

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

Coal Mining Productivity by State, Mine Type, and Union Status, 2012" Coal Mining Productivity by State, Mine Type, and Union Status, 2012" "(short tons produced per employee hour)" ,"Union",,"Nonunion" "Coal-Producing State and Region1","Underground","Surface","Underground","Surface" "Alabama",1.69,"-",0.66,1.8 "Alaska","-",5.98,"-","-" "Arizona","-",7.38,"-","-" "Arkansas","-","-",0.59,"-" "Colorado",4.9,6.09,6.02,4.45 "Illinois",2.09,"-",5.34,4.7 "Indiana","-","-",3.23,5.41 "Kentucky Total",3.02,2.45,2.36,3.06 " Kentucky (East)","-",2.45,1.64,2.65

309

SAS Output  

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

Average Sales Price of U.S. Coal by State and Disposition, 2012" Average Sales Price of U.S. Coal by State and Disposition, 2012" "(dollars per short ton)" "Coal-Producing State","Open Market1","Captive2","Total3" "Alabama",85.06,"-",106.57 "Alaska","w","-","w" "Arizona","w","-","w" "Arkansas","w","-","w" "Colorado",38.51,43.19,37.54 "Illinois",49.04,54.71,53.08 "Indiana",49.16,54.5,52.01 "Kentucky Total",61.85,73.08,63.12 " Kentucky (East)",75.8,73.08,75.62 " Kentucky (West)",48.6,"-",48.67 "Louisiana","w","-","w"

310

SAS Output  

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

5. Emissions from Energy Consumption at 5. Emissions from Energy Consumption at Conventional Power Plants and Combined-Heat-and-Power Plants, by State, 2011 and 2012 (Thousand Metric Tons) Census Division and State Carbon Dioxide (CO2) Sulfur Dioxide (SO2) Nitrogen Oxides (NOx) Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 34,766 37,698 33 58 39 37 Connecticut 8,987 8,196 7 1 12 6 Maine 3,722 4,351 8 12 7 8 Massachusetts 14,346 16,404 15 22 14 14 New Hampshire 4,295 5,127 2 23 4 5 Rhode Island 3,403 3,595 0.03 0.07 2 3 Vermont 12 24 0.05 0.09 1 1 Middle Atlantic 161,786 171,603 275 370 187 203 New Jersey 16,120 16,917 4 5 14 13 New York 35,669 37,256 31 52 40 43 Pennsylvania 109,997 117,430 240 313 133 147

311

SAS Output  

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

Recoverable Coal Reserves and Average Recovery Percentage at Producing Mines by State, 2012 and 2011" Recoverable Coal Reserves and Average Recovery Percentage at Producing Mines by State, 2012 and 2011" "(million short tons)" ,2012,,2011 "Coal-Producing","Recoverable Coal","Average Recovery","Recoverable Coal","Average Recovery","Percent Change" "State","Reserves","Percentage","Reserves","Percentage","Recoverable Coal" ,,,,,"Reserves" "Alabama",265,53.63,306,55.39,-13.2 "Alaska","w","w","w","w","w" "Arizona","w","w","w","w","w" "Arkansas","w","w","w","w","w"

312

SAS Output  

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

7. Average Retail Price of Electricity to Ultimate Customers: 7. Average Retail Price of Electricity to Ultimate Customers: Total by End-Use Sector, 2003 - December 2012 (Cents per Kilowatthour) Period Residential Commercial Industrial Transportation All Sectors Annual Totals 2003 8.72 8.03 5.11 7.54 7.44 2004 8.95 8.17 5.25 7.18 7.61 2005 9.45 8.67 5.73 8.57 8.14 2006 10.40 9.46 6.16 9.54 8.90 2007 10.65 9.65 6.39 9.70 9.13 2008 11.26 10.36 6.83 10.74 9.74 2009 11.51 10.17 6.81 10.65 9.82 2010 11.54 10.19 6.77 10.57 9.83 2011 11.72 10.23 6.82 10.46 9.90 2012 11.88 10.09 6.67 10.21 9.84 2010 January 10.49 9.55 6.50 10.17 9.28 February 10.89 9.89 6.55 10.48 9.47 March 11.11 9.95 6.53 10.28 9.48 April 11.71 9.95 6.55 10.52 9.53 May 11.91 10.15 6.64 10.52 9.72

313

SAS Output  

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

1. Stocks of Coal, Petroleum Liquids, and Petroleum Coke: Electric Power Sector, 2002 - 2012 1. Stocks of Coal, Petroleum Liquids, and Petroleum Coke: Electric Power Sector, 2002 - 2012 Electric Power Sector Electric Utilities Independent Power Producers Period Coal (Thousand Tons) Petroluem Liquids (Thousand Barrels) Petroleum Coke (Thousand Tons) Coal (Thousand Tons) Petroluem Liquids (Thousand Barrels) Petroleum Coke (Thousand Tons) Coal (Thousand Tons) Petroluem Liquids (Thousand Barrels) Petroleum Coke (Thousand Tons) End of Year Stocks 2002 141,714 43,935 1,711 116,952 29,601 328 24,761 14,334 1,383 2003 121,567 45,752 1,484 97,831 28,062 378 23,736 17,691 1,105 2004 106,669 46,750 937 84,917 29,144 627 21,751 17,607 309 2005 101,137 47,414 530 77,457 29,532 374 23,680 17,882 156 2006 140,964 48,216 674 110,277 29,799 456 30,688 18,416 217

314

SAS Output  

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

A. U.S. Transmission Circuit Sustained Automatic Outage Counts and Hours A. U.S. Transmission Circuit Sustained Automatic Outage Counts and Hours by High-Voltage Size and NERC Region, 2012 Sustained Automatic Outage Counts Voltage Region Type Operating (kV) FRCC MRO NPCC RFC SERC SPP TRE WECC Contiguous U.S. AC 200-299 142 49 14 141 242 49 -- 484 1,121 AC 300-399 -- 88 107 95 46 56 80 165 637 AC 400-599 9 3 -- 22 86 -- -- 125 245 AC 600+ -- -- 6 9 -- -- -- -- 15 AC Total 151 140 127 267 374 105 80 774 2,018 DC 100-199 -- -- -- -- -- -- -- -- -- DC 200-299 -- 18 -- -- -- -- -- 5 23 DC 300-399 -- -- -- -- -- -- -- -- -- DC 400-499 -- 5 -- -- -- -- -- -- 5 DC 500-599 -- -- -- 5 -- -- -- 17 22 DC 600+ -- -- -- -- -- -- -- -- --

315

SAS Output  

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

Sales Price of Coal by State and Underground Mining Method, 2012" Sales Price of Coal by State and Underground Mining Method, 2012" "(dollars per short ton)" "Coal-Producing State","Continuous1","Conventional and","Longwall3","Total" ,,"Other2" "Alabama","w","-","w",107.73 "Arkansas","w","-","-","w" "Colorado","w","-",37.18,"w" "Illinois",48.08,"-",59.51,54.18 "Indiana",52.94,"-","-",52.94 "Kentucky Total","w","w","-",62.24 " Kentucky (East)","w","w","-",79.23 " Kentucky (West)",50.18,"-","-",50.18

316

SAS Output  

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

Steam Coal Exports by Customs District" Steam Coal Exports by Customs District" "(short tons)" ,,,,"Year to Date" "Customs District","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "Eastern Total",4951041,5566950,6554494,10517991,11407664,-7.8 " Baltimore, MD",1275530,831976,1715016,2107506,2852092,-26.1 " Boston, MA",7,"-",12,7,24,-70.8 " Buffalo, NY",1180,1516,2826,2696,5257,-48.7 " New York City, NY",3088,2664,2168,5752,6106,-5.8 " Norfolk, VA",3578715,4697769,4760354,8276484,8443756,-2 " Ogdensburg, NY",36894,3610,3090,40504,6838,492.3 " Philadelphia, PA",55513,29255,34241,84768,56733,49.4

317

SAS Output  

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

and Number of Mines by State, County, and Mine Type, 2012" and Number of Mines by State, County, and Mine Type, 2012" "(thousand short tons)" ,"Underground",,"Surface",,"Total" "Coal-Producing","Number of Mines","Production","Number of Mines","Production","Number of Mines","Production" "State and County" "Alabama",8,12570,38,6752,46,19321 " Bibb","-","-",2,119,2,119 " Blount","-","-",2,236,2,236 " Fayette",1,2249,"-","-",1,2249 " Franklin","-","-",2,137,2,137 " Jackson","-","-",3,152,3,152 " Jefferson",3,3589,9,1106,12,4695

318

SAS Output  

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

2. Average Tested Heat Rates by Prime Mover and Energy Source, 2007 - 2012 2. Average Tested Heat Rates by Prime Mover and Energy Source, 2007 - 2012 (Btu per Kilowatthour) Prime Mover Coal Petroluem Natural Gas Nuclear 2007 Steam Generator 10,158 10,398 10,440 10,489 Gas Turbine -- 13,217 11,632 -- Internal Combustion -- 10,447 10,175 -- Combined Cycle W 10,970 7,577 -- 2008 Steam Generator 10,138 10,356 10,377 10,452 Gas Turbine -- 13,311 11,576 -- Internal Combustion -- 10,427 9,975 -- Combined Cycle W 10,985 7,642 -- 2009 Steam Generator 10,150 10,349 10,427 10,459 Gas Turbine -- 13,326 11,560 -- Internal Combustion -- 10,428 9,958 -- Combined Cycle W 10,715 7,605 -- 2010 Steam Generator 10,142 10,249 10,416 10,452 Gas Turbine -- 13,386 11,590 -- Internal Combustion -- 10,429 9,917 --

319

SAS Output  

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

0. Receipts, Average Cost, and Quality of Fossil Fuels: Commerical Sector, 2002 - 2012 (continued) 0. Receipts, Average Cost, and Quality of Fossil Fuels: Commerical Sector, 2002 - 2012 (continued) Petroleum Coke Natural Gas All Fossil Fuels Receipts Average Cost Receipts Average Cost Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMbtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Mcf) (Dollars per MMBtu) (Dollars per Mcf) Percentage of Consumption (Dollars per MMBtu) Annual Totals 2002 0 0 -- -- -- -- 18,671 18,256 3.44 3.52 24.7 3.03 2003 0 0 -- -- -- 0.0 18,169 17,827 4.96 5.06 30.5 4.02 2004 0 0 -- -- -- 0.0 16,176 15,804 5.93 6.07 21.9 4.58 2005 0 0 -- -- -- 0.0 17,600 17,142 8.38 8.60 25.2 6.25 2006 0 0 -- -- -- 0.0 21,369 20,819 8.33 8.55 30.7 6.42

320

SAS Output  

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

3.A. Net Generation by Energy Source: Independent Power Producers, 2002 - 2012 3.A. Net Generation by Energy Source: Independent Power Producers, 2002 - 2012 (Thousand Megawatthours) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Nuclear Hydroelectric Conventional Renewable Sources Excluding Hydroelectric Hydroelectric Pumped Storage Other Total Annual Totals 2002 395,943 22,241 8,368 378,044 1,763 272,684 18,189 44,466 -1,309 8,612 1,149,001 2003 452,433 35,818 7,949 380,337 2,404 304,904 21,890 46,060 -1,003 8,088 1,258,879 2004 443,547 33,574 7,410 427,510 3,194 312,846 19,518 48,636 -962 7,856 1,303,129 2005 507,199 37,096 9,664 445,625 3,767 345,690 21,486 51,708 -1,174 6,285 1,427,346 2006 498,316 10,396 8,409 452,329 4,223 361,877 24,390 59,345 -1,277 6,412 1,424,421

Note: This page contains sample records for the topic "model output location" 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

SAS Output  

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

9. Consumption of Coal for Electricity Generation by State by Sector, 9. Consumption of Coal for Electricity Generation by State by Sector, 2012 and 2011 (Thousand Tons) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 1,787 2,998 -40% 520 898 1,257 2,087 0 0 10 12 Connecticut 297 317 -6.5% 0 0 297 317 0 0 0 0 Maine 11 14 -18% 0 0 6 7 0 0 5 6 Massachusetts 959 1,769 -46% 0 0 954 1,763 0 0 5 6 New Hampshire 520 898 -42% 520 898 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0 Middle Atlantic 44,000 53,658 -18% 6 16 43,734 53,052 4 1 256 589

322

SAS Output  

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

4. Average Retail Price of Electricity to Ultimate Customers 4. Average Retail Price of Electricity to Ultimate Customers by End-Use Sector 2002 through 2012 (Cents per kilowatthour) Year Residential Commercial Industrial Transportation Other Total Total Electric Industry 2002 8.44 7.89 4.88 N/A 6.75 7.20 2003 8.72 8.03 5.11 7.54 N/A 7.44 2004 8.95 8.17 5.25 7.18 N/A 7.61 2005 9.45 8.67 5.73 8.57 N/A 8.14 2006 10.40 9.46 6.16 9.54 N/A 8.90 2007 10.65 9.65 6.39 9.70 N/A 9.13 2008 11.26 10.36 6.83 10.74 N/A 9.74 2009 11.51 10.17 6.81 10.65 N/A 9.82 2010 11.54 10.19 6.77 10.57 N/A 9.83 2011 11.72 10.23 6.82 10.46 N/A 9.90 2012 11.88 10.09 6.67 10.21 N/A 9.84 Full-Service Providers 2002 8.40 7.77 4.78 N/A 6.65 7.13 2003 8.68 7.89 5.01 6.82 N/A 7.38

323

SAS Output  

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

Average Price of U.S. Steam Coal Exports" Average Price of U.S. Steam Coal Exports" "(dollars per short ton)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",65.1,63.67,73.81,64.48,78.9,-18.3 " Canada*",59.34,55.22,63.02,57.57,73.63,-21.8 " Dominican Republic",78.47,74.41,73.89,75.4,76.61,-1.6 " Honduras","-",54.58,54.43,54.58,54.43,0.3 " Jamaica",480,54.43,"-",54.72,55.42,-1.3 " Mexico",69.42,73.33,82.64,70.83,86.44,-18.1 " Other**",80.33,389.3,70.37,82.45,76.1,8.3

324

SAS Output  

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

Coal Production by Coalbed Thickness and Mine Type, 2012" Coal Production by Coalbed Thickness and Mine Type, 2012" "(thousand short tons)" "Coal Thickness (inches)","Underground","Surface","Total" "Under 7","-",17,17 "7 - Under 13","-",2108,2108 "13 - Under 19",429,6688,7117 "19 - Under 25",111,14107,14217 "25 - Under 31",4147,12913,17060 "31 - Under 37",15128,19022,34150 "37 - Under 43",23868,17285,41153 "43 - Under 49",26035,15597,41632 "49 - Under 55",18909,22544,41453 "55 - Under 61",36946,11285,48231 "61 - Under 67",43146,15074,58220 "67 - Under 73",40983,8783,49766 "73 - Under 79",32914,10193,43107 "79 - Under 85",27011,3554,30565

325

SAS Output  

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

3. Carbon Dioxide Uncontrolled Emission Factors 3. Carbon Dioxide Uncontrolled Emission Factors Fuel EIA Fuel Code Source and Tables (As Appropriate) Factor (Pounds of CO2 Per Million Btu)*** Bituminous Coal BIT Source: 1 205.30000 Distillate Fuel Oil DFO Source: 1 161.38600 Geothermal GEO Estimate from EIA, Office of Integrated Analysis and Forecasting 16.59983 Jet Fuel JF Source: 1 156.25800 Kerosene KER Source: 1 159.53500 Lignite Coal LIG Source: 1 215.40000 Municipal Solid Waste MSW Source: 1 (including footnote 2 within source) 91.90000 Natural Gas NG Source: 1 117.08000 Petroleum Coke PC Source: 1 225.13000 Propane Gas PG Sources: 1 139.17800 Residual Fuel Oil RFO Source: 1 173.90600 Synthetic Coal SC Assumed to have the emissions similar to Bituminous Coal. 205.30000

326

SAS Output  

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

Coal Imports by Customs District" Coal Imports by Customs District" "(short tons)" ,,,,"Year to Date" "Customs District","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "Eastern Total",469878,331008,156004,800886,350124,128.7 " Baltimore, MD","-","-",106118,"-",154318,"-" " Boston, MA",373985,154438,"-",528423,51185,"NM" " Buffalo, NY",44,"-","-",44,"-","-" " New York City, NY",1373,1402,487,2775,507,447.3 " Norfolk, VA","-",68891,"-",68891,35856,92.1 " Ogdensburg, NY","-",1,12,1,12,-91.7

327

SAS Output  

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

U.S. Coke Exports" U.S. Coke Exports" "(short tons)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",162796,79217,201795,242013,340944,-29 " Canada*",73859,17837,112348,91696,161596,-43.3 " Mexico",88535,60517,86721,149052,176163,-15.4 " Other**",402,863,2726,1265,3185,-60.3 "South America Total",223,217,591,440,1158,-62 " Other**",223,217,591,440,1158,-62 "Europe Total",48972,59197,"-",108169,6,"NM" " Other**",347,11743,"-",12090,"-","-"

328

SAS Output  

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

7. U.S. Coal Stocks, 2007 - 2013" 7. U.S. Coal Stocks, 2007 - 2013" "(thousand short tons)" ,"Coal Consumers" "Last Day of Quarter","Electric","Coke","Other","Commercial","Total","Coal Producers","Total" ,"Power","Plants","Industrial2","and",,"and" ,"Sector1",,,"Institutional Users",,"Distributors" 2007 " March 31",141389,2444,5756,"-",149588,34007,183595 " June 30",154812,2364,5672,"-",162849,32484,195333 " September 30",142666,1972,5811,"-",150448,30090,180538 " December 31",151221,1936,5624,"-",158781,33977,192758

329

SAS Output  

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

5. Unit of Measure Equivalents 5. Unit of Measure Equivalents Unit Equivalent Kilowatt (kW) 1,000 (One Thousand) Watts Megawatt (MW) 1,000,000 (One Million) Watts Gigawatt (GW) 1,000,000,000 (One Billion) Watts Terawatt (TW) 1,000,000,000,000 (One Trillion) Watts Gigawatt 1,000,000 (One Million) Kilowatts Thousand Gigawatts 1,000,000,000 (One Billion) Kilowatts Kilowatthours (kWh) 1,000 (One Thousand) Watthours Megawatthours (MWh) 1,000,000 (One Million) Watthours Gigawatthours (GWh) 1,000,000,000 (One Billion) Watthours Terawatthours (TWh) 1,000,000,000,000 (One Trillion) Watthours Gigawatthours 1,000,000 (One Million) Kilowatthours Thousand Gigawatthours 1,000,000,000(One Billion Kilowatthours U.S. Dollar 1,000 (One Thousand) Mills U.S. Cent 10 (Ten) Mills Barrel of Oil 42 Gallons

