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Note: This page contains sample records for the topic "kwh load profiles" from the National Library of EnergyBeta (NLEBeta).
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they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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1

kWh | OpenEI  

Open Energy Info (EERE)

kWh kWh Dataset Summary Description This dataset contains hourly load profile data for 16 commercial building types (based off the DOE commercial reference building models) and residential buildings (based off the Building America House Simulation Protocols). This dataset also includes the Residential Energy Consumption Survey (RECS) for statistical references of building types by location. Source Commercial and Residential Reference Building Models Date Released April 18th, 2013 (9 months ago) Date Updated July 02nd, 2013 (7 months ago) Keywords building building demand building load Commercial data demand Energy Consumption energy data hourly kWh load profiles Residential Data Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage Frequency Annually

2

load profile | OpenEI Community  

Open Energy Info (EERE)

data load data load profile OpenEI residential load TMY3 United States Load data Image source: NREL Files: applicationzip icon System Advisor Model Tool for Downloading Load Data...

3

Analysis Methodology for Industrial Load Profiles  

E-Print Network (OSTI)

ANALYSIS METHODOLOGY FOR INDUSTRIAL LOAD PROFILES Thomas W. Reddoch Executive Vice President Eleclrolek Concepts, Inc. Knoxvillc, Tennessee ABSTRACT A methodology is provided for evaluating the impact of various demand-side management... (OSM) options on industrial customers. The basic approach uses customer metered load profile data as a basis for the customer load shape. OSM technologies are represented as load shapes and are used as a basis for altering the customers existing...

Reddoch, T. W.

4

max kwh | OpenEI Community  

Open Energy Info (EERE)

max kwh max kwh Home Ewilson's picture Submitted by Ewilson(53) Contributor 4 January, 2013 - 08:42 Rates with tier problems max kwh tiers I've detected that the following rates all have the improper number of "Max kWh" values (should be one less than the number of charges, since the highest tier is always "all remaining"). This is likely due to users not understanding the meaning of "Max kWh"--often I see things like: "300, 700, 1000" (derived from "first 300, next 700, greater than 1000") which should be entered as "300, 1000". This is why we need checks on input that prevent users from entering this incorrectly. Here is the list (my script only checked residential rates): Syndicate content 429 Throttled (bot load)

5

OpenEI Community - load profile  

Open Energy Info (EERE)

/0 en Commercial and /0 en Commercial and Residential Hourly Load Data Now Available on OpenEI! http://en.openei.org/community/blog/commercial-and-residential-hourly-load-data-now-available-openei <span class=Load data" src="http://en.openei.org/community/files/load_data_figure_small.jpg" style="width:527px; height:285px" title="" />Image source: NREL 

Files: 
application/zip icon

6

Water Energy Load Profiling (WELP) Tool | Open Energy Information  

Open Energy Info (EERE)

Water Energy Load Profiling (WELP) Tool Water Energy Load Profiling (WELP) Tool Jump to: navigation, search Tool Summary Name: Water Energy Load Profiling (WELP) Tool Agency/Company /Organization: California Public Utilities Commission (CPUC) Sector: Energy, Water Focus Area: Energy Efficiency, - Embodied Energy, Water Conservation Phase: Determine Baseline, "Evaluate Effectiveness and Revise" is not in the list of possible values (Bring the Right People Together, Create a Vision, Determine Baseline, Evaluate Options, Develop Goals, Prepare a Plan, Get Feedback, Develop Finance and Implement Projects, Create Early Successes, Evaluate Effectiveness and Revise as Needed) for this property. Topics: GHG inventory, Policies/deployment programs, Resource assessment, Background analysis

7

Generation of synthetic benchmark electrical load profiles using publicly available load and weather data  

Science Journals Connector (OSTI)

Abstract Electrical load profiles of a particular region are usually required in order to study the performance of renewable energy technologies and the impact of different operational strategies on the power grid. Load profiles are generally constructed based on measurements and load research surveys which are capital and labour-intensive. In the absence of true load profiles, synthetically generated load profiles can be a viable alternative to be used as benchmarks for research or renewable energy investment planning. In this paper, the feasibility of using publicly available load and weather data to generate synthetic load profiles is investigated. An artificial neural network (ANN) based method is proposed to synthesize load profiles for a target region using its typical meteorological year 2 (TMY2) weather data as the input. To achieve this, the proposed ANN models are first trained using TMY2 weather data and load profile data of neighbouring regions as the input and targeted output. The limited number of data points in the load profile dataset and the consequent averaging of TMY2 weather data to match its period resulted in limited data availability for training. This challenge was tackled by incorporating generalization using Bayesian regularization into training. The other major challenge was facilitating ANN extrapolation and this was accomplished by the incorporation of domain knowledge into the input weather data for training. The performance of the proposed technique has been evaluated by simulation studies and tested on three real datasets. Results indicate that the generated synthetic load profiles closely resemble the real ones and therefore can be used as benchmarks.

Gobind G. Pillai; Ghanim A. Putrus; Nicola M. Pearsall

2014-01-01T23:59:59.000Z

8

Building Energy Software Tools Directory: Prophet Load Profiler  

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

Prophet Load Profiler Prophet Load Profiler Prophet Load Profiler logo. Internet-enabled software that empowers business energy customers to manage energy and reduce costs. Valuable to facility managers, energy managers and energy service companies, the Prophet web-based service delivers real-time and near-real-time energy information on energy consumption and demand for any size facility. A number of facilities can be managed using consumption data gathered in 15 minute, 30 minute, 60 minute, daily, weekly and monthly intervals. Users can immediately view and analyze data with an eye toward load shedding, cost avoidance strategies, energy budget management, utility cost validation and energy forecasting. All tools are contained within the Prophet Web application and enabled via the internet using a standard web

9

Navy Estimated Average Hourly Load Profile by Month (in MW)  

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

Navy Estimated Average Hourly Load Profile by Month (in MW) MONTH HE1 HE2 HE3 HE4 HE5 HE6 HE7 HE8 HE9 HE10 HE11 HE12 HE13 HE14 HE15 HE16 HE17 HE18 HE19 HE20 HE21 HE22 HE23 HE24...

10

Property:Incentive/PVComFitDolKWh | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:Incentive/PVComFitDolKWh Jump to: navigation, search Property Name Incentive/PVComFitDolKWh Property Type String Description Feed-in tariff for commercial systems. The $ amount per kWh generated such that the incentive is disbursed over time based on metered production. 100% of energy generated is exported; none is used on-site. Ex: TVA Green Power Switch $0.15/kWh; We Energies $0.225/kWh Format: $0.225 [1] References ↑ DSIRE Pages using the property "Incentive/PVComFitDolKWh" Showing 25 pages using this property. (previous 25) (next 25) A Alliant Energy (Wisconsin Power and Light) - Advanced Renewables Tariff (Wisconsin) + $0.25 + C CPS Energy - Solartricity Producer Program (Texas) + $0.27 +

11

Property:Incentive/PVResFitDolKWh | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:Incentive/PVResFitDolKWh Jump to: navigation, search Property Name Incentive/PVResFitDolKWh Property Type String Description Feed-in Tariff (FIT): The $ amount per kWh generated such that the incentive is disbursed over time based on metered production. 100% of energy generated is exported; none is used on-site. Ex: TVA Green Power Switch $0.15/kWh; We Energies $0.225/kWh Format: $0.225 [1] References ↑ DSIRE Pages using the property "Incentive/PVResFitDolKWh" Showing 25 pages using this property. (previous 25) (next 25) A Alliant Energy (Wisconsin Power and Light) - Advanced Renewables Tariff (Wisconsin) + $0.25 + C CPS Energy - Solartricity Producer Program (Texas) + $0.27 +

12

Property:Incentive/PVNPFitDolKWh | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:Incentive/PVNPFitDolKWh Jump to: navigation, search Property Name Incentive/PVNPFitDolKWh Property Type String Description Feed-in tariff for non-profit and/or government systems. The $ amount per kWh generated such that the incentive is disbursed over time based on metered production. 100% of energy generated is exported; none is used on-site. Ex: TVA Green Power Switch $0.15/kWh; We Energies $0.225/kWh Format: $0.225 [1] References ↑ DSIRE Pages using the property "Incentive/PVNPFitDolKWh" Showing 25 pages using this property. (previous 25) (next 25) A Alliant Energy (Wisconsin Power and Light) - Advanced Renewables Tariff (Wisconsin) + $0.25 + C CPS Energy - Solartricity Producer Program (Texas) + $0.27 +

13

Extension of multivariate regression trees to interval data. Application to electricity load profiling  

Science Journals Connector (OSTI)

Several data can be presented as interval curves where ... particular, this representation is well adapted for load profiles, which depict the electricity consumption of a class of customers. Electricity load pro...

Vronique Cariou

2006-01-01T23:59:59.000Z

14

Commercial and Residential Hourly Load Profiles for all TMY3 Locations in  

Open Energy Info (EERE)

and Residential Hourly Load Profiles for all TMY3 Locations in and Residential Hourly Load Profiles for all TMY3 Locations in the United States Dataset Summary Description This dataset contains hourly load profile data for 16 commercial building types (based off the DOE commercial reference building models) and residential buildings (based off the Building America House Simulation Protocols). This dataset also includes the Residential Energy Consumption Survey (RECS) for statistical references of building types by location. Hourly load profiles are available for over all TMY3 locations in the United States here. Browse files in this dataset, accessible as individual files and as commercial and residential downloadable ZIP files. This dataset is approximately 4.8GiB compressed or 19GiB uncompressed. July 2nd, 2013 update: Residential High and Low load files have been updated from 366 days in a year for leap years to the more general 365 days in a normal year.

15

load | OpenEI  

Open Energy Info (EERE)

load load Dataset Summary Description This dataset contains hourly load profile data for 16 commercial building types (based off the DOE commercial reference building models) and residential buildings (based off the Building America House Simulation Protocols). This dataset also includes the Residential Energy Consumption Survey (RECS) for statistical references of building types by location. Source Commercial and Residential Reference Building Models Date Released April 18th, 2013 (9 months ago) Date Updated July 02nd, 2013 (7 months ago) Keywords building building demand building load Commercial data demand Energy Consumption energy data hourly kWh load profiles Residential Data Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage Frequency Annually

16

Variability of Behaviour in Electricity Load Profile Clustering; Who Does Things at the  

E-Print Network (OSTI)

Variability of Behaviour in Electricity Load Profile Clustering; Who Does Things at the Same Time://ima.ac.uk/dent 2 The James Hutton Institute, Aberdeen, UK Abstract. UK electricity market changes provide opportunities to alter households' electricity usage patterns for the benefit of the overall elec- tricity

Aickelin, Uwe

17

profiles | OpenEI  

Open Energy Info (EERE)

profiles profiles Dataset Summary Description This dataset contains hourly load profile data for 16 commercial building types (based off the DOE commercial reference building models) and residential buildings (based off the Building America House Simulation Protocols). This dataset also includes the Residential Energy Consumption Survey (RECS) for statistical references of building types by location. Source Commercial and Residential Reference Building Models Date Released April 18th, 2013 (9 months ago) Date Updated July 02nd, 2013 (7 months ago) Keywords building building demand building load Commercial data demand Energy Consumption energy data hourly kWh load profiles Residential Data Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage Frequency Annually

18

building load | OpenEI  

Open Energy Info (EERE)

load load Dataset Summary Description This dataset contains hourly load profile data for 16 commercial building types (based off the DOE commercial reference building models) and residential buildings (based off the Building America House Simulation Protocols). This dataset also includes the Residential Energy Consumption Survey (RECS) for statistical references of building types by location. Source Commercial and Residential Reference Building Models Date Released April 18th, 2013 (9 months ago) Date Updated July 02nd, 2013 (7 months ago) Keywords building building demand building load Commercial data demand Energy Consumption energy data hourly kWh load profiles Residential Data Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage Frequency Annually

19

Microsoft Word - Load Availability Profiles and Constraints for the Western Interconnect_102513_clean.docx  

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

7E 7E Grid Integration of Aggregated Demand Response, Part I: Load Availability Profiles and Constraints for the Western Interconnection Daniel J. Olsen, Nance Matson, Michael D. Sohn, Cody Rose, Junqiao Dudley, Sasank Goli, and Sila Kiliccote Lawrence Berkeley National Laboratory Marissa Hummon, David Palchak, Paul Denholm, and Jennie Jorgenson National Renewable Energy Laboratory Ookie Ma U.S. Department of Energy September 2013 Disclaimer Acknowledgements Abstract Foreword Table of Contents List of Figures List of Tables Executive Summary Introduction ≤ ≤ ≤

20

Beyond kWh and kW demand: Understanding the new real-time electric power  

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

Beyond kWh and kW demand: Understanding the new real-time electric power Beyond kWh and kW demand: Understanding the new real-time electric power measurement system in LBNL Building 90 Speaker(s): Alex McEachern Date: January 14, 2010 - 12:00pm Location: 90-3122 In the Summer of 2009, LBNL researchers installed end-use sub-metering equipment and associated Energy Information System (EIS) tools to characterize energy use and comfort in Building 90. Seven of 40 key electric loads were measured using advanced meters that make sophisticated real-time measurements of dozens of power flow parameters, power disturbances, and harmonics. The talk will review some electrical engineering fundamentals, how use and interpret data measured in building 90 in real-time. The real-time data available includes power, volt-amps, VAR's, unbalance voltage and current, voltage and current distortion,

Note: This page contains sample records for the topic "kwh load profiles" 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

Load Scheduling with Profile Information ? Gotz Lindenmaier 1 , Kathryn S. M c Kinley 2 , and Olivier Temam 3  

E-Print Network (OSTI)

Load Scheduling with Profile Information ? G?otz Lindenmaier 1 , Kathryn S. M c Kinley 2, Universit?at Karlsruhe 2 Department of Computer Science, University of Massachusetts 3 Laboratoire de have added hardware per­ formance counters to their microprocessors to generate profile data cheaply

Massachusetts at Amherst, University of

22

KWH_APS_DPP07_1Page.ppt  

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

Ion-Temperature and Rotation-Velocity Profiles from a Spatially Resolving X-Ray Crystal Spectrometer on Alcator C-Mod Ion-Temperature and Rotation-Velocity Profiles from a Spatially Resolving X-Ray Crystal Spectrometer on Alcator C-Mod K. W. Hill, 1 M. Bitter, 1 P. Beiersdorfer, 3 Ch. Broennimann, 4 E. F. Eikenberry, 4 A. Ince-Cushman, 2 Ming-Feng Gu, 3 S. G. Lee, 5 M. Reinke, 2 J. E. Rice, 2 S. D. Scott, 1 and B. Stratton 1 1 Princeton Plasma Physics Laboratory, Princeton, NJ 2 MIT Plasma Science and Fusion Center, Cambridge, MA 3 LLNL, Livermore, CA 4 DECTRIS Ltd., 5232 Villigen-PSI, Switzerland 5 NFRC, Korea Basic Science Institute, Daejeon, Korea Abstract A new x-ray crystal spectrometer capable of providing spatially (~1.5 cm) and temporally (~10 ms) resolved, high resolution spectra of He-like Ar Kα lines has been installed on Alcator C-Mod. The imaging spectrometer consists of a

23

Daily load profile and monthly power peaks evaluation of the urban substation of the capital of Jordan Amman  

Science Journals Connector (OSTI)

The hourly recorded power of an urban substation of the National Electric Power Company (NEPCO) in the capital of Jordan Amman is used to calculate the diversity and conversion factors of the substation. These factors are used to estimate the daily load power profile and the monthly peak power of the substation. The results show that the conversion factors are almost independent of the number of feeders in the substation, while the diversity factors vary in substations that have six feeders or less. The results show a good correlation between the estimated and actual recorded data of the daily load profile with less than 5% percentage error.

Nabeel I.A. Tawalbeh

2012-01-01T23:59:59.000Z

24

Identifying Customer Profiles in Power Load Time Series Using Spectral Clustering  

Science Journals Connector (OSTI)

An application of multiway spectral clustering with out-of-sample extensions towards clustering time series is presented. The data correspond to power load time series acquired from substations in the ... eigenve...

Carlos Alzate; Marcelo Espinoza; Bart De Moor

2009-01-01T23:59:59.000Z

25

Property:Building/SPBreakdownOfElctrcityUseKwhM2Total | Open Energy  

Open Energy Info (EERE)

SPBreakdownOfElctrcityUseKwhM2Total" SPBreakdownOfElctrcityUseKwhM2Total" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 71.4577086539 + Sweden Building 05K0002 + 110.926946534 + Sweden Building 05K0003 + 72.9096074806 + Sweden Building 05K0004 + 66.0248923654 + Sweden Building 05K0005 + 54.8654809632 + Sweden Building 05K0006 + 65.291976787 + Sweden Building 05K0007 + 65.5403331042 + Sweden Building 05K0008 + 41.6418235453 + Sweden Building 05K0009 + 56.5413268466 + Sweden Building 05K0010 + 150.269021739 + Sweden Building 05K0011 + 27.5018481341 + Sweden Building 05K0012 + 37.9937990385 + Sweden Building 05K0013 + 68.8990371973 + Sweden Building 05K0014 + 166.794253904 + Sweden Building 05K0015 + 71.0813662687 + Sweden Building 05K0016 + 38.5267410327 +

26

Property:Building/SPPurchasedEngyPerAreaKwhM2Total | Open Energy  

Open Energy Info (EERE)

SPPurchasedEngyPerAreaKwhM2Total" SPPurchasedEngyPerAreaKwhM2Total" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 221.549575215 + Sweden Building 05K0002 + 213.701117318 + Sweden Building 05K0003 + 195.801526718 + Sweden Building 05K0004 + 174.148148148 + Sweden Building 05K0005 + 340.088495575 + Sweden Building 05K0006 + 211.255924171 + Sweden Building 05K0007 + 144.028151521 + Sweden Building 05K0008 + 171.282051282 + Sweden Building 05K0009 + 140.296360236 + Sweden Building 05K0010 + 300.961098398 + Sweden Building 05K0011 + 98.1045751634 + Sweden Building 05K0012 + 106.609793929 + Sweden Building 05K0013 + 175.776187637 + Sweden Building 05K0014 + 291.160427408 + Sweden Building 05K0015 + 174.193548387 + Sweden Building 05K0016 + 145.793794187 +

27

Property:Building/SPPurchasedEngyPerAreaKwhM2DstrtHeating | Open Energy  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:Building/SPPurchasedEngyPerAreaKwhM2DstrtHeating Jump to: navigation, search This is a property of type String. District heating Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2DstrtHeating" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 111.56331078 + Sweden Building 05K0002 + 72.7932960894 + Sweden Building 05K0003 + 111.899416255 + Sweden Building 05K0004 + 72.865497076 + Sweden Building 05K0005 + 285.840707965 + Sweden Building 05K0006 + 128.449958182 + Sweden Building 05K0007 + 63.8377147588 + Sweden Building 05K0008 + 115.128205128 + Sweden Building 05K0009 + 66.5515753129 + Sweden Building 05K0010 + 148.741418764 +

28

Property:Building/SPBreakdownOfElctrcityUseKwhM2Misc | Open Energy  

Open Energy Info (EERE)

SPBreakdownOfElctrcityUseKwhM2Misc SPBreakdownOfElctrcityUseKwhM2Misc Jump to: navigation, search This is a property of type String. Miscellaneous Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Misc" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 9.09953195331 + Sweden Building 05K0003 + 8.78442379242 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 12.9530389597 + Sweden Building 05K0008 + 6.03377747253 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 10.9950724049 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 14.2856105095 + Sweden Building 05K0014 + 27.8718727739 +

29

Property:Building/SPPurchasedEngyPerAreaKwhM2Oil-FiredBoiler | Open Energy  

Open Energy Info (EERE)

SPPurchasedEngyPerAreaKwhM2Oil-FiredBoiler SPPurchasedEngyPerAreaKwhM2Oil-FiredBoiler Jump to: navigation, search This is a property of type String. Oil-fired boiler Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2Oil-FiredBoiler" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 +

30

Property:Building/SPBreakdownOfElctrcityUseKwhM2HeatPumps | Open Energy  

Open Energy Info (EERE)

SPBreakdownOfElctrcityUseKwhM2HeatPumps SPBreakdownOfElctrcityUseKwhM2HeatPumps Jump to: navigation, search This is a property of type String. Heat pumps Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2HeatPumps" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 +

31

Property:Building/SPPurchasedEngyPerAreaKwhM2ElctrcHeating | Open Energy  

Open Energy Info (EERE)

SPPurchasedEngyPerAreaKwhM2ElctrcHeating" SPPurchasedEngyPerAreaKwhM2ElctrcHeating" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.915704329247 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.745132743363 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 25.8064516129 + Sweden Building 05K0016 + 5.89159465829 + Sweden Building 05K0017 + 0.0 + Sweden Building 05K0018 + 0.0 + Sweden Building 05K0019 + 0.0 +

32

Property:Building/SPBreakdownOfElctrcityUseKwhM2ElctrcHeating | Open Energy  

Open Energy Info (EERE)

SPBreakdownOfElctrcityUseKwhM2ElctrcHeating" SPBreakdownOfElctrcityUseKwhM2ElctrcHeating" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.915704329247 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.745132743363 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 25.8064516129 + Sweden Building 05K0016 + 5.89159465829 + Sweden Building 05K0017 + 0.0 + Sweden Building 05K0018 + 0.0 + Sweden Building 05K0019 + 0.0 +

33

Characterizing probability density distributions for household electricity load profiles from high-resolution electricity use data  

Science Journals Connector (OSTI)

Abstract This paper presents a high-resolution bottom-up model of electricity use in an average household based on fit to probability distributions of a comprehensive high-resolution household electricity use data set for detached houses in Sweden. The distributions used in this paper are the Weibull distribution and the Log-Normal distribution. These fitted distributions are analyzed in terms of relative variation estimates of electricity use and standard deviation. It is concluded that the distributions have a reasonable overall goodness of fit both in terms of electricity use and standard deviation. A KolmogorovSmirnov test of goodness of fit is also provided. In addition to this, the model is extended to multiple households via convolution of individual electricity use profiles. With the use of the central limit theorem this is analytically extended to the general case of a large number of households. Finally a brief comparison with other models of probability distributions is made along with a discussion regarding the model and its applicability.