330

SAS Output  

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

6. Receipts, Average Cost, and Quality of Fossil Fuels: Electric Utilities, 2002 - 2012 (continued) 6. Receipts, Average Cost, and Quality of Fossil Fuels: Electric Utilities, 2002 - 2012 (continued) Petroleum Coke Natural Gas All Fossil Fuels Receipts Average Cost Receipts Average Cost Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMbtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Mcf) (Dollars per MMBtu) (Dollars per Mcf) Percentage of Consumption (Dollars per MMBtu) Annual Totals 2002 75,711 2,677 0.63 17.68 4.98 126.0 1,680,518 1,634,734 3.68 3.78 72.3 1.53 2003 89,618 3,165 0.74 20.94 5.51 124.0 1,486,088 1,439,513 5.59 5.77 81.6 1.74 2004 107,985 3,817 0.89 25.15 5.10 92.0 1,542,746 1,499,933 6.15 6.33 82.9 1.87 2005 102,450 3,632 1.29 36.31 5.16 87.9 1,835,221 1,780,721 8.32 8.57 83.4 2.38

331

SAS Output  

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

2 Stocks of Coal, Petroleum Liquids, and Petroleum Coke: 2 Stocks of Coal, Petroleum Liquids, and Petroleum Coke: Electric Power Sector, by State, 2012 and 2011 Census Division and State Coal (Thousand Tons) Petroleum Liquids (Thousand Barrels) Petroleum Coke (Thousand Tons) December 2012 December 2011 Percentage Change December 2012 December 2011 Percentage Change December 2012 December 2011 Percentage Change New England 1,030 1,389 -26% 2,483 2,680 -7.3% 0 0 -- Connecticut W W W 1,300 954 36% 0 0 -- Maine 0 0 -- W W W 0 0 -- Massachusetts W 675 W 837 990 -15% 0 0 -- New Hampshire W W W W W W 0 0 -- Rhode Island 0 0 -- W W W 0 0 -- Vermont 0 0 -- 51 49 3.0% 0 0 -- Middle Atlantic 7,553 7,800 -3.2% 5,496 6,591 -17% W W W New Jersey 926 871 6.3% 1,084 1,113 -2.6% 0 0 --

332

SAS Output  

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

0. Coal Receipts at Commercial and Institutional Users by Census Division and State" 0. Coal Receipts at Commercial and Institutional Users by Census Division and State" "(thousand short tons)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "Middle Atlantic",25,54,32,79,90,-12 " Pennsylvania",25,54,32,79,90,-12 "East North Central",115,183,117,298,301,-0.9 " Illinois",31,42,28,73,67,8.1 " Indiana","w","w","w","w","w","w" " Michigan","w","w","w","w","w","w"

333

SAS Output  

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

Coal Receipts at Other Industrial Plants by Census Division and State" Coal Receipts at Other Industrial Plants by Census Division and State" "(thousand short tons)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "New England","w","w","w","w","w","w" " Maine","w","w","w","w","w","w" " Massachusetts","w","w","w","w","w","w" "Middle Atlantic",627,587,637,1214,1254,-3.1 " New York",214,178,194,392,377,4

334

SAS Output  

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

Major U.S. Coal Mines, 2012" Major U.S. Coal Mines, 2012" "Rank","Mine Name / Company","Mine Type","State","Production (short tons)" 1,"North Antelope Rochelle Mine / Peabody Powder River Mining Ll","Surface","Wyoming",107639188 2,"Black Thunder / Thunder Basin Coal Company Llc","Surface","Wyoming",93082919 3,"Cordero Mine / Cordero Mining Llc","Surface","Wyoming",39204736 4,"Antelope Coal Mine / Antelope Coal Llc","Surface","Wyoming",34316314 5,"Belle Ayr Mine / Alpha Coal West, Inc.","Surface","Wyoming",24227846 6,"Eagle Butte Mine / Alpha Coal West, Inc.","Surface","Wyoming",22466733

335

SAS Output  

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

D. Petroleum Liquids: Consumption for Electricity Generation, D. Petroleum Liquids: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 835,481 553,390 241,892 3,953 36,243 2003 1,089,307 658,868 380,378 5,358 44,702 2004 1,031,954 651,712 350,093 4,544 25,606 2005 1,035,045 618,811 387,355 3,469 25,410 2006 459,392 335,130 105,312 1,963 16,987 2007 512,423 355,999 139,977 1,505 14,942 2008 332,367 242,379 79,816 957 9,215 2009 266,508 196,346 59,277 1,101 9,784 2010 244,114 188,987 49,042 970 5,115 2011 163,954 125,755 33,166 801 4,233 2012 134,956 105,179 24,081 1,618 4,078 2010 January 33,737 26,715 6,282 100 639

336

SAS Output  

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

9. Total Capacity of Distributed and Dispersed Generators by Technology Type, 9. Total Capacity of Distributed and Dispersed Generators by Technology Type, 2005 through 2012 Capacity (MW) Year Internal Combustion Combustion Turbine Steam Turbine Hydro Wind Photovoltaic Storage Other Wind and Other Total Number of Generators Distributed Generators 2005 4,025.0 1,917.0 1,830.0 999.0 -- -- -- -- 995.0 9,766.0 17,371 2006 3,646.0 1,298.0 2,582.0 806.0 -- -- -- -- 1,081.0 9,411.0 5,044 2007 4,624.0 1,990.0 3,596.0 1,051.0 -- -- -- -- 1,441.0 12,702.0 7,103 2008 5,112.0 1,949.0 3,060.0 1,154.0 -- -- -- -- 1,588.0 12,863.0 9,591 2009 4,339.0 4,147.0 4,621.0 1,166.0 -- -- -- -- 1,729.0 16,002.0 13,006 2010 886.8 186.0 109.9 97.4 98.9 236.3 -- 372.7 -- 1,988.0 15,630

337

SAS Output  

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

D. Wood / Wood Waste Biomass: Consumption for Electricity Generation, D. Wood / Wood Waste Biomass: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 605,054 10,659 129,947 469 463,980 2003 519,294 16,545 139,852 437 362,460 2004 344,134 19,973 130,248 168 193,745 2005 355,250 27,373 138,407 207 189,263 2006 350,074 27,455 135,546 269 186,803 2007 353,025 31,568 132,953 284 188,220 2008 338,786 29,150 130,122 287 179,227 2009 320,444 29,565 130,894 274 159,712 2010 349,530 40,167 137,072 274 172,016 2011 347,623 35,474 130,108 482 181,559 2012 390,342 32,723 138,217 478 218,924 2010 January 29,578 3,731 11,954 23 13,870

338

SAS Output  

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

U.S. Coal Exports and Imports, 2007 - 2013" U.S. Coal Exports and Imports, 2007 - 2013" "(thousand short tons)" ,"January - March",,"April - June",,"July - September",,"October - December",,"Total" "Year","Exports","Imports","Exports","Imports","Exports","Imports","Exports","Imports","Exports","Imports" 2007,11139,8786,14702,8405,16198,10559,17124,8597,59163,36347 2008,15802,7640,23069,8982,20321,8485,22329,9101,81519,34208 2009,13335,6325,12951,5426,15159,5441,17653,5447,59097,22639 2010,17807,4803,21965,5058,21074,4680,20870,4811,81716,19353 2011,26617,3381,26987,3419,25976,3588,27679,2700,107259,13088 2012,28642,2022,37534,2329,31563,2415,28006,2394,125746,9159

339

SAS Output  

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

1. Consumption of Petroleum Coke for Electricity Generation by State, by Sector, 1. Consumption of Petroleum Coke for Electricity Generation by State, by Sector, 2012 and 2011 (Thousand Tons) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 0 0 -- 0 0 0 0 0 0 0 0 Connecticut 0 0 -- 0 0 0 0 0 0 0 0 Maine 0 0 -- 0 0 0 0 0 0 0 0 Massachusetts 0 0 -- 0 0 0 0 0 0 0 0 New Hampshire 0 0 -- 0 0 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0 Middle Atlantic 56 121 -54% 0 0 0 94 0 0 56 27

340

SAS Output  

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

2. Nitrogen Oxides Uncontrolled Emission Factors 2. Nitrogen Oxides Uncontrolled Emission Factors Fuel, Code, Source and Emission Units Combustion System Type / Firing Configuration Cyclone Boiler Fluidized Bed Boiler Opposed Firing Boiler Spreader Stoker Boiler Fuel EIA Fuel Code Source and Tables (As Appropriate) Emissions Units Lbs = Pounds MMCF = Million Cubic Feet MG = Thousand Gallons Dry-Bottom Boilers Dry-Bottom Boilers Dry-Bottom Boilers Wet-Bottom Boilers Dry-Bottom Boilers Agricultural Byproducts AB Source: 1 Lbs per ton 1.20 1.20 1.20 N/A 1.20 Blast Furnace Gas BFG Sources: 1 (including footnote 7 within source); EIA estimates Lbs per MMCF 15.40 15.40 15.40 N/A 15.40 Bituminous Coal BIT Source: 2, Table 1.1-3 Lbs per ton 33.00 5.00 12.00 31.00 11.00 Black Liquor BLQ Source: 1 Lbs per ton ** 1.50 1.50 1.50 N/A 1.50

Note: This page contains sample records for the topic "model output location" 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

SAS Output  

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

2.1. Number of Ultimate Customers Served by Sector, by Provider, 2.1. Number of Ultimate Customers Served by Sector, by Provider, 2002 through 2012 Year Residential Commercial Industrial Transportation Other Total Total Electric Industry 2002 116,622,037 15,333,700 601,744 N/A 1,066,554 133,624,035 2003 117,280,481 16,549,519 713,221 1,127 N/A 134,544,348 2004 118,763,768 16,606,783 747,600 1,025 N/A 136,119,176 2005 120,760,839 16,871,940 733,862 518 N/A 138,367,159 2006 122,471,071 17,172,499 759,604 791 N/A 140,403,965 2007 123,949,916 17,377,219 793,767 750 N/A 142,121,652 2008 124,937,469 17,562,726 774,713 727 N/A 143,275,635 2009 125,177,175 17,561,661 757,519 705 N/A 143,497,060 2010 125,717,935 17,674,338 747,746 239 N/A 144,140,258 2011 126,143,072 17,638,062 727,920 92 N/A 144,509,146

342

SAS Output  

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

Average Price of U.S. Coke Exports" Average Price of U.S. Coke Exports" "(dollars per short ton)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",240.59,241.38,218.4,240.85,225.8,6.7 " Canada*",147.49,330.47,243.04,183.08,286.56,-36.1 " Mexico",316.57,211.63,189.12,273.97,171.71,59.6 " Other**",612.42,485.63,134.48,525.92,135.04,289.5 "South America Total",140.65,156.15,322.7,148.29,250.36,-40.8 " Other**",140.65,156.15,322.7,148.29,250.36,-40.8 "Europe Total",259.26,255.24,"-",257.06,427.83,-39.9

343

SAS Output  

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

2. Demand-Side Management Program Annual Effects by Program 2. Demand-Side Management Program Annual Effects by Program Category, by Sector, 2002 through 2012 Year Residential Commercial Industrial Transportation Total Energy Efficiency - Energy Savings (Thousand MWh) 2002 15,284 24,803 10,242 -- 50,328 2003 12,914 24,758 10,031 551 48,254 2004 17,185 24,290 11,137 50 52,663 2005 18,894 28,073 11,986 47 59,000 2006 21,150 28,720 13,155 50 63,076 2007 22,772 30,359 14,038 108 67,278 2008 25,396 34,634 14,766 75 74,871 2009 27,395 34,831 14,610 76 76,912 2010 32,150 37,416 17,259 89 86,914 2011 46,790 50,732 23,061 76 120,659 2012 54,516 58,894 25,023 92 138,525 Energy Efficiency - Actual Peak Load Reduction (MW) 2002 5,300 5,389 2,768 -- 13,457 2003 5,909 4,911 2,671 94 13,585

344

SAS Output  

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

A. Net Generation by Energy Source: Total (All Sectors), 2002 - 2012 A. Net Generation by Energy Source: Total (All Sectors), 2002 - 2012 (Thousand Megawatthours) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Nuclear Hydroelectric Conventional Renewable Sources Excluding Hydroelectric Hydroelectric Pumped Storage Other Total Annual Totals 2002 1,933,130 78,701 15,867 691,006 11,463 780,064 264,329 79,109 -8,743 13,527 3,858,452 2003 1,973,737 102,734 16,672 649,908 15,600 763,733 275,806 79,487 -8,535 14,045 3,883,185 2004 1,978,301 100,391 20,754 710,100 15,252 788,528 268,417 83,067 -8,488 14,232 3,970,555 2005 2,012,873 99,840 22,385 760,960 13,464 781,986 270,321 87,329 -6,558 12,821 4,055,423 2006 1,990,511 44,460 19,706 816,441 14,177 787,219 289,246 96,525 -6,558 12,974 4,064,702

345

SAS Output  

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

8. Retail Sales of Electricity to Ultimate Customers by End-Use Sector, 8. Retail Sales of Electricity to Ultimate Customers by End-Use Sector, by State, 2012 and 2011 (Million Kilowatthours) Residential Commercial Industrial Transportation All Sectors Census Division and State Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 47,208 47,481 44,864 45,018 27,818 27,927 566 569 120,456 120,995 Connecticut 12,758 12,919 12,976 13,087 3,566 3,668 193 185 29,492 29,859 Maine 4,481 4,382 4,053 4,018 3,027 3,016 0 0 11,561 11,415 Massachusetts 20,313 20,473 17,723 17,767 16,927 16,974 350 357 55,313 55,570 New Hampshire 4,439 4,454 4,478 4,478 1,953 1,936 0 0 10,870 10,869 Rhode Island 3,121 3,129 3,640 3,660 923 916 24 27 7,708 7,732

346

SAS Output  

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

C. Net Summer Capacity of Utility Scale Units Using Primarily Fossil Fuels and by State, 2012 and 2011 (Megawatts) C. Net Summer Capacity of Utility Scale Units Using Primarily Fossil Fuels and by State, 2012 and 2011 (Megawatts) Census Division and State Natural Gas Fired Combined Cycle Natural Gas Fired Combustion Turbine Other Natural Gas Coal Petroleum Coke Petroleum Liquids Other Gases Total Fossil Fuels Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 12,190.5 11,593.8 1,090.0 1,058.9 876.4 830.1 2,546.1 2,755.5 0.0 0.0 7,916.1 7,915.3 0.0 0.0 24,619.1 24,153.6 Connecticut 2,513.4 2,447.7 458.1 432.7 61.0 44.7 389.1 564.4 0.0 0.0 3,186.1 3,185.0 0.0 0.0 6,607.7 6,674.5 Maine 1,250.0 1,250.0 306.0 302.2 119.0 93.0 85.0 85.0 0.0 0.0 1,004.9 1,007.2 0.0 0.0 2,764.9 2,737.4

347

SAS Output  

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

0. U.S. Coal Stocks at Manufacturing Plants by North American Industry Classification System (NAICS) Code" 0. U.S. Coal Stocks at Manufacturing Plants by North American Industry Classification System (NAICS) Code" "(thousand short tons)" "NAICS Code","June 30 2013","March 31 2013","June 30 2012","Percent Change" ,,,,"(June 30)" ,,,,"2013 versus 2012" "311 Food Manufacturing",875,926,1015,-13.9 "312 Beverage and Tobacco Product Mfg.",26,17,19,35.8 "313 Textile Mills",22,22,25,-13.9 "315 Apparel Manufacturing","w","w","w","w" "321 Wood Product Manufacturing","w","w","w","w" "322 Paper Manufacturing",570,583,743,-23.3 "324 Petroleum and Coal Products*",127,113,156,-18.7

348

SAS Output  

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

Recoverable Coal Reserves and Average Recovery Percentage at Producing U.S. Mines by Mine Production Range and Mine Type, 2012" Recoverable Coal Reserves and Average Recovery Percentage at Producing U.S. Mines by Mine Production Range and Mine Type, 2012" "(million short tons)" ,"Underground",,"Surface",,"Total" "Mine Production Range","Recoverable Coal","Average Recovery","Recoverable Coal","Average Recovery","Recoverable Coal","Average Recovery" "(thousand short tons)","Reserves","Percentage","Reserves","Percentage","Reserves","Percentage" "Over 1,000",4874,57.96,11153,91.28,16028,81.15 "Over 500 to 1,000",531,47.14,226,81.9,757,57.49 "Over 200 to 500",604,52.72,333,69.16,938,58.57

349

SAS Output  

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

4. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: 4. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: Commercial Sector by State, 2012 Bituminous Subbituminous Lignite Census Division and State Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight New England 0 -- -- 0 -- -- 0 -- -- Connecticut 0 -- -- 0 -- -- 0 -- -- Maine 0 -- -- 0 -- -- 0 -- -- Massachusetts 0 -- -- 0 -- -- 0 -- -- New Hampshire 0 -- -- 0 -- -- 0 -- -- Rhode Island 0 -- -- 0 -- -- 0 -- -- Vermont 0 -- -- 0 -- -- 0 -- -- Middle Atlantic 0 -- -- 0 -- -- 0 -- --

350

SAS Output  

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

8. Average Cost of Petroleum Liquids Delivered for Electricity Generation by State, 2012 and 2011 8. Average Cost of Petroleum Liquids Delivered for Electricity Generation by State, 2012 and 2011 (Dollars per MMBtu) Census Division and State Electric Power Sector Electric Utilities Independent Power Producers Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 New England 18.64 W W 21.43 21.12 18.47 W Connecticut W 21.91 W 23.87 NM W 21.93 Maine W W W -- NM W W Massachusetts 17.17 19.76 -13% 17.45 NM 17.16 19.66 New Hampshire 23.23 W W 23.23 19.90 -- W Rhode Island -- W W -- NM -- W Vermont 24.11 NM NM 24.11 NM -- -- Middle Atlantic W 20.15 W 21.01 19.21 W 20.66 New Jersey 19.77 18.36 7.7% -- NM 19.77 20.28 New York W 19.66 W 21.01 20.00 W 19.36 Pennsylvania 21.84 22.19 -1.6% -- NM 21.84 22.19

351

SAS Output  

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

Productive Capacity of Coal Mines by State, 2012 and 2011" Productive Capacity of Coal Mines by State, 2012 and 2011" "(thousand short tons)" ,2012,,,2011,,,"Percent Change" "Coal-Producing","Underground","Surface","Total","Underground","Surface","Total","Underground","Surface","Total" "State" "Alabama",14594,7967,22561,16102,8911,25013,-9.4,-10.6,-9.8 "Alaska","-","w","w","-","w","w","-","w","w" "Arizona","-","w","w","-","w","w","-","w","w" "Arkansas","w","-","w","w","-","w","w","-","w"

352

SAS Output  

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

Quantity and Average Price of U.S. Coal Imports by Origin, 2007 - 2013" Quantity and Average Price of U.S. Coal Imports by Origin, 2007 - 2013" "(thousand short tons and dollars per short ton)" "Year and Quarter","Australia","Canada","Colombia","Indonesia","China","Venezuela","Other","Total" ,,,,,,,"Countries" 2007,66,1967,26864,3663,50,3425,311,36347 2008,149,2027,26262,3374,45,2312,39,34208 2009,152,1288,17787,2084,9,1297,21,22639 2010,380,1767,14584,1904,53,582,83,19353 2011,62,1680,9500,856,22,779,188,13088 2012 " January - March","-",260,1594,59,7,80,22,2022 " April - June","-",281,1728,49,21,170,80,2329 " July - September","-",297,1762,266,39,"-",51,2415

353

SAS Output  

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

Average Sales Price of Coal by State, County, and Number of Mines, 2012" Average Sales Price of Coal by State, County, and Number of Mines, 2012" "Coal-Producing State and County","Number of Mines","Sales","Average Sales Price" ,,"(thousand short tons)","(dollars per short ton)" "Alabama",39,19021,106.57 " Bibb",1,"w","w" " Blount",2,"w","w" " Fayette",1,"w","w" " Franklin",1,"w","w" " Jackson",2,"w","w" " Jefferson",11,4298,146.04 " Marion",1,"w","w" " Tuscaloosa",7,8599,111.55 " Walker",11,2370,81.88

354

SAS Output  

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

2. Coal Stocks at Commercial and Institutional Users by Census Division and State" 2. Coal Stocks at Commercial and Institutional Users by Census Division and State" "(thousand short tons)" "Census Division","June 30 2013","March 31 2013","June 30 2012","Percent Change" "and State",,,,"(June 30)" ,,,,"2013 versus 2012" "Middle Atlantic",62,58,56,10.9 " Pennsylvania",62,58,56,10.9 "East North Central",168,171,197,-14.7 " Illinois","w","w","w","w" " Indiana",75,76,75,0.5 " Michigan","w","w","w","w" " Ohio",25,15,19,27 " Wisconsin",5,5,3,59.1 "West North Central",66,75,97,-32.2

355

SAS Output  

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

3. Summary Statistics for Coal Refining Plants, 2012 - 2013" 3. Summary Statistics for Coal Refining Plants, 2012 - 2013" "(thousand short tons)" "Year and","Coal Receipts","Average Price of Coal Receipts","Coal Used","Coal Stocks1" "Quarter",,"(dollars per short ton)" 2012 " January - March",2151,27.47,1756,771 " April - June",3844,25.42,3688,825 " July - September",5399,24.32,5286,812 " October - December",4919,24.55,4680,787 " Total",16313,25.06,15410 2013 " January - March",5067,24.6,4989,793 " April - June",4015,25.24,3754,756 " Total",9082,24.88,8744 "1 Reported as of the last day of the quarter." "Note: Average price is based on the cost, insurance, and freight (c.i.f. value). Total may not equal sum of components because of independent rounding."

356

SAS Output  

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

B. Proposed Transmission Capacity Additions by High-Voltage Size, 2013 - 2019 B. Proposed Transmission Capacity Additions by High-Voltage Size, 2013 - 2019 (Circuit Miles of Transmission) Voltage Circuit Miles Type Operating (kV) Year 2013 Year 2014 Year 2015 Year 2016 Year 2017 Year 2018 Year 2019 All Years AC 100-199 954 1,222 992 1,047 392 382 176 5,165 AC 200-299 1,003 792 1,398 319 539 427 118 4,596 AC 300-399 4,779 839 1,532 1,527 502 1,650 349 11,178 AC 400-599 399 708 669 643 660 1,151 334 4,564 AC 600+ -- -- 14 -- -- 69 -- 83 AC Total 7,134 3,562 4,606 3,536 2,092 3,679 978 25,586 DC 100-199 2 11 5 -- -- 7 -- 25 DC 200-299 -- -- -- -- -- -- -- -- DC 300-399 -- -- -- -- 333 -- -- 333 DC 400-599 -- -- 10 -- -- -- -- 10 DC 600+ -- -- -- -- -- -- -- --

357

SAS Output  

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

3. Revenue and Expense Statistics for Major U.S. Investor-Owned Electric Utilities, 2002 through 2012 (Million Dollars) 3. Revenue and Expense Statistics for Major U.S. Investor-Owned Electric Utilities, 2002 through 2012 (Million Dollars) Description 2002 2003 2004 2005 2006 2007 Utility Operating Revenues 219,609 230,151 238,759 265,652 275,501 270,964 ......Electric Utility 200,360 206,268 213,012 234,909 246,736 240,864 ......Other Utility 19,250 23,883 25,747 30,743 28,765 30,100 Utility Operating Expenses 189,062 201,057 206,960 236,786 245,589 241,198 ......Electric Utility 171,604 179,044 183,121 207,830 218,445 213,076 ............Operation 116,660 125,436 131,560 150,645 158,893 153,885 ..................Production 90,715 98,305 103,871 120,586 127,494 121,700 ........................Cost of Fuel 24,149 26,871 28,544 36,106 37,945 39,548

358

SAS Output  

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

U.S. Coke Imports" U.S. Coke Imports" "(short tons)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Origin",2013,2013,2012,,,"Change" "North America Total",10284,2293,159462,12577,183712,-93.2 " Canada",3009,2293,159462,5302,183712,-97.1 " Panama",7275,"-","-",7275,"-","-" "South America Total",25267,13030,88424,38297,106612,-64.1 " Brazil","-","-",78595,"-",78595,"-" " Colombia",25267,13030,9829,38297,28017,36.7 "Europe Total",6044,40281,165027,46325,485791,-90.5

359

SAS Output  

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

Coal Production and Coalbed Thickness by Major Coalbeds and Mine Type, 2012" Coal Production and Coalbed Thickness by Major Coalbeds and Mine Type, 2012" ,"Production (thousand short tons)",,,"Thickness (inches)" "Coalbed ID Number1","Underground","Surface","Total","Average2","Low","High" "Coalbed Name" "1699 Wyodak","-",351188,351188,778,160,913 "0036 Pittsburgh",52476,3871,56348,74,18,138 "0489 No. 9",42193,12181,54374,61,24,74 "0484 Herrin (Illinois No. 6)",48526,1910,50436,71,46,89 "0212 Pittsburgh",27355,76,27431,75,27,98 "1701 Smith","-",23847,23847,822,745,912 "1696 Anderson-Dietz 1-Dietz 2","-",18992,18992,932,660,960

360

SAS Output  

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

0. Average Retail Price of Electricity to Ultimate Customers by End-Use Sector, 0. Average Retail Price of Electricity to Ultimate Customers by End-Use Sector, by State, 2012 and 2011 (Cents per Kilowatthour) Residential Commercial Industrial Transportation All Sectors Census Division and State Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 15.71 15.89 13.68 14.31 11.83 12.55 6.68 7.85 14.02 14.49 Connecticut 17.34 18.11 14.65 15.57 12.67 13.24 9.69 10.25 15.54 16.35 Maine 14.66 15.38 11.53 12.29 7.98 8.88 -- -- 11.81 12.58 Massachusetts 14.91 14.67 13.84 14.33 12.57 13.38 4.91 6.14 13.79 14.11 New Hampshire 16.07 16.52 13.36 14.04 11.83 12.27 -- -- 14.19 14.74 Rhode Island 14.40 14.33 11.87 12.37 10.68 11.27 8.28 14.11 12.74 13.04

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361

SAS Output  

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

3. Revenue from Retail Sales of Electricity to Ultimate Customers 3. Revenue from Retail Sales of Electricity to Ultimate Customers by Sector, by Provider, 2002 through 2012 (Million Dollars) Year Residential Commercial Industrial Transportation Other Total Total Electric Industry 2002 106,834 87,117 48,336 N/A 7,124 249,411 2003 111,249 96,263 51,741 514 N/A 259,767 2004 115,577 100,546 53,477 519 N/A 270,119 2005 128,393 110,522 58,445 643 N/A 298,003 2006 140,582 122,914 62,308 702 N/A 326,506 2007 148,295 128,903 65,712 792 N/A 343,703 2008 155,433 138,469 68,920 827 N/A 363,650 2009 157,008 132,940 62,504 828 N/A 353,280 2010 166,782 135,559 65,750 815 N/A 368,906 2011 166,714 135,926 67,606 803 N/A 371,049 2012 163,280 133,898 65,761 747 N/A 363,687

362

SAS Output  

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

U.S. Metallurgical Coal Exports" U.S. Metallurgical Coal Exports" "(short tons)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",1503162,764701,1411897,2267863,2261900,0.3 " Canada*",975783,343309,1260473,1319092,1895263,-30.4 " Dominican Republic",94,51064,"-",51158,"-","-" " Mexico",527285,370328,151424,897613,366637,144.8 "South America Total",2091488,2561772,2389018,4653260,4543747,2.4 " Argentina",104745,155806,203569,260551,253841,2.6 " Brazil",1921144,2352098,2185449,4273242,4022618,6.2

363

SAS Output  

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

1. Average Price of Coal Receipts at Commercial and Institutional Users by Census Division and State" 1. Average Price of Coal Receipts at Commercial and Institutional Users by Census Division and State" "(dollars per short ton)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "Middle Atlantic",139.64,145,158.61,143.29,158.91,-9.8 " Pennsylvania",139.64,145,158.61,143.29,158.91,-9.8 "East North Central",87.62,97.3,87.11,93.56,95.13,-1.7 " Illinois",59.27,60.3,62.17,59.86,66.69,-10.2 " Indiana","w","w","w","w","w","w" " Michigan","w","w","w","w","w","w"

364

SAS Output  

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

Average Price of Coal Receipts at Other Industrial Plants by Census Division and State" Average Price of Coal Receipts at Other Industrial Plants by Census Division and State" "(dollars per short ton)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "New England","w","w","w","w","w","w" " Maine","w","w","w","w","w","w" " Massachusetts","w","w","w","w","w","w" "Middle Atlantic",87.05,93.03,93.73,89.93,95.68,-6 " New York",102.14,105.8,117.15,103.8,117.61,-11.7

365

SAS Output  

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

8. Coal Stocks at Coke Plants by Census Division" 8. Coal Stocks at Coke Plants by Census Division" "(thousand short tons)" "Census Division","June 30 2013","March 31 2013","June 30 2012","Percent Change" ,,,,"(June 30)" ,,,,"2013 versus 2012" "Middle Atlantic","w","w","w","w" "East North Central",1313,1177,1326,-1 "South Atlantic","w","w","w","w" "East South Central","w","w","w","w" "U.S. Total",2500,2207,2295,8.9 "w = Data withheld to avoid disclosure." "Note: Total may not equal sum of components because of independent rounding."

366

SAS Output  

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

7 Receipts, Average Cost, and Quality of Fossil Fuels: Independent Power Producers, 2002 - 2012 7 Receipts, Average Cost, and Quality of Fossil Fuels: Independent Power Producers, 2002 - 2012 Coal Petroleum Liquids Receipts Average Cost Receipts Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMBtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Barrels) (Dollars per MMBtu) (Dollars per Barrel) Average Sulfur Percent by Weight Percentage of Consumption Annual Totals 2002 3,710,847 182,482 1.37 27.96 1.15 87.0 186,271 30,043 4.19 25.98 0.61 76.4 2003 4,365,996 223,984 1.34 26.20 1.15 90.4 347,546 56,138 5.41 33.50 0.58 89.7 2004 4,410,775 227,700 1.41 27.27 1.13 93.3 337,011 54,152 5.35 33.31 0.61 93.6 2005 4,459,333 229,071 1.56 30.39 1.10 83.0 381,871 61,753 8.30 51.34 0.54 97.2

367

SAS Output  

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

Metallurgical Coal Exports by Customs District" Metallurgical Coal Exports by Customs District" "(short tons)" ,,,,"Year to Date" "Customs District","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "Eastern Total",11716074,14136513,15167377,25852587,27578514,-6.3 " Baltimore, MD",2736470,4225450,5123600,6961920,9037970,-23 " Boston, MA","-","-","-","-",28873,"-" " Buffalo, NY",247714,121347,524040,369061,725698,-49.1 " Norfolk, VA",8730257,9784866,9519119,18515123,17784479,4.1 " Ogdensburg, NY",1633,4850,618,6483,1494,333.9 "Southern Total",3551564,3824484,4264938,7376048,8976503,-17.8

368

SAS Output  

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

3 Stocks of Coal, Petroleum Liquids, and Petroleum Coke: 3 Stocks of Coal, Petroleum Liquids, and Petroleum Coke: Electric Power Sector, by Census Divison, 2012 and 2011 Electric Power Sector Electric Utilities Independent Power Producers Census Division December 2012 December 2011 Percentage Change December 2012 December 2011 December 2012 December 2011 Coal (Thousand Tons) New England 1,030 1,389 -25.9% W W W W Middle Atlantic 7,553 7,800 -3.2% W W W W East North Central 36,139 37,262 -3.0% 27,069 27,316 9,070 9,946 West North Central 30,554 28,544 7.0% 30,554 28,544 0 0 South Atlantic 38,859 36,920 5.3% 35,527 33,163 3,331 3,757 East South Central 19,657 17,185 14.4% 19,657 17,185 0 0 West South Central 28,807 22,910 25.7% 17,047 15,125 11,760 7,785

369

SAS Output  

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

D. Coal: Consumption for Electricity Generation, D. Coal: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 19,996,890 15,517,857 4,215,043 9,168 254,821 2003 20,366,879 15,391,188 4,745,545 13,080 217,066 2004 20,375,751 15,610,335 4,606,584 8,251 150,581 2005 20,801,716 15,397,688 5,250,824 8,314 144,889 2006 20,527,410 15,211,077 5,166,001 7,526 142,807 2007 20,841,871 15,436,110 5,287,202 7,833 110,727 2008 20,548,610 15,189,050 5,242,194 8,070 109,296 2009 18,240,611 13,744,178 4,390,596 7,007 98,829 2010 19,196,315 14,333,496 4,709,686 6,815 146,318 2011 18,074,298 13,551,416 4,399,144 7,263 116,475

370

SAS Output  

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

A. Net Generation by Energy Source: Electric Utilities, 2002 - 2012 A. Net Generation by Energy Source: Electric Utilities, 2002 - 2012 (Thousand Megawatthours) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Nuclear Hydroelectric Conventional Renewable Sources Excluding Hydroelectric Hydroelectric Pumped Storage Other Total Annual Totals 2002 1,514,670 52,838 6,286 229,639 206 507,380 242,302 3,089 -7,434 480 2,549,457 2003 1,500,281 62,774 7,156 186,967 243 458,829 249,622 3,421 -7,532 519 2,462,281 2004 1,513,641 62,196 11,498 199,662 374 475,682 245,546 3,692 -7,526 467 2,505,231 2005 1,484,855 58,572 11,150 238,204 10 436,296 245,553 4,945 -5,383 643 2,474,846 2006 1,471,421 31,269 9,634 282,088 30 425,341 261,864 6,588 -5,281 700 2,483,656

371

SAS Output  

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

10.6. Advanced Metering Count by Technology Type, 10.6. Advanced Metering Count by Technology Type, 2007 through 2012 Year Residential Commercial Industrial Transportation Total Automated Meter Reading (AMR) 2007 25,785,782 2,322,329 44,015 109 28,152,235 2008 36,425,943 3,529,985 77,122 13 40,033,063 2009 41,462,111 4,239,531 107,033 11 45,808,686 2010 43,913,225 4,611,877 159,315 626 48,685,043 2011 41,451,888 4,341,105 172,692 77 45,965,762 2012 43,455,437 4,691,018 185,862 125 48,330,822 Advanced Metering Infrastructure (AMI) 2007 2,202,222 262,159 9,106 2 2,473,489 2008 4,190,244 444,003 12,757 12 4,647,016 2009 8,712,297 876,419 22,675 10 9,611,401 2010 18,369,908 1,904,983 59,567 67 20,334,525 2011 33,453,548 3,682,159 154,659 7 37,290,373

372

SAS Output  

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

0. Net Metering Customers and Capacity by Technology Type, by End Use Sector, 0. Net Metering Customers and Capacity by Technology Type, by End Use Sector, 2003 through 2012 Capacity (MW) Customers Year Residential Commercial Industrial Transportation Total Residential Commercial Industrial Transportation Total Historical Data 2003 N/A N/A N/A N/A N/A 5,870 775 168 -- 6,813 2004 N/A N/A N/A N/A N/A 14,114 1,494 215 3 15,826 2005 N/A N/A N/A N/A N/A 19,244 1,565 337 -- 21,146 2006 N/A N/A N/A N/A N/A 30,689 2,553 376 -- 33,618 2007 N/A N/A N/A N/A N/A 44,450 3,513 391 -- 48,354 2008 N/A N/A N/A N/A N/A 64,400 5,305 304 -- 70,009 2009 N/A N/A N/A N/A N/A 88,205 7,365 919 -- 96,489 Photovoltaic 2010 697.890 517.861 243.051 -- 1,458.802 137,618 11,897 1,225 -- 150,740

373

SAS Output  

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

2. Summary Statistics for the United States, 2002 - 2012 2. Summary Statistics for the United States, 2002 - 2012 (From Table 2.1.) Number of Ultimate Customers Year Residential Commercial Industrial Transportation Other Total 2002 116,622,037 15,333,700 601,744 N/A 1,066,554 133,624,035 2003 117,280,481 16,549,519 713,221 1,127 N/A 134,544,348 2004 118,763,768 16,606,783 747,600 1,025 N/A 136,119,176 2005 120,760,839 16,871,940 733,862 518 N/A 138,367,159 2006 122,471,071 17,172,499 759,604 791 N/A 140,403,965 2007 123,949,916 17,377,219 793,767 750 N/A 142,121,652 2008 124,937,469 17,562,726 774,713 727 N/A 143,275,635 2009 125,177,175 17,561,661 757,519 705 N/A 143,497,060 2010 125,717,935 17,674,338 747,746 239 N/A 144,140,258 2011 126,143,072 17,638,062 727,920 92 N/A 144,509,146

374

SAS Output  

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

Coal Disposition by State, 2012" Coal Disposition by State, 2012" "(thousand short tons)" "Coal-Producing State","Open Market Sales1","Captive Sales / Transactions2","Exports3","Total" "Alabama",8688,"-",10333,19021 "Alaska","w","-",968,"w" "Arizona","w","-","-","w" "Arkansas","w","-","-","w" "Colorado",20836,4552,3468,28856 "Illinois",29252,5113,12341,46705 "Indiana",17127,18404,375,35906 "Kentucky Total",76602,6884,5668,89154 " Kentucky (East)",37324,6884,3588,47796 " Kentucky (West)",39277,"-",2081,41358