Joakim Munkhammar; Jesper Rydn; Joakim Widn

2014-01-01T23:59:59.000Z

34

Energy conservation in high-rise buildings: Changes in air conditioning load induced by vertical temperature and humidity profile in Delhi  

Science Journals Connector (OSTI)

Temperature and humidity profiles in the upper atmosphere are different from those observed by ground level meteorological stations and used to design HVAC systems for high-rise buildings. There exist correlations among solar energy, atmospheric turbidity and pollutants in urban areas, affecting the temperature and humidity profiles with variation in height. In the present study, a theoretical model is developed considering these parameters, and the HVAC load is calculated. The results are compared with the HVAC load calculated from data obtained from the meteorological station, and the comparison showed that the results differ significantly (20%) for a hypothetical 200 m high office building.

S. Sinha; Sanjay Kumar; N. Kumar

1998-01-01T23:59:59.000Z

35

Property:Building/SPPurchasedEngyPerAreaKwhM2OtherElctrty | Open Energy  

Open Energy Info (EERE)

OtherElctrty OtherElctrty Jump to: navigation, search This is a property of type String. Other electricity Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2OtherElctrty" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 70.305743501 + Sweden Building 05K0002 + 95.9357541899 + Sweden Building 05K0003 + 72.2496632241 + Sweden Building 05K0004 + 65.8830409357 + Sweden Building 05K0005 + 53.5026548673 + Sweden Building 05K0006 + 58.7608028994 + Sweden Building 05K0007 + 61.5607534672 + Sweden Building 05K0008 + 40.3846153846 + Sweden Building 05K0009 + 56.4810818587 + Sweden Building 05K0010 + 152.219679634 + Sweden Building 05K0011 + 25.5555555556 + Sweden Building 05K0012 + 35.8807888323 + Sweden Building 05K0013 + 61.3267863536 +

36

Property:Building/SPBreakdownOfElctrcityUseKwhM2Pumps | Open Energy  

Open Energy Info (EERE)

Pumps Pumps Jump to: navigation, search This is a property of type String. Pumps Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Pumps" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 6.37190900733 + Sweden Building 05K0002 + 6.03888185355 + Sweden Building 05K0003 + 3.38991548528 + Sweden Building 05K0004 + 4.33303636174 + Sweden Building 05K0005 + 2.75390897598 + Sweden Building 05K0006 + 7.77750996655 + Sweden Building 05K0007 + 1.66724551261 + Sweden Building 05K0008 + 3.32543498168 + Sweden Building 05K0009 + 3.08636405861 + Sweden Building 05K0010 + 14.8373684211 + Sweden Building 05K0011 + 1.47492819795 + Sweden Building 05K0012 + 3.32673206926 + Sweden Building 05K0013 + 2.63132906976 +

37

Property:Building/SPBreakdownOfElctrcityUseKwhM2LargeComputersServers |  

Open Energy Info (EERE)

LargeComputersServers LargeComputersServers Jump to: navigation, search This is a property of type String. Large computers / servers Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2LargeComputersServers" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 2.88701226026 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 3.90838206628 + Sweden Building 05K0005 + 0.697674418605 + Sweden Building 05K0006 + 1.18332311465 + Sweden Building 05K0007 + 11.4098804421 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.556088941246 + Sweden Building 05K0010 + 10.0228832952 + Sweden Building 05K0011 + 0.471022727273 + Sweden Building 05K0012 + 0.774049003718 + Sweden Building 05K0013 + 0.0 +

38

Property:Building/SPBreakdownOfElctrcityUseKwhM2Elevators | Open Energy  

Open Energy Info (EERE)

Elevators Elevators Jump to: navigation, search This is a property of type String. Elevators Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Elevators" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.139664804469 + Sweden Building 05K0003 + 5.78356533453 + Sweden Building 05K0004 + 0.0116959064327 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.699648105982 + Sweden Building 05K0008 + 0.192307692308 + Sweden Building 05K0009 + 0.0661775284132 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.163674492353 + Sweden Building 05K0014 + 2.7497571546 +

39

Property:Building/SPBreakdownOfElctrcityUseKwhM2Fans | Open Energy  

Open Energy Info (EERE)

Fans Fans Jump to: navigation, search This is a property of type String. Fans Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Fans" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 5.21311928139 + Sweden Building 05K0002 + 18.5995610535 + Sweden Building 05K0003 + 20.3514016294 + Sweden Building 05K0004 + 8.08671679198 + Sweden Building 05K0005 + 16.0166245259 + Sweden Building 05K0006 + 10.358795651 + Sweden Building 05K0007 + 8.3953561818 + Sweden Building 05K0008 + 9.28527472527 + Sweden Building 05K0009 + 12.8398873749 + Sweden Building 05K0010 + 20.0966982674 + Sweden Building 05K0011 + 6.90408963585 + Sweden Building 05K0012 + 8.60719192175 + Sweden Building 05K0013 + 16.7539365907 +

40

Property:Building/SPBreakdownOfElctrcityUseKwhM2Copiers | Open Energy  

Open Energy Info (EERE)

Copiers Copiers Jump to: navigation, search This is a property of type String. Copiers Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Copiers" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.85593220339 + Sweden Building 05K0003 + 0.447247706422 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.897811865554 + Sweden Building 05K0008 + 0.9 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 7.78032036613 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 1.24104401228 + Sweden Building 05K0014 + 2.91414481058 + Sweden Building 05K0015 + 0.41935483871 +

Note: This page contains sample records for the topic "kwh load profiles" 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

Property:Building/SPPurchasedEngyPerAreaKwhM2ElctrtyTotal | Open Energy  

Open Energy Info (EERE)

ElctrtyTotal ElctrtyTotal Jump to: navigation, search This is a property of type String. Electricity, total Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2ElctrtyTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 71.2214478303 + Sweden Building 05K0002 + 95.9357541899 + Sweden Building 05K0003 + 72.2496632241 + Sweden Building 05K0004 + 65.8830409357 + Sweden Building 05K0005 + 54.2477876106 + Sweden Building 05K0006 + 58.7608028994 + Sweden Building 05K0007 + 61.5607534672 + Sweden Building 05K0008 + 40.3846153846 + Sweden Building 05K0009 + 56.4810818587 + Sweden Building 05K0010 + 152.219679634 + Sweden Building 05K0011 + 25.5555555556 + Sweden Building 05K0012 + 35.8807888323 + Sweden Building 05K0013 + 61.3267863536 +

42

Property:Building/SPBreakdownOfElctrcityUseKwhM2CirculationFans | Open  

Open Energy Info (EERE)

CirculationFans CirculationFans Jump to: navigation, search This is a property of type String. Circulation fans Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2CirculationFans" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 13.3422495258 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 2.80646609789 + Sweden Building 05K0004 + 8.95823904901 + Sweden Building 05K0005 + 5.55016340076 + Sweden Building 05K0006 + 6.81308969891 + Sweden Building 05K0007 + 2.02541916787 + Sweden Building 05K0008 + 0.625641025641 + Sweden Building 05K0009 + 7.59721281624 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.757191316527 + Sweden Building 05K0012 + 6.04077487892 + Sweden Building 05K0013 + 0.767224182906 +

43

Property:Building/SPPurchasedEngyPerAreaKwhM2DstrtColg | Open Energy  

Open Energy Info (EERE)

DstrtColg DstrtColg Jump to: navigation, search This is a property of type String. District cooling Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2DstrtColg" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 38.7648166048 + Sweden Building 05K0002 + 44.9720670391 + Sweden Building 05K0003 + 11.6524472384 + Sweden Building 05K0004 + 35.3996101365 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 24.0451630889 + Sweden Building 05K0007 + 18.6296832954 + Sweden Building 05K0008 + 15.7692307692 + Sweden Building 05K0009 + 17.2637030643 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 5.09803921569 + Sweden Building 05K0012 + 15.0675825393 + Sweden Building 05K0013 + 21.4822771214 +

44

Property:Building/SPBreakdownOfElctrcityUseKwhM2AirCompressors | Open  

Open Energy Info (EERE)

AirCompressors AirCompressors Jump to: navigation, search This is a property of type String. Air compressors Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2AirCompressors" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 1.33591087145 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 1.86549707602 + Sweden Building 05K0005 + 2.04651162791 + Sweden Building 05K0006 + 1.92596566524 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.970107495214 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 1.30894886364 + Sweden Building 05K0012 + 2.01978262942 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 +

45

Property:Building/SPBreakdownOfElctrcityUseKwhM2Lighting | Open Energy  

Open Energy Info (EERE)

This is a property of type String. This is a property of type String. Lighting Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Lighting" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 13.6004313481 + Sweden Building 05K0002 + 51.2740526316 + Sweden Building 05K0003 + 25.3519773429 + Sweden Building 05K0004 + 14.5539566929 + Sweden Building 05K0005 + 17.1088606195 + Sweden Building 05K0006 + 11.7758321884 + Sweden Building 05K0007 + 16.0796522459 + Sweden Building 05K0008 + 15.7053876478 + Sweden Building 05K0009 + 19.44639866 + Sweden Building 05K0010 + 37.0625 + Sweden Building 05K0011 + 12.9336787565 + Sweden Building 05K0012 + 12.985779547 + Sweden Building 05K0013 + 21.6361810339 + Sweden Building 05K0014 + 29.853732347 +

46

Property:Building/SPBreakdownOfElctrcityUseKwhM2LargeKitchens | Open Energy  

Open Energy Info (EERE)

LargeKitchens LargeKitchens Jump to: navigation, search This is a property of type String. Large kitchens Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2LargeKitchens" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.763086941039 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.409356725146 + Sweden Building 05K0005 + 2.13953488372 + Sweden Building 05K0006 + 0.383200490497 + Sweden Building 05K0007 + 3.38701556508 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.294507436313 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.177556818182 + Sweden Building 05K0012 + 0.0953379731147 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 +

47

Property:Building/SPBreakdownOfElctrcityUseKwhM2Pcs | Open Energy  

Open Energy Info (EERE)

Pcs Pcs Jump to: navigation, search This is a property of type String. PCs Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Pcs" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 26.0998626444 + Sweden Building 05K0002 + 22.2888135593 + Sweden Building 05K0003 + 4.12075688073 + Sweden Building 05K0004 + 22.9175048733 + Sweden Building 05K0005 + 6.03962790698 + Sweden Building 05K0006 + 15.790619252 + Sweden Building 05K0007 + 5.8172794947 + Sweden Building 05K0008 + 4.66333333333 + Sweden Building 05K0009 + 8.50154616404 + Sweden Building 05K0010 + 8.05491990847 + Sweden Building 05K0011 + 2.70028409091 + Sweden Building 05K0012 + 2.19353608542 + Sweden Building 05K0013 + 8.43270214944 +

48

Property:Building/SPBreakdownOfElctrcityUseKwhM2Printers | Open Energy  

Open Energy Info (EERE)

Printers Printers Jump to: navigation, search This is a property of type String. Printers Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Printers" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.928422444931 + Sweden Building 05K0002 + 1.42372881356 + Sweden Building 05K0003 + 0.412844036697 + Sweden Building 05K0004 + 0.980506822612 + Sweden Building 05K0005 + 1.76744186047 + Sweden Building 05K0006 + 1.27988963826 + Sweden Building 05K0007 + 1.12158808933 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.765719334413 + Sweden Building 05K0010 + 1.01601830664 + Sweden Building 05K0011 + 0.774147727273 + Sweden Building 05K0012 + 1.11545428544 + Sweden Building 05K0013 + 0.549891248721 +

49

Property:Building/SPBreakdownOfElctrcityUseKwhM2SmallKitchensCoffeeRms |  

Open Energy Info (EERE)

SmallKitchensCoffeeRms SmallKitchensCoffeeRms Jump to: navigation, search This is a property of type String. Small kitchens / coffee rooms Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2SmallKitchensCoffeeRms" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 1.20677966102 + Sweden Building 05K0003 + 1.46100917431 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 2.53105456775 + Sweden Building 05K0007 + 1.08639747349 + Sweden Building 05K0008 + 0.910666666667 + Sweden Building 05K0009 + 2.06390811368 + Sweden Building 05K0010 + 3.29519450801 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 1.54234902764 +

50

Property:Building/SPBreakdownOfElctrcityUseKwhM2Refrigeration | Open Energy  

Open Energy Info (EERE)

Refrigeration Refrigeration Jump to: navigation, search This is a property of type String. Refrigeration Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Refrigeration" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 2.77390577084 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 37.1080462614 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.895094880057 + Sweden Building 05K0014 + 12.4536103016 + Sweden Building 05K0015 + 0.0 +

51

Design and testing of the HTS bearing for a 10 kWh flywheel system  

Science Journals Connector (OSTI)

Flywheels are of interest for a wide range of energy storage applications, from support of renewable resources to distributed power applications and uninterruptible power systems (UPS) (Day et al 2000 Proc. EESAT 2000 (Orlando, FL, Sept. 2000)). The use of high-temperature superconducting (HTS) bearings for such systems has significant advantages for applications requiring large amounts of energy to be stored with low parasitic losses and with minimal system maintenance. As flywheel systems increase in size, it becomes a significant challenge to provide adequate stiffness in these bearings without exceeding the strength limits of rotating magnet assemblies. The Boeing Company is designing and building a prototype flywheel of 10 kWh total stored energy and has focused much effort on the HTS bearing system. This paper will describe the general structure of the bearing and the steps taken to optimize its magnetic and structural performance and show recent test results.

A C Day; M Strasik; K E McCrary; P E Johnson; J W Gabrys; J R Schindler; R A Hawkins; D L Carlson; M D Higgins; J R Hull

2002-01-01T23:59:59.000Z

52

Property:Building/SPPurchasedEngyPerAreaKwhM2DigesterLandfillGas | Open  

Open Energy Info (EERE)

DigesterLandfillGas DigesterLandfillGas Jump to: navigation, search This is a property of type String. Digester / landfill gas Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2DigesterLandfillGas" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 +

53

Property:Building/SPBreakdownOfElctrcityUseKwhM2Laundry | Open Energy  

Open Energy Info (EERE)

Laundry Laundry Jump to: navigation, search This is a property of type String. Laundry Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2Laundry" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 +

54

Property:Building/SPPurchasedEngyPerAreaKwhM2WoodChips | Open Energy  

Open Energy Info (EERE)

WoodChips WoodChips Jump to: navigation, search This is a property of type String. Wood chips Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2WoodChips" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 +

55

Property:Building/SPPurchasedEngyPerAreaKwhM2Pellets | Open Energy  

Open Energy Info (EERE)

Pellets Pellets Jump to: navigation, search This is a property of type String. Pellets Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2Pellets" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 +

56

Property:Building/SPPurchasedEngyPerAreaKwhM2Other | Open Energy  

Open Energy Info (EERE)

This is a property of type String. This is a property of type String. Other Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2Other" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 + Sweden Building 05K0018 + 0.0 +

57

Property:Building/SPPurchasedEngyPerAreaKwhM2Logs | Open Energy Information  

Open Energy Info (EERE)

Logs Logs Jump to: navigation, search This is a property of type String. Logs Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2Logs" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 +

58

Property:Building/SPBreakdownOfElctrcityUseKwhM2ElctrcEngineHeaters | Open  

Open Energy Info (EERE)

ElctrcEngineHeaters ElctrcEngineHeaters Jump to: navigation, search This is a property of type String. Electric engine heaters Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2ElctrcEngineHeaters" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 2.44788473329 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.353408923575 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.835160644485 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 +

59

Property:Building/SPPurchasedEngyPerAreaKwhM2TownGas | Open Energy  

Open Energy Info (EERE)

TownGas TownGas Jump to: navigation, search This is a property of type String. Town gas Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2TownGas" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 +

60

Property:Building/SPPurchasedEngyPerAreaKwhM2NaturalGas | Open Energy  

Open Energy Info (EERE)

NaturalGas NaturalGas Jump to: navigation, search This is a property of type String. Natural gas Pages using the property "Building/SPPurchasedEngyPerAreaKwhM2NaturalGas" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.0 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 + Sweden Building 05K0016 + 0.0 + Sweden Building 05K0017 + 0.0 +

Note: This page contains sample records for the topic "kwh load profiles" 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

Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection  

E-Print Network (OSTI)

is estimated. Keywords: Demand response, ancillary services,of Aggregated Demand Response, Part 1: Load Availabilityof Energy (DOE) Demand Response and Energy Storage

Olsen, Daniel J.

2014-01-01T23:59:59.000Z

62

Using measured equipment load profiles to 'right-size' HVACsystems and reduce energy use in laboratory buildings (Pt. 2)  

SciTech Connect

There is a general paucity of measured equipment load datafor laboratories and other complex buildings and designers often useestimates based on nameplate rated data or design assumptions from priorprojects. Consequently, peak equipment loads are frequentlyoverestimated, and load variation across laboratory spaces within abuilding is typically underestimated. This results in two design flaws.Firstly, the overestimation of peak equipment loads results in over-sizedHVAC systems, increasing initial construction costs as well as energy usedue to inefficiencies at low part-load operation. Secondly, HVAC systemsthat are designed without accurately accounting for equipment loadvariation across zones can significantly increase simultaneous heatingand cooling, particularly for systems that use zone reheat fortemperature control. Thus, when designing a laboratory HVAC system, theuse of measured equipment load data from a comparable laboratory willsupport right-sizing HVAC systems and optimizing their configuration tominimize simultaneous heating and cooling, saving initial constructioncosts as well as life-cycle energy costs.In this paper, we present datafrom recent studies to support the above thesis. We first presentmeasured equipment load data from two sources: time-series measurementsin several laboratory modules in a university research laboratorybuilding; and peak load data for several facilities recorded in anational energy benchmarking database. We then contrast this measureddata with estimated values that are typically used for sizing the HVACsystems in these facilities, highlighting the over-sizing problem. Next,we examine the load variation in the time series measurements and analyzethe impact of this variation on energy use, via parametric energysimulations. We then briefly discuss HVAC design solutions that minimizesimultaneous heating and cooling energy use.

Mathew, Paul; Greenberg, Steve; Frenze, David; Morehead, Michael; Sartor, Dale; Starr, William

2005-06-29T23:59:59.000Z

63

Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection  

E-Print Network (OSTI)

0.20-2.33 (0.80) 0.35-4.09 (1.78) BPA 0.10-0.85 (0.35) 0.14-of Load M [ PSE i _ SCL 339%! BpA 032? a 042? } TPWR; 285 MWh 275 MWh 3,200 MWh BPA 68 MW 788 MW 97 MWh 478 MWh

Olsen, Daniel J.

2014-01-01T23:59:59.000Z

64

Property:Building/SPBreakdownOfElctrcityUseKwhM2HeatPumpsUsedForColg | Open  

Open Energy Info (EERE)

HeatPumpsUsedForColg HeatPumpsUsedForColg Jump to: navigation, search This is a property of type String. Heat pumps used for cooling Pages using the property "Building/SPBreakdownOfElctrcityUseKwhM2HeatPumpsUsedForColg" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 0.0 + Sweden Building 05K0002 + 0.0 + Sweden Building 05K0003 + 0.0 + Sweden Building 05K0004 + 0.0 + Sweden Building 05K0005 + 0.0 + Sweden Building 05K0006 + 0.250906049624 + Sweden Building 05K0007 + 0.0 + Sweden Building 05K0008 + 0.0 + Sweden Building 05K0009 + 0.0 + Sweden Building 05K0010 + 0.0 + Sweden Building 05K0011 + 0.0 + Sweden Building 05K0012 + 0.0 + Sweden Building 05K0013 + 0.0 + Sweden Building 05K0014 + 0.0 + Sweden Building 05K0015 + 0.0 +

65

Chlorine hazard evaluation for the zinc-chlorine electric vehicle battery. Final technical report. [50 kWh  

SciTech Connect

Hazards associated with conceivable accidental chlorine releases from zinc-chlorine electric vehicle batteries are evaluated. Since commercial batteries are not yet available, this hazard assessment is based on both theoretical chlorine dispersion models and small-scale and large-scale spill tests with chlorine hydrate (which is the form of chlorine storage in the charged battery). Six spill tests involving the chlorine hydrate equivalent of a 50-kWh battery indicate that the danger zone in which chlorine vapor concentrations intermittently exceed 100 ppM extends at least 23 m directly downwind of a spill onto a warm (30 to 38/sup 0/C) road surface. Other accidental chlorine release scenarios may also cause some distress, but are not expected to produce the type of life-threatening chlorine exposures that can result from large hydrate spills. Chlorine concentration data from the hydrate spill tests compare favorably with calculations based on a quasi-steady area source dispersion model and empirical estimates of the hydrate decomposition rate. The theoretical dispersion model was combined with assumed hydrate spill probabilities and current motor vehicle accident statistics in order to project expected chlorine-induced fatality rates. These calculations indicate that expected chlorine fataility rates are several times higher in a city such as Los Angeles with a warm and calm climate than in a colder and windier city such as Boston. Calculated chlorine-induced fatality rate projections for various climates are presented as a function of hydrate spill probability in order to illustrate the degree of vehicle/battery crashworthiness required to maintain chlorine-induced fatality rates below current vehicle fatality rates due to fires and asphyxiations. 37 figures, 19 tables.