375

SAS Output  

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

A. Natural Gas: Consumption for Electricity Generation, A. Natural Gas: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Million Cubic Feet) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 6,126,062 2,259,684 3,148,595 32,545 685,239 2003 5,616,135 1,763,764 3,145,485 38,480 668,407 2004 5,674,580 1,809,443 3,265,896 32,839 566,401 2005 6,036,370 2,134,859 3,349,921 33,785 517,805 2006 6,461,615 2,478,396 3,412,826 34,623 535,770 2007 7,089,342 2,736,418 3,765,194 34,087 553,643 2008 6,895,843 2,730,134 3,612,197 33,403 520,109 2009 7,121,069 2,911,279 3,655,712 34,279 519,799 2010 7,680,185 3,290,993 3,794,423 39,462 555,307 2011 7,883,865 3,446,087 3,819,107 47,170 571,501

376

SAS Output  

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

2. Consumption of Nautral Gas for Electricity Generation by State, by Sector, 2. Consumption of Nautral Gas for Electricity Generation by State, by Sector, 2012 and 2011 (Million Cubic Feet) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 460,887 461,590 -0.2% 3,652 4,218 428,781 432,350 8,630 6,287 19,824 18,735 Connecticut 120,380 110,546 8.9% 69 730 113,620 105,965 3,952 2,061 2,739 1,790 Maine 44,424 49,352 -10% 0 0 28,456 33,555 307 12 15,662 15,785 Massachusetts 184,330 190,063 -3.0% 2,792 2,393 176,497 182,865 3,749 3,761 1,293 1,045 New Hampshire 50,678 46,927 8.0% 754 1,046 49,655 45,765 139 0 131 115

377

SAS Output  

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

D. Other Waste Biomass: Consumption for Electricity Generation, D. Other Waste Biomass: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 34,775 2,456 15,859 4,566 11,894 2004 19,215 2,014 9,240 4,308 3,654 2005 17,852 2,485 7,365 4,677 3,325 2006 17,727 2,611 7,788 4,436 2,893 2007 19,083 2,992 8,861 4,049 3,181 2008 24,288 3,409 12,745 3,684 4,450 2009 24,847 3,679 13,231 3,760 4,177 2010 29,996 3,668 14,449 3,790 8,090 2011 30,771 4,488 16,115 3,816 6,352 2012 30,342 4,191 15,740 4,016 6,395 2010 January 2,223 189 1,078 321 635 February 2,336 275 1,208 291 561 March 2,287 311 1,079 302 594

378

SAS Output  

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

1. U.S. Coal Summary Statistics, 2007 - 2013" 1. U.S. Coal Summary Statistics, 2007 - 2013" "(thousand short tons)" "Year and","Production1","Imports","Waste Coal","Producer and","Consumption","Exports","Consumer","Losses and" "Quarter",,,"Supplied","Distributor",,,"Stocks2","Unaccounted" ,,,,"Stocks2",,,,"For3" 2007 " January - March",286041,8786,3264,34007,278727,11139,149588 " April - June",285687,8405,3387,32484,267106,14702,162849 " July - September",286035,10559,3697,30090,303665,16198,150448 " October - December",288872,8597,3727,33977,278500,17124,158781 " Total",1146635,36347,14076,,1127998,59163,,4085

379

SAS Output  

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

1. Receipts, Average Cost, and Quality of Fossil Fuels: Industrial Sector, 2002 - 2012 1. Receipts, Average Cost, and Quality of Fossil Fuels: Industrial Sector, 2002 - 2012 Coal Petroleum Liquids Receipts Average Cost Receipts Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMBtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Barrels) (Dollars per MMBtu) (Dollars per Barrel) Average Sulfur Percent by Weight Percentage of Consumption Annual Totals 2002 294,234 13,659 1.45 31.29 1.56 52.1 29,137 4,638 3.55 22.33 1.24 26.5 2003 322,547 15,076 1.45 31.01 1.37 60.7 27,538 4,624 4.85 28.86 1.25 23.2 2004 326,495 15,324 1.63 34.79 1.43 57.6 25,491 4,107 4.98 30.93 1.38 18.5 2005 339,968 16,011 1.94 41.17 1.42 61.9 36,383 5,876 6.64 41.13 1.36 26.4

380

SAS Output  

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

2. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: Electric Utilties by State, 2012 2. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: Electric Utilties by State, 2012 Bituminous Subbituminous Lignite Census Division and State Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight New England 353 2.20 7.7 0 -- -- 0 -- -- Connecticut 0 -- -- 0 -- -- 0 -- -- Maine 0 -- -- 0 -- -- 0 -- -- Massachusetts 0 -- -- 0 -- -- 0 -- -- New Hampshire 353 2.20 7.7 0 -- -- 0 -- -- Rhode Island 0 -- -- 0 -- -- 0 -- -- Vermont 0 -- -- 0 -- -- 0 -- --

Note: This page contains sample records for the topic "model output location" 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

SAS Output  

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

Productive Capacity and Capacity Utilization of Underground Coal Mines by State and Mining Method, 2012" Productive Capacity and Capacity Utilization of Underground Coal Mines by State and Mining Method, 2012" "(thousand short tons)" ,"Continuous1",,"Conventional and Other2",,"Longwall3",,"Total" "Coal-Producing","Productive","Capacity","Productive","Capacity","Productive","Capacity","Productive","Capacity" "State","Capacity","Utilization","Capacity","Utilization","Capacity","Utilization","Capacity","Utilization" ,,"Percent",,"Percent",,"Percent",,"Percent" "Alabama","w","w","-","-","w","w",14594,85.99

382

SAS Output  

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

6. Receipts of Natural Gas Delivered for Electricity Generation by State, 2012 and 2011 6. Receipts of Natural Gas Delivered for Electricity Generation by State, 2012 and 2011 (Million Cubic Feet) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 440,421 484,260 -9.1% 3,652 4,226 419,062 434,504 3,636 13,156 14,072 32,373 Connecticut 112,084 116,563 -3.8% 71 738 112,012 107,121 0 3,210 0 5,494 Maine 42,374 56,230 -25% 0 0 28,302 33,578 0 NM 14,072 22,639 Massachusetts 175,314 198,295 -12% 2,789 2,393 168,890 184,156 3,636 7,872 0 3,875 New Hampshire 50,408 47,137 6.9% 754 1,046 49,655 45,725 0 0 0 NM

383

SAS Output  

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

A. U.S. Transmission Circuit Sustained Automatic Outage Counts and Hours by Cause Code and by NERC Region, 2012 A. U.S. Transmission Circuit Sustained Automatic Outage Counts and Hours by Cause Code and by NERC Region, 2012 AC & DC Circuit Outage Counts Sustained Outage Causes FRCC MRO NPCC RFC SERC SPP TRE WECC Contiguous U.S. Weather, excluding lightning 6.00 27.00 3.00 30.00 63.00 12.00 -- 69.00 210.00 Lightning 5.00 10.00 8.00 5.00 31.00 16.00 13.00 57.00 145.00 Environmental -- 1.00 1.00 5.00 -- 1.00 -- -- 8.00 Contamination 14.00 -- -- -- 22.00 3.00 6.00 7.00 52.00 Foreign Interference 34.00 3.00 -- 4.00 13.00 1.00 2.00 14.00 71.00 Fire -- 2.00 -- 1.00 6.00 3.00 1.00 85.00 98.00 Vandalism, Terrorism, or Malicious Acts -- -- -- -- 2.00 -- -- 1.00 3.00 Failed AC Substation Equipment 18.00 16.00 35.00 63.00 57.00 16.00 15.00 65.00 285.00

384

SAS Output  

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

B. Winter Net Internal Demand, Capacity Resources, and Capacity Margins B. Winter Net Internal Demand, Capacity Resources, and Capacity Margins by North American Electric Reliability Corporation Assessment Area, 2012 Actual, 2013-2017 Projected Net Internal Demand (Megawatts) -- Winter Eastern Interconnection ERCOT Western Interconnection All Interconnections Period FRCC NPCC Balance of Eastern Region MAPP MISO PJM SERC SPP TRE WECC Contiguous U.S. Actual 2012 / 2013 36,409 45,545 386,359 4,925 74,430 122,566 149,359 35,079 46,909 101,706 616,927 Projected 2013 / 2014 43,384 46,008 399,149 5,385 75,320 132,229 145,657 40,558 51,435 107,341 647,317 Projected 2014 / 2015 44,060 46,090 403,883 5,500 76,252 134,742 146,130 41,259 53,742 109,418 657,192 Projected 2015 / 2016 44,596 46,184 408,927 5,563 77,058 137,338 147,201 41,767 55,346 110,814 665,866

385

SAS Output  

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

B. Noncoincident Peak Load by North American Electric Reliability Corporation Assessment Area, B. Noncoincident Peak Load by North American Electric Reliability Corporation Assessment Area, 2012 Actual, 2013-2017 Projected Summer Peak Load (Megawatts) Eastern Interconnection ERCOT Western Interconnection All Interconnections Period FRCC NPCC Balance of Eastern Region MAPP MISO PJM SERC SPP TRE WECC Contiguous U.S. Actual 2012 44,338 58,319 468,092 5,051 96,769 154,339 161,687 50,246 66,548 130,465 767,762 Projected 2013 45,668 59,969 469,857 5,109 96,192 155,553 159,032 53,971 67,998 133,523 777,015 Projected 2014 46,338 60,654 475,005 5,249 96,879 158,717 159,457 54,703 69,289 132,731 784,017 Projected 2015 47,053 61,428 484,637 5,360 97,565 162,216 164,150 55,346 71,423 134,183 798,724

386

SAS Output  

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

3. Coal Mining Productivity by State, Mine Type, and Mine Production Range, 2012" 3. Coal Mining Productivity by State, Mine Type, and Mine Production Range, 2012" "(short tons produced per employee hour)" ,"Mine Production Range (thousand short tons)" "Coal-Producing State, Region1","Above 1,000","Above 500","Above 200","Above 100","Above 50","Above 10","10 or Under","Total2" "and Mine Type",,"to 1,000","to 500","to 200","to 100","to 50" "Alabama",1.69,2.5,1.95,1.72,1.83,0.69,0.55,1.68 " Underground",1.73,"-","-","-",1.08,0.31,"-",1.64 " Surface",1.36,2.5,1.95,1.72,2.11,1.19,0.55,1.75

387

SAS Output  

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

9. Average Cost of Petroleum Coke Delivered for Electricity Generation by State, 2012 and 2011 9. Average Cost of Petroleum Coke Delivered for Electricity Generation by State, 2012 and 2011 (Dollars per MMBtu) Census Division and State Electric Power Sector Electric Utilities Independent Power Producers Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 New England -- -- -- -- -- -- -- Connecticut -- -- -- -- -- -- -- Maine -- -- -- -- -- -- -- Massachusetts -- -- -- -- -- -- -- New Hampshire -- -- -- -- -- -- -- Rhode Island -- -- -- -- -- -- -- Vermont -- -- -- -- -- -- -- Middle Atlantic -- W W -- -- -- W New Jersey -- -- -- -- -- -- -- New York -- W W -- -- -- W Pennsylvania -- -- -- -- -- -- -- East North Central W W W 4.10 4.01 W W

388

SAS Output  

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

5. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: 5. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: Industrial Sector by State, 2012 Bituminous Subbituminous Lignite Census Division and State Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight New England 19 0.66 6.9 0 -- -- 0 -- -- Connecticut 0 -- -- 0 -- -- 0 -- -- Maine 19 0.66 6.9 0 -- -- 0 -- -- Massachusetts 0 -- -- 0 -- -- 0 -- -- New Hampshire 0 -- -- 0 -- -- 0 -- -- Rhode Island 0 -- -- 0 -- -- 0 -- -- Vermont 0 -- -- 0 -- -- 0 -- --

389

SAS Output  

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

B. Existing Net Summer Capacity of Other Renewable Sources by Producer Type, 2002 through 2012 (Megawatts) B. Existing Net Summer Capacity of Other Renewable Sources by Producer Type, 2002 through 2012 (Megawatts) Year Wind Solar Thermal and Photovoltaic Wood and Wood-Derived Fuels Geothermal Other Biomass Total (Other Renewable Sources) Total (All Sectors) 2002 4,417 397 5,844 2,252 3,800 16,710 2003 5,995 397 5,871 2,133 3,758 18,153 2004 6,456 398 6,182 2,152 3,529 18,717 2005 8,706 411 6,193 2,285 3,609 21,205 2006 11,329 411 6,372 2,274 3,727 24,113 2007 16,515 502 6,704 2,214 4,134 30,069 2008 24,651 536 6,864 2,229 4,186 38,466 2009 34,296 619 6,939 2,382 4,317 48,552 2010 39,135 866 7,037 2,405 4,369 53,811 2011 45,676 1,524 7,077 2,409 4,536 61,221 2012 59,075 3,170 7,508 2,592 4,811 77,155

390

SAS Output  

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

Recoverable Coal Reserves and Average Recovery Percentage at Producing Underground Coal Mines by State and Mining Method, 2012" Recoverable Coal Reserves and Average Recovery Percentage at Producing Underground Coal Mines by State and Mining Method, 2012" "(million short tons)" ,"Continuous1",,"Conventional and Other2",,"Longwall3",,"Total" "Coal-Producing","Recoverable","Average Recovery","Recoverable","Average Recovery","Recoverable","Average Recovery","Recoverable","Average Recovery" "State","Coal Reserves","Percentage","Coal Reserves","Percentage","Coal Reserves","Percentage","Coal Reserves","Percentage" ,"at Producing",,"at Producing",,"at Producing",,"at Producing"

391

SAS Output  

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

A. U.S. Transmission Circuit Outages by Type and NERC region, 2012 A. U.S. Transmission Circuit Outages by Type and NERC region, 2012 Outage Type FRCC MRO NPCC RFC SERC SPP TRE WECC Contiguous U.S. Circuit Outage Counts Automatic Outages (Sustained) 151.00 163.00 127.00 272.00 374.00 105.00 80.00 796.00 2,068.00 Non-Automatic Outages (Operational) 77.00 44.00 97.00 230.00 192.00 27.00 45.00 337.00 1,049.00 Non-Automatic Outages (Planned) 2,650.00 453.00 512.00 2,050.00 2,450.00 369.00 472.00 2,744.00 11,700.00 Circuit Outage Hours Automatic Outages (Sustained) 2,852.28 1,312.97 14,244.87 19,857.23 7,123.70 1,509.51 682.60 24,238.64 71,821.80 Non-Automatic Outages (Operational) 186.87 27.08 67.68 186.08 426.59 3.32 13.96 67.59 979.17 Non-Automatic Outages (Planned) 872.65 710.33 1,222.36 1,095.46 503.01 357.44 105.06 1,105.43 5,971.74

392

SAS Output  

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

A. Biogenic Municipal Solid Waste: Consumption for Electricity Generation, A. Biogenic Municipal Solid Waste: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 21,196 695 18,300 2,087 115 2004 19,587 444 17,308 1,811 24 2005 19,370 560 17,033 1,753 25 2006 19,629 500 17,343 1,761 25 2007 19,576 553 17,116 1,785 122 2008 19,805 509 17,487 1,809 0 2009 19,669 465 17,048 2,155 0 2010 19,437 402 16,802 2,233 0 2011 16,972 388 14,625 1,955 4 2012 16,968 418 14,235 2,304 12 2010 January 1,546 30 1,332 184 0 February 1,384 25 1,215 144 0 March 1,650 36 1,434 180 0 April 1,655 33 1,426 196 0

393

SAS Output  

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

3. Consumption of Landfill Gas for Electricity Generation by State, by Sector, 3. Consumption of Landfill Gas for Electricity Generation by State, by Sector, 2012 and 2011 (Million Cubic Feet) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 9,595 9,945 -3.5% 0 0 9,074 9,945 520 0 0 0 Connecticut 595 624 -4.6% 0 0 595 624 0 0 0 0 Maine 518 524 -1.0% 0 0 518 524 0 0 0 0 Massachusetts 3,603 3,623 -0.6% 0 0 3,603 3,623 0 0 0 0 New Hampshire 1,790 1,485 21% 0 0 1,270 1,485 520 0 0 0 Rhode Island 2,409 3,037 -21% 0 0 2,409 3,037 0 0 0 0

394

SAS Output  

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

4. Average Price of Coal Delivered to End Use Sector by Census Division and State, 2012 and 2011" 4. Average Price of Coal Delivered to End Use Sector by Census Division and State, 2012 and 2011" "(dollars per short ton)" ,2012,,,,2011,,,,"Annual Percent Change" "Census Division","Electric","Other","Coke","Commercial","Electric","Other","Coke","Commercial","Electric","Other","Coke","Commercial" "and State","Power1","Industrial",,"and","Power1","Industrial",,"and","Power1","Industrial",,"and" ,,,,"Institutional",,,,"Institutional",,,,"Institutional" "New England",88.32,165.17,"-","-",87.62,"w","-","-",0.8,"w","-","-"

395

SAS Output  

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

U.S. Coal Consumption by End-Use Sector, 2007 - 2013" U.S. Coal Consumption by End-Use Sector, 2007 - 2013" "(thousand short tons)" ,,,"Other Industrial",,,"Commercial and Institutional" "Year and","Electric","Coke","CHP2","Non-","Total","CHP4","Non-","Total","Total" "Quarter","Power","Plants",,"CHP3",,,"CHP5" ,"Sector1" 2007 " January - March",257516,5576,5834,8743,14578,547,510,1058,278727 " April - June",246591,5736,5552,8521,14074,426,279,705,267106 " July - September",283556,5678,5546,8180,13725,458,247,705,303665 " October - December",257478,5726,5605,8634,14238,495,563,1058,278500

396

SAS Output  

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

9. Average Price of U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code" 9. Average Price of U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code" "(dollars per short ton)" ,,,,"Year to Date" "NAICS Code","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "311 Food Manufacturing",51.17,49.59,50.96,50.35,50.94,-1.2 "312 Beverage and Tobacco Product Mfg.",111.56,115.95,113.47,113.49,117.55,-3.5 "313 Textile Mills",115.95,118.96,127.41,117.4,128.07,-8.3 "315 Apparel Manufacturing","w","w","w","w","w","w" "321 Wood Product Manufacturing","w","w","w","w","w","w"

397

SAS Output  

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

A. Landfill Gas: Consumption for Electricity Generation, A. Landfill Gas: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Million Cubic Feet) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 136,421 9,168 121,984 3,280 1,989 2004 143,844 11,250 125,848 4,081 2,665 2005 141,899 11,490 123,064 4,797 2,548 2006 160,033 16,617 136,108 6,644 664 2007 166,774 17,442 144,104 4,598 630 2008 195,777 20,465 169,547 5,235 530 2009 206,792 19,583 180,689 5,931 589 2010 218,331 19,975 192,428 5,535 393 2011 232,795 22,086 180,856 29,469 384 2012 256,376 25,193 201,965 26,672 2,545 2010 January 17,531 1,715 15,323 461 32 February 16,189 1,653 14,120 384 33

398

SAS Output  

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

. Receipts, Average Cost, and Quality of Fossil Fuels for the Electric Power Industry, 2002 through 2012 . Receipts, Average Cost, and Quality of Fossil Fuels for the Electric Power Industry, 2002 through 2012 Coal Petroleum Natural Gas All Fossil Fuels Average Cost Average Cost Average Cost Average Cost Period Receipts (Thousand Tons) Average Sulfur Percent by Weight (Dollars per MMBtu) (Dollars per Ton) Receipts (Thousand Barrels) Average Sulfur Percent by Weight (Dollars per MMBtu) (Dollars per Barrel) Receipts (Thousand Mcf) (Dollars per MMBtu) (Dollars per MMBtu) 2002 884,287 0.94 1.25 25.52 120,851 1.64 3.34 20.77 5,607,737 3.56 1.86 2003 986,026 0.97 1.28 26.00 185,567 1.53 4.33 26.78 5,500,704 5.39 2.28 2004 1,002,032 0.97 1.36 27.42 186,655 1.66 4.29 26.56 5,734,054 5.96 2.48 2005 1,021,437 0.98 1.54 31.20 194,733 1.61 6.44 39.65 6,181,717 8.21 3.25

399

SAS Output  

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

9. Receipts, Average Cost, and Quality of Fossil Fuels: Commercial Sector, 2002 - 2012 9. Receipts, Average Cost, and Quality of Fossil Fuels: Commercial Sector, 2002 - 2012 Coal Petroleum Liquids Receipts Average Cost Receipts Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMBtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Barrels) (Dollars per MMBtu) (Dollars per Barrel) Average Sulfur Percent by Weight Percentage of Consumption Annual Totals 2002 9,580 399 2.10 50.44 2.59 28.4 503 91 5.38 29.73 0.02 7.5 2003 8,835 372 1.99 47.24 2.43 20.5 248 43 7.00 40.82 0.04 3.1 2004 10,682 451 2.08 49.32 2.48 23.5 3,066 527 6.19 35.96 0.20 26.9 2005 11,081 464 2.57 61.21 2.43 24.2 1,684 289 8.28 48.22 0.17 18.3 2006 12,207 518 2.63 61.95 2.51 27.5 798 137 13.50 78.70 0.17 15.5

400

SAS Output  

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

Coke and Breeze Production at Coke Plants" Coke and Breeze Production at Coke Plants" "(thousand short tons)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "Middle Atlantic","w","w","w","w","w","w" "East North Central",2303,2314,2365,4617,4754,-2.9 "South Atlantic","w","w","w","w","w","w" "East South Central","w","w","w","w","w","w" "U.S. Total",4152,4098,4104,8249,8233,0.2 "Coke Total",3954,3841,3863,7795,7721,1

Note: This page contains sample records for the topic "model output location" 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

SAS Output  

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

2. Electric Power Industry - Electricity Sales for Resale, 2. Electric Power Industry - Electricity Sales for Resale, 2002 through 2012 (Thousand Megawatthours) Year Electric Utilities Energy-Only Providers Independent Power Producers Combined Heat and Power U.S. Total 2002 1,838,901 5,757,283 943,531 28,963 8,568,678 2003 1,824,030 3,906,220 1,156,796 33,909 6,920,954 2004 1,923,440 3,756,175 1,053,364 25,996 6,758,975 2005 1,925,710 2,867,048 1,252,796 26,105 6,071,659 2006 1,698,389 2,446,104 1,321,342 27,638 5,493,473 2007 1,603,179 2,476,740 1,368,310 31,165 5,479,394 2008 1,576,976 2,718,661 1,355,017 30,079 5,680,733 2009 1,495,636 2,240,399 1,295,857 33,139 5,065,031 2010 1,541,554 2,946,452 1,404,137 37,068 5,929,211 2011 1,529,434 2,206,981 1,372,306 34,400 5,143,121

402

SAS Output  

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

2. Fuel-Switching Capacity of Operable Generators Reporting Petroleum Liquids as the Primary Fuel, 2. Fuel-Switching Capacity of Operable Generators Reporting Petroleum Liquids as the Primary Fuel, by Producer Type, 2012 (Megawatts, Percent) Fuel-Switchable Part of Total Producer Type Total Net Summer Capacity of All Generators Reporting Petroleum as the Primary Fuel Net Summer Capacity of Petroleum-Fired Generators Reporting the Ability to Switch to Natural Gas Fuel Switchable Capacity as Percent of Total Maximum Achievable Net Summer Capacity Using Natural Gas Electric Utilities 26,732 7,640 28.6 7,224 Independent Power Producers, Non-Combined Heat and Power Plants 18,644 7,867 42.2 6,628 Independent Power Producers, Combined Heat and Power Plants 317 -- -- -- Electric Power Sector Subtotal 45,693 15,507 33.9 13,852 Commercial Sector 443 21 4.8 21

403

SAS Output  

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

A. Petroleum Coke: Consumption for Electricity Generation, A. Petroleum Coke: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 6,836 2,125 3,580 2 1,130 2003 6,303 2,554 3,166 2 582 2004 7,677 4,150 2,985 1 541 2005 8,330 4,130 3,746 1 452 2006 7,363 3,619 3,286 1 456 2007 6,036 2,808 2,715 2 512 2008 5,417 2,296 2,704 1 416 2009 4,821 2,761 1,724 1 335 2010 4,994 3,325 1,354 2 313 2011 5,012 3,449 1,277 1 286 2012 3,675 2,105 756 1 812 2010 January 433 283 121 0.17 29 February 404 258 120 0.15 25 March 438 308 108 0.19 23 April 382 253 107 0.12 22 May 415 261 129 0 25

404

SAS Output  

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

5. Retail Sales of Electricity to Ultimate Customers: 5. Retail Sales of Electricity to Ultimate Customers: Total by End-Use Sector, 2003 - December 2012 (Million Kilowatthours) Period Residential Commercial Industrial Transportation All Sectors Annual Totals 2003 1,275,824 1,198,728 1,012,373 6,810 3,493,734 2004 1,291,982 1,230,425 1,017,850 7,224 3,547,479 2005 1,359,227 1,275,079 1,019,156 7,506 3,660,969 2006 1,351,520 1,299,744 1,011,298 7,358 3,669,919 2007 1,392,241 1,336,315 1,027,832 8,173 3,764,561 2008 1,379,981 1,335,981 1,009,300 7,700 3,732,962 2009 1,364,474 1,307,168 917,442 7,781 3,596,865 2010 1,445,708 1,330,199 970,873 7,712 3,754,493 2011 1,422,801 1,328,057 991,316 7,672 3,749,846 2012 1,374,515 1,327,101 985,714 7,320 3,694,650 2010

405

SAS Output  

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

3. Coal Carbonized at Coke Plants by Census Division" 3. Coal Carbonized at Coke Plants by Census Division" "(thousand short tons)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "Middle Atlantic","w","w","w","w","w","w" "East North Central",3051,2997,3092,6048,6156,-1.8 "South Atlantic","w","w","w","w","w","w" "East South Central","w","w","w","w","w","w" "U.S. Total",5471,5280,5296,10751,10579,1.6 "w = Data withheld to avoid disclosure."

406

SAS Output  

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

4. Consumption of Biogenic Municipal Solid Waste for Electricity Generation by State, by Sector, 4. Consumption of Biogenic Municipal Solid Waste for Electricity Generation by State, by Sector, 2012 and 2011 (Thousand Tons) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 4,041 4,122 -2.0% 0 0 3,838 3,922 203 200 0 0 Connecticut 1,415 1,442 -1.9% 0 0 1,415 1,442 0 0 0 0 Maine 440 445 -1.3% 0 0 237 246 203 200 0 0 Massachusetts 2,017 2,063 -2.2% 0 0 2,017 2,063 0 0 0 0 New Hampshire 169 172 -2.0% 0 0 169 172 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0

407

SAS Output  

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

A. Summer Net Internal Demand, Capacity Resources, and Capacity Margins by North American Electric Reliability Assessment Area, A. Summer Net Internal Demand, Capacity Resources, and Capacity Margins by North American Electric Reliability Assessment Area, 2002 - 2012, Actual Net Internal Demand (Megawatts) -- Summer Eastern Interconnection ERCOT Western Interconnection All Interconnections Period FRCC NPCC Balance of Eastern Region ECAR MAAC MAIN MAPP MISO MRO PJM RFC SERC SPP TRE WECC Contiguous U.S. 2002 37,951 55,164 430,396 101,251 54,296 53,267 -- -- 28,825 -- -- 154,459 38,298 55,833 117,032 696,376 2003 40,387 53,936 422,253 98,487 53,566 53,617 -- -- 28,775 -- -- 148,380 39,428 59,282 120,894 696,752 2004 42,243 51,580 419,349 95,300 52,049 50,499 -- -- 29,094 -- -- 153,024 39,383 58,531 121,205 692,908

408

SAS Output  

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

B. Net Generation from Renewable Sources: Industrial Sector, 2002 - 2012 B. Net Generation from Renewable Sources: Industrial Sector, 2002 - 2012 (Thousand Megawatthours) Period Wind Solar Photovoltaic Solar Thermal Wood and Wood-Derived Fuels Landfill Gas Biogenic Municipal Solid Waste Other Waste Biomass Geothermal Conventional Hydroelectric Total Renewable Sources Annual Totals 2002 0 N/A N/A 29,643 N/A N/A N/A 0 3,825 N/A 2003 0 0 0 27,988 96 36 583 0 4,222 32,926 2004 0 0 0 28,367 120 30 647 0 3,248 32,413 2005 0 0 0 28,271 113 34 585 0 3,195 32,199 2006 0 0 0 28,400 29 35 509 0 2,899 31,872 2007 0 0 0 28,287 27 40 565 0 1,590 30,509 2008 0 0 0 26,641 21 0 800 0 1,676 29,138 2009 0 0 0 25,292 22 0 718 0 1,868 27,901 2010 0 2 0 25,706 15 0 853 0 1,668 28,244

409

SAS Output  

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

6. Net Generation from Other Energy Sources 6. Net Generation from Other Energy Sources by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 2,153 2,019 6.7% 0 0 1,944 1,888 88 84 121 46 Connecticut 756 705 7.3% 0 0 756 704 0 0 0 1 Maine 424 390 8.7% 0 0 245 261 88 84 92 45 Massachusetts 906 860 5.5% 0 0 877 860 0 0 29 0 New Hampshire 66 64 2.6% 0 0 66 64 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0 Middle Atlantic 2,497 2,441 2.3% 0 0 1,924 1,975 465 344 107 122

410

SAS Output  

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

U.S. Steam Coal Exports" U.S. Steam Coal Exports" "(short tons)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",1619502,1246181,2153814,2865683,3065683,-6.5 " Canada*",797861,599752,841061,1397613,1280803,9.1 " Dominican Republic",51698,160672,124720,212370,312741,-32.1 " Honduras","-",41664,34161,41664,68124,-38.8 " Jamaica",25,36311,"-",36336,33585,8.2 " Mexico",717687,407422,1116653,1125109,1331754,-15.5 " Other**",52231,360,37219,52591,38676,36

411

SAS Output  

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

. Receipts and Quality of Coal Delivered for the Electric Power Industry, 2002 through 2012 . Receipts and Quality of Coal Delivered for the Electric Power Industry, 2002 through 2012 Bituminous Subbituminous Lignite Period Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight 2002 423,128 1.47 10.1 391,785 0.36 6.2 65,555 0.93 13.3 2003 467,286 1.50 10.0 432,513 0.38 6.4 79,869 1.03 14.4 2004 470,619 1.52 10.4 445,603 0.36 6.0 78,268 1.05 14.2 2005 480,179 1.56 10.5 456,856 0.36 6.2 77,677 1.02 14.0 2006 489,550 1.59 10.5 504,947 0.35 6.1 75,742 0.95 14.4 2007 467,817 1.62 10.3 505,155 0.34 6.0 71,930 0.90 14.0

412

SAS Output  

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

Coal Consumption at Other Industrial Plants by Census Division and State" Coal Consumption at Other Industrial Plants by Census Division and State" "(thousand short tons)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "New England","w","w",20,"w","w","w" " Maine","w","w","w","w","w","w" " Massachusetts","w","w","w","w","w","w" "Middle Atlantic",583,589,651,1171,1237,-5.3 " New York",155,181,206,337,374,-10.1

413

SAS Output  

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

D. Landfill Gas: Consumption for Electricity Generation, D. Landfill Gas: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 65,770 3,930 59,089 1,753 998 2004 69,331 5,373 60,514 2,093 1,351 2005 67,902 5,650 58,624 2,360 1,269 2006 75,970 8,287 63,950 3,388 345 2007 79,712 8,620 68,432 2,344 316 2008 94,215 10,242 81,029 2,668 276 2009 99,821 9,748 86,773 2,999 301 2010 105,835 10,029 92,763 2,837 205 2011 112,538 11,146 89,857 11,332 203 2012 124,297 12,721 99,938 10,356 1,282 2010 January 8,441 853 7,335 236 17 February 7,824 830 6,781 197 17 March 9,056 1,013 7,796 226 21

414

SAS Output  

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

D. Natural Gas: Consumption for Electricity Generation, D. Natural Gas: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 6,249,585 2,307,358 3,214,286 30,626 697,315 2003 5,735,770 1,809,003 3,200,057 39,424 687,286 2004 5,827,470 1,857,247 3,351,469 33,623 585,132 2005 6,212,116 2,198,098 3,444,875 34,645 534,498 2006 6,643,926 2,546,169 3,508,597 35,473 553,687 2007 7,287,714 2,808,500 3,872,646 34,872 571,697 2008 7,087,191 2,803,283 3,712,872 34,138 536,899 2009 7,301,522 2,981,285 3,750,080 35,046 535,111 2010 7,852,665 3,359,035 3,882,995 40,356 570,279 2011 8,052,309 3,511,732 3,906,484 48,509 585,584

415

SAS Output  

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

4. Average Price of Coal Receipts at Coke Plants by Census Division" 4. Average Price of Coal Receipts at Coke Plants by Census Division" "(dollars per short ton)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "Middle Atlantic","w","w","w","w","w","w" "East North Central",157.29,176.84,199.7,166.21,198.26,-16.2 "South Atlantic","w","w","w","w","w","w" "East South Central","w","w","w","w","w","w" "U.S. Total",157.26,171.51,191.48,163.85,190.51,-14

416

SAS Output  

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

5. Demand-Side Management Program Direct and Indirect Costs, 5. Demand-Side Management Program Direct and Indirect Costs, 2002 through 2012 (Thousand Dollars) Year Energy Efficiency Load Management Direct Cost Indirect Cost Total Cost 2002 1,032,911 410,323 1,443,234 206,169 1,649,403 2003 807,403 352,137 1,159,540 137,670 1,340,686 2004 910,816 510,281 1,421,097 132,295 1,560,578 2005 1,180,576 622,287 1,802,863 127,925 1,939,115 2006 1,270,602 663,980 1,934,582 128,886 2,072,962 2007 1,677,969 700,362 2,378,331 160,326 2,604,711 2008 2,137,452 836,359 2,973,811 181,843 3,186,742 2009 2,221,480 944,261 3,165,741 394,193 3,607,076 2010 2,906,906 1,048,356 3,955,262 275,158 4,230,420 2011 4,002,672 1,213,102 5,215,774 328,622 5,544,396 2012 4,397,635 1,270,391 5,668,026 332,440 6,000,466

417

SAS Output  

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

B. Net Generation from Renewable Sources: Electric Utilities, 2002 - 2012 B. Net Generation from Renewable Sources: Electric Utilities, 2002 - 2012 (Thousand Megawatthours) Period Wind Solar Photovoltaic Solar Thermal Wood and Wood-Derived Fuels Landfill Gas Biogenic Municipal Solid Waste Other Waste Biomass Geothermal Conventional Hydroelectric Total Renewable Sources Annual Totals 2002 213 N/A N/A 709 N/A N/A N/A 1,402 242,302 N/A 2003 354 2 0 882 394 326 214 1,249 249,622 253,043 2004 405 6 0 1,209 460 198 166 1,248 245,546 249,238 2005 1,046 16 0 1,829 503 250 175 1,126 245,553 250,499 2006 2,351 15 0.18 1,937 705 228 190 1,162 261,864 268,452 2007 4,361 10 1 2,226 751 240 226 1,139 226,734 235,687 2008 6,899 16 1 1,888 844 211 252 1,197 229,645 240,953

418

SAS Output  

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

A. Petroleum Liquids: Consumption for Electricity Generation, A. Petroleum Liquids: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Thousand Barrels) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 134,415 88,595 39,035 826 5,959 2003 175,136 105,319 61,420 882 7,514 2004 165,107 103,793 56,342 760 4,212 2005 165,137 98,223 62,154 580 4,180 2006 73,821 53,529 17,179 327 2,786 2007 82,433 56,910 22,793 250 2,480 2008 53,846 38,995 13,152 160 1,538 2009 43,562 31,847 9,880 184 1,652 2010 40,103 30,806 8,278 164 855 2011 27,326 20,844 5,633 133 716 2012 22,604 17,521 4,110 272 702 2010 January 5,587 4,381 1,083 17 106 February 2,156 1,599 454 15 88

419

SAS Output  

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

4. Average Power Plant Operating Expenses for Major U.S. Investor-Owned Electric Utilities, 2002 through 2012 (Mills per Kilowatthour) 4. Average Power Plant Operating Expenses for Major U.S. Investor-Owned Electric Utilities, 2002 through 2012 (Mills per Kilowatthour) Operation Maintenance Year Nuclear Fossil Steam Hydro-electric Gas Turbine and Small Scale Nuclear Fossil Steam Hydro-electric Gas Turbine and Small Scale 2002 9.00 2.59 3.71 3.26 5.04 2.67 2.62 2.38 2003 9.12 2.74 3.47 3.50 5.23 2.72 2.32 2.26 2004 8.97 3.13 3.83 4.27 5.38 2.96 2.76 2.14 2005 8.26 3.21 3.95 3.69 5.27 2.98 2.73 1.89 2006 9.03 3.57 3.76 3.51 5.69 3.19 2.70 2.16 2007 9.54 3.63 5.44 3.26 5.79 3.37 3.87 2.42 2008 9.89 3.72 5.78 3.77 6.20 3.59 3.89 2.72 2009 10.00 4.23 4.88 3.05 6.34 3.96 3.50 2.58 2010 10.50 4.04 5.33 2.79 6.80 3.99 3.81 2.73

420

SAS Output  

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

Price of U.S. Coal Imports" Price of U.S. Coal Imports" "(dollars per short ton)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Origin",2013,2013,2012,,,"Change" "North America Total",147.86,138.39,191.01,144.86,197.96,-26.8 " Canada",147.86,138.39,191,144.86,197.95,-26.8 " Mexico","-","-",286.23,"-",286.23,"-" "South America Total",75.29,80.74,86.52,77.2,87.17,-11.4 " Argentina","-","-",504.7,"-",504.7,"-" " Colombia",74.87,80.74,83.03,76.96,85.25,-9.7 " Peru",87.09,"-","-",87.09,"-","-"

Note: This page contains sample records for the topic "model output location" 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

SAS Output  

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

4. Fuel-Switching Capacity of Operable Generators: From Natural Gas to Petroleum Liquids, 4. Fuel-Switching Capacity of Operable Generators: From Natural Gas to Petroleum Liquids, by Year of Initial Commercial Operation, 2012 (Megawatts, Percent) Year of Initial Commercial Operation Number of Generators Net Summer Capacity Fuel Switchable Net Summer Capacity Reported to Have No Factors that Limit the Ability to Switch to Petroleum Liquids Pre-1970 318 11,735 7,535 1970-1974 376 18,210 11,033 1975-1979 105 11,031 7,283 1980-1984 46 945 211 1985-1989 107 3,155 413 1990-1994 208 11,738 1,453 1995-1999 134 9,680 2,099 2000-2004 392 39,841 5,098 2005-2009 116 14,791 2,066 2010-2012 78 8,479 320 Total 1,880 129,604 37,510 Notes: Petroleum includes distillate fuel oil (all diesel and No. 1, No. 2, and No. 4 fuel oils), residual fuel oil (No. 5 and No. 6 fuel oils and bunker C fuel oil), jet fuel, kerosene, petroleum coke (converted to liquid petroleum, see Technical Notes for conversion methodology), waste oil, and beginning in 2011, synthetic gas and propane. Prior to 2011, synthetic gas and propane were included in Other Gases.