Zalosh, R. G.; Bajpai, S. N.; Short, T. P.; Tsui, R. K.

1980-04-01T23:59:59.000Z

66

Interpreting human activity from electrical consumption data through non-intrusive load monitoring  

E-Print Network (OSTI)

Non-intrusive load monitoring (NILM) has three distinct advantages over today's smart meters. First, it offers accountability. Few people know where their kWh's are going. Second, it is a maintenance tool. Signs of wear ...

Gillman, Mark Daniel

2014-01-01T23:59:59.000Z

67

load data | OpenEI Community  

Open Energy Info (EERE)

51 51 Varnish cache server Home Groups Community Central Green Button Applications Developer Utility Rate FRED: FRee Energy Database More Public Groups Private Groups Features Groups Blog posts Content Stream Documents Discussions Polls Q & A Events Notices My stuff Energy blogs 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2142234851 Varnish cache server load data Home Sfomail's picture Submitted by Sfomail(48) Member 17 May, 2013 - 12:03 Commercial and Residential Hourly Load Data Now Available on OpenEI! building load building load data commercial load data dataset datasets electric load data load data load profile OpenEI residential load TMY3 United States Load data Image source: NREL Files: application/zip icon System Advisor Model Tool for Downloading Load Data

68

A Study of the Pre-Programmed Thermostat Timer as a Load Control Device  

E-Print Network (OSTI)

. The purpose of this research was to determine if a pre-programs3 thmstat timing device can operate similarly to a dispatcher controlled load managanent device to rehce peak generation dmds without adversely affecting energy kwh) sales. SCOPE: The scope... of this research is: (1) to detennine if the device can be used as a viable means of load reduction, (2) to determine the parameters for equiprent and programing for more extensive research involving dispatcher control of dis- tribution load, and (3...

Wallace, M. L.; Thedford, M.

1985-01-01T23:59:59.000Z

69

Plug Load  

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

Residential Commercial Commercial Industrial Lighting Energy Smart Grocer Program HVAC Program Shell Measures Commercial Kitchen & Food Service Equipment Plug Load New...

70

Load Control  

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

Visualization and Controls Peer Review Visualization and Controls Peer Review Load Control for System Reliability and Measurement-Based Stability Assessment Dan Trudnowski, PhD, PE Montana Tech Butte, MT 59701 dtrudnowski@mtech.edu 406-496-4681 October 2006 2 Presentation Outline * Introduction - Goals, Enabling technologies, Overview * Load Control - Activities, Status * Stability Assessment - Activities, Status * Wrap up - Related activities, Staff 3 Goals * Research and develop technologies to improve T&D reliability * Technologies - Real-time load control methodologies - Measurement-based stability-assessment 4 Enabling Technologies * Load control enabled by GridWise technology (e.g. PNNL's GridFriendly appliance) * Real-time stability assessment enabled by Phasor Measurement (PMU) technology 5 Project Overview * Time line: April 18, 2006 thru April 17, 2008

71

LEDs and Specification for Parking Lots Lighten Energy Load | Department of  

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

LEDs and Specification for Parking Lots Lighten Energy Load LEDs and Specification for Parking Lots Lighten Energy Load LEDs and Specification for Parking Lots Lighten Energy Load March 5, 2013 - 11:17am Addthis At its Supercenter in Leavenworth, Kansas—the first site to implement the LED Site Lighting Specification—Walmart anticipates energy savings of over 125,000 kWh per year and a 30% reduction in maintenance costs. In addition to parking lot lights, LED bollard lights illuminate the pedestrian walkway. Credit: Walmart At its Supercenter in Leavenworth, Kansas-the first site to implement the LED Site Lighting Specification-Walmart anticipates energy savings of over 125,000 kWh per year and a 30% reduction in maintenance costs. In addition to parking lot lights, LED bollard lights illuminate the

72

Load Management for Industry  

E-Print Network (OSTI)

In the electric utility industry, load management provides the opportunity to control customer loads to beneficially alter a utility's load curve Load management alternatives are covered. Load management methods can be broadly classified into four...

Konsevick, W. J., Jr.

1982-01-01T23:59:59.000Z

73

Load Data and Load Vector Assembly  

Science Journals Connector (OSTI)

Data for loading cases in solid mechanics problems is described. The following external loading factors can be specified: concentrated nodal forces, distributed surface forces, and thermal loading. JavaTM class F...

2010-01-01T23:59:59.000Z

74

16 Load Data Cleansing and Bus Load  

E-Print Network (OSTI)

375 16 Load Data Cleansing and Bus Load Coincidence Factors* Wenyuan Li, Ke Wang, and Wijarn Wangdee 16.1 INTRODUCTION Load curve data refer to power consumptions recorded by meters at certain time intervals at buses of individual substations. Load curve data are one of the most important datasets

Wang, Ke

75

2012 CERTS LAAR Program Peer Review - Integration and Extension of Direct Load Management of Smart Loads - Anna Scaglioni, UC Davis  

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

Integration and Extension of Direct Integration and Extension of Direct Load Management of Smart Loads Anna Scaglione, UC Davis GRA: Mahnoosh Alizadeh Project objective  Invent methods to "store" load demand for * Real-time "generation following" * Integration of load reserves as dispatchable assets in the Energy Market  Architecture for virtual "reserves" (queues) of electrical load demand * Watts to Job mapping (analysis)  Captures digitally the service requirements - Equal service type = Equal queue * Job to Watts mapping (synthesis)  Allows to optimally schedule the load profile Major technical accomplishments  Centralized model: Digital Direct Load Scheduling (DDLS) - Year 1-Year 2

76

KWhOURS | Open Energy Information  

Open Energy Info (EERE)

Zip: 1982 Sector: Services Product: Massachusetts software maker which provides mobile data collection, calculation, and report generation services that reduce cost and time...

77

People Profiles  

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

What Is NIF? How NIF Works Seven Wonders Beamline NIF Construction Who Works for NIF & PS? People Profiles Management Awards Honors Fellows Who Partners with NIF? FAQs Visit Us...

78

Commercial and Residential Hourly Load Data Now Available on OpenEI! |  

Open Energy Info (EERE)

Commercial and Residential Hourly Load Data Now Available on OpenEI! Commercial and Residential Hourly Load Data Now Available on OpenEI! Home > Groups > Utility Rate Sfomail's picture Submitted by Sfomail(48) Member 17 May, 2013 - 12:03 building load building load data commercial load data dataset datasets electric load data load data load profile OpenEI residential load TMY3 United States Load data Image source: NREL I am pleased to announce that simulated hourly residential and commercial building load datasets are now available on OpenEI. These datasets are available for all TMY3 locations in the United States. They contain hourly load profile data for 16 commercial building types (based off the DOE commercial reference building models) and residential buildings (based off the Building America House Simulation Protocols). In addition to various

79

Application of Classification Methods for Forecasting Mid-Term Power Load Patterns  

Science Journals Connector (OSTI)

Currently an automated methodology based on data mining techniques is presented for the prediction of customer load patterns in long duration load profiles. The proposed approach in this paper...i) data preproces...

Minghao Piao; Heon Gyu Lee; Jin Hyoung Park

2008-01-01T23:59:59.000Z

80

1991 Pacific Northwest Loads and Resources Study.  

SciTech Connect

This study establishes the Bonneville Power Administration's (BPA) planning basis for supplying electricity to BPA customers. The Loads and Resources Study is presented in three documents: (1) this summary of federal system and Pacific Northwest region loads and resources; (2) a technical appendix detailing forecasted Pacific Northwest economic trends and loads, and (3) a technical appendix detailing the loads and resources for each major Pacific Northwest generating utility. This analysis updates our 1990 study. BPS's long-range planning incorporates resource availability with a range of forecasted electrical consumption. The forecasted future electrical demands-firm loads--are subtracted from the projected capability of existing resources to determine whether BPA and the region will be surplus or deficit. If resources are greater than loads in any particular year or month, there is a surplus of energy and/or capacity, which BPA can sell to increase revenues. Conversely, if firm loads exceed available resources, there is a deficit of energy and/or capacity, then additional conservation, contract purchases, or generating resources will be needed to meet load growth. This study analyzes the Pacific Northwest's projected loads and available generating resources in two parts: (1) the loads and resources of the federal system, for which BPA is the marketing agency; and (2) the larger Pacific Northwest regional profile, which includes loads and resources in addition to the federal system. This study presents the federal system and regional analyses for five load forecasts: high, medium-high, medium, medium-low, and low. This analysis projects the yearly average energy consumption and resource availability for 1992- 2012.

United States. Bonneville Power Administration.

1991-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "kwh load profiles" 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

OG&E Uses Time-Based Rate Program to Reduce Peak Demand  

Office of Environmental Management (EM)

46.0kWh 6 Critical Peak Event 46.0kWh 46.0kWh 7 (included in the above) Demand Response to Time-Based Rates The figure below shows 24-hour load profiles for the average...

82

Mentee Profile  

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

Mentee Profile Mentee Profile The information you provide on this form will assist us in providing you with a list of prospective mentor from which to choose the most appropriate match. Once you've completed the form, please email it to doementoringprogram@hq.doe.gov . Thank you for your interest in the DOE Mentoring Program. Name (last/first): Phone Number: Job Title/Series/Grade: Organization (indicate HQ or field - complete address): Email Address: Are you a Veteran? If yes, do want a veteran mentee? If yes, which branch of the service? Are you student or intern? Do you have a preference on mentor? For example, male, female, particular career field, specific person or other? If so, what or who? Do you want a mentor in your career field? What are your career goals?

83

Mentor Profile  

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

Mentor Profile Mentor Profile The information you provide on this form will assist us in providing you with a list of prospective mentee from which to choose the most appropriate match. Once you've completed the form, please email it to doementoringprogram@hq.doe.gov . Thank you for your interest in the DOE Mentoring Program. Name (last/first): Phone Number: Job Title/Series/Grade: Organization (indicate HQ or field - complete address): Email Address: Are you a Veteran? If yes, do want a veteran mentee? If yes, which branch of the service? Do you want a student or intern mentee? Do you have a preference on mentee? For example, male, female, particular career field or other? If so, what or state name of pre selected mentee? Do you want a mentee in your career field? What are your hobbies?

84

Fetch Halting on Critical Load Misses Nikil Mehta,  

E-Print Network (OSTI)

Fetch Halting on Critical Load Misses Nikil Mehta, Brian Singer, R. Iris Bahar Division, such as loads that miss to main memory and floating point arithmetic operations, are primarily responsible to characterize critical instructions, our approach com- bines software profiling and hardware monitoring

DeHon, André

85

IPM Profiling Tool at NERSC  

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

IPM IPM IPM Description and Overview IPM is a portable profiling infrastructure which provide a high level report on the execution of a parallel job. IPM reports hardware counters data, MPI function timings, and memory usage. It provides a low overhead means to generate scaling studies or performance data for ERCAP submissions. When you run a job using the IPM module you will get a performance summary (see below) to stdout as well as a web accessible summary of all your IPM jobs. The two main objectives of IPM are ease-of-use and scalability in performance analysis. Usage % module load ipm On HPC architectures that support shared libraries that's all you need to do. Once the module is loaded you can run as you normally and get a performance profile once the job has successfully completed. You do not

86

Load sensing system  

DOE Patents (OSTI)

A load sensing system inexpensively monitors the weight and temperature of stored nuclear material for long periods of time in widely variable environments. The system can include an electrostatic load cell that encodes weight and temperature into a digital signal which is sent to a remote monitor via a coaxial cable. The same cable is used to supply the load cell with power. When multiple load cells are used, vast

Sohns, Carl W. (Oak Ridge, TN); Nodine, Robert N. (Knoxville, TN); Wallace, Steven Allen (Knoxville, TN)

1999-01-01T23:59:59.000Z

87

Industrial Load Shaping: A Utility Strategy to Deal with Competition  

E-Print Network (OSTI)

INDUSTRIAL LOAD SHAPING: A UTILITY STRATEGY TO DEAL WITH COMPETITION DONALD BULES BULES AND ASSOCIATES SAN FRANCISCO, ABSTRACT In recent years competition from various sources such as cogeneration and bypass has led many utilities... to refocus attention on their large industrial customers. Industrial load shaping is a customized program involving cost-effective process modifications and operational changes which result in a restructuring of the electric load profile of individual...

Bules, D.

88

Loading margin Stable operating  

E-Print Network (OSTI)

Linear approximation at p1 Actual loading margin Loadingmargin Parameter p p1 p2 p3 IEEE Transactions collapse. Linear and quadratic estimates to the variation of the loading margin with respect to any sys power support, wheeling, load model param- eters, line susceptance, and generator dispatch. The accuracy

89

A critical evaluation of the use of the profile model in calculating mineral weathering rates  

Science Journals Connector (OSTI)

The PROFILE model is used extensively in the European Critical Loads programme as an aid to international negotiations on SO2 emission abatement. PROFILE calculates the rates of cation release by mineral weatheri...

Mark E. Hodson; Simon J. Langan; M. Jeff Wilson

1997-08-01T23:59:59.000Z

90

a critical evaluation of the use of the PROFILE model in calculating mineral weathering rates  

Science Journals Connector (OSTI)

The PROFILE model is used extensively in the European Critical Loads programme as an aid to international negotiations on SO2 emission abatement. PROFILE calculates the rates of cation release by mineral weatheri...

MARK E. HODSON; SIMON J. LANGAN; M. JEFF WILSON

1997-08-01T23:59:59.000Z

91

Load regulating expansion fixture  

DOE Patents (OSTI)

A free standing self contained device for bonding ultra thin metallic films, such as 0.001 inch beryllium foils is disclosed. The device will regulate to a predetermined load for solid state bonding when heated to a bonding temperature. The device includes a load regulating feature, whereby the expansion stresses generated for bonding are regulated and self adjusting. The load regulator comprises a pair of friction isolators with a plurality of annealed copper members located therebetween. The device, with the load regulator, will adjust to and maintain a stress level needed to successfully and economically complete a leak tight bond without damaging thin foils or other delicate components. 1 fig.

Wagner, L.M.; Strum, M.J.

1998-12-15T23:59:59.000Z

92

Load regulating expansion fixture  

DOE Patents (OSTI)

A free standing self contained device for bonding ultra thin metallic films, such as 0.001 inch beryllium foils. The device will regulate to a predetermined load for solid state bonding when heated to a bonding temperature. The device includes a load regulating feature, whereby the expansion stresses generated for bonding are regulated and self adjusting. The load regulator comprises a pair of friction isolators with a plurality of annealed copper members located therebetween. The device, with the load regulator, will adjust to and maintain a stress level needed to successfully and economically complete a leak tight bond without damaging thin foils or other delicate components.

Wagner, Lawrence M. (San Jose, CA); Strum, Michael J. (San Jose, CA)

1998-01-01T23:59:59.000Z

93

Load sensing system  

DOE Patents (OSTI)

A load sensing system inexpensively monitors the weight and temperature of stored nuclear material for long periods of time in widely variable environments. The system can include an electrostatic load cell that encodes weight and temperature into a digital signal which is sent to a remote monitor via a coaxial cable. The same cable is used to supply the load cell with power. When multiple load cells are used, vast inventories of stored nuclear material can be continuously monitored and inventoried of minimal cost. 4 figs.

Sohns, C.W.; Nodine, R.N.; Wallace, S.A.

1999-05-04T23:59:59.000Z

94

Development of Zinc/Bromine Batteries for Load-Leveling Applications: Phase 1 Final Report  

SciTech Connect

The Zinc/Bromine Load-Leveling Battery Development contract (No. 40-8965) was partitioned at the outset into two phases of equal length. Phase 1 started in September 1990 and continued through December 1991. In Phase 1, zinc/bromine battery technology was to be advanced to the point that it would be clear that the technology was viable and would be an appropriate choice for electric utilities wishing to establish stationary energy-storage facilities. Criteria were established that addressed most of the concerns that had been observed in the previous development efforts. The performances of 8-cell and 100-cell laboratory batteries demonstrated that the criteria were met or exceeded. In Phase 2, 100-kWh batteries will be built and demonstrated, and a conceptual design for a load-leveling plant will be presented. At the same time, work will continue to identify improved assembly techniques and operating conditions. This report details the results of the efforts carried out in Phase 1. The highlights are: (1) Four 1-kWh stacks achieved over 100 cycles, One l-kWh stack achieved over 200 cycles, One 1-kWh stack achieved over 300 cycles; (2) Less than 10% degradation in performance occurred in the four stacks that achieved over 100 cycles; (3) The battery used for the zinc loading investigation exhibited virtually no loss in performance for loadings up to 130 mAh/cm{sup 2}; (4) Charge-current densities of 50 ma/cm{sup 2} have been achieved in minicells; (5) Fourteen consecutive no-strip cycles have been conducted on the stack with 300+ cycles; (6) A mass and energy balance spreadsheet that describes battery operation was completed; (7) Materials research has continued to provide improvements in the electrode, activation layer, and separator; and (8) A battery made of two 50-cell stacks (15 kWh) was produced and delivered to Sandia National Laboratories (SNL) for testing. The most critical development was the ability to assemble a battery stack that remained leak free. The task of sealing the battery stack using vibration welding has undergone significant improvement resulting in a viable production process. Through several design iterations, a solid technology base for larger battery stack designs was established. Internal stack stresses can now be modeled, in addition to fluid velocity and fluid pressure distribution, through the use of a finite element analysis computer program. Additionally, the Johnson Controls Battery Group, Inc. (JCBGI) proprietary FORTRAN model has been improved significantly, enabling accurate performance predictions. This modeling was used to improve the integrity and performance of the battery stacks, and should be instrumental in reducing the turnaround time from concept to assembly.

Eidler, Phillip

1999-07-01T23:59:59.000Z

95

Commercial and Residential Hourly Load Profiles for all TMY3...  

Open Energy Info (EERE)

America House Simulation Protocols). This dataset also uses the Residential Energy Consumption Survey (RECS) for statistical references of building types by location (Additional...

96

Predicting pipeline frost load  

SciTech Connect

A study was undertaken to find a formula for predicting the additional load imposed on underground pipelines by soil freezing. The authors conclude that a modified Boussinesq equation can be used to assess this load. Results also showed that frost affects the modulus of soil reaction and therefore the induced stress in flexible pipe.

Fielding, M.B.; Cohen, A.

1988-11-01T23:59:59.000Z

97

A commercial electromechanical actuator (EMA) is to be dynamically tested with predetermined stroke and load  

E-Print Network (OSTI)

with predetermined stroke and load profiles for transient thermal and electric power behavior to validate a numerical model used for aerospace applications. The EMA will follow the stroke profile representative of a real. The EMA is commanded to follow a stroke profile representative of a real aircraft mission duty cycle

Wu, Thomas

98

Scalable Load Distribution and Load Balancing for Dynamic Parallel Programs  

E-Print Network (OSTI)

shown that the algorithm scales according to the definition of scalability given following. LoadScalable Load Distribution and Load Balancing for Dynamic Parallel Programs E. Berger and J. C of an integrated load distribution-load balancing algorithm which was targeted to be both efficient and scalable

Berger, Emery

99

HLW Glass Waste Loadings  

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

HLW HLW Glass Waste Loadings Ian L. Pegg Vitreous State Laboratory The Catholic University of America Washington, DC Overview Overview  Vitrification - general background  Joule heated ceramic melter (JHCM) technology  Factors affecting waste loadings  Waste loading requirements and projections  WTP DWPF  DWPF  Yucca Mountain License Application requirements on waste loading  Summary Vitrification  Immobilization of waste by conversion into a glass  Internationally accepted treatment for HLW  Why glass?  Amorphous material - able to incorporate a wide spectrum of elements over wide ranges of composition; resistant to radiation damage  Long-term durability - natural analogs Relatively simple process - amenable to nuclearization at large  Relatively simple process - amenable to nuclearization at large scale  There

100

Buildings Stock Load Control  

E-Print Network (OSTI)

: An assembly of the various blocks of the library of simbad and simulink permit to model building. Finally the last part prensents the study results: Graphs and tables to see the load shedding strategies impacts....