422

SAS Output  

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

5. U.S. Coal Consumption at Manufacturing Plants by North American Industry Classification System (NAICS) Code" 5. U.S. Coal Consumption at Manufacturing Plants by North American Industry Classification System (NAICS) Code" "(thousand short tons)" ,,,,"Year to Date" "NAICS Code","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "311 Food Manufacturing",2256,2561,1864,4817,4343,10.9 "312 Beverage and Tobacco Product Mfg.",38,50,48,88,95,-7.7 "313 Textile Mills",31,29,21,60,59,2.2 "315 Apparel Manufacturing","w","w","w","w","w","w" "321 Wood Product Manufacturing","w","w","w","w","w","w"

423

SAS Output  

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

D. Biogenic Municipal Solid Waste: Consumption for Electricity Generation, D. Biogenic Municipal Solid Waste: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 148,110 5,766 128,947 13,095 302 2004 141,577 3,705 124,815 12,909 146 2005 144,339 4,724 126,529 12,923 164 2006 146,987 4,078 129,779 12,964 165 2007 146,308 4,557 127,826 13,043 881 2008 148,452 4,476 130,041 13,934 0 2009 146,971 3,989 126,649 16,333 0 2010 144,934 3,322 124,437 17,176 0 2011 135,241 3,433 115,841 15,933 34 2012 135,735 3,910 113,418 18,307 100 2010 January 11,540 244 9,886 1,410 0 February 10,313 190 9,030 1,094 0

424

SAS Output  

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

3. Average Quality of Fossil Fuel Receipts for the Electric Power Industry, 3. Average Quality of Fossil Fuel Receipts for the Electric Power Industry, 2002 through 2012 Coal Petroleum Natural Gas Period Average Btu per Pound Average Sulfur Percent by Weight Average Ash Percent by Weight Average Btu per Gallon Average Sulfur Percent by Weight Average Ash Percent by Weight Average Btu per Cubic Foot 2002 10,168 0.94 8.7 147,903 1.64 0.2 1,025 2003 10,137 0.97 9.0 147,086 1.53 0.1 1,030 2004 10,074 0.97 9.0 147,286 1.66 0.2 1,027 2005 10,107 0.98 9.0 146,481 1.61 0.2 1,028 2006 10,063 0.97 9.0 143,883 2.31 0.2 1,027 2007 10,028 0.96 8.8 144,546 2.10 0.1 1,027 2008 9,947 0.97 9.0 142,205 2.21 0.3 1,027 2009 9,902 1.01 8.9 141,321 2.14 0.2 1,025 2010 9,842 1.16 8.8 140,598 2.14 0.2 1,022

425

SAS Output  

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

5. Net Generation from Hydroelectric (Pumped Storage) Power 5. Net Generation from Hydroelectric (Pumped Storage) Power by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England -305 -435 -29.9% 0 0 -305 -435 0 0 0 0 Connecticut 3 6 -51.5% 0 0 3 6 0 0 0 0 Maine 0 0 -- 0 0 0 0 0 0 0 0 Massachusetts -308 -440 -30.1% 0 0 -308 -440 0 0 0 0 New Hampshire 0 0 -- 0 0 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0 Middle Atlantic -1,022 -1,124 -9.0% -579 -630 -443 -494 0 0 0 0

426

SAS Output  

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

Average Price of U.S. Coal Exports" Average Price of U.S. Coal Exports" "(dollars per short ton)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",78.29,77.25,102.62,77.88,105.14,-25.9 " Canada*",81.61,80.7,110.67,81.3,112.16,-27.5 " Dominican Republic",78.54,75.09,73.89,75.77,76.61,-1.1 " Honduras","-",54.58,54.43,54.58,54.43,0.3 " Jamaica",480,54.43,"-",54.72,55.42,-1.3 " Mexico",73.45,75.81,94.36,74.35,100.95,-26.3 " Other**",80.33,389.3,70.37,82.45,76.1,8.3

427

SAS Output  

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

5. Receipts, Average Cost, and Quality of Fossil Fuels: Electric Utilities, 2002 - 2012 Coal Petroleum Liquids Receipts Average Cost Receipts Average Cost Period (Billion Btu)...

428

SAS Output  

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

4. Weighted Average Cost of Fossil Fuels for the Electric Power Industry, 2002 through 2012 Coal Petroleum Natural Gas Total Fossil Bituminous Subbituminous Lignite All Coal Ranks...

429

SAS Output  

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

3. Fuel-Switching Capacity of Operable Generators: From Natural Gas to Petroleum Liquids, by Type of Prime Mover, 2012 (Megawatts, Percent) Prime Mover Type Number of Generators...

430

SAS Output  

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

" Italy","-","-","-","-",3,"-" " Netherlands","-","-","-","-",1046,"-" " Russia",42439,"-","-",42439,"-","-" " Ukraine",80025,23142,"-",103167,22155,365.7 " United...

431

SAS Output  

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

455,214 Other Gases 94 2,253 1,946 1,933 Nuclear 104 107,938 101,885 104,182 Hydroelectric Conventional 4,023 78,241 78,738 78,215 Wind 947 59,629 59,075 59,082 Solar...

432

SAS Output  

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

3,001 2,267 2,431 Other Gases 1 * * * 4 120 152 152 Nuclear -- -- -- -- -- -- -- -- Hydroelectric Conventional 15 345 344 342 28 317 315 314 Wind 149 12,953 12,885 12,885 1 13 12...

433

SAS Output  

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

3. Net Generation from Hydroelectric (Conventional) Power by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors...

434

SAS Output  

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

because of independent rounding." "Source: U.S. Department of Labor, Mine Safety and Health Administration, Form 7000-2, 'Quarterly Mine Employment and Coal Production Report.'...

435

SAS Output  

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

2012 (From Chapter 2.) Supply (Million Megawatthours) Generation Year Electric Utilities IPP (Non-CHP) IPP (CHP) Commercial Sector Industrial Sector Total Imports Total...

436

SAS Output  

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

- Electricity Purchases, 2002 through 2012 (Thousand Megawatthours) Year Electric Utilities Energy-Only Providers Independent Power Producers Combined Heat and Power U.S. Total...

437

SAS Output  

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

to Date" "Customs District","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "Eastern Total",14307904,16331296,16667115,3063920...

438

SAS Output  

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

,,,,"Year to Date" "Commodity","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "Coke" " Sales",1969,1865,1969,3834,3905,-1.8 "...

439

SAS Output  

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

18,481,678 1,320,095 624,502 45,083,186 19,106,180 2011 51,075,952 14,398,470 1,223,758 650,082 52,299,710 15,048,552 2012 57,971,110 11,392,267 1,285,959 603,382...

440

SAS Output  

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

Coal Productivity by State and Mine Type, 2012 and 2011" ,"Number of Mining Operations2",,,"Number of Employees3",,,"Average Production per Employee Hour" ,,,"(short tons)4"...

Note: This page contains sample records for the topic "model output location" 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

SAS Output  

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

Recoverable Coal Reserves at Producing Mines, Estimated Recoverable Reserves, and Demonstrated Reserve by Mining Method, 2012" "(million short tons)" ,"Underground - Minable...

442

SAS Output  

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

Coal Production and Number of Mines by State and Coal Rank, 2012" "(thousand short tons)" ,"Bituminous",,"Subbituminous",,"Lignite",,"Anthracite",,"Total" "Coal-Producing","Number...

443

SAS Output  

Gasoline and Diesel Fuel Update (EIA)

B. U.S. Transformer Outages by Type and NERC region, 2012 Outage Type Eastern Interconnection TRE WECC Contiguous U.S. Circuit Outage Counts Automatic Outages (Sustained) 16.00 --...

444

SAS Output  

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

2012 2,162,230 102,223 1,509 -- 2,265,963 In 2006 the single largest provider of green pricing services in the country discontinued service in two States. More than...

445

SAS Output  

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

B. Summer Net Internal Demand, Capacity Resources, and Capacity Margins B. Summer Net Internal Demand, Capacity Resources, and Capacity Margins by North American Electric Reliability Corporation Assessment Area, 2012 Actual, 2013-2017 Projected Net Internal Demand (Megawatts) -- Summer Eastern Interconnection ERCOT Western Interconnection All Interconnections Period FRCC NPCC Balance of Eastern Region MAPP MISO PJM SERC SPP TRE WECC Contiguous U.S. Actual 2012 44,338 58,319 469,273 4,967 96,769 156,319 158,041 53,177 66,548 130,465 768,943 Projected 2013 42,532 59,969 447,171 5,022 91,644 144,378 152,949 53,177 65,901 129,278 744,851 Projected 2014 43,142 60,654 448,912 5,161 92,331 144,497 152,843 54,080 67,592 128,200 748,499 Projected 2015 43,812 61,428 457,865 5,270 93,017 147,568 157,287 54,722 69,679 129,553 762,336

446

SAS Output  

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

A. Net Generation by Energy Source: Industrial Sector, 2002 - 2012 A. Net Generation by Energy Source: Industrial Sector, 2002 - 2012 (Thousand Megawatthours) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Nuclear Hydroelectric Conventional Renewable Sources Excluding Hydroelectric Hydroelectric Pumped Storage Other Total Annual Totals 2002 21,525 3,196 1,207 79,013 9,493 0 3,825 30,489 0 3,832 152,580 2003 19,817 3,726 1,559 78,705 12,953 0 4,222 28,704 0 4,843 154,530 2004 19,773 4,128 1,839 78,959 11,684 0 3,248 29,164 0 5,129 153,925 2005 19,466 3,804 1,564 72,882 9,687 0 3,195 29,003 0 5,137 144,739 2006 19,464 2,567 1,656 77,669 9,923 0 2,899 28,972 0 5,103 148,254 2007 16,694 2,355 1,889 77,580 9,411 0 1,590 28,919 0 4,690 143,128

447

SAS Output  

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

A. Existing Net Summer Capacity by Energy Source and Producer Type, 2002 through 2012 (Megawatts) A. Existing Net Summer Capacity by Energy Source and Producer Type, 2002 through 2012 (Megawatts) Year Coal Petroleum Natural Gas Other Gases Nuclear Hydroelectric Conventional Other Renewable Sources Hydroelectric Pumped Storage Other Energy Sources Total Total (All Sectors) 2002 315,350 59,651 312,512 2,008 98,657 79,356 16,710 20,371 686 905,301 2003 313,019 60,730 355,442 1,994 99,209 78,694 18,153 20,522 684 948,446 2004 313,020 59,119 371,011 2,296 99,628 77,641 18,717 20,764 746 962,942 2005 313,380 58,548 383,061 2,063 99,988 77,541 21,205 21,347 887 978,020 2006 312,956 58,097 388,294 2,256 100,334 77,821 24,113 21,461 882 986,215 2007 312,738 56,068 392,876 2,313 100,266 77,885 30,069 21,886 788 994,888

448

SAS Output  

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

0. Average Cost of Natural Gas Delivered for Electricity Generation by State, 2012 and 2011 0. Average Cost of Natural Gas Delivered for Electricity Generation by State, 2012 and 2011 (Dollars per MMBtu) Census Division and State Electric Power Sector Electric Utilities Independent Power Producers Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 New England 3.69 4.94 -25% 4.73 5.70 3.68 4.93 Connecticut 3.88 4.97 -22% 6.45 NM 3.87 4.96 Maine W W W -- -- W W Massachusetts 3.55 4.88 -27% 4.47 5.75 3.53 4.87 New Hampshire W W W 5.54 6.01 W W Rhode Island 3.86 5.01 -23% -- -- 3.86 5.01 Vermont 4.06 5.22 -22% 4.06 5.22 -- -- Middle Atlantic 3.52 5.14 -32% 3.86 5.32 3.46 5.11 New Jersey 3.52 5.11 -31% -- -- 3.52 5.11 New York 3.85 5.45 -29% 3.86 5.32 3.84 5.50

449

SAS Output  

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

. Average Operating Heat Rate for Selected Energy Sources, . Average Operating Heat Rate for Selected Energy Sources, 2002 through 2012 (Btu per Kilowatthour) Year Coal Petroleum Natural Gas Nuclear 2002 10,314 10,641 9,533 10,442 2003 10,297 10,610 9,207 10,422 2004 10,331 10,571 8,647 10,428 2005 10,373 10,631 8,551 10,436 2006 10,351 10,809 8,471 10,435 2007 10,375 10,794 8,403 10,489 2008 10,378 11,015 8,305 10,452 2009 10,414 10,923 8,159 10,459 2010 10,415 10,984 8,185 10,452 2011 10,444 10,829 8,152 10,464 2012 10,498 10,991 8,039 10,479 Coal includes anthracite, bituminous, subbituminous and lignite coal. Waste coal and synthetic coal are included starting in 2002. Petroleum includes distillate fuel oil (all diesel and No. 1 and No. 2 fuel oils), residual fuel oil (No. 5 and No. 6 fuel oils and bunker C fuel oil, jet fuel, kerosene, petroleum coke, and waste oil.

450

SAS Output  

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

0. Net Generation from Natural Gas 0. Net Generation from Natural Gas by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 62,490 63,236 -1.2% 345 357 58,757 59,763 901 700 2,488 2,416 Connecticut 16,537 15,188 8.9% 6 NM 15,801 14,715 397 211 333 227 Maine 6,044 6,877 -12.1% 0 0 4,057 4,850 26 0.26 1,960 2,026 Massachusetts 24,672 25,940 -4.9% 278 240 23,812 25,120 416 443 166 136 New Hampshire 7,050 6,658 5.9% 58 80 6,947 6,552 16 0 29 26 Rhode Island 8,185 8,571 -4.5% 0 0 8,140 8,525 45 46 0 0

451

SAS Output  

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

4. Average Quality of Coal Received at Commercial and Institutional Users by Census Division and State" 4. Average Quality of Coal Received at Commercial and Institutional Users by Census Division and State" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State1",2013,2013,2012,,,"Change" "Middle Atlantic" " Btu",12906,12815,11709,12844,12440,3.2 " Sulfur",1.03,0.92,0.99,0.96,0.97,-1 " Ash",8.94,8.62,10,8.72,9.11,-4.3 "Pennsylvania" " Btu",12906,12815,11709,12844,12440,3.2 " Sulfur",1.03,0.92,0.99,0.96,0.97,-1 " Ash",8.94,8.62,10,8.72,9.11,-4.3 "East North Central" " Btu",11928,12228,11682,12112,11933,1.5

452

SAS Output  

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

Major U.S. Coal Producers, 2012" Major U.S. Coal Producers, 2012" "Rank","Controlling Company Name","Production (thousand short tons)","Percent of Total Production" 1,"Peabody Energy Corp",192563,18.9 2,"Arch Coal Inc",136992,13.5 3,"Alpha Natural Resources LLC",104306,10.3 4,"Cloud Peak Energy",90721,8.9 5,"CONSOL Energy Inc",55752,5.5 6,"Alliance Resource Operating Partners LP",35406,3.5 7,"Energy Future Holdings Corp",31032,3.1 8,"Murray Energy Corp",29216,2.9 9,"NACCO Industries Inc",28207,2.8 10,"Patriot Coal Corp",23946,2.4 11,"Peter Kiewit Sons Inc",22725,2.2 12,"Westmoreland Coal Co",22215,2.2 13,"BHP Billiton Ltd",12580,1.2

453

SAS Output  

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

5. Receipts of Petroleum Coke Delivered for Electricity Generation by State, 2012 and 2011 5. Receipts of Petroleum Coke Delivered for Electricity Generation by State, 2012 and 2011 (Thousand Tons) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 0 0 -- 0 0 0 0 0 0 0 0 Connecticut 0 0 -- 0 0 0 0 0 0 0 0 Maine 0 0 -- 0 0 0 0 0 0 0 0 Massachusetts 0 0 -- 0 0 0 0 0 0 0 0 New Hampshire 0 0 -- 0 0 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0 Middle Atlantic 106 79 35% 0 0 0 23 0 0 106 56 New Jersey 0 NM NM 0 0 0 0 0 0 0 NM

454

SAS Output  

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

6. Net Generation 6. Net Generation by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 120,887 123,338 -2.0% 3,278 4,408 111,191 112,613 1,178 949 5,240 5,368 Connecticut 36,118 33,745 7.0% 37 93 35,347 33,208 397 211 337 233 Maine 14,429 15,974 -9.7% 0.17 1 10,186 10,890 208 176 4,035 4,907 Massachusetts 36,198 38,055 -4.9% 591 610 34,321 36,783 469 490 817 172 New Hampshire 19,264 20,066 -4.0% 2,017 2,994 17,170 17,020 49 20 29 31

455

SAS Output  

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

B. Net Summer Capacity of Utility Scale Units Using Primarily Renewable Energy Sources and by State, 2012 and 2011 (Megawatts) B. Net Summer Capacity of Utility Scale Units Using Primarily Renewable Energy Sources and by State, 2012 and 2011 (Megawatts) Census Division and State Wind Solar Photovoltaic Solar Thermal Conventional Hydroelectric Biomass Sources Geothermal Total Renewable Sources Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 784.1 422.8 49.2 13.9 0.0 0.0 1,956.9 1,946.9 1,367.5 1,421.6 0.0 0.0 4,157.7 3,805.2 Connecticut 0.0 0.0 0.0 0.0 0.0 0.0 122.2 121.7 172.5 178.2 0.0 0.0 294.7 299.9 Maine 427.6 322.5 0.0 0.0 0.0 0.0 742.3 742.3 534.6 576.0 0.0 0.0 1,704.5 1,640.8 Massachusetts 63.8 29.6 41.2 11.7 0.0 0.0 261.1 262.7 395.4 406.9 0.0 0.0 761.5 710.9

456

SAS Output  

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

3. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: Independent Power Producers by State, 2012 3. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: Independent Power Producers by State, 2012 Bituminous Subbituminous Lignite Census Division and State Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight New England 732 0.87 10.5 41 0.09 2.0 0 -- -- Connecticut 0 -- -- 41 0.09 2.0 0 -- -- Maine 32 0.80 7.0 0 -- -- 0 -- -- Massachusetts 700 0.88 10.7 0 -- -- 0 -- -- New Hampshire 0 -- -- 0 -- -- 0 -- -- Rhode Island 0 -- -- 0 -- -- 0 -- -- Vermont 0 -- -- 0 -- -- 0 -- --

457

SAS Output  

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

7. Average Cost of Coal Delivered for Electricity Generation by State, 2012 and 2011 7. Average Cost of Coal Delivered for Electricity Generation by State, 2012 and 2011 (Dollars per MMBtu) Census Division and State Electric Power Sector Electric Utilities Independent Power Producers Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 New England 3.59 3.68 -2.4% 4.07 3.55 3.34 3.74 Connecticut W W W -- -- W W Maine W W W -- -- W W Massachusetts W W W -- -- W W New Hampshire 4.07 3.55 15% 4.07 3.55 -- -- Rhode Island -- -- -- -- -- -- -- Vermont -- -- -- -- -- -- -- Middle Atlantic 2.50 2.68 -6.7% -- 2.92 2.50 2.63 New Jersey 4.05 4.18 -3.1% -- -- 4.05 4.18 New York 3.12 3.27 -4.6% -- 3.88 3.12 3.27 Pennsylvania 2.43 2.55 -4.7% -- 2.91 2.43 2.45

458

SAS Output  

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

. Count of Electric Power Industry Power Plants, by Sector, by Predominant Energy Sources within Plant, 2002 through 2012 . Count of Electric Power Industry Power Plants, by Sector, by Predominant Energy Sources within Plant, 2002 through 2012 Year Coal Petroleum Natural Gas Other Gases Nuclear Hydroelectric Conventional Other Renewables Hydroelectric Pumped Storage Other Energy Sources Total (All Sectors) 2002 633 1,147 1,649 40 66 1,426 682 38 28 2003 629 1,166 1,693 40 66 1,425 741 38 27 2004 625 1,143 1,670 46 66 1,425 749 39 28 2005 619 1,133 1,664 44 66 1,422 781 39 29 2006 616 1,148 1,659 46 66 1,421 843 39 29 2007 606 1,163 1,659 46 66 1,424 929 39 25 2008 598 1,170 1,655 43 66 1,423 1,076 39 29 2009 593 1,168 1,652 43 66 1,427 1,219 39 28 2010 580 1,169 1,657 48 66 1,432 1,355 39 32

459

SAS Output  

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

2. Receipts, Average Cost, and Quality of Fossil Fuels: Industrial Sector, 2002 - 2012 (continued) 2. Receipts, Average Cost, and Quality of Fossil Fuels: Industrial Sector, 2002 - 2012 (continued) Petroleum Coke Natural Gas All Fossil Fuels Receipts Average Cost Receipts Average Cost Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMbtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Mcf) (Dollars per MMBtu) (Dollars per Mcf) Percentage of Consumption (Dollars per MMBtu) Annual Totals 2002 3,846 138 0.76 21.20 5.91 9.1 852,547 828,439 3.36 3.46 66.8 2.88 2003 16,383 594 1.04 28.74 5.73 47.3 823,681 798,996 5.32 5.48 69.9 4.20 2004 14,876 540 0.98 27.01 5.59 40.4 839,886 814,843 6.04 6.22 68.4 4.76 2005 16,620 594 1.21 33.75 5.44 58.2 828,882 805,132 8.00 8.24 74.3 6.18

460

SAS Output  

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

A. Existing Transmission Capacity by High-Voltage Size, 2012 A. Existing Transmission Capacity by High-Voltage Size, 2012 Voltage Circuit Miles Type Operating (kV) FRCC MRO NPCC RFC SERC SPP TRE WECC Contiguous U.S. AC 100-199 -- -- -- -- -- -- -- -- -- AC 200-299 6,018 7,813 1,538 6,933 21,757 2,948 -- 38,410 85,416 AC 300-399 -- 7,362 5,850 13,429 3,650 5,303 9,529 10,913 56,036 AC 400-599 1,201 543 -- 2,618 8,876 94 -- 12,794 26,125 AC 600-799 -- -- 190 2,226 -- -- -- -- 2,416 AC Multi-Circuit Structure 200-299 1,198 686 36 2,008 4,156 9 -- -- 8,092 AC Multi-Circuit Structure 300-399 -- 372 274 3,706 313 153 2,747 -- 7,564 AC Multi-Circuit Structure 400-599 -- -- -- 90 857 -- -- -- 947 AC Multi-Circuit Structure 600-799 -- -- -- -- -- -- -- -- --

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461

SAS Output  

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

A. Net Energy for Load by North American Electric Reliability Corporation Assessment Area, A. Net Energy for Load by North American Electric Reliability Corporation Assessment Area, 2002 - 2012, Actual Net Energy (Thousands of Megawatthours) Eastern Interconnection ERCOT Western Interconnection All Interconnections Period FRCC NPCC Balance of Eastern Region ECAR MAAC MAIN MAPP MISO MRO PJM RFC SERC SPP TRE WECC Contiguous U.S. 2002 211,116 286,199 2,301,321 567,897 273,907 279,264 -- -- 150,058 -- -- 835,319 194,876 280,269 666,696 3,745,601 2003 219,021 288,791 2,255,233 545,109 276,600 267,068 -- -- 153,918 -- -- 826,964 185,574 283,868 664,754 3,711,667 2004 220,335 292,725 2,313,180 553,236 283,646 274,760 -- -- 152,975 -- -- 856,734 191,829 289,146 682,053 3,797,439 2005 226,544 303,607 2,385,461 -- -- -- -- -- 216,633 -- 1,005,226 962,054 201,548 299,225 685,624 3,900,461

462

SAS Output  

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

U.S. Coal Exports" U.S. Coal Exports" "(short tons)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",3122664,2010882,3565711,5133546,5327583,-3.6 " Canada*",1773644,943061,2101534,2716705,3176066,-14.5 " Dominican Republic",51792,211736,124720,263528,312741,-15.7 " Honduras","-",41664,34161,41664,68124,-38.8 " Jamaica",25,36311,"-",36336,33585,8.2 " Mexico",1244972,777750,1268077,2022722,1698391,19.1 " Other**",52231,360,37219,52591,38676,36

463

SAS Output  

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

B. U.S. Transformer Sustained Automatic Outage Counts and Hours by Cause Code and by NERC Region, 2012 B. U.S. Transformer Sustained Automatic Outage Counts and Hours by Cause Code and by NERC Region, 2012 Transformer Outage Counts Sustained Outage Causes FRCC MRO NPCC RFC SERC SPP TRE WECC Contiguous U.S. Weather, excluding lightning -- -- -- -- 1.00 -- -- -- 1.00 Lightning -- -- -- -- -- -- -- -- -- Environmental -- -- -- -- -- -- -- -- -- Contamination 1.00 -- -- -- -- -- -- -- 1.00 Foreign Interference -- -- -- -- -- -- -- -- -- Fire -- -- -- -- -- -- -- -- -- Vandalism, Terrorism, or Malicious Acts -- -- -- -- -- -- -- -- -- Failed AC Substation Equipment 3.00 1.00 -- 1.00 5.00 -- -- 4.00 14.00 Failed AC/DC Terminal Equipment -- -- -- -- -- -- -- -- -- Failed Protection System Equipment -- 1.00 -- -- 3.00 -- -- -- 4.00

464

SAS Output  

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

A. Net Summer Capacity of Utility Scale Units by Technology and by State, 2012 and 2011 (Megawatts) A. Net Summer Capacity of Utility Scale Units by Technology and by State, 2012 and 2011 (Megawatts) Census Division and State Renewable Sources Fossil Fuels Hydroelectric Pumped Storage Other Energy Storage Nuclear All Other Sources All Sources Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 4,157.7 3,805.2 24,619.1 24,153.6 1,753.4 1,709.4 3.0 3.0 4,630.3 4,653.7 48.0 26.0 35,211.5 34,350.9 Connecticut 294.7 299.9 6,607.7 6,674.5 29.4 29.4 0.0 0.0 2,102.5 2,102.5 26.0 26.0 9,060.3 9,132.3 Maine 1,704.5 1,640.8 2,764.9 2,737.4 0.0 0.0 0.0 0.0 0.0 0.0 22.0 0.0 4,491.4 4,378.2 Massachusetts 761.5 710.9 11,155.2 10,637.8 1,724.0 1,680.0 3.0 3.0 677.3 684.7 0.0 0.0 14,321.0 13,716.4

465

SAS Output  

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

by State" by State" "(thousand short tons)" ,,,,"Year to Date" "Coal-Producing Region","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "Alabama",4649,4410,5171,9059,10150,-10.8 "Alaska",442,300,542,742,1091,-32 "Arizona",2184,1825,2002,4009,4169,-3.8 "Arkansas",2,4,11,6,33,-83.1 "Colorado",5297,5781,6885,11079,13914,-20.4 "Illinois",13474,13996,12487,27470,24419,12.5 "Indiana",9516,9422,9147,18938,18794,0.8 "Kansas",5,5,5,9,8,23.7 "Kentucky Total",20683,20594,22803,41276,49276,-16.2 " Eastern (Kentucky)",10392,10144,12444,20536,27516,-25.4

466

SAS Output  

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

0. Net Generation from Solar 0. Net Generation from Solar by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 35 7 427.1% 9 4 25 2 1 1 0 0 Connecticut 0 0 -- 0 0 0 0 0 0 0 0 Maine 0 0 -- 0 0 0 0 0 0 0 0 Massachusetts 30 5 521.6% 9 4 20 0.14 1 1 0 0 New Hampshire 0 0 -- 0 0 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 5 2 179.0% 0 0 5 2 0 0 0 0 Middle Atlantic 389 98 295.3% 41 19 303 65 37 8 8 5

467

SAS Output  

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

A. Winter Net Internal Demand, Capacity Resources, and Capacity Margins by North American Electric Reliability Assessment Area, A. Winter Net Internal Demand, Capacity Resources, and Capacity Margins by North American Electric Reliability Assessment Area, 2002 - 2012, Actual Net Internal Demand (Megawatts) -- Winter Eastern Interconnection ERCOT Western Interconnection All Interconnections Period FRCC NPCC Balance of Eastern Region ECAR MAAC MAIN MAPP MISO MRO PJM RFC SERC SPP TRE WECC Contiguous U.S. 2002 / 2003 42,001 45,980 360,748 84,844 46,159 39,974 -- -- 23,090 -- -- 137,541 29,140 44,719 94,554 588,002 2003 / 2004 36,229 47,850 357,026 86,332 45,625 39,955 -- -- 24,042 -- -- 133,244 27,828 41,988 100,337 583,430 2004 / 2005 41,449 47,859 371,011 91,800 45,565 40,618 -- -- 24,446 -- -- 139,486 29,096 44,010 101,002 605,331

468

SAS Output  

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

B. Net Generation from Renewable Sources: Commerical Sector, 2002 - 2012 B. Net Generation from Renewable Sources: Commerical Sector, 2002 - 2012 (Thousand Megawatthours) Period Wind Solar Photovoltaic Solar Thermal Wood and Wood-Derived Fuels Landfill Gas Biogenic Municipal Solid Waste Other Waste Biomass Geothermal Conventional Hydroelectric Total Renewable Sources Annual Totals 2002 0 N/A N/A 13 N/A N/A N/A 0 13 N/A 2003 0 0 0 13 152 717 420 0 72 1,374 2004 0 0 0 13 172 945 444 0 105 1,680 2005 0 0 0 16 218 953 486 0 86 1,759 2006 0 0 0 21 173 956 470 0 93 1,713 2007 0 0 0 15 203 962 434 0 77 1,691 2008 0 0.08 0 21 234 911 389 0 60 1,615 2009 0.21 0.04 0 20 318 1,045 386 0 71 1,839 2010 16 5 0 21 256 1,031 386 0 80 1,794 2011 51 84 0 26 952 971 393 0 26 2,502

469

SAS Output  

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

4. Net Generation from Renewable Sources Excluding Hydroelectric 4. Net Generation from Renewable Sources Excluding Hydroelectric by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 8,557 8,015 6.8% 664 574 5,652 5,352 136 104 2,105 1,985 Connecticut 667 660 1.0% 0 0 667 660 0 0 0 0 Maine 4,099 4,495 -8.8% 0 0 2,468 2,421 92 89 1,539 1,985 Massachusetts 1,843 1,207 52.8% 68 48 1,198 1,145 11 13 566 0 New Hampshire 1,381 1,091 26.6% 347 291 1,003 800 31 0 0 0.35 Rhode Island 102 130 -21.8% 0 0 102 130 0 0 0 0

470

SAS Output  

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

3. Average Quality of Coal Received at Manufacturing and Coke Plants by Census Division and State" 3. Average Quality of Coal Received at Manufacturing and Coke Plants by Census Division and State" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State1",2013,2013,2012,,,"Change" "New England" " Btu",13323,13196,13391,13253,13339,-0.6 " Sulfur",0.84,0.89,0.72,0.87,0.72,20.3 " Ash",5.95,5.81,5.93,5.87,6.09,-3.6 "Maine" " Btu","w","w","w","w","w","w" " Sulfur","w","w","w","w","w","w" " Ash","w","w","w","w","w","w"

471

SAS Output  

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

9. Net Generation from Petroleum Coke 9. Net Generation from Petroleum Coke by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 0 0 -- 0 0 0 0 0 0 0 0 Connecticut 0 0 -- 0 0 0 0 0 0 0 0 Maine 0 0 -- 0 0 0 0 0 0 0 0 Massachusetts 0 0 -- 0 0 0 0 0 0 0 0 New Hampshire 0 0 -- 0 0 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0 Middle Atlantic 76 344 -78.0% 0 0 0 263 0 0 76 81 New Jersey 40 58 -30.6% 0 0 0 0 0 0 40 58

472

SAS Output  

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

8. Net Generation from Petroleum Liquids 8. Net Generation from Petroleum Liquids by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 413 639 -35.4% 52 120 267 374 49 55 45 90 Connecticut 112 166 -32.6% 4 5 104 155 0.05 0 4 5 Maine 84 178 -52.8% 0.17 1 65 89 2 3 16 85 Massachusetts 174 197 -11.2% 15 40 98 128 37 28 25 NM New Hampshire 22 78 -72.1% 20 57 0.12 1 2 20 0.17 0.10 Rhode Island 18 14 31.0% 11 10 0.12 1 7 2 0 0 Vermont 3 8 -58.1% 2 6 0 0 1 2 0 0

473

SAS Output  

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

Average Number of Employees at Underground and Surface Mines by State and Union Status, 2012" Average Number of Employees at Underground and Surface Mines by State and Union Status, 2012" ,"Union",,"Nonunion" "Coal-Producing State","Underground","Surface","Underground","Surface" "and Region1" "Alabama",3044,70,89,1677 "Alaska","-",143,"-","-" "Arizona","-",432,"-","-" "Arkansas","-","-",70,"-" "Colorado",174,212,1858,261 "Illinois",647,58,3291,534 "Indiana","-","-",2054,1868 "Kentucky Total",564,93,10122,4595 " Kentucky (East)",48,93,6821,3943 " Kentucky (West)",516,"-",3301,652

474

SAS Output  

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

A. Net Generation by Energy Source: Commerical Sector, 2002 - 2012 A. Net Generation by Energy Source: Commerical Sector, 2002 - 2012 (Thousand Megawatthours) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Nuclear Hydroelectric Conventional Renewable Sources Excluding Hydroelectric Hydroelectric Pumped Storage Other Total Annual Totals 2002 992 426 6 4,310 0.01 0 13 1,065 0 603 7,415 2003 1,206 416 8 3,899 0 0 72 1,302 0 594 7,496 2004 1,340 493 7 3,969 0 0 105 1,575 0 781 8,270 2005 1,353 368 7 4,249 0 0 86 1,673 0 756 8,492 2006 1,310 228 7 4,355 0.04 0 93 1,619 0 758 8,371 2007 1,371 180 9 4,257 0 0 77 1,614 0 764 8,273 2008 1,261 136 6 4,188 0 0 60 1,555 0 720 7,926 2009 1,096 157 5 4,225 0 0 71 1,769 0 842 8,165

475

SAS Output  

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

Average Number of Employees by State and Mine Type, 2012 and 2011" Average Number of Employees by State and Mine Type, 2012 and 2011" ,2012,,,2011,,,"Percent Change" "Coal-Producing","Underground","Surface","Total","Underground","Surface","Total","Underground","Surface","Total" "State and Region1" "Alabama",3190,1851,5041,3138,1618,4756,1.7,14.4,6 "Alaska","-",143,143,"-",136,136,"-",5.1,5.1 "Arizona","-",432,432,"-",419,419,"-",3.1,3.1 "Arkansas",70,3,73,67,3,70,4.5,"-",4.3 "Colorado",2032,473,2505,1927,478,2405,5.4,-1,4.2 "Illinois",3938,574,4512,3563,542,4105,10.5,5.9,9.9

476

SAS Output  

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

Capacity Utilization of Coal Mines by State, 2012 and 2011" Capacity Utilization of Coal Mines by State, 2012 and 2011" "(percent)" ,2012,,,2011 "Coal-Producing","Underground","Surface","Total","Underground","Surface","Total" "State" "Alabama",85.99,83.96,85.28,67.52,90.91,75.85 "Alaska","-","w","w","-","w","w" "Arizona","-","w","w","-","w","w" "Arkansas","w","-","w","w","-","w" "Colorado","w","w",76.65,"w","w",74.63 "Illinois",71.02,57.41,69.11,71.73,53.22,68.54

477

SAS Output  

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

2. U.S. Coke Summary Statistics, 2007 - 2013" 2. U.S. Coke Summary Statistics, 2007 - 2013" "(thousand short tons)" "Year and","Production","Imports","Producer and","Consumption2","Exports" "Quarter",,,"Distributor" ,,,"Stocks1" 2007 " January - March",4000,454,717,4078,343 " April - June",4083,685,767,4428,291 " July - September",4063,521,637,4371,344 " October - December",4055,800,632,4394,466 " Total",16201,2460,,17270,1444 2008 " January - March",4036,850,478,4723,316 " April - June",3810,1243,505,4559,466 " July - September",4107,998,464,4494,653 " October - December",3694,512,916,3229,524