Joutey, H. A.; Vaezi-Nejad, H.; Clemoncon, B.; Rosenstein, F.

2006-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "kwh load profiles" 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

Composite Load Model Evaluation  

SciTech Connect

The WECC load modeling task force has dedicated its effort in the past few years to develop a composite load model that can represent behaviors of different end-user components. The modeling structure of the composite load model is recommended by the WECC load modeling task force. GE Energy has implemented this composite load model with a new function CMPLDW in its power system simulation software package, PSLF. For the last several years, Bonneville Power Administration (BPA) has taken the lead and collaborated with GE Energy to develop the new composite load model. Pacific Northwest National Laboratory (PNNL) and BPA joint force and conducted the evaluation of the CMPLDW and test its parameter settings to make sure that: the model initializes properly, all the parameter settings are functioning, and the simulation results are as expected. The PNNL effort focused on testing the CMPLDW in a 4-bus system. An exhaustive testing on each parameter setting has been performed to guarantee each setting works. This report is a summary of the PNNL testing results and conclusions.

Lu, Ning; Qiao, Hong (Amy)

2007-09-30T23:59:59.000Z

102

EIA - State Nuclear Profiles  

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

Massachusetts Nuclear Profile 2010 Massachusetts profile Massachusetts total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy...

103

EIA - State Nuclear Profiles  

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

Iowa Nuclear Profile 2010 Iowa profile Iowa total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw)...

104

EIA - State Nuclear Profiles  

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

Illinois Nuclear Profile 2010 Illinois profile Illinois total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer...

105

EIA - State Nuclear Profiles  

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

Louisiana Nuclear Profile 2010 Louisiana profile Louisiana total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer...

106

Load Monitoring CEC/LMTF Load Research Program  

SciTech Connect

This white paper addresses the needs, options, current practices of load monitoring. Recommendations on load monitoring applications and future directions are also presented.

Huang, Zhenyu; Lesieutre, B.; Yang, Steve; Ellis, A.; Meklin, A.; Wong, B.; Gaikwad, A.; Brooks, D.; Hammerstrom, Donald J.; Phillips, John; Kosterev, Dmitry; Hoffman, M.; Ciniglio, O.; Hartwell, R.; Pourbeik, P.; Maitra, A.; Lu, Ning

2007-11-30T23:59:59.000Z

107

Truck loading rack blending  

SciTech Connect

Blending, the combining of two or more components to make a single product, has become widely used in most loading rack applications. Blending should not be confused with additive injection, which is the injection of very small doses of enhancers, detergents and dyes into a product stream. Changes in the environmental protection laws in the early 90`s have put increasing demands on marketing terminals with regards to reformulated fuels and environmental protection concerns. As a result of these new mandates, terminals have turned to blending at the loading rack as an economical and convenient means in meeting these new requirements. This paper will discuss some of these mandates and how loading rack blending is used for different applications. Various types of blending will also be discussed along with considerations for each method.

Boubenider, E. [Daniel Flow Products, Inc., Houston, TX (United States)

1995-12-01T23:59:59.000Z

108

User_TalentProfile  

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

Accessing and Modifying Talent Profile Accessing and Modifying Talent Profile © 2011 SuccessFactors, Inc. - 1 - SuccessFactors Learning Confidential. All rights reserved. Job Aid: Accessing and Modifying Talent Profile Purpose The purpose of this job aid is to guide users through the step-by-step process of accessing their talent profiles, adding information to their profiles, and editing existing talent profile information. Task A. Access Talent Profile Enter the web address (URL) of the user application into your browser Address field and press the Enter key. Enter your user ID in the User ID textbox. Enter your password in the Password textbox. Click Sign In. Access Talent Profile 4 Steps Task A Add Information to Talent Profile Sections 5 Steps Task B Edit Talent Profile Sections

109

Characterization of Rivastigmine Loaded Chitosan  

E-Print Network (OSTI)

cholinesterase inhibitors (ChEI). In present study rivastigmine loaded chitosan-tripolyphosphate nanoparticles

Simar Preet Kaur; Rekha Rao; Afzal Hussain; Sarita Khatkar

110

Bridge Monitoring and Loading  

E-Print Network (OSTI)

#12;1 Bridge Monitoring and Loading P. Fanning, E. OBrien Stone Arch Bridges - Modelling simulations were conducted for a range of stone arch bridges spanning 5.0m to 32m. Traditional assessment procedures for the determination of both longitudinal and transverse bridge strengths were developed

111

Bridge Monitoring and Loading  

E-Print Network (OSTI)

1 Bridge Monitoring and Loading P. Fanning, E. OBrien Stone Arch Bridges - Modelling and Assessment dimensional non- linear finite element simulations of a range of stone arch- bridges spanning 5.0m to 32m and novel assessment proce- dures for the determination of both longitudinal andtrans- verse bridge

112

Load Management Made Simple  

E-Print Network (OSTI)

Company have moved to a demand side or load management mode which seeks to influence customers to change electric usage patterns to more efficiently use available generating capacity. Since 1970, the TUEC system peak demand has more than doubled from about...

Schneider, K.

1985-01-01T23:59:59.000Z

113

recreate load le Rick Whitman  

E-Print Network (OSTI)

is an example of an initial unexpanded fos load le. It loads data for the le: u-init-y.cy0 u data for the le: e-init-y.cy0 2 #12;e-next-y.lod - this is an expanded fos load which uses erecreate load le Rick Whitman November 27, 1996 Usage The tool is invoked by entering recreate load

Sirianni, Marco

114

Regression Models for Demand Reduction based on Cluster Analysis of Load  

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

Regression Models for Demand Reduction based on Cluster Analysis of Load Regression Models for Demand Reduction based on Cluster Analysis of Load Profiles Speaker(s): Nobuyuki Yamaguchi Date: March 26, 2009 - 12:00pm Location: 90-3122 This seminar provides new regression models for demand reduction of Demand Response programs for the purpose of ex ante evaluation of the programs and screening for recruiting customer enrollment into the programs. The proposed regression models employ load sensitivity to outside air temperature and representative load pattern derived from cluster analysis of customer baseline load as explanatory variables. We examined the performance of the proposed models with respect to the validity of explanatory variables and fitness of regressions, using actual load profile data of Pacific Gas and Electric Company's commercial and industrial

115

Load Management: Opportunity or Calamity?  

E-Print Network (OSTI)

larger now than prior to 1973. Utilities are examining two options which can be termed load management. One option is to control discretionary loads during peak periods. Cycling of residential water heaters or shutting off industrial electric furnaces...

Males, R.; Hassig, N.

1981-01-01T23:59:59.000Z

116

Variable loading roller  

DOE Patents (OSTI)

An automatic loading roller for transmitting torque in traction drive devices in manipulator arm joints includes a two-part camming device having a first cam portion rotatable in place on a shaft by an input torque and a second cam portion coaxially rotatable and translatable having a rotating drive surface thereon for engaging the driven surface of an output roller with a resultant force proportional to the torque transmitted. Complementary helical grooves in the respective cam portions interconnected through ball bearings interacting with those grooves effect the rotation and translation of the second cam portion in response to rotation of the first. 14 figs.

Williams, D.M.

1988-01-21T23:59:59.000Z

117

Commercial Building Profiles | OpenEI  

Open Energy Info (EERE)

Building Profiles Building Profiles Dataset Summary Description This dataset includes simulation results from a national-scale study of the commercial buildings sector. Electric load profiles contain the hour-by-hour demand for electricity for each building. Summary tables describe individual buildings and their overall annual energy performance. The study developed detailed EnergyPlus models for 4,820 different samples in 2003 CBECS. Simulation output is available for all and organized by CBECS's identification number in public use datasets. Three modeling scenarios are available: existing stock (with 2003 historical weather), stock as if rebuilt new (with typical weather), and the stock if rebuilt using maximum efficiency technology (with typical weather). The following reports describe how the dataset was developed:

118

Project Profile: Brayton Cycle Baseload Power Tower  

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

Wilson Solarpower, under the Baseload CSP FOA, is validating a proposed utility-scale, Brayton cycle baseload power tower system with a capacity factor of at least 75% and LCOE of $0.09/kWh.

119

Grid Integration of Aggregated Demand Response, Part 1: Load Availability  

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

Grid Integration of Aggregated Demand Response, Part 1: Load Availability Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection Title Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection Publication Type Report LBNL Report Number LBNL-6417E Year of Publication 2013 Authors Olsen, Daniel, Nance Matson, Michael D. Sohn, Cody Rose, Junqiao Han Dudley, Sasank Goli, Sila Kiliccote, Marissa Hummon, David Palchak, Paul Denholm, Jennie Jorgenson, and Ookie Ma Date Published 09/2013 Abstract Demand response (DR) has the potential to improve electric grid reliability and reduce system operation costs. However, including DR in grid modeling can be difficult due to its variable and non-traditional response characteristics, compared to traditional generation. Therefore, efforts to value the participation of DR in procurement of grid services have been limited. In this report, we present methods and tools for predicting demand response availability profiles, representing their capability to participate in capacity, energy, and ancillary services. With the addition of response characteristics mimicking those of generation, the resulting profiles will help in the valuation of the participation of demand response through production cost modeling, which informs infrastructure and investment planning.

120

MTS Table Top Load frame  

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

MTS Table Top Load frame MTS Table Top Load frame The Non-destructive Evaluation group operates an MTS Table Top Load frame for ultimate strength and life cycle testing of various ceramic, ceramic-matrix (FGI), carbon, carbon fiber, cermet (CMC) and metal alloy engineering samples. The load frame is a servo-hydraulic type designed to function in a closed loop configuration under computer control. The system can perform non-cyclic, tension, compression and flexure testing and cyclic fatigue tests. The system is comprised of two parts: * The Load Frame and * The Control System. Load Frame The Load Frame (figure 1) is a cross-head assembly which includes a single moving grip, a stationary grip and LVDT position sensor. It can generate up to 25 kN (5.5 kip) of force in the sample under test and can

Note: This page contains sample records for the topic "kwh load profiles" 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

PWR AXIAL BURNUP PROFILE ANALYSIS  

SciTech Connect

The purpose of this activity is to develop a representative ''limiting'' axial burnup profile for pressurized water reactors (PWRs), which would encompass the isotopic axial variations caused by different assembly irradiation histories, and produce conservative isotopics with respect to criticality. The effect that the low burnup regions near the ends of spent fuel have on system reactivity is termed the ''end-effect''. This calculation will quantify the end-effects associated with Pressurized Water Reactor (PWR) fuel assemblies emplaced in a hypothetical 21 PWR waste package. The scope of this calculation covers an initial enrichment range of 3.0 through 5.0 wt% U-235 and a burnup range of 10 through 50 GWd/MTU. This activity supports the validation of the process for ensuring conservative generation of spent fuel isotopics with respect to criticality safety applications, and the use of burnup credit for commercial spent nuclear fuel. The intended use of these results will be in the development of PWR waste package loading curves, and applications involving burnup credit. Limitations of this evaluation are that the limiting profiles are only confirmed for use with the B&W 15 x 15 fuel assembly design. However, this assembly design is considered bounding of all other typical commercial PWR fuel assembly designs. This calculation is subject to the Quality Assurance Requirements and Description (QARD) because this activity supports investigations of items or barriers on the Q-list (YMP 2001).

J.M. Acaglione

2003-09-17T23:59:59.000Z

122

kWh Analytics: Quality Ratings for PV  

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

This presentation summarizes the information given during the SunShot Grand Challenge Summit and Technology Forum, June 13-14, 2012.

123

Comparing Mainframe and Windows Server Transactions per kWh  

E-Print Network (OSTI)

........................................................................................14 Appendix A. Platform Comparison and Conversion Factors...............................................................................................................15 Conversion Factors............................................................................................................................3 Objective: Estimate Energy Consumption for Similar Uses

Narasayya, Vivek

124

LANSCE | News & Media | Profiles  

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

Profiles Shea Mosby: Lighting the way for nuclear science discoveries By Diana Del Mauro ADEPS Communications Photos by Richard Robinson, IRM-CAS Shea Mosby Cradling a heavy...

125

EIA - State Electricity Profiles  

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

Electricity Profile 2012 Table 1. 2012 Summary statistics (Missouri) Item Value U.S. Rank NERC Region(s) SERCSPP Primary Energy Source Coal Net Summer Capacity (megawatts)...

126

Management's Discussion & Analysis Profile  

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

7-26-2013. Management's Discussion & Analysis Profile The Bonneville Power Administration is a federal agency under the Department of Energy. BPA markets wholesale electrical power...

127

EIA - State Electricity Profiles  

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

Arkansas Electricity Profile 2012 Table 1. 2012 Summary Statistics (Arkansas) Item Value U.S. Rank NERC Region(s) SERCSPP Primary Energy Source Coal Net Summer Capacity...

128

Measured Peak Equipment Loads in Laboratories  

E-Print Network (OSTI)

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

Mathew, Paul A.

2008-01-01T23:59:59.000Z

129

Demand Response: Load Management Programs  

E-Print Network (OSTI)

CenterPoint Load Management Programs CATEE Conference October, 2012 Agenda Outline I. General Demand Response Definition II. General Demand Response Program Rules III. CenterPoint Commercial Program IV. CenterPoint Residential Programs... V. Residential Discussion Points Demand Response Definition of load management per energy efficiency rule 25.181: ? Load control activities that result in a reduction in peak demand, or a shifting of energy usage from a peak to an off...

Simon, J.

2012-01-01T23:59:59.000Z

130

Dynamic load balancing of applications  

DOE Patents (OSTI)

An application-level method for dynamically maintaining global load balance on a parallel computer, particularly on massively parallel MIMD computers. Global load balancing is achieved by overlapping neighborhoods of processors, where each neighborhood performs local load balancing. The method supports a large class of finite element and finite difference based applications and provides an automatic element management system to which applications are easily integrated.

Wheat, Stephen R. (Albuquerque, NM)

1997-01-01T23:59:59.000Z

131

FINAL PROJECT REPORT LOAD MODELING TRANSMISSION RESEARCH  

E-Print Network (OSTI)

atPSEistocollectloaddataforvalidatingdynamicandapproach decomposes recorded load data into different load to continuously record load data for a selected time period

Lesieutre, Bernard

2013-01-01T23:59:59.000Z

132

High-Power Rf Load  

DOE Patents (OSTI)

A compact high-power RF load comprises a series of very low Q resonators, or chokes [16], in a circular waveguide [10]. The sequence of chokes absorb the RF power gradually in a short distance while keeping the bandwidth relatively wide. A polarizer [12] at the input end of the load is provided to convert incoming TE.sub.10 mode signals to circularly polarized TE.sub.11 mode signals. Because the load operates in the circularly polarized mode, the energy is uniformly and efficiently absorbed and the load is more compact than a rectangular load. Using these techniques, a load having a bandwidth of 500 MHz can be produced with an average power dissipation level of 1.5 kW at X-band, and a peak power dissipation of 100 MW. The load can be made from common lossy materials, such as stainless steel, and is less than 15 cm in length. These techniques can also produce loads for use as an alternative to ordinary waveguide loads in small and medium RF accelerators, in radar systems, and in other microwave applications. The design is easily scalable to other RF frequencies and adaptable to the use of other lossy materials.

Tantawi, Sami G. (San Mateo, CA); Vlieks, Arnold E. (Livermore, CA)

1998-09-01T23:59:59.000Z

133

Online Load Balancing for Related Machines  

E-Print Network (OSTI)

of entire schedule s as follows: load(s; i) = 1 v i X s(j)=i p j ; Load(s) = max i load(s; i) It is easyOn­line Load Balancing for Related Machines Piotr Berman \\Lambda Moses Charikar y Marek Karpinski z­line load balancing was studied extensively over the years (cf., e.g., [7], [3], [4], and [2

Karpinski, Marek

134

Examination of shaped charge liner shock loading  

SciTech Connect

A series of experiments was conducted for the purpose of achieving a more fundamental understanding of the shaped charge liner shock loading environment. The test configuration, representing the middle portion of a shaped charge, consists of a 50 mm deep, 100 mm tall, and 2 mm thick copper plate driven by 50 mm deep, 100 mm tall, tapered thickness wedge of LX-14. An electrically driven 50 mm square flyer is used to surface initiate the base of the LX-14 causing a plane detonation wave to propagate into the explosive wedge along the liner surface. Fabry-Perot laser velocimetry measures the particle velocity time history of the plate. The CTH and DYNA2D hydrocodes are used to simulate the experiments. Calculations of the velocity profiles are compared to the experimental results. The effects of mesh density, copper material failure and strength models, and explosive detonation models are discussed.

Murphy, M.J.; Moore, T.W.; Lee, C.G.; Breithaupt, R.; Avara, G.R.

1996-07-01T23:59:59.000Z

135

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

136

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

137

Load Forecasting of Supermarket Refrigeration  

E-Print Network (OSTI)

energy system. Observed refrigeration load and local ambient temperature from a Danish su- permarket renewable energy, is increasing, therefore a flexible energy system is needed. In the present ThesisLoad Forecasting of Supermarket Refrigeration Lisa Buth Rasmussen Kongens Lyngby 2013 M.Sc.-2013

138

EIA - State Electricity Profiles  

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

Michigan Electricity Profile 2010 Michigan profile Michigan Electricity Profile 2010 Michigan profile Table 1. 2010 Summary Statistics (Michigan) Item Value U.S. Rank NERC Region(s) MRO/RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 29,831 11 Electric Utilities 21,639 10 Independent Power Producers & Combined Heat and Power 8,192 14 Net Generation (megawatthours) 111,551,371 13 Electric Utilities 89,666,874 13 Independent Power Producers & Combined Heat and Power 21,884,497 16 Emissions (thousand metric tons) Sulfur Dioxide 254 6 Nitrogen Oxide 89 6 Carbon Dioxide 74,480 11 Sulfur Dioxide (lbs/MWh) 5.0 8 Nitrogen Oxide (lbs/MWh) 1.8 19 Carbon Dioxide (lbs/MWh) 1,472 20 Total Retail Sales (megawatthours) 103,649,219 12 Full Service Provider Sales (megawatthours) 94,565,247 11

139

EIA - State Electricity Profiles  

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

Ohio Electricity Profile 2010 Ohio profile Ohio Electricity Profile 2010 Ohio profile Table 1. 2010 Summary Statistics (Ohio) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 33,071 8 Electric Utilities 20,179 13 Independent Power Producers & Combined Heat and Power 12,892 7 Net Generation (megawatthours) 143,598,337 7 Electric Utilities 92,198,096 10 Independent Power Producers & Combined Heat and Power 51,400,241 7 Emissions (thousand metric tons) Sulfur Dioxide 610 1 Nitrogen Oxide 122 3 Carbon Dioxide 121,964 4 Sulfur Dioxide (lbs/MWh) 9.4 1 Nitrogen Oxide (lbs/MWh) 1.9 17 Carbon Dioxide (lbs/MWh) 1,872 8 Total Retail Sales (megawatthours) 154,145,418 4 Full Service Provider Sales (megawatthours) 105,329,797 9

140

EIA - State Electricity Profiles  

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

Wisconsin Electricity Profile 2010 Wisconsin profile Wisconsin Electricity Profile 2010 Wisconsin profile Table 1. 2010 Summary Statistics (Wisconsin) Item Value U.S. Rank NERC Region(s) MRO/RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 17,836 23 Electric Utilities 13,098 19 Independent Power Producers & Combined Heat and Power 4,738 20 Net Generation (megawatthours) 64,314,067 24 Electric Utilities 45,579,970 22 Independent Power Producers & Combined Heat and Power 18,734,097 18 Emissions (thousand metric tons) Sulfur Dioxide 145 12 Nitrogen Oxide 49 25 Carbon Dioxide 47,238 19 Sulfur Dioxide (lbs/MWh) 5.0 9 Nitrogen Oxide (lbs/MWh) 1.7 20 Carbon Dioxide (lbs/MWh) 1,619 16 Total Retail Sales (megawatthours) 68,752,417 22 Full Service Provider Sales (megawatthours) 68,752,417 21

Note: This page contains sample records for the topic "kwh load profiles" 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

EIA - State Electricity Profiles  

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

Florida Electricity Profile 2010 Florida profile Florida Electricity Profile 2010 Florida profile Table 1. 2010 Summary Statistics (Florida) Item Value U.S. Rank NERC Region(s) FRCC/SERC Primary Energy Source Gas Net Summer Capacity (megawatts) 59,147 3 Electric Utilities 50,853 1 Independent Power Producers & Combined Heat and Power 8,294 13 Net Generation (megawatthours) 229,095,935 3 Electric Utilities 206,062,185 1 Independent Power Producers & Combined Heat and Power 23,033,750 15 Emissions (thousand metric tons) Sulfur Dioxide 160 11 Nitrogen Oxide 101 5 Carbon Dioxide 123,811 2 Sulfur Dioxide (lbs/MWh) 1.5 37 Nitrogen Oxide (lbs/MWh) 1.0 35 Carbon Dioxide (lbs/MWh) 1,191 31 Total Retail Sales (megawatthours) 231,209,614 3 Full Service Provider Sales (megawatthours) 231,209,614 3

142

EIA - State Electricity Profiles  

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

Arizona Electricity Profile 2010 Arizona profile Arizona Electricity Profile 2010 Arizona profile Table 1. 2010 Summary Statistics (Arizona) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Coal Net Summer Capacity (megawatts) 26,392 15 Electric Utilities 20,115 14 Independent Power Producers & Combined Heat and Power 6,277 16 Net Generation (megawatthours) 111,750,957 12 Electric Utilities 91,232,664 11 Independent Power Producers & Combined Heat and Power 20,518,293 17 Emissions (thousand metric tons) Sulfur Dioxide 33 33 Nitrogen Oxide 57 17 Carbon Dioxide 55,683 15 Sulfur Dioxide (lbs/MWh) 0.7 43 Nitrogen Oxide (lbs/MWh) 1.1 31 Carbon Dioxide (lbs/MWh) 1,099 35 Total Retail Sales (megawatthours) 72,831,737 21 Full Service Provider Sales (megawatthours) 72,831,737 20

143

EIA - State Electricity Profiles  

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

Kentucky Electricity Profile 2010 Kentucky profile Kentucky Electricity Profile 2010 Kentucky profile Table 1. 2010 Summary Statistics (Kentucky) Item Value U.S. Rank NERC Region(s) RFC/SERC Primary Energy Source Coal Net Summer Capacity (megawatts) 20,453 21 Electric Utilities 18,945 16 Independent Power Producers & Combined Heat and Power 1,507 38 Net Generation (megawatthours) 98,217,658 17 Electric Utilities 97,472,144 7 Independent Power Producers & Combined Heat and Power 745,514 48 Emissions (thousand metric tons) Sulfur Dioxide 249 7 Nitrogen Oxide 85 7 Carbon Dioxide 93,160 7 Sulfur Dioxide (lbs/MWh) 5.6 5 Nitrogen Oxide (lbs/MWh) 1.9 15 Carbon Dioxide (lbs/MWh) 2,091 3 Total Retail Sales (megawatthours) 93,569,426 14 Full Service Provider Sales (megawatthours) 93,569,426 12

144

EIA - State Electricity Profiles  

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

Alabama Electricity Profile 2010 Alabama profile Alabama Electricity Profile 2010 Alabama profile Table 1. 2010 Summary Statistics (Alabama) Item Value U.S. Rank NERC Region(s) SERC Primary Energy Source Coal Net Summer Capacity (megawatts) 32,417 9 Electric Utilities 23,642 7 Independent Power Producers & Combined Heat and Power 8,775 12 Net Generation (megawatthours) 152,150,512 6 Electric Utilities 122,766,490 2 Independent Power Producers & Combined Heat and Power 29,384,022 12 Emissions (thousand metric tons) Sulfur Dioxide 218 10 Nitrogen Oxide 66 14 Carbon Dioxide 79,375 9 Sulfur Dioxide (lbs/MWh) 3.2 18 Nitrogen Oxide (lbs/MWh) 1.0 36 Carbon Dioxide (lbs/MWh) 1,150 33 Total Retail Sales (megawatthours) 90,862,645 15 Full Service Provider Sales (megawatthours) 90,862,645 13

145

EIA - State Electricity Profiles  

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

Arkansas Electricity Profile 2010 Arkansas profile Arkansas Electricity Profile 2010 Arkansas profile Table 1. 2010 Summary Statistics (Arkansas) Item Value U.S. Rank NERC Region(s) SERC/SPP Primary Energy Source Coal Net Summer Capacity (megawatts) 15,981 25 Electric Utilities 11,488 23 Independent Power Producers & Combined Heat and Power 4,493 24 Net Generation (megawatthours) 61,000,185 25 Electric Utilities 47,108,063 20 Independent Power Producers & Combined Heat and Power 13,892,122 27 Emissions (thousand metric tons) Sulfur Dioxide 74 22 Nitrogen Oxide 40 29 Carbon Dioxide 34,018 28 Sulfur Dioxide (lbs/MWh) 2.7 22 Nitrogen Oxide (lbs/MWh) 1.5 24 Carbon Dioxide (lbs/MWh) 1,229 29 Total Retail Sales (megawatthours) 48,194,285 29 Full Service Provider Sales (megawatthours) 48,194,285 27

146

EIA - State Electricity Profiles  

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

Maryland Electricity Profile 2010 Maryland profile Maryland Electricity Profile 2010 Maryland profile Table 1. 2010 Summary Statistics (Maryland) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 12,516 33 Electric Utilities 80 47 Independent Power Producers & Combined Heat and Power 12,436 9 Net Generation (megawatthours) 43,607,264 33 Electric Utilities 2,996 48 Independent Power Producers & Combined Heat and Power 43,604,268 9 Emissions (thousand metric tons) Sulfur Dioxide 45 28 Nitrogen Oxide 25 34 Carbon Dioxide 26,369 33 Sulfur Dioxide (lbs/MWh) 2.3 29 Nitrogen Oxide (lbs/MWh) 1.3 29 Carbon Dioxide (lbs/MWh) 1,333 24 Total Retail Sales (megawatthours) 65,335,498 24 Full Service Provider Sales (megawatthours) 36,082,473 31

147

EIA - State Electricity Profiles  

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

Hawaii Electricity Profile 2010 Hawaii profile Hawaii Electricity Profile 2010 Hawaii profile Table 1. 2010 Summary Statistics (Hawaii) Item Value U.S. Rank NERC Region(s) -- Primary Energy Source Petroleum Net Summer Capacity (megawatts) 2,536 47 Electric Utilities 1,828 40 Independent Power Producers & Combined Heat and Power 708 47 Net Generation (megawatthours) 10,836,036 45 Electric Utilities 6,416,068 38 Independent Power Producers & Combined Heat and Power 4,419,968 38 Emissions (thousand metric tons) Sulfur Dioxide 17 36 Nitrogen Oxide 21 36 Carbon Dioxide 8,287 42 Sulfur Dioxide (lbs/MWh) 3.4 16 Nitrogen Oxide (lbs/MWh) 4.3 2 Carbon Dioxide (lbs/MWh) 1,686 13 Total Retail Sales (megawatthours) 10,016,509 48 Full Service Provider Sales (megawatthours) 10,016,509 44

148

EIA - State Electricity Profiles  

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

Mexico Electricity Profile 2010 New Mexico profile Mexico Electricity Profile 2010 New Mexico profile Table 1. 2010 Summary Statistics (New Mexico) Item Value U.S. Rank NERC Region(s) SPP/WECC Primary Energy Source Coal Net Summer Capacity (megawatts) 8,130 36 Electric Utilities 6,345 33 Independent Power Producers & Combined Heat and Power 1,785 36 Net Generation (megawatthours) 36,251,542 37 Electric Utilities 30,848,406 33 Independent Power Producers & Combined Heat and Power 5,403,136 37 Emissions (thousand metric tons) Sulfur Dioxide 15 38 Nitrogen Oxide 56 19 Carbon Dioxide 29,379 31 Sulfur Dioxide (lbs/MWh) 0.9 42 Nitrogen Oxide (lbs/MWh) 3.4 5 Carbon Dioxide (lbs/MWh) 1,787 11 Total Retail Sales (megawatthours) 22,428,344 39 Full Service Provider Sales (megawatthours) 22,428,344 38

149

EIA - State Electricity Profiles  

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

Hampshire Electricity Profile 2010 New Hampshire profile Hampshire Electricity Profile 2010 New Hampshire profile Table 1. 2010 Summary Statistics (New Hampshire) Item Value U.S. Rank NERC Region(s) NPCC Primary Energy Source Nuclear Net Summer Capacity (megawatts) 4,180 43 Electric Utilities 1,132 41 Independent Power Producers & Combined Heat and Power 3,048 32 Net Generation (megawatthours) 22,195,912 42 Electric Utilities 3,979,333 41 Independent Power Producers & Combined Heat and Power 18,216,579 19 Emissions (thousand metric tons) Sulfur Dioxide 34 32 Nitrogen Oxide 6 46 Carbon Dioxide 5,551 43 Sulfur Dioxide (lbs/MWh) 3.4 17 Nitrogen Oxide (lbs/MWh) 0.6 46 Carbon Dioxide (lbs/MWh) 551 47 Total Retail Sales (megawatthours) 10,890,074 47 Full Service Provider Sales (megawatthours) 7,712,938 45

150

EIA - State Electricity Profiles  

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

Oregon Electricity Profile 2010 Oregon profile Oregon Electricity Profile 2010 Oregon profile Table 1. 2010 Summary Statistics (Oregon) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Hydroelectric Net Summer Capacity (megawatts) 14,261 29 Electric Utilities 10,846 27 Independent Power Producers & Combined Heat and Power 3,415 28 Net Generation (megawatthours) 55,126,999 27 Electric Utilities 41,142,684 26 Independent Power Producers & Combined Heat and Power 13,984,316 26 Emissions (thousand metric tons) Sulfur Dioxide 16 37 Nitrogen Oxide 15 42 Carbon Dioxide 10,094 40 Sulfur Dioxide (lbs/MWh) 0.6 44 Nitrogen Oxide (lbs/MWh) 0.6 47 Carbon Dioxide (lbs/MWh) 404 48 Total Retail Sales (megawatthours) 46,025,945 30 Full Service Provider Sales (megawatthours) 44,525,865 29

151

EIA - State Electricity Profiles  

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

Maine Electricity Profile 2010 Maine profile Maine Electricity Profile 2010 Maine profile Table 1. 2010 Summary Statistics (Maine) Item Value U.S. Rank NERC Region(s) NPCC Primary Energy Source Gas Net Summer Capacity (megawatts) 4,430 42 Electric Utilities 19 49 Independent Power Producers & Combined Heat and Power 4,410 25 Net Generation (megawatthours) 17,018,660 43 Electric Utilities 1,759 49 Independent Power Producers & Combined Heat and Power 17,016,901 22 Emissions (thousand metric tons) Sulfur Dioxide 12 42 Nitrogen Oxide 8 44 Carbon Dioxide 4,948 44 Sulfur Dioxide (lbs/MWh) 1.6 36 Nitrogen Oxide (lbs/MWh) 1.1 33 Carbon Dioxide (lbs/MWh) 641 44 Total Retail Sales (megawatthours) 11,531,568 45 Full Service Provider Sales (megawatthours) 151,588 51 Energy-Only Provider Sales (megawatthours) 11,379,980 10

152

EIA - State Electricity Profiles  

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

Mississippi Electricity Profile 2010 Mississippi profile Mississippi Electricity Profile 2010 Mississippi profile Table 1. 2010 Summary Statistics (Mississippi) Item Value U.S. Rank NERC Region(s) SERC Primary Energy Source Gas Net Summer Capacity (megawatts) 15,691 26 Electric Utilities 10,858 26 Independent Power Producers & Combined Heat and Power 4,833 18 Net Generation (megawatthours) 54,487,260 28 Electric Utilities 40,841,436 27 Independent Power Producers & Combined Heat and Power 13,645,824 28 Emissions (thousand metric tons) Sulfur Dioxide 59 26 Nitrogen Oxide 31 32 Carbon Dioxide 26,845 32 Sulfur Dioxide (lbs/MWh) 2.4 26 Nitrogen Oxide (lbs/MWh) 1.2 30 Carbon Dioxide (lbs/MWh) 1,086 36 Total Retail Sales (megawatthours) 49,687,166 28 Full Service Provider Sales (megawatthours) 49,687,166 26

153

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Washington Electricity Profile 2010 Washington profile Washington Electricity Profile 2010 Washington profile Table 1. 2010 Summary Statistics (Washington) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Hydroelectric Net Summer Capacity (megawatts) 30,478 10 Electric Utilities 26,498 5 Independent Power Producers & Combined Heat and Power 3,979 26 Net Generation (megawatthours) 103,472,729 15 Electric Utilities 88,057,219 14 Independent Power Producers & Combined Heat and Power 15,415,510 23 Emissions (thousand metric tons) Sulfur Dioxide 14 39 Nitrogen Oxide 21 37 Carbon Dioxide 13,984 39 Sulfur Dioxide (lbs/MWh) 0.3 47 Nitrogen Oxide (lbs/MWh) 0.4 50 Carbon Dioxide (lbs/MWh) 298 49 Total Retail Sales (megawatthours) 90,379,970 16 Full Service Provider Sales (megawatthours) 88,116,958 14

154

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Mexico Electricity Profile 2010 New Mexico profile Mexico Electricity Profile 2010 New Mexico profile Table 1. 2010 Summary Statistics (New Mexico) Item Value U.S. Rank NERC Region(s) SPP/WECC Primary Energy Source Coal Net Summer Capacity (megawatts) 8,130 36 Electric Utilities 6,345 33 Independent Power Producers & Combined Heat and Power 1,785 36 Net Generation (megawatthours) 36,251,542 37 Electric Utilities 30,848,406 33 Independent Power Producers & Combined Heat and Power 5,403,136 37 Emissions (thousand metric tons) Sulfur Dioxide 15 38 Nitrogen Oxide 56 19 Carbon Dioxide 29,379 31 Sulfur Dioxide (lbs/MWh) 0.9 42 Nitrogen Oxide (lbs/MWh) 3.4 5 Carbon Dioxide (lbs/MWh) 1,787 11 Total Retail Sales (megawatthours) 22,428,344 39 Full Service Provider Sales (megawatthours) 22,428,344 38

155

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Delaware Electricity Profile 2010 Delaware profile Delaware Electricity Profile 2010 Delaware profile Table 1. 2010 Summary Statistics (Delaware) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Gas Net Summer Capacity (megawatts) 3,389 46 Electric Utilities 55 48 Independent Power Producers & Combined Heat and Power 3,334 29 Net Generation (megawatthours) 5,627,645 50 Electric Utilities 30,059 46 Independent Power Producers & Combined Heat and Power 5,597,586 36 Emissions (thousand metric tons) Sulfur Dioxide 13 41 Nitrogen Oxide 5 47 Carbon Dioxide 4,187 45 Sulfur Dioxide (lbs/MWh) 5.2 7 Nitrogen Oxide (lbs/MWh) 1.9 16 Carbon Dioxide (lbs/MWh) 1,640 15 Total Retail Sales (megawatthours) 11,605,932 44 Full Service Provider Sales (megawatthours) 7,582,539 46

156

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Ohio Electricity Profile 2010 Ohio profile Ohio Electricity Profile 2010 Ohio profile Table 1. 2010 Summary Statistics (Ohio) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 33,071 8 Electric Utilities 20,179 13 Independent Power Producers & Combined Heat and Power 12,892 7 Net Generation (megawatthours) 143,598,337 7 Electric Utilities 92,198,096 10 Independent Power Producers & Combined Heat and Power 51,400,241 7 Emissions (thousand metric tons) Sulfur Dioxide 610 1 Nitrogen Oxide 122 3 Carbon Dioxide 121,964 4 Sulfur Dioxide (lbs/MWh) 9.4 1 Nitrogen Oxide (lbs/MWh) 1.9 17 Carbon Dioxide (lbs/MWh) 1,872 8 Total Retail Sales (megawatthours) 154,145,418 4 Full Service Provider Sales (megawatthours) 105,329,797 9

157

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Arkansas Electricity Profile 2010 Arkansas profile Arkansas Electricity Profile 2010 Arkansas profile Table 1. 2010 Summary Statistics (Arkansas) Item Value U.S. Rank NERC Region(s) SERC/SPP Primary Energy Source Coal Net Summer Capacity (megawatts) 15,981 25 Electric Utilities 11,488 23 Independent Power Producers & Combined Heat and Power 4,493 24 Net Generation (megawatthours) 61,000,185 25 Electric Utilities 47,108,063 20 Independent Power Producers & Combined Heat and Power 13,892,122 27 Emissions (thousand metric tons) Sulfur Dioxide 74 22 Nitrogen Oxide 40 29 Carbon Dioxide 34,018 28 Sulfur Dioxide (lbs/MWh) 2.7 22 Nitrogen Oxide (lbs/MWh) 1.5 24 Carbon Dioxide (lbs/MWh) 1,229 29 Total Retail Sales (megawatthours) 48,194,285 29 Full Service Provider Sales (megawatthours) 48,194,285 27

158

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Oklahoma Electricity Profile 2010 Oklahoma profile Oklahoma Electricity Profile 2010 Oklahoma profile Table 1. 2010 Summary Statistics (Oklahoma) Item Value U.S. Rank NERC Region(s) SPP Primary Energy Source Gas Net Summer Capacity (megawatts) 21,022 20 Electric Utilities 16,015 18 Independent Power Producers & Combined Heat and Power 5,006 17 Net Generation (megawatthours) 72,250,733 22 Electric Utilities 57,421,195 17 Independent Power Producers & Combined Heat and Power 14,829,538 24 Emissions (thousand metric tons) Sulfur Dioxide 85 21 Nitrogen Oxide 71 12 Carbon Dioxide 49,536 17 Sulfur Dioxide (lbs/MWh) 2.6 24 Nitrogen Oxide (lbs/MWh) 2.2 11 Carbon Dioxide (lbs/MWh) 1,512 17 Total Retail Sales (megawatthours) 57,845,980 25 Full Service Provider Sales (megawatthours) 57,845,980 23

159

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Iowa Electricity Profile 2010 Iowa profile Iowa Electricity Profile 2010 Iowa profile Table 1. 2010 Summary Statistics (Iowa) Item Value U.S. Rank NERC Region(s) MRO/SERC Primary Energy Source Coal Net Summer Capacity (megawatts) 14,592 28 Electric Utilities 11,282 24 Independent Power Producers & Combined Heat and Power 3,310 30 Net Generation (megawatthours) 57,508,721 26 Electric Utilities 46,188,988 21 Independent Power Producers & Combined Heat and Power 11,319,733 30 Emissions (thousand metric tons) Sulfur Dioxide 108 18 Nitrogen Oxide 50 22 Carbon Dioxide 47,211 20 Sulfur Dioxide (lbs/MWh) 4.1 11 Nitrogen Oxide (lbs/MWh) 1.9 14 Carbon Dioxide (lbs/MWh) 1,810 10 Total Retail Sales (megawatthours) 45,445,269 31 Full Service Provider Sales (megawatthours) 45,445,269 28

160

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

West Virginia Electricity Profile 2010 West Virginia profile West Virginia Electricity Profile 2010 West Virginia profile Table 1. 2010 Summary Statistics (West Virginia) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 16,495 24 Electric Utilities 11,719 21 Independent Power Producers & Combined Heat and Power 4,775 19 Net Generation (megawatthours) 80,788,947 20 Electric Utilities 56,719,755 18 Independent Power Producers & Combined Heat and Power 24,069,192 13 Emissions (thousand metric tons) Sulfur Dioxide 105 20 Nitrogen Oxide 49 23 Carbon Dioxide 74,283 12 Sulfur Dioxide (lbs/MWh) 2.9 20 Nitrogen Oxide (lbs/MWh) 1.3 25 Carbon Dioxide (lbs/MWh) 2,027 5 Total Retail Sales (megawatthours) 32,031,803 34 Full Service Provider Sales (megawatthours) 32,031,803 33

Note: This page contains sample records for the topic "kwh load profiles" 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

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Vermont Electricity Profile 2010 Vermont profile Vermont Electricity Profile 2010 Vermont profile Table 1. 2010 Summary Statistics (Vermont) Item Value U.S. Rank NERC Region(s) NPCC Primary Energy Source Nuclear Net Summer Capacity (megawatts) 1,128 50 Electric Utilities 260 45 Independent Power Producers & Combined Heat and Power 868 43 Net Generation (megawatthours) 6,619,990 49 Electric Utilities 720,853 44 Independent Power Producers & Combined Heat and Power 5,899,137 35 Emissions (thousand metric tons) Sulfur Dioxide * 51 Nitrogen Oxide 1 50 Carbon Dioxide 8 51 Sulfur Dioxide (lbs/MWh) * 51 Nitrogen Oxide (lbs/MWh) 0.2 51 Carbon Dioxide (lbs/MWh) 3 51 Total Retail Sales (megawatthours) 5,594,833 51 Full Service Provider Sales (megawatthours) 5,594,833 48 Direct Use (megawatthours) 19,806 47

162

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Mississippi Electricity Profile 2010 Mississippi profile Mississippi Electricity Profile 2010 Mississippi profile Table 1. 2010 Summary Statistics (Mississippi) Item Value U.S. Rank NERC Region(s) SERC Primary Energy Source Gas Net Summer Capacity (megawatts) 15,691 26 Electric Utilities 10,858 26 Independent Power Producers & Combined Heat and Power 4,833 18 Net Generation (megawatthours) 54,487,260 28 Electric Utilities 40,841,436 27 Independent Power Producers & Combined Heat and Power 13,645,824 28 Emissions (thousand metric tons) Sulfur Dioxide 59 26 Nitrogen Oxide 31 32 Carbon Dioxide 26,845 32 Sulfur Dioxide (lbs/MWh) 2.4 26 Nitrogen Oxide (lbs/MWh) 1.2 30 Carbon Dioxide (lbs/MWh) 1,086 36 Total Retail Sales (megawatthours) 49,687,166 28 Full Service Provider Sales (megawatthours) 49,687,166 26

163

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Wisconsin Electricity Profile 2010 Wisconsin profile Wisconsin Electricity Profile 2010 Wisconsin profile Table 1. 2010 Summary Statistics (Wisconsin) Item Value U.S. Rank NERC Region(s) MRO/RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 17,836 23 Electric Utilities 13,098 19 Independent Power Producers & Combined Heat and Power 4,738 20 Net Generation (megawatthours) 64,314,067 24 Electric Utilities 45,579,970 22 Independent Power Producers & Combined Heat and Power 18,734,097 18 Emissions (thousand metric tons) Sulfur Dioxide 145 12 Nitrogen Oxide 49 25 Carbon Dioxide 47,238 19 Sulfur Dioxide (lbs/MWh) 5.0 9 Nitrogen Oxide (lbs/MWh) 1.7 20 Carbon Dioxide (lbs/MWh) 1,619 16 Total Retail Sales (megawatthours) 68,752,417 22 Full Service Provider Sales (megawatthours) 68,752,417 21

164

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Colorado Electricity Profile 2010 Colorado profile Colorado Electricity Profile 2010 Colorado profile Table 1. 2010 Summary Statistics (Colorado) Item Value U.S. Rank NERC Region(s) RFC/WECC Primary Energy Source Coal Net Summer Capacity (megawatts) 13,777 30 Electric Utilities 9,114 28 Independent Power Producers & Combined Heat and Power 4,662 22 Net Generation (megawatthours) 50,720,792 30 Electric Utilities 39,584,166 28 Independent Power Producers & Combined Heat and Power 11,136,626 31 Emissions (thousand metric tons) Sulfur Dioxide 45 29 Nitrogen Oxide 55 20 Carbon Dioxide 40,499 24 Sulfur Dioxide (lbs/MWh) 2.0 32 Nitrogen Oxide (lbs/MWh) 2.4 10 Carbon Dioxide (lbs/MWh) 1,760 12 Total Retail Sales (megawatthours) 52,917,786 27 Full Service Provider Sales (megawatthours) 52,917,786 24

165

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Hampshire Electricity Profile 2010 New Hampshire profile Hampshire Electricity Profile 2010 New Hampshire profile Table 1. 2010 Summary Statistics (New Hampshire) Item Value U.S. Rank NERC Region(s) NPCC Primary Energy Source Nuclear Net Summer Capacity (megawatts) 4,180 43 Electric Utilities 1,132 41 Independent Power Producers & Combined Heat and Power 3,048 32 Net Generation (megawatthours) 22,195,912 42 Electric Utilities 3,979,333 41 Independent Power Producers & Combined Heat and Power 18,216,579 19 Emissions (thousand metric tons) Sulfur Dioxide 34 32 Nitrogen Oxide 6 46 Carbon Dioxide 5,551 43 Sulfur Dioxide (lbs/MWh) 3.4 17 Nitrogen Oxide (lbs/MWh) 0.6 46 Carbon Dioxide (lbs/MWh) 551 47 Total Retail Sales (megawatthours) 10,890,074 47 Full Service Provider Sales (megawatthours) 7,712,938 45

166

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Carolina Electricity Profile 2010 North Carolina profile Carolina Electricity Profile 2010 North Carolina profile Table 1. 2010 Summary Statistics (North Carolina) Item Value U.S. Rank NERC Region(s) SERC Primary Energy Source Coal Net Summer Capacity (megawatts) 27,674 12 Electric Utilities 25,553 6 Independent Power Producers & Combined Heat and Power 2,121 34 Net Generation (megawatthours) 128,678,483 10 Electric Utilities 121,251,138 3 Independent Power Producers & Combined Heat and Power 7,427,345 34 Emissions (thousand metric tons) Sulfur Dioxide 131 14 Nitrogen Oxide 57 16 Carbon Dioxide 73,241 13 Sulfur Dioxide (lbs/MWh) 2.2 31 Nitrogen Oxide (lbs/MWh) 1.0 34 Carbon Dioxide (lbs/MWh) 1,255 28 Total Retail Sales (megawatthours) 136,414,947 9 Full Service Provider Sales (megawatthours) 136,414,947 5

167

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Nevada Electricity Profile 2010 Nevada profile Nevada Electricity Profile 2010 Nevada profile Table 1. 2010 Summary Statistics (Nevada) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Gas Net Summer Capacity (megawatts) 11,421 34 Electric Utilities 8,713 29 Independent Power Producers & Combined Heat and Power 2,708 33 Net Generation (megawatthours) 35,146,248 38 Electric Utilities 23,710,917 34 Independent Power Producers & Combined Heat and Power 11,435,331 29 Emissions (thousand metric tons) Sulfur Dioxide 7 44 Nitrogen Oxide 15 40 Carbon Dioxide 17,020 38 Sulfur Dioxide (lbs/MWh) 0.4 46 Nitrogen Oxide (lbs/MWh) 1.0 37 Carbon Dioxide (lbs/MWh) 1,068 37 Total Retail Sales (megawatthours) 33,772,595 33 Full Service Provider Sales (megawatthours) 32,348,879 32

168

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Kansas Electricity Profile 2010 Kansas profile Kansas Electricity Profile 2010 Kansas profile Table 1. 2010 Summary Statistics (Kansas) Item Value U.S. Rank NERC Region(s) MRO/SPP Primary Energy Source Coal Net Summer Capacity (megawatts) 12,543 32 Electric Utilities 11,732 20 Independent Power Producers & Combined Heat and Power 812 45 Net Generation (megawatthours) 47,923,762 32 Electric Utilities 45,270,047 24 Independent Power Producers & Combined Heat and Power 2,653,716 44 Emissions (thousand metric tons) Sulfur Dioxide 41 30 Nitrogen Oxide 46 26 Carbon Dioxide 36,321 26 Sulfur Dioxide (lbs/MWh) 1.9 33 Nitrogen Oxide (lbs/MWh) 2.1 13 Carbon Dioxide (lbs/MWh) 1,671 14 Total Retail Sales (megawatthours) 40,420,675 32 Full Service Provider Sales (megawatthours) 40,420,675 30

169

EIA - State Electricity Profiles  

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

Nebraska Electricity Profile 2010 Nebraska profile Nebraska Electricity Profile 2010 Nebraska profile Table 1. 2010 Summary Statistics (Nebraska) Item Value U.S. Rank NERC Region(s) MRO/SPP Primary Energy Source Coal Net Summer Capacity (megawatts) 7,857 38 Electric Utilities 7,647 30 Independent Power Producers & Combined Heat and Power 210 50 Net Generation (megawatthours) 36,630,006 36 Electric Utilities 36,242,921 30 Independent Power Producers & Combined Heat and Power 387,085 50 Emissions (thousand metric tons) Sulfur Dioxide 65 24 Nitrogen Oxide 40 30 Carbon Dioxide 24,461 34 Sulfur Dioxide (lbs/MWh) 3.9 12 Nitrogen Oxide (lbs/MWh) 2.4 9 Carbon Dioxide (lbs/MWh) 1,472 19 Total Retail Sales (megawatthours) 29,849,460 36 Full Service Provider Sales (megawatthours) 29,849,460 35

170

EIA - State Electricity Profiles  

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

Missouri Electricity Profile 2010 Missouri profile Missouri Electricity Profile 2010 Missouri profile Table 1. 2010 Summary Statistics (Missouri) Item Value U.S. Rank NERC Region(s) SERC/SPP Primary Energy Source Coal Net Summer Capacity (megawatts) 21,739 18 Electric Utilities 20,360 12 Independent Power Producers & Combined Heat and Power 1,378 39 Net Generation (megawatthours) 92,312,989 18 Electric Utilities 90,176,805 12 Independent Power Producers & Combined Heat and Power 2,136,184 46 Emissions (thousand metric tons) Sulfur Dioxide 233 8 Nitrogen Oxide 56 18 Carbon Dioxide 78,815 10 Sulfur Dioxide (lbs/MWh) 5.6 6 Nitrogen Oxide (lbs/MWh) 1.3 26 Carbon Dioxide (lbs/MWh) 1,882 7 Total Retail Sales (megawatthours) 86,085,117 17 Full Service Provider Sales (megawatthours) 86,085,117 15

171

EIA - State Electricity Profiles  

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

Dakota Electricity Profile 2010 North Dakota profile Dakota Electricity Profile 2010 North Dakota profile Table 1. 2010 Summary Statistics (North Dakota) Item Value U.S. Rank NERC Region(s) MRO Primary Energy Source Coal Net Summer Capacity (megawatts) 6,188 40 Electric Utilities 4,912 34 Independent Power Producers & Combined Heat and Power 1,276 40 Net Generation (megawatthours) 34,739,542 39 Electric Utilities 31,343,796 32 Independent Power Producers & Combined Heat and Power 3,395,746 41 Emissions (thousand metric tons) Sulfur Dioxide 116 17 Nitrogen Oxide 52 21 Carbon Dioxide 31,064 30 Sulfur Dioxide (lbs/MWh) 7.3 3 Nitrogen Oxide (lbs/MWh) 3.3 6 Carbon Dioxide (lbs/MWh) 1,971 6 Total Retail Sales (megawatthours) 12,956,263 42 Full Service Provider Sales (megawatthours) 12,956,263 41

172

EIA - State Electricity Profiles  

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

Minnesota Electricity Profile 2010 Minnesota profile Minnesota Electricity Profile 2010 Minnesota profile Table 1. 2010 Summary Statistics (Minnesota) Item Value U.S. Rank NERC Region(s) MRO Primary Energy Source Coal Net Summer Capacity (megawatts) 14,715 27 Electric Utilities 11,547 22 Independent Power Producers & Combined Heat and Power 3,168 31 Net Generation (megawatthours) 53,670,227 29 Electric Utilities 45,428,599 23 Independent Power Producers & Combined Heat and Power 8,241,628 32 Emissions (thousand metric tons) Sulfur Dioxide 57 27 Nitrogen Oxide 44 27 Carbon Dioxide 32,946 29 Sulfur Dioxide (lbs/MWh) 2.3 27 Nitrogen Oxide (lbs/MWh) 1.8 18 Carbon Dioxide (lbs/MWh) 1,353 21 Total Retail Sales (megawatthours) 67,799,706 23 Full Service Provider Sales (megawatthours) 67,799,706 22

173

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Louisiana Electricity Profile 2010 Louisiana profile Louisiana Electricity Profile 2010 Louisiana profile Table 1. 2010 Summary Statistics (Louisiana) Item Value U.S. Rank NERC Region(s) SERC/SPP Primary Energy Source Gas Net Summer Capacity (megawatts) 26,744 14 Electric Utilities 16,471 17 Independent Power Producers & Combined Heat and Power 10,272 10 Net Generation (megawatthours) 102,884,940 16 Electric Utilities 51,680,682 19 Independent Power Producers & Combined Heat and Power 51,204,258 8 Emissions (thousand metric tons) Sulfur Dioxide 126 15 Nitrogen Oxide 75 11 Carbon Dioxide 58,706 14 Sulfur Dioxide (lbs/MWh) 2.7 21 Nitrogen Oxide (lbs/MWh) 1.6 21 Carbon Dioxide (lbs/MWh) 1,258 27 Total Retail Sales (megawatthours) 85,079,692 18 Full Service Provider Sales (megawatthours) 85,079,692 16

174

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Utah Electricity Profile 2010 Utah profile Utah Electricity Profile 2010 Utah profile Table 1. 2010 Summary Statistics (Utah) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Coal Net Summer Capacity (megawatts) 7,497 39 Electric Utilities 6,648 32 Independent Power Producers & Combined Heat and Power 849 44 Net Generation (megawatthours) 42,249,355 35 Electric Utilities 39,522,124 29 Independent Power Producers & Combined Heat and Power 2,727,231 43 Emissions (thousand metric tons) Sulfur Dioxide 25 34 Nitrogen Oxide 68 13 Carbon Dioxide 35,519 27 Sulfur Dioxide (lbs/MWh) 1.3 38 Nitrogen Oxide (lbs/MWh) 3.6 4 Carbon Dioxide (lbs/MWh) 1,853 9 Total Retail Sales (megawatthours) 28,044,001 37 Full Service Provider Sales (megawatthours) 28,044,001 36

175

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Virginia Electricity Profile 2010 Virginia profile Virginia Electricity Profile 2010 Virginia profile Table 1. 2010 Summary Statistics (Virginia) Item Value U.S. Rank NERC Region(s) RFC/SERC Primary Energy Source Nuclear Net Summer Capacity (megawatts) 24,109 16 Electric Utilities 19,434 15 Independent Power Producers & Combined Heat and Power 4,676 21 Net Generation (megawatthours) 72,966,456 21 Electric Utilities 58,902,054 16 Independent Power Producers & Combined Heat and Power 14,064,402 25 Emissions (thousand metric tons) Sulfur Dioxide 120 16 Nitrogen Oxide 49 24 Carbon Dioxide 39,719 25 Sulfur Dioxide (lbs/MWh) 3.6 15 Nitrogen Oxide (lbs/MWh) 1.5 23 Carbon Dioxide (lbs/MWh) 1,200 30 Total Retail Sales (megawatthours) 113,806,135 10 Full Service Provider Sales (megawatthours) 113,806,135 7

176

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Dakota Electricity Profile 2010 North Dakota profile Dakota Electricity Profile 2010 North Dakota profile Table 1. 2010 Summary Statistics (North Dakota) Item Value U.S. Rank NERC Region(s) MRO Primary Energy Source Coal Net Summer Capacity (megawatts) 6,188 40 Electric Utilities 4,912 34 Independent Power Producers & Combined Heat and Power 1,276 40 Net Generation (megawatthours) 34,739,542 39 Electric Utilities 31,343,796 32 Independent Power Producers & Combined Heat and Power 3,395,746 41 Emissions (thousand metric tons) Sulfur Dioxide 116 17 Nitrogen Oxide 52 21 Carbon Dioxide 31,064 30 Sulfur Dioxide (lbs/MWh) 7.3 3 Nitrogen Oxide (lbs/MWh) 3.3 6 Carbon Dioxide (lbs/MWh) 1,971 6 Total Retail Sales (megawatthours) 12,956,263 42 Full Service Provider Sales (megawatthours) 12,956,263 41

177

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Alaska Electricity Profile 2010 Alaska profile Alaska Electricity Profile 2010 Alaska profile Table 1. 2010 Summary Statistics (Alaska) Item Value U.S. Rank NERC Region(s) -- Primary Energy Source Gas Net Summer Capacity (megawatts) 2,067 48 Electric Utilities 1,889 39 Independent Power Producers & Combined Heat and Power 178 51 Net Generation (megawatthours) 6,759,576 48 Electric Utilities 6,205,050 40 Independent Power Producers & Combined Heat and Power 554,526 49 Emissions (thousand metric tons) Sulfur Dioxide 3 46 Nitrogen Oxide 16 39 Carbon Dioxide 4,125 46 Sulfur Dioxide (lbs/MWh) 1.0 41 Nitrogen Oxide (lbs/MWh) 5.2 1 Carbon Dioxide (lbs/MWh) 1,345 23 Total Retail Sales (megawatthours) 6,247,038 50 Full Service Provider Sales (megawatthours) 6,247,038 47

178

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Minnesota Electricity Profile 2010 Minnesota profile Minnesota Electricity Profile 2010 Minnesota profile Table 1. 2010 Summary Statistics (Minnesota) Item Value U.S. Rank NERC Region(s) MRO Primary Energy Source Coal Net Summer Capacity (megawatts) 14,715 27 Electric Utilities 11,547 22 Independent Power Producers & Combined Heat and Power 3,168 31 Net Generation (megawatthours) 53,670,227 29 Electric Utilities 45,428,599 23 Independent Power Producers & Combined Heat and Power 8,241,628 32 Emissions (thousand metric tons) Sulfur Dioxide 57 27 Nitrogen Oxide 44 27 Carbon Dioxide 32,946 29 Sulfur Dioxide (lbs/MWh) 2.3 27 Nitrogen Oxide (lbs/MWh) 1.8 18 Carbon Dioxide (lbs/MWh) 1,353 21 Total Retail Sales (megawatthours) 67,799,706 23 Full Service Provider Sales (megawatthours) 67,799,706 22

179

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Maryland Electricity Profile 2010 Maryland profile Maryland Electricity Profile 2010 Maryland profile Table 1. 2010 Summary Statistics (Maryland) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 12,516 33 Electric Utilities 80 47 Independent Power Producers & Combined Heat and Power 12,436 9 Net Generation (megawatthours) 43,607,264 33 Electric Utilities 2,996 48 Independent Power Producers & Combined Heat and Power 43,604,268 9 Emissions (thousand metric tons) Sulfur Dioxide 45 28 Nitrogen Oxide 25 34 Carbon Dioxide 26,369 33 Sulfur Dioxide (lbs/MWh) 2.3 29 Nitrogen Oxide (lbs/MWh) 1.3 29 Carbon Dioxide (lbs/MWh) 1,333 24 Total Retail Sales (megawatthours) 65,335,498 24 Full Service Provider Sales (megawatthours) 36,082,473 31

180

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

York Electricity Profile 2010 New York profile York Electricity Profile 2010 New York profile Table 1. 2010 Summary Statistics (New York) Item Value U.S. Rank NERC Region(s) NPCC Primary Energy Source Gas Net Summer Capacity (megawatts) 39,357 6 Electric Utilities 11,032 25 Independent Power Producers & Combined Heat and Power 28,325 5 Net Generation (megawatthours) 136,961,654 9 Electric Utilities 34,633,335 31 Independent Power Producers & Combined Heat and Power 102,328,319 5 Emissions (thousand metric tons) Sulfur Dioxide 62 25 Nitrogen Oxide 44 28 Carbon Dioxide 41,584 22 Sulfur Dioxide (lbs/MWh) 1.0 40 Nitrogen Oxide (lbs/MWh) 0.7 44 Carbon Dioxide (lbs/MWh) 669 42 Total Retail Sales (megawatthours) 144,623,573 7 Full Service Provider Sales (megawatthours) 79,119,769 18

Note: This page contains sample records for the topic "kwh load profiles" 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

EIA - State Electricity Profiles  

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

Carolina Electricity Profile 2010 North Carolina profile Carolina Electricity Profile 2010 North Carolina profile Table 1. 2010 Summary Statistics (North Carolina) Item Value U.S. Rank NERC Region(s) SERC Primary Energy Source Coal Net Summer Capacity (megawatts) 27,674 12 Electric Utilities 25,553 6 Independent Power Producers & Combined Heat and Power 2,121 34 Net Generation (megawatthours) 128,678,483 10 Electric Utilities 121,251,138 3 Independent Power Producers & Combined Heat and Power 7,427,345 34 Emissions (thousand metric tons) Sulfur Dioxide 131 14 Nitrogen Oxide 57 16 Carbon Dioxide 73,241 13 Sulfur Dioxide (lbs/MWh) 2.2 31 Nitrogen Oxide (lbs/MWh) 1.0 34 Carbon Dioxide (lbs/MWh) 1,255 28 Total Retail Sales (megawatthours) 136,414,947 9 Full Service Provider Sales (megawatthours) 136,414,947 5

182

EIA - State Electricity Profiles  

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

Montana Electricity Profile 2010 Montana profile Montana Electricity Profile 2010 Montana profile Table 1. 2010 Summary Statistics (Montana) Item Value U.S. Rank NERC Region(s) MRO/WECC Primary Energy Source Coal Net Summer Capacity (megawatts) 5,866 41 Electric Utilities 2,340 38 Independent Power Producers & Combined Heat and Power 3,526 27 Net Generation (megawatthours) 29,791,181 41 Electric Utilities 6,271,180 39 Independent Power Producers & Combined Heat and Power 23,520,001 14 Emissions (thousand metric tons) Sulfur Dioxide 22 35 Nitrogen Oxide 21 35 Carbon Dioxide 20,370 35 Sulfur Dioxide (lbs/MWh) 1.6 35 Nitrogen Oxide (lbs/MWh) 1.6 22 Carbon Dioxide (lbs/MWh) 1,507 18 Total Retail Sales (megawatthours) 13,423,138 41 Full Service Provider Sales (megawatthours) 10,803,422 43

183

EIA - State Electricity Profiles  

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

Iowa Electricity Profile 2010 Iowa profile Iowa Electricity Profile 2010 Iowa profile Table 1. 2010 Summary Statistics (Iowa) Item Value U.S. Rank NERC Region(s) MRO/SERC Primary Energy Source Coal Net Summer Capacity (megawatts) 14,592 28 Electric Utilities 11,282 24 Independent Power Producers & Combined Heat and Power 3,310 30 Net Generation (megawatthours) 57,508,721 26 Electric Utilities 46,188,988 21 Independent Power Producers & Combined Heat and Power 11,319,733 30 Emissions (thousand metric tons) Sulfur Dioxide 108 18 Nitrogen Oxide 50 22 Carbon Dioxide 47,211 20 Sulfur Dioxide (lbs/MWh) 4.1 11 Nitrogen Oxide (lbs/MWh) 1.9 14 Carbon Dioxide (lbs/MWh) 1,810 10 Total Retail Sales (megawatthours) 45,445,269 31 Full Service Provider Sales (megawatthours) 45,445,269 28

184

EIA - State Electricity Profiles  

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

Illinois Electricity Profile 2010 Illinois profile Illinois Electricity Profile 2010 Illinois profile Table 1. 2010 Summary Statistics (Illinois) Item Value U.S. Rank NERC Region(s) MRO/RFC/SERC Primary Energy Source Nuclear Net Summer Capacity (megawatts) 44,127 5 Electric Utilities 4,800 35 Independent Power Producers & Combined Heat and Power 39,327 3 Net Generation (megawatthours) 201,351,872 5 Electric Utilities 12,418,332 35 Independent Power Producers & Combined Heat and Power 188,933,540 3 Emissions (thousand metric tons) Sulfur Dioxide 232 9 Nitrogen Oxide 83 8 Carbon Dioxide 103,128 6 Sulfur Dioxide (lbs/MWh) 2.5 25 Nitrogen Oxide (lbs/MWh) 0.9 38 Carbon Dioxide (lbs/MWh) 1,129 34 Total Retail Sales (megawatthours) 144,760,674 6 Full Service Provider Sales (megawatthours) 77,890,532 19

185

EIA - State Electricity Profiles  

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

Louisiana Electricity Profile 2010 Louisiana profile Louisiana Electricity Profile 2010 Louisiana profile Table 1. 2010 Summary Statistics (Louisiana) Item Value U.S. Rank NERC Region(s) SERC/SPP Primary Energy Source Gas Net Summer Capacity (megawatts) 26,744 14 Electric Utilities 16,471 17 Independent Power Producers & Combined Heat and Power 10,272 10 Net Generation (megawatthours) 102,884,940 16 Electric Utilities 51,680,682 19 Independent Power Producers & Combined Heat and Power 51,204,258 8 Emissions (thousand metric tons) Sulfur Dioxide 126 15 Nitrogen Oxide 75 11 Carbon Dioxide 58,706 14 Sulfur Dioxide (lbs/MWh) 2.7 21 Nitrogen Oxide (lbs/MWh) 1.6 21 Carbon Dioxide (lbs/MWh) 1,258 27 Total Retail Sales (megawatthours) 85,079,692 18 Full Service Provider Sales (megawatthours) 85,079,692 16

186

EIA - State Electricity Profiles  

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

California Electricity Profile 2010 California profile California Electricity Profile 2010 California profile Table 1. 2010 Summary Statistics (California) Item Value U.S. Rank NERC Region(s) SPP/WECC Primary Energy Source Gas Net Summer Capacity (megawatts) 67,328 2 Electric Utilities 28,689 2 Independent Power Producers & Combined Heat and Power 38,639 4 Net Generation (megawatthours) 204,125,596 4 Electric Utilities 96,939,535 8 Independent Power Producers & Combined Heat and Power 107,186,061 4 Emissions (thousand metric tons) Sulfur Dioxide 3 47 Nitrogen Oxide 80 9 Carbon Dioxide 55,406 16 Sulfur Dioxide (lbs/MWh) * 49 Nitrogen Oxide (lbs/MWh) 0.9 41 Carbon Dioxide (lbs/MWh) 598 46 Total Retail Sales (megawatthours) 258,525,414 2 Full Service Provider Sales (megawatthours) 240,948,673 2

187

EIA - State Electricity Profiles  

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

Dakota Electricity Profile 2010 South Dakota profile Dakota Electricity Profile 2010 South Dakota profile Table 1. 2010 Summary Statistics (South Dakota) Item Value U.S. Rank NERC Region(s) MRO/WECC Primary Energy Source Hydroelectric Net Summer Capacity (megawatts) 3,623 45 Electric Utilities 2,994 37 Independent Power Producers & Combined Heat and Power 629 48 Net Generation (megawatthours) 10,049,636 46 Electric Utilities 8,682,448 36 Independent Power Producers & Combined Heat and Power 1,367,188 47 Emissions (thousand metric tons) Sulfur Dioxide 12 43 Nitrogen Oxide 12 43 Carbon Dioxide 3,611 47 Sulfur Dioxide (lbs/MWh) 2.6 23 Nitrogen Oxide (lbs/MWh) 2.6 8 Carbon Dioxide (lbs/MWh) 792 41 Total Retail Sales (megawatthours) 11,356,149 46 Full Service Provider Sales (megawatthours) 11,356,149 42

188

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Jersey Electricity Profile 2010 New Jersey profile Jersey Electricity Profile 2010 New Jersey profile Table 1. 2010 Summary Statistics (New Jersey) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Nuclear Net Summer Capacity (megawatts) 18,424 22 Electric Utilities 460 43 Independent Power Producers & Combined Heat and Power 17,964 6 Net Generation (megawatthours) 65,682,494 23 Electric Utilities -186,385 50 Independent Power Producers & Combined Heat and Power 65,868,878 6 Emissions (thousand metric tons) Sulfur Dioxide 14 40 Nitrogen Oxide 15 41 Carbon Dioxide 19,160 37 Sulfur Dioxide (lbs/MWh) 0.5 45 Nitrogen Oxide (lbs/MWh) 0.5 48 Carbon Dioxide (lbs/MWh) 643 43 Total Retail Sales (megawatthours) 79,179,427 20 Full Service Provider Sales (megawatthours) 50,482,035 25

189

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Massachusetts Electricity Profile 2010 Massachusetts profile Massachusetts Electricity Profile 2010 Massachusetts profile Table 1. 2010 Summary Statistics (Massachusetts) Item Value U.S. Rank NERC Region(s) NPCC Primary Energy Source Gas Net Summer Capacity (megawatts) 13,697 31 Electric Utilities 937 42 Independent Power Producers & Combined Heat and Power 12,760 8 Net Generation (megawatthours) 42,804,824 34 Electric Utilities 802,906 43 Independent Power Producers & Combined Heat and Power 42,001,918 10 Emissions (thousand metric tons) Sulfur Dioxide 35 31 Nitrogen Oxide 17 38 Carbon Dioxide 20,291 36 Sulfur Dioxide (lbs/MWh) 1.8 34 Nitrogen Oxide (lbs/MWh) 0.9 39 Carbon Dioxide (lbs/MWh) 1,045 38 Total Retail Sales (megawatthours) 57,123,422 26 Full Service Provider Sales (megawatthours) 31,822,942 34

190

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Nebraska Electricity Profile 2010 Nebraska profile Nebraska Electricity Profile 2010 Nebraska profile Table 1. 2010 Summary Statistics (Nebraska) Item Value U.S. Rank NERC Region(s) MRO/SPP Primary Energy Source Coal Net Summer Capacity (megawatts) 7,857 38 Electric Utilities 7,647 30 Independent Power Producers & Combined Heat and Power 210 50 Net Generation (megawatthours) 36,630,006 36 Electric Utilities 36,242,921 30 Independent Power Producers & Combined Heat and Power 387,085 50 Emissions (thousand metric tons) Sulfur Dioxide 65 24 Nitrogen Oxide 40 30 Carbon Dioxide 24,461 34 Sulfur Dioxide (lbs/MWh) 3.9 12 Nitrogen Oxide (lbs/MWh) 2.4 9 Carbon Dioxide (lbs/MWh) 1,472 19 Total Retail Sales (megawatthours) 29,849,460 36 Full Service Provider Sales (megawatthours) 29,849,460 35

191

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Montana Electricity Profile 2010 Montana profile Montana Electricity Profile 2010 Montana profile Table 1. 2010 Summary Statistics (Montana) Item Value U.S. Rank NERC Region(s) MRO/WECC Primary Energy Source Coal Net Summer Capacity (megawatts) 5,866 41 Electric Utilities 2,340 38 Independent Power Producers & Combined Heat and Power 3,526 27 Net Generation (megawatthours) 29,791,181 41 Electric Utilities 6,271,180 39 Independent Power Producers & Combined Heat and Power 23,520,001 14 Emissions (thousand metric tons) Sulfur Dioxide 22 35 Nitrogen Oxide 21 35 Carbon Dioxide 20,370 35 Sulfur Dioxide (lbs/MWh) 1.6 35 Nitrogen Oxide (lbs/MWh) 1.6 22 Carbon Dioxide (lbs/MWh) 1,507 18 Total Retail Sales (megawatthours) 13,423,138 41 Full Service Provider Sales (megawatthours) 10,803,422 43

192

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Maine Electricity Profile 2010 Maine profile Maine Electricity Profile 2010 Maine profile Table 1. 2010 Summary Statistics (Maine) Item Value U.S. Rank NERC Region(s) NPCC Primary Energy Source Gas Net Summer Capacity (megawatts) 4,430 42 Electric Utilities 19 49 Independent Power Producers & Combined Heat and Power 4,410 25 Net Generation (megawatthours) 17,018,660 43 Electric Utilities 1,759 49 Independent Power Producers & Combined Heat and Power 17,016,901 22 Emissions (thousand metric tons) Sulfur Dioxide 12 42 Nitrogen Oxide 8 44 Carbon Dioxide 4,948 44 Sulfur Dioxide (lbs/MWh) 1.6 36 Nitrogen Oxide (lbs/MWh) 1.1 33 Carbon Dioxide (lbs/MWh) 641 44 Total Retail Sales (megawatthours) 11,531,568 45 Full Service Provider Sales (megawatthours) 151,588 51 Energy-Only Provider Sales (megawatthours) 11,379,980 10

193

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Texas Electricity Profile 2010 Texas profile Texas Electricity Profile 2010 Texas profile Table 1. 2010 Summary Statistics (Texas) Item Value U.S. Rank NERC Region(s) SERC/SPP/TRE/WECC Primary Energy Source Gas Net Summer Capacity (megawatts) 108,258 1 Electric Utilities 26,533 4 Independent Power Producers & Combined Heat and Power 81,724 1 Net Generation (megawatthours) 411,695,046 1 Electric Utilities 95,099,161 9 Independent Power Producers & Combined Heat and Power 316,595,885 1 Emissions (thousand metric tons) Sulfur Dioxide 430 2 Nitrogen Oxide 204 1 Carbon Dioxide 251,409 1 Sulfur Dioxide (lbs/MWh) 2.3 28 Nitrogen Oxide (lbs/MWh) 1.1 32 Carbon Dioxide (lbs/MWh) 1,346 22 Total Retail Sales (megawatthours) 358,457,550 1 Full Service Provider Sales (megawatthours) 358,457,550 1

194

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Florida Electricity Profile 2010 Florida profile Florida Electricity Profile 2010 Florida profile Table 1. 2010 Summary Statistics (Florida) Item Value U.S. Rank NERC Region(s) FRCC/SERC Primary Energy Source Gas Net Summer Capacity (megawatts) 59,147 3 Electric Utilities 50,853 1 Independent Power Producers & Combined Heat and Power 8,294 13 Net Generation (megawatthours) 229,095,935 3 Electric Utilities 206,062,185 1 Independent Power Producers & Combined Heat and Power 23,033,750 15 Emissions (thousand metric tons) Sulfur Dioxide 160 11 Nitrogen Oxide 101 5 Carbon Dioxide 123,811 2 Sulfur Dioxide (lbs/MWh) 1.5 37 Nitrogen Oxide (lbs/MWh) 1.0 35 Carbon Dioxide (lbs/MWh) 1,191 31 Total Retail Sales (megawatthours) 231,209,614 3 Full Service Provider Sales (megawatthours) 231,209,614 3

195

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Hawaii Electricity Profile 2010 Hawaii profile Hawaii Electricity Profile 2010 Hawaii profile Table 1. 2010 Summary Statistics (Hawaii) Item Value U.S. Rank NERC Region(s) -- Primary Energy Source Petroleum Net Summer Capacity (megawatts) 2,536 47 Electric Utilities 1,828 40 Independent Power Producers & Combined Heat and Power 708 47 Net Generation (megawatthours) 10,836,036 45 Electric Utilities 6,416,068 38 Independent Power Producers & Combined Heat and Power 4,419,968 38 Emissions (thousand metric tons) Sulfur Dioxide 17 36 Nitrogen Oxide 21 36 Carbon Dioxide 8,287 42 Sulfur Dioxide (lbs/MWh) 3.4 16 Nitrogen Oxide (lbs/MWh) 4.3 2 Carbon Dioxide (lbs/MWh) 1,686 13 Total Retail Sales (megawatthours) 10,016,509 48 Full Service Provider Sales (megawatthours) 10,016,509 44

196

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Connecticut Electricity Profile 2010 Connecticut profile Connecticut Electricity Profile 2010 Connecticut profile Table 1. 2010 Summary Statistics (Connecticut) Item Value U.S. Rank NERC Region(s) NPCC Primary Energy Source Nuclear Net Summer Capacity (megawatts) 8,284 35 Electric Utilities 160 46 Independent Power Producers & Combined Heat and Power 8,124 15 Net Generation (megawatthours) 33,349,623 40 Electric Utilities 65,570 45 Independent Power Producers & Combined Heat and Power 33,284,053 11 Emissions (thousand metric tons) Sulfur Dioxide 2 48 Nitrogen Oxide 7 45 Carbon Dioxide 9,201 41 Sulfur Dioxide (lbs/MWh) 0.1 48 Nitrogen Oxide (lbs/MWh) 0.5 49 Carbon Dioxide (lbs/MWh) 608 45 Total Retail Sales (megawatthours) 30,391,766 35 Full Service Provider Sales (megawatthours) 13,714,958 40

197

EIA - State Electricity Profiles  

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

Wyoming Electricity Profile 2010 Wyoming profile Wyoming Electricity Profile 2010 Wyoming profile Table 1. 2010 Summary Statistics (Wyoming) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Coal Net Summer Capacity (megawatts) 7,986 37 Electric Utilities 6,931 31 Independent Power Producers & Combined Heat and Power 1,056 41 Net Generation (megawatthours) 48,119,254 31 Electric Utilities 44,738,543 25 Independent Power Producers & Combined Heat and Power 3,380,711 42 Emissions (thousand metric tons) Sulfur Dioxide 67 23 Nitrogen Oxide 61 15 Carbon Dioxide 45,703 21 Sulfur Dioxide (lbs/MWh) 3.1 19 Nitrogen Oxide (lbs/MWh) 2.8 7 Carbon Dioxide (lbs/MWh) 2,094 2 Total Retail Sales (megawatthours) 17,113,458 40 Full Service Provider Sales (megawatthours) 17,113,458 39

198

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Idaho Electricity Profile 2010 Idaho profile Idaho Electricity Profile 2010 Idaho profile Table 1. 2010 Summary Statistics (Idaho) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Hydroelectric Net Summer Capacity (megawatts) 3,990 44 Electric Utilities 3,035 36 Independent Power Producers & Combined Heat and Power 955 42 Net Generation (megawatthours) 12,024,564 44 Electric Utilities 8,589,208 37 Independent Power Producers & Combined Heat and Power 3,435,356 40 Emissions (thousand metric tons) Sulfur Dioxide 7 45 Nitrogen Oxide 4 48 Carbon Dioxide 1,213 49 Sulfur Dioxide (lbs/MWh) 1.2 39 Nitrogen Oxide (lbs/MWh) 0.8 43 Carbon Dioxide (lbs/MWh) 222 50 Total Retail Sales (megawatthours) 22,797,668 38 Full Service Provider Sales (megawatthours) 22,797,668 37

199

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

California Electricity Profile 2010 California profile California Electricity Profile 2010 California profile Table 1. 2010 Summary Statistics (California) Item Value U.S. Rank NERC Region(s) SPP/WECC Primary Energy Source Gas Net Summer Capacity (megawatts) 67,328 2 Electric Utilities 28,689 2 Independent Power Producers & Combined Heat and Power 38,639 4 Net Generation (megawatthours) 204,125,596 4 Electric Utilities 96,939,535 8 Independent Power Producers & Combined Heat and Power 107,186,061 4 Emissions (thousand metric tons) Sulfur Dioxide 3 47 Nitrogen Oxide 80 9 Carbon Dioxide 55,406 16 Sulfur Dioxide (lbs/MWh) * 49 Nitrogen Oxide (lbs/MWh) 0.9 41 Carbon Dioxide (lbs/MWh) 598 46 Total Retail Sales (megawatthours) 258,525,414 2 Full Service Provider Sales (megawatthours) 240,948,673 2

200

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Carolina Electricity Profile 2010 South Carolina profile Carolina Electricity Profile 2010 South Carolina profile Table 1. 2010 Summary Statistics (South Carolina) Item Value U.S. Rank NERC Region(s) SERC Primary Energy Source Nuclear Net Summer Capacity (megawatts) 23,982 17 Electric Utilities 22,172 9 Independent Power Producers & Combined Heat and Power 1,810 35 Net Generation (megawatthours) 104,153,133 14 Electric Utilities 100,610,887 6 Independent Power Producers & Combined Heat and Power 3,542,246 39 Emissions (thousand metric tons) Sulfur Dioxide 106 19 Nitrogen Oxide 30 33 Carbon Dioxide 41,364 23 Sulfur Dioxide (lbs/MWh) 2.2 30 Nitrogen Oxide (lbs/MWh) 0.6 45 Carbon Dioxide (lbs/MWh) 876 40 Total Retail Sales (megawatthours) 82,479,293 19 Full Service Provider Sales (megawatthours) 82,479,293 17

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201

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

District of Columbia Electricity Profile 2010 District of Columbia profile District of Columbia Electricity Profile 2010 District of Columbia profile Table 1. 2010 Summary Statistics (District of Columbia) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Petroleum Net Summer Capacity (megawatts) 790 51 Independent Power Producers & Combined Heat and Power 790 46 Net Generation (megawatthours) 199,858 51 Independent Power Producers & Combined Heat and Power 199,858 51 Emissions (thousand metric tons) Sulfur Dioxide 1 49 Nitrogen Oxide * 51 Carbon Dioxide 191 50 Sulfur Dioxide (lbs/MWh) 8.8 2 Nitrogen Oxide (lbs/MWh) 4.0 3 Carbon Dioxide (lbs/MWh) 2,104 1 Total Retail Sales (megawatthours) 11,876,995 43 Full Service Provider Sales (megawatthours) 3,388,490 50 Energy-Only Provider Sales (megawatthours) 8,488,505 12

202

EIA - State Electricity Profiles  

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

Virginia Electricity Profile 2010 Virginia profile Virginia Electricity Profile 2010 Virginia profile Table 1. 2010 Summary Statistics (Virginia) Item Value U.S. Rank NERC Region(s) RFC/SERC Primary Energy Source Nuclear Net Summer Capacity (megawatts) 24,109 16 Electric Utilities 19,434 15 Independent Power Producers & Combined Heat and Power 4,676 21 Net Generation (megawatthours) 72,966,456 21 Electric Utilities 58,902,054 16 Independent Power Producers & Combined Heat and Power 14,064,402 25 Emissions (thousand metric tons) Sulfur Dioxide 120 16 Nitrogen Oxide 49 24 Carbon Dioxide 39,719 25 Sulfur Dioxide (lbs/MWh) 3.6 15 Nitrogen Oxide (lbs/MWh) 1.5 23 Carbon Dioxide (lbs/MWh) 1,200 30 Total Retail Sales (megawatthours) 113,806,135 10 Full Service Provider Sales (megawatthours) 113,806,135 7

203

EIA - State Electricity Profiles  

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

Delaware Electricity Profile 2010 Delaware profile Delaware Electricity Profile 2010 Delaware profile Table 1. 2010 Summary Statistics (Delaware) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Gas Net Summer Capacity (megawatts) 3,389 46 Electric Utilities 55 48 Independent Power Producers & Combined Heat and Power 3,334 29 Net Generation (megawatthours) 5,627,645 50 Electric Utilities 30,059 46 Independent Power Producers & Combined Heat and Power 5,597,586 36 Emissions (thousand metric tons) Sulfur Dioxide 13 41 Nitrogen Oxide 5 47 Carbon Dioxide 4,187 45 Sulfur Dioxide (lbs/MWh) 5.2 7 Nitrogen Oxide (lbs/MWh) 1.9 16 Carbon Dioxide (lbs/MWh) 1,640 15 Total Retail Sales (megawatthours) 11,605,932 44 Full Service Provider Sales (megawatthours) 7,582,539 46

204

EIA - State Electricity Profiles  

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

Colorado Electricity Profile 2010 Colorado profile Colorado Electricity Profile 2010 Colorado profile Table 1. 2010 Summary Statistics (Colorado) Item Value U.S. Rank NERC Region(s) RFC/WECC Primary Energy Source Coal Net Summer Capacity (megawatts) 13,777 30 Electric Utilities 9,114 28 Independent Power Producers & Combined Heat and Power 4,662 22 Net Generation (megawatthours) 50,720,792 30 Electric Utilities 39,584,166 28 Independent Power Producers & Combined Heat and Power 11,136,626 31 Emissions (thousand metric tons) Sulfur Dioxide 45 29 Nitrogen Oxide 55 20 Carbon Dioxide 40,499 24 Sulfur Dioxide (lbs/MWh) 2.0 32 Nitrogen Oxide (lbs/MWh) 2.4 10 Carbon Dioxide (lbs/MWh) 1,760 12 Total Retail Sales (megawatthours) 52,917,786 27 Full Service Provider Sales (megawatthours) 52,917,786 24

205

EIA - State Electricity Profiles  

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

Kansas Electricity Profile 2010 Kansas profile Kansas Electricity Profile 2010 Kansas profile Table 1. 2010 Summary Statistics (Kansas) Item Value U.S. Rank NERC Region(s) MRO/SPP Primary Energy Source Coal Net Summer Capacity (megawatts) 12,543 32 Electric Utilities 11,732 20 Independent Power Producers & Combined Heat and Power 812 45 Net Generation (megawatthours) 47,923,762 32 Electric Utilities 45,270,047 24 Independent Power Producers & Combined Heat and Power 2,653,716 44 Emissions (thousand metric tons) Sulfur Dioxide 41 30 Nitrogen Oxide 46 26 Carbon Dioxide 36,321 26 Sulfur Dioxide (lbs/MWh) 1.9 33 Nitrogen Oxide (lbs/MWh) 2.1 13 Carbon Dioxide (lbs/MWh) 1,671 14 Total Retail Sales (megawatthours) 40,420,675 32 Full Service Provider Sales (megawatthours) 40,420,675 30

206

EIA - State Electricity Profiles  

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

Pennsylvania Electricity Profile 2010 Pennsylvania profile Pennsylvania Electricity Profile 2010 Pennsylvania profile Table 1. 2010 Summary Statistics (Pennsylvania) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 45,575 4 Electric Utilities 455 44 Independent Power Producers & Combined Heat and Power 45,120 2 Net Generation (megawatthours) 229,752,306 2 Electric Utilities 1,086,500 42 Independent Power Producers & Combined Heat and Power 228,665,806 2 Emissions (thousand metric tons) Sulfur Dioxide 387 3 Nitrogen Oxide 136 2 Carbon Dioxide 122,830 3 Sulfur Dioxide (lbs/MWh) 3.7 13 Nitrogen Oxide (lbs/MWh) 1.3 27 Carbon Dioxide (lbs/MWh) 1,179 32 Total Retail Sales (megawatthours) 148,963,968 5 Full Service Provider Sales (megawatthours) 114,787,417 6

207

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Pennsylvania Electricity Profile 2010 Pennsylvania profile Pennsylvania Electricity Profile 2010 Pennsylvania profile Table 1. 2010 Summary Statistics (Pennsylvania) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 45,575 4 Electric Utilities 455 44 Independent Power Producers & Combined Heat and Power 45,120 2 Net Generation (megawatthours) 229,752,306 2 Electric Utilities 1,086,500 42 Independent Power Producers & Combined Heat and Power 228,665,806 2 Emissions (thousand metric tons) Sulfur Dioxide 387 3 Nitrogen Oxide 136 2 Carbon Dioxide 122,830 3 Sulfur Dioxide (lbs/MWh) 3.7 13 Nitrogen Oxide (lbs/MWh) 1.3 27 Carbon Dioxide (lbs/MWh) 1,179 32 Total Retail Sales (megawatthours) 148,963,968 5 Full Service Provider Sales (megawatthours) 114,787,417 6

208

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Wyoming Electricity Profile 2010 Wyoming profile Wyoming Electricity Profile 2010 Wyoming profile Table 1. 2010 Summary Statistics (Wyoming) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Coal Net Summer Capacity (megawatts) 7,986 37 Electric Utilities 6,931 31 Independent Power Producers & Combined Heat and Power 1,056 41 Net Generation (megawatthours) 48,119,254 31 Electric Utilities 44,738,543 25 Independent Power Producers & Combined Heat and Power 3,380,711 42 Emissions (thousand metric tons) Sulfur Dioxide 67 23 Nitrogen Oxide 61 15 Carbon Dioxide 45,703 21 Sulfur Dioxide (lbs/MWh) 3.1 19 Nitrogen Oxide (lbs/MWh) 2.8 7 Carbon Dioxide (lbs/MWh) 2,094 2 Total Retail Sales (megawatthours) 17,113,458 40 Full Service Provider Sales (megawatthours) 17,113,458 39

209

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Kentucky Electricity Profile 2010 Kentucky profile Kentucky Electricity Profile 2010 Kentucky profile Table 1. 2010 Summary Statistics (Kentucky) Item Value U.S. Rank NERC Region(s) RFC/SERC Primary Energy Source Coal Net Summer Capacity (megawatts) 20,453 21 Electric Utilities 18,945 16 Independent Power Producers & Combined Heat and Power 1,507 38 Net Generation (megawatthours) 98,217,658 17 Electric Utilities 97,472,144 7 Independent Power Producers & Combined Heat and Power 745,514 48 Emissions (thousand metric tons) Sulfur Dioxide 249 7 Nitrogen Oxide 85 7 Carbon Dioxide 93,160 7 Sulfur Dioxide (lbs/MWh) 5.6 5 Nitrogen Oxide (lbs/MWh) 1.9 15 Carbon Dioxide (lbs/MWh) 2,091 3 Total Retail Sales (megawatthours) 93,569,426 14 Full Service Provider Sales (megawatthours) 93,569,426 12

210

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Michigan Electricity Profile 2010 Michigan profile Michigan Electricity Profile 2010 Michigan profile Table 1. 2010 Summary Statistics (Michigan) Item Value U.S. Rank NERC Region(s) MRO/RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 29,831 11 Electric Utilities 21,639 10 Independent Power Producers & Combined Heat and Power 8,192 14 Net Generation (megawatthours) 111,551,371 13 Electric Utilities 89,666,874 13 Independent Power Producers & Combined Heat and Power 21,884,497 16 Emissions (thousand metric tons) Sulfur Dioxide 254 6 Nitrogen Oxide 89 6 Carbon Dioxide 74,480 11 Sulfur Dioxide (lbs/MWh) 5.0 8 Nitrogen Oxide (lbs/MWh) 1.8 19 Carbon Dioxide (lbs/MWh) 1,472 20 Total Retail Sales (megawatthours) 103,649,219 12 Full Service Provider Sales (megawatthours) 94,565,247 11

211

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Alabama Electricity Profile 2010 Alabama profile Alabama Electricity Profile 2010 Alabama profile Table 1. 2010 Summary Statistics (Alabama) Item Value U.S. Rank NERC Region(s) SERC Primary Energy Source Coal Net Summer Capacity (megawatts) 32,417 9 Electric Utilities 23,642 7 Independent Power Producers & Combined Heat and Power 8,775 12 Net Generation (megawatthours) 152,150,512 6 Electric Utilities 122,766,490 2 Independent Power Producers & Combined Heat and Power 29,384,022 12 Emissions (thousand metric tons) Sulfur Dioxide 218 10 Nitrogen Oxide 66 14 Carbon Dioxide 79,375 9 Sulfur Dioxide (lbs/MWh) 3.2 18 Nitrogen Oxide (lbs/MWh) 1.0 36 Carbon Dioxide (lbs/MWh) 1,150 33 Total Retail Sales (megawatthours) 90,862,645 15 Full Service Provider Sales (megawatthours) 90,862,645 13

212

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Electricity Profile 2012 Table 1. 2012 Summary Statistics (Indiana) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 26,837 14...

213

EIA - State Electricity Profiles  

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

Electricity Profile 2012 Table 1. 2012 Summary Statistics (Arizona) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Coal Net Summer Capacity (megawatts) 27,587...

214

Profiling for Performance  

Science Journals Connector (OSTI)

Performance and profiling are critical words in our everyday conversations in the office where I work, in our engagements with clients, and in our teaching. Both words apply equally well to all aspec...

Ron Crisco

2011-01-01T23:59:59.000Z

215

EIA - State Electricity Profiles  

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

Connecticut Electricity Profile 2010 Connecticut profile Connecticut Electricity Profile 2010 Connecticut profile Table 1. 2010 Summary Statistics (Connecticut) Item Value U.S. Rank NERC Region(s) NPCC Primary Energy Source Nuclear Net Summer Capacity (megawatts) 8,284 35 Electric Utilities 160 46 Independent Power Producers & Combined Heat and Power 8,124 15 Net Generation (megawatthours) 33,349,623 40 Electric Utilities 65,570 45 Independent Power Producers & Combined Heat and Power 33,284,053 11 Emissions (thousand metric tons) Sulfur Dioxide 2 48 Nitrogen Oxide 7 45 Carbon Dioxide 9,201 41 Sulfur Dioxide (lbs/MWh) 0.1 48 Nitrogen Oxide (lbs/MWh) 0.5 49 Carbon Dioxide (lbs/MWh) 608 45 Total Retail Sales (megawatthours) 30,391,766 35 Full Service Provider Sales (megawatthours) 13,714,958 40

216

EIA - State Electricity Profiles  

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

Utah Electricity Profile 2010 Utah profile Utah Electricity Profile 2010 Utah profile Table 1. 2010 Summary Statistics (Utah) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Coal Net Summer Capacity (megawatts) 7,497 39 Electric Utilities 6,648 32 Independent Power Producers & Combined Heat and Power 849 44 Net Generation (megawatthours) 42,249,355 35 Electric Utilities 39,522,124 29 Independent Power Producers & Combined Heat and Power 2,727,231 43 Emissions (thousand metric tons) Sulfur Dioxide 25 34 Nitrogen Oxide 68 13 Carbon Dioxide 35,519 27 Sulfur Dioxide (lbs/MWh) 1.3 38 Nitrogen Oxide (lbs/MWh) 3.6 4 Carbon Dioxide (lbs/MWh) 1,853 9 Total Retail Sales (megawatthours) 28,044,001 37 Full Service Provider Sales (megawatthours) 28,044,001 36

217

EIA - State Electricity Profiles  

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

Carolina Electricity Profile 2010 South Carolina profile Carolina Electricity Profile 2010 South Carolina profile Table 1. 2010 Summary Statistics (South Carolina) Item Value U.S. Rank NERC Region(s) SERC Primary Energy Source Nuclear Net Summer Capacity (megawatts) 23,982 17 Electric Utilities 22,172 9 Independent Power Producers & Combined Heat and Power 1,810 35 Net Generation (megawatthours) 104,153,133 14 Electric Utilities 100,610,887 6 Independent Power Producers & Combined Heat and Power 3,542,246 39 Emissions (thousand metric tons) Sulfur Dioxide 106 19 Nitrogen Oxide 30 33 Carbon Dioxide 41,364 23 Sulfur Dioxide (lbs/MWh) 2.2 30 Nitrogen Oxide (lbs/MWh) 0.6 45 Carbon Dioxide (lbs/MWh) 876 40 Total Retail Sales (megawatthours) 82,479,293 19 Full Service Provider Sales (megawatthours) 82,479,293 17

218

EIA - State Electricity Profiles  

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

Alaska Electricity Profile 2010 Alaska profile Alaska Electricity Profile 2010 Alaska profile Table 1. 2010 Summary Statistics (Alaska) Item Value U.S. Rank NERC Region(s) -- Primary Energy Source Gas Net Summer Capacity (megawatts) 2,067 48 Electric Utilities 1,889 39 Independent Power Producers & Combined Heat and Power 178 51 Net Generation (megawatthours) 6,759,576 48 Electric Utilities 6,205,050 40 Independent Power Producers & Combined Heat and Power 554,526 49 Emissions (thousand metric tons) Sulfur Dioxide 3 46 Nitrogen Oxide 16 39 Carbon Dioxide 4,125 46 Sulfur Dioxide (lbs/MWh) 1.0 41 Nitrogen Oxide (lbs/MWh) 5.2 1 Carbon Dioxide (lbs/MWh) 1,345 23 Total Retail Sales (megawatthours) 6,247,038 50 Full Service Provider Sales (megawatthours) 6,247,038 47

219

EIA - State Electricity Profiles  

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

Nevada Electricity Profile 2010 Nevada profile Nevada Electricity Profile 2010 Nevada profile Table 1. 2010 Summary Statistics (Nevada) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Gas Net Summer Capacity (megawatts) 11,421 34 Electric Utilities 8,713 29 Independent Power Producers & Combined Heat and Power 2,708 33 Net Generation (megawatthours) 35,146,248 38 Electric Utilities 23,710,917 34 Independent Power Producers & Combined Heat and Power 11,435,331 29 Emissions (thousand metric tons) Sulfur Dioxide 7 44 Nitrogen Oxide 15 40 Carbon Dioxide 17,020 38 Sulfur Dioxide (lbs/MWh) 0.4 46 Nitrogen Oxide (lbs/MWh) 1.0 37 Carbon Dioxide (lbs/MWh) 1,068 37 Total Retail Sales (megawatthours) 33,772,595 33 Full Service Provider Sales (megawatthours) 32,348,879 32

220

EIA - State Electricity Profiles  

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

Washington Electricity Profile 2010 Washington profile Washington Electricity Profile 2010 Washington profile Table 1. 2010 Summary Statistics (Washington) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Hydroelectric Net Summer Capacity (megawatts) 30,478 10 Electric Utilities 26,498 5 Independent Power Producers & Combined Heat and Power 3,979 26 Net Generation (megawatthours) 103,472,729 15 Electric Utilities 88,057,219 14 Independent Power Producers & Combined Heat and Power 15,415,510 23 Emissions (thousand metric tons) Sulfur Dioxide 14 39 Nitrogen Oxide 21 37 Carbon Dioxide 13,984 39 Sulfur Dioxide (lbs/MWh) 0.3 47 Nitrogen Oxide (lbs/MWh) 0.4 50 Carbon Dioxide (lbs/MWh) 298 49 Total Retail Sales (megawatthours) 90,379,970 16 Full Service Provider Sales (megawatthours) 88,116,958 14

Note: This page contains sample records for the topic "kwh load profiles" 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

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Oregon Electricity Profile 2010 Oregon profile Oregon Electricity Profile 2010 Oregon profile Table 1. 2010 Summary Statistics (Oregon) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Hydroelectric Net Summer Capacity (megawatts) 14,261 29 Electric Utilities 10,846 27 Independent Power Producers & Combined Heat and Power 3,415 28 Net Generation (megawatthours) 55,126,999 27 Electric Utilities 41,142,684 26 Independent Power Producers & Combined Heat and Power 13,984,316 26 Emissions (thousand metric tons) Sulfur Dioxide 16 37 Nitrogen Oxide 15 42 Carbon Dioxide 10,094 40 Sulfur Dioxide (lbs/MWh) 0.6 44 Nitrogen Oxide (lbs/MWh) 0.6 47 Carbon Dioxide (lbs/MWh) 404 48 Total Retail Sales (megawatthours) 46,025,945 30 Full Service Provider Sales (megawatthours) 44,525,865 29

222

EIA - State Electricity Profiles  

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

Texas Electricity Profile 2010 Texas profile Texas Electricity Profile 2010 Texas profile Table 1. 2010 Summary Statistics (Texas) Item Value U.S. Rank NERC Region(s) SERC/SPP/TRE/WECC Primary Energy Source Gas Net Summer Capacity (megawatts) 108,258 1 Electric Utilities 26,533 4 Independent Power Producers & Combined Heat and Power 81,724 1 Net Generation (megawatthours) 411,695,046 1 Electric Utilities 95,099,161 9 Independent Power Producers & Combined Heat and Power 316,595,885 1 Emissions (thousand metric tons) Sulfur Dioxide 430 2 Nitrogen Oxide 204 1 Carbon Dioxide 251,409 1 Sulfur Dioxide (lbs/MWh) 2.3 28 Nitrogen Oxide (lbs/MWh) 1.1 32 Carbon Dioxide (lbs/MWh) 1,346 22 Total Retail Sales (megawatthours) 358,457,550 1 Full Service Provider Sales (megawatthours) 358,457,550 1

223

EIA - State Electricity Profiles  

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

Indiana Electricity Profile 2010 Indiana profile Indiana Electricity Profile 2010 Indiana profile Table 1. 2010 Summary Statistics (Indiana) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Coal Net Summer Capacity (megawatts) 27,638 13 Electric Utilities 23,008 8 Independent Power Producers & Combined Heat and Power 4,630 23 Net Generation (megawatthours) 125,180,739 11 Electric Utilities 107,852,560 5 Independent Power Producers & Combined Heat and Power 17,328,179 20 Emissions (thousand metric tons) Sulfur Dioxide 385 4 Nitrogen Oxide 120 4 Carbon Dioxide 116,283 5 Sulfur Dioxide (lbs/MWh) 6.8 4 Nitrogen Oxide (lbs/MWh) 2.1 12 Carbon Dioxide (lbs/MWh) 2,048 4 Total Retail Sales (megawatthours) 105,994,376 11 Full Service Provider Sales (megawatthours) 105,994,376 8

224

EIA - State Electricity Profiles  

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

Oklahoma Electricity Profile 2010 Oklahoma profile Oklahoma Electricity Profile 2010 Oklahoma profile Table 1. 2010 Summary Statistics (Oklahoma) Item Value U.S. Rank NERC Region(s) SPP Primary Energy Source Gas Net Summer Capacity (megawatts) 21,022 20 Electric Utilities 16,015 18 Independent Power Producers & Combined Heat and Power 5,006 17 Net Generation (megawatthours) 72,250,733 22 Electric Utilities 57,421,195 17 Independent Power Producers & Combined Heat and Power 14,829,538 24 Emissions (thousand metric tons) Sulfur Dioxide 85 21 Nitrogen Oxide 71 12 Carbon Dioxide 49,536 17 Sulfur Dioxide (lbs/MWh) 2.6 24 Nitrogen Oxide (lbs/MWh) 2.2 11 Carbon Dioxide (lbs/MWh) 1,512 17 Total Retail Sales (megawatthours) 57,845,980 25 Full Service Provider Sales (megawatthours) 57,845,980 23

225

EIA - State Electricity Profiles  

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

Jersey Electricity Profile 2010 New Jersey profile Jersey Electricity Profile 2010 New Jersey profile Table 1. 2010 Summary Statistics (New Jersey) Item Value U.S. Rank NERC Region(s) RFC Primary Energy Source Nuclear Net Summer Capacity (megawatts) 18,424 22 Electric Utilities 460 43 Independent Power Producers & Combined Heat and Power 17,964 6 Net Generation (megawatthours) 65,682,494 23 Electric Utilities -186,385 50 Independent Power Producers & Combined Heat and Power 65,868,878 6 Emissions (thousand metric tons) Sulfur Dioxide 14 40 Nitrogen Oxide 15 41 Carbon Dioxide 19,160 37 Sulfur Dioxide (lbs/MWh) 0.5 45 Nitrogen Oxide (lbs/MWh) 0.5 48 Carbon Dioxide (lbs/MWh) 643 43 Total Retail Sales (megawatthours) 79,179,427 20 Full Service Provider Sales (megawatthours) 50,482,035 25

226

EIA - State Electricity Profiles  

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

Idaho Electricity Profile 2010 Idaho profile Idaho Electricity Profile 2010 Idaho profile Table 1. 2010 Summary Statistics (Idaho) Item Value U.S. Rank NERC Region(s) WECC Primary Energy Source Hydroelectric Net Summer Capacity (megawatts) 3,990 44 Electric Utilities 3,035 36 Independent Power Producers & Combined Heat and Power 955 42 Net Generation (megawatthours) 12,024,564 44 Electric Utilities 8,589,208 37 Independent Power Producers & Combined Heat and Power 3,435,356 40 Emissions (thousand metric tons) Sulfur Dioxide 7 45 Nitrogen Oxide 4 48 Carbon Dioxide 1,213 49 Sulfur Dioxide (lbs/MWh) 1.2 39 Nitrogen Oxide (lbs/MWh) 0.8 43 Carbon Dioxide (lbs/MWh) 222 50 Total Retail Sales (megawatthours) 22,797,668 38 Full Service Provider Sales (megawatthours) 22,797,668 37

227

Investigation of residential central air conditioning load shapes in NEMS  

SciTech Connect

This memo explains what Berkeley Lab has learned about how the residential central air-conditioning (CAC) end use is represented in the National Energy Modeling System (NEMS). NEMS is an energy model maintained by the Energy Information Administration (EIA) that is routinely used in analysis of energy efficiency standards for residential appliances. As part of analyzing utility and environmental impacts related to the federal rulemaking for residential CAC, lower-than-expected peak utility results prompted Berkeley Lab to investigate the input load shapes that characterize the peaky CAC end use and the submodule that treats load demand response. Investigations enabled a through understanding of the methodology by which hourly load profiles are input to the model and how the model is structured to respond to peak demand. Notably, it was discovered that NEMS was using an October-peaking load shape to represent residential space cooling, which suppressed peak effects to levels lower than expected. An apparent scaling down of the annual load within the load-demand submodule was found, another significant suppressor of the peak impacts. EIA promptly responded to Berkeley Lab's discoveries by updating numerous load shapes for the AEO2002 version of NEMS; EIA is still studying the scaling issue. As a result of this work, it was concluded that Berkeley Lab's customary end-use decrement approach was the most defensible way for Berkeley Lab to perform the recent CAC utility impact analysis. This approach was applied in conjunction with the updated AEO2002 load shapes to perform last year's published rulemaking