478

SAS Output  

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

2. Underground Coal Mining Productivity by State and Mining Method, 2012" 2. Underground Coal Mining Productivity by State and Mining Method, 2012" "(short tons produced per employee hour)" "Coal-Producing State, Region1 and Mine Type","Continuous2","Conventional and","Longwall4","Total" ,,"Other3" "Alabama",0.71,"-",1.69,1.66 "Arkansas",0.59,"-","-",0.59 "Colorado",1.9,"-",6.38,5.93 "Illinois",3.65,"-",6.6,4.86 "Indiana",3.25,"-","-",3.25 "Kentucky Total",2.43,1.77,"-",2.39 " Kentucky (East)",1.61,1.77,"-",1.62 " Kentucky (West)",3.61,"-","-",3.56 "Maryland",1.8,"-","-",1.8

479

SAS Output  

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

1. Average Sales Price of Coal by State and Coal Rank, 2012" 1. Average Sales Price of Coal by State and Coal Rank, 2012" "(dollars per short ton)" "Coal-Producing State","Bituminous","Subbituminous","Lignite","Anthracite","Total" "Alabama",106.57,"-","-","-",106.57 "Alaska","-","w","-","-","w" "Arizona","w","-","-","-","w" "Arkansas","w","-","-","-","w" "Colorado","w","w","-","-",37.54 "Illinois",53.08,"-","-","-",53.08 "Indiana",52.01,"-","-","-",52.01

480

SAS Output  

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

Average Price of U.S. Coal Exports and Imports, 2007 - 2013" Average Price of U.S. Coal Exports and Imports, 2007 - 2013" "(dollars per short ton)" ,"January - March",,"April - June",,"July - September",,"October - December",,"Total" "Year","Exports","Imports","Exports","Imports","Exports","Imports","Exports","Imports","Exports","Imports" 2007,74.13,45.91,64.3,46.86,72.1,47.38,71.09,50.51,70.25,47.64 2008,81.81,52.91,97.24,55.59,102.51,64.65,104.97,65.33,97.68,59.83 2009,113.08,61.03,93.28,65.44,98.7,64.93,100.98,64.72,101.44,63.91 2010,106.52,62.02,121.36,71.91,125.45,77.12,126.16,76.18,120.41,71.77 2011,139.34,86,153,105.86,155.88,112.06,147.38,110.19,148.86,103.32

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481

SAS Output  

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

1. Coke and Breeze Stocks at Coke Plants by Census Division" 1. Coke and Breeze Stocks at Coke Plants by Census Division" "(thousand short tons)" "Census Division","April - June","January - March","April - June","Percent Change" ,2013,2013,2012,"(June 30)" ,,,,"2013 versus 2012" "Middle Atlantic","w","w","w","w" "East North Central",724,510,509,42.1 "South Atlantic","w","w","w","w" "East South Central","w","w","w","w" "U.S. Total",914,690,674,35.6 "Coke Total",757,573,594,27.5 "Breeze Total",157,117,80,95.2 "w = Data withheld to avoid disclosure."

482

SAS Output  

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

5. Planned Generating Capacity Changes, by Energy Source, 2013-2017 5. Planned Generating Capacity Changes, by Energy Source, 2013-2017 Generator Additions Generator Retirements Net Capacity Additions Energy Source Number of Generators Net Summer Capacity Number of Generators Net Summer Capacity Number of Generators Net Summer Capacity 2013 U.S. Total 513 15,144 179 12,604 334 2,540 Coal 4 1,482 28 4,465 -24 -2,983 Petroleum 21 45 41 1,401 -20 -1,356 Natural Gas 87 6,818 55 2,950 32 3,868 Other Gases -- -- 1 4 -1 -4 Nuclear -- -- 4 3,576 -4 -3,576 Hydroelectric Conventional 17 385 36 185 -19 201 Wind 25 2,225 -- -- 25 2,225 Solar Thermal and Photovoltaic 277 3,460 1 1 276 3,459 Wood and Wood-Derived Fuels 10 489 -- -- 10 489 Geothermal 5 50 1 11 4 39

483

SAS Output  

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

Coal Production and Number of Mines by State and Mine Type, 2012 and 2011" Coal Production and Number of Mines by State and Mine Type, 2012 and 2011" "(thousand short tons)" ,2012,,2011,,"Percent Change" "Coal-Producing","Number of Mines","Production","Number of Mines","Production","Number of Mines","Production" "State and Region1" "Alabama",46,19321,52,19071,-11.5,1.3 " Underground",8,12570,9,10879,-11.1,15.5 " Surface",38,6752,43,8192,-11.6,-17.6 "Alaska",1,2052,1,2149,"-",-4.5 " Surface",1,2052,1,2149,"-",-4.5 "Arizona",1,7493,1,8111,"-",-7.6 " Surface",1,7493,1,8111,"-",-7.6 "Arkansas",2,98,2,133,"-",-26.4

484

SAS Output  

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

8. Net Generation from Biomass 8. Net Generation from Biomass by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 7,229 7,138 1.3% 570 515 4,428 4,544 125 94 2,105 1,985 Connecticut 667 660 1.0% 0 0 667 660 0 0 0 0 Maine 3,212 3,788 -15.2% 0 0 1,581 1,714 92 89 1,539 1,985 Massachusetts 1,724 1,140 51.2% 0 0 1,157 1,137 1 3 566 0 New Hampshire 1,173 1,025 14.4% 347 291 795 734 31 0 0 0.35 Rhode Island 101 127 -21.1% 0 0 101 127 0 0 0 0

485

SAS Output  

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

B. Net Generation from Renewable Sources: Independent Power Producers, 2002 - 2012 B. Net Generation from Renewable Sources: Independent Power Producers, 2002 - 2012 (Thousand Megawatthours) Period Wind Solar Photovoltaic Solar Thermal Wood and Wood-Derived Fuels Landfill Gas Biogenic Municipal Solid Waste Other Waste Biomass Geothermal Conventional Hydroelectric Total Renewable Sources Annual Totals 2002 10,141 N/A N/A 8,300 N/A N/A N/A 13,089 18,189 N/A 2003 10,834 0 532 8,645 4,435 7,227 1,211 13,175 21,890 67,949 2004 13,739 0 569 8,528 4,377 6,978 884 13,563 19,518 68,154 2005 16,764 0 535 8,741 4,308 7,092 701 13,566 21,486 73,195 2006 24,238 0 493 8,404 4,771 7,259 774 13,406 24,390 83,736 2007 30,089 6 595 8,486 5,177 7,061 839 13,498 19,109 84,860 2008 48,464 60 787 8,750 6,057 6,975 1,040 13,643 23,451 109,226

486

SAS Output  

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

7. Year-End Coal Stocks by Sector, Census Division, and State, 2012 and 2011" 7. Year-End Coal Stocks by Sector, Census Division, and State, 2012 and 2011" "(thousand short tons)" ,2012,,,,,2011,,,,,"Total" "Census Division","Electric","Other","Coke","Commercial","Producer","Electric","Other","Coke","Commercial","Producer",2012,2011,"Percent" "and State","Power1","Industrial",,"and","and","Power1","Industrial",,"and","and",,,"Change" ,,,,"Institutional","Distributor",,,,"Institutional","Distributor" "New England",1030,13,"-","-","-",1389,"w","-","-","-",1042,"w","w"

487

SAS Output  

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

2. Net Generation from Nuclear Energy 2. Net Generation from Nuclear Energy by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 36,116 34,283 5.3% 0 0 36,116 34,283 0 0 0 0 Connecticut 17,078 15,928 7.2% 0 0 17,078 15,928 0 0 0 0 Maine 0 0 -- 0 0 0 0 0 0 0 0 Massachusetts 5,860 5,085 15.2% 0 0 5,860 5,085 0 0 0 0 New Hampshire 8,189 8,363 -2.1% 0 0 8,189 8,363 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 4,989 4,907 1.7% 0 0 4,989 4,907 0 0 0 0

488

SAS Output  

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

7. Net Generation from Coal 7. Net Generation from Coal by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 4,103 6,848 -40.1% 1,268 2,208 2,793 4,592 0 0 42 47 Connecticut 653 526 24.2% 0 0 653 526 0 0 0 0 Maine 45 55 -18.0% 0 0 30 38 0 0 15 18 Massachusetts 2,137 4,059 -47.4% 0 0 2,110 4,029 0 0 27 30 New Hampshire 1,268 2,208 -42.6% 1,268 2,208 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0

489

SAS Output  

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

4. Nitrogen Oxides Control Technology Emissions Reduction Factors 4. Nitrogen Oxides Control Technology Emissions Reduction Factors Nitrogen Oxides Control Technology EIA-Code(s) Reduction Factor Advanced Overfire Air AA 30% Alternate Burners BF 20% Flue Gas Recirculation FR 40% Fluidized Bed Combustor CF 20% Fuel Reburning FU 30% Low Excess Air LA 20% Low NOx Burners LN 30% Other (or Unspecified) OT 20% Overfire Air OV 20% Selective Catalytic Reduction SR 70% Selective Catalytic Reduction With Low Nitrogen Oxide Burners SR and LN 90% Selective Noncatalytic Reduction SN 30% Selective Noncatalytic Reduction With Low NOx Burners SN and LN 50% Slagging SC 20% Notes: Starting with 1995 data, reduction factors for Advanced Overfire Air, Low NOx Burners, and Overfire Air were reduced by 10 percent.

490

SAS Output  

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

2. Retail Sales and Direct Use of Electricity to Ultimate Customers 2. Retail Sales and Direct Use of Electricity to Ultimate Customers by Sector, by Provider, 2002 through 2012 (Megawatthours) Year Residential Commercial Industrial Transportation Other Total Direct Use Total End Use Total Electric Industry 2002 1,265,179,869 1,104,496,607 990,237,631 N/A 105,551,904 3,465,466,011 166,184,296 3,631,650,307 2003 1,275,823,910 1,198,727,601 1,012,373,247 6,809,728 N/A 3,493,734,486 168,294,526 3,662,029,012 2004 1,291,981,578 1,230,424,731 1,017,849,532 7,223,642 N/A 3,547,479,483 168,470,002 3,715,949,485 2005 1,359,227,107 1,275,079,020 1,019,156,065 7,506,321 N/A 3,660,968,513 150,015,531 3,810,984,044 2006 1,351,520,036 1,299,743,695 1,011,297,566 7,357,543 N/A 3,669,918,840 146,926,612 3,816,845,452

491

SAS Output  

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

1. Total Electric Power Industry Summary Statistics, 2012 and 2011 1. Total Electric Power Industry Summary Statistics, 2012 and 2011 Net Generation and Consumption of Fuels for January through December Total (All Sectors) Electric Power Sector Commercial Industrial Electric Utilities Independent Power Producers Fuel Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Net Generation (Thousand Megawatthours) Coal 1,514,043 1,733,430 -12.7% 1,146,480 1,301,107 354,076 416,783 883 1,049 12,603 14,490 Petroleum Liquids 13,403 16,086 -16.7% 9,892 11,688 2,757 3,655 191 86 563 657 Petroleum Coke 9,787 14,096 -30.6% 5,664 9,428 1,758 3,431 6 3 2,359 1,234 Natural Gas 1,225,894 1,013,689 20.9% 504,958 414,843 627,833 511,447 6,603 5,487 86,500 81,911

492

SAS Output  

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

9. Revenue from Retail Sales of Electricity to Ultimate Customers by End-Use Sector, 9. Revenue from Retail Sales of Electricity to Ultimate Customers by End-Use Sector, by State, 2012 and 2011 (Million Dollars) Residential Commercial Industrial Transportation All Sectors Census Division and State Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 7,418 7,546 6,137 6,441 3,292 3,504 38 45 16,885 17,536 Connecticut 2,213 2,339 1,901 2,038 452 486 19 19 4,584 4,882 Maine 657 674 467 494 242 268 0 0 1,366 1,436 Massachusetts 3,029 3,003 2,453 2,547 2,127 2,270 17 22 7,627 7,842 New Hampshire 713 736 598 629 231 238 0 0 1,543 1,602 Rhode Island 450 449 432 453 99 103 2 4 982 1,008 Vermont 356 346 285 281 142 139 0 0 784 766

493

SAS Output  

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

8. Receipts, Average Cost, and Quality of Fossil Fuels: Independent Power Producers, 2002 - 2012 (continued) 8. Receipts, Average Cost, and Quality of Fossil Fuels: Independent Power Producers, 2002 - 2012 (continued) Petroleum Coke Natural Gas All Fossil Fuels Receipts Average Cost Receipts Average Cost Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMbtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Mcf) (Dollars per MMBtu) (Dollars per Mcf) Percentage of Consumption (Dollars per MMBtu) Annual Totals 2002 47,805 1,639 1.03 29.98 4.85 44.4 3,198,108 3,126,308 3.55 3.63 91.6 2.42 2003 59,377 2,086 0.60 17.16 4.88 64.3 3,335,086 3,244,368 5.33 5.48 96.2 3.15 2004 73,745 2,609 0.72 20.30 4.95 81.0 3,491,942 3,403,474 5.86 6.01 93.1 3.43 2005 92,706 3,277 0.90 25.42 5.09 82.9 3,675,165 3,578,722 8.20 8.42 95.8 4.69

494

SAS Output  

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

9. Coal Stocks at Other Industrial Plants by Census Division and State" 9. Coal Stocks at Other Industrial Plants by Census Division and State" "(thousand short tons)" "Census Division","June 30 2013","March 31 2013","June 30 2012","Percent Change" "and State",,,,"(June 30)" ,,,,"2013 versus 2012" "New England","w","w",21,"w" " Maine","w","w","w","w" " Massachusetts","w","w","w","w" "Middle Atlantic",295,251,286,3.2 " New York",137,78,107,27.6 " Pennsylvania",158,172,179,-11.5 "East North Central",734,692,761,-3.5 " Illinois",160,152,187,-14.1

495

SAS Output  

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

4. Stocks of Coal by Coal Rank: Electric Power Sector, 2002 - 2012 4. Stocks of Coal by Coal Rank: Electric Power Sector, 2002 - 2012 Electric Power Sector Period Bituminous Coal Subbituminous Coal Lignite Coal Total End of Year Stocks 2002 70,704 66,593 4,417 141,714 2003 57,716 59,884 3,967 121,567 2004 49,022 53,618 4,029 106,669 2005 52,923 44,377 3,836 101,137 2006 67,760 68,408 4,797 140,964 2007 63,964 82,692 4,565 151,221 2008 65,818 91,214 4,556 161,589 2009 91,922 92,448 5,097 189,467 2010 81,108 86,915 6,894 174,917 2011 82,056 85,151 5,179 172,387 2012 86,437 93,833 4,846 185,116 2010, End of Month Stocks January 86,354 86,893 4,845 178,091 February 82,469 83,721 4,836 171,026 March 86,698 86,014 5,030 177,742 April 92,621 89,545 7,095 189,260 May 93,069 91,514 7,085 191,669

496

SAS Output  

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

8. U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code" 8. U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code" "(thousand short tons)" ,,,,"Year to Date" "NAICS Code","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "311 Food Manufacturing",2214,2356,1994,4570,4353,5 "312 Beverage and Tobacco Product Mfg.",48,37,53,85,90,-5.6 "313 Textile Mills",31,29,22,59,63,-6.1 "315 Apparel Manufacturing","w","w","w","w","w","w" "321 Wood Product Manufacturing","w","w","w","w","w","w"

497

SAS Output  

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

Average Price of U.S. Metallurgical Coal Exports" Average Price of U.S. Metallurgical Coal Exports" "(dollars per short ton)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",92.5,99.4,146.56,94.82,140.7,-32.6 " Canada*",99.83,125.2,142.46,106.43,138.19,-23 " Dominican Republic",114.6,77.21,"-",77.27,"-","-" " Mexico",78.93,78.54,180.76,78.77,153.65,-48.7 "South America Total",119.26,117.51,167.05,118.3,168.12,-29.6 " Argentina",146.7,131.08,182.47,137.36,196.37,-30.1 " Brazil",119.21,117.38,165.61,118.2,171.84,-31.2

498

SAS Output  

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

Coal Production by State, Mine Type, and Union Status, 2012" Coal Production by State, Mine Type, and Union Status, 2012" "(thousand short tons)" ,"Union",,"Nonunion",,"Total" "Coal-Producing","Underground","Surface","Underground","Surface","Underground","Surface" "State and Region1" "Alabama",12410,"-",139,6669,12549,6669 "Alaska","-",2052,"-","-","-",2052 "Arizona","-",7493,"-","-","-",7493 "Arkansas","-","-",96,"-",96,"-" "Colorado",1673,2655,21955,2265,23628,4920 "Illinois",2897,"-",39939,5649,42837,5649

499

SAS Output  

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

B. Net Generation from Renewable Sources: Total (All Sectors), 2002 - 2012 B. Net Generation from Renewable Sources: Total (All Sectors), 2002 - 2012 (Thousand Megawatthours) Period Wind Solar Photovoltaic Solar Thermal Wood and Wood-Derived Fuels Landfill Gas Biogenic Municipal Solid Waste Other Waste Biomass Geothermal Conventional Hydroelectric Total Renewable Sources Annual Totals 2002 10,354 N/A N/A 38,665 N/A N/A N/A 14,491 264,329 N/A 2003 11,187 2 532 37,529 5,077 8,306 2,428 14,424 275,806 355,293 2004 14,144 6 569 38,117 5,128 8,151 2,141 14,811 268,417 351,485 2005 17,811 16 535 38,856 5,142 8,330 1,948 14,692 270,321 357,651 2006 26,589 15 493 38,762 5,677 8,478 1,944 14,568 289,246 385,772 2007 34,450 16 596 39,014 6,158 8,304 2,063 14,637 247,510 352,747

500

SAS Output  

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

1. Sulfur Dioxide Uncontrolled Emission Factors 1. Sulfur Dioxide Uncontrolled Emission Factors Fuel, Code, Source and Emission Units Combustion System Type / Firing Configuration Fuel EIA Fuel Code Source and Tables (As Appropriate) Emissions Units Lbs = Pounds MMCF = Million Cubic Feet MG = Thousand Gallons Cyclone Boiler Fluidized Bed Boiler Opposed Firing Boiler Spreader Stoker Boiler Tangential Boiler All Other Boiler Types Combustion Turbine Internal Combustion Engine Agricultural Byproducts AB Source: 1 Lbs per ton 0.08 0.01 0.08 0.08 0.08 0.08 N/A N/A Blast Furnace Gas BFG Sources: 1 (including footnote 7 within source); 2, Table 1.4-2 (including footnote d within source) Lbs per MMCF 0.60 0.06 0.60 0.60 0.60 0.60 0.60 0.60 Bituminous Coal* BIT Source: 2, Table 1.1-3 Lbs per ton 38.00 3.80 38.00 38.00 38.00 38.00 N/A N/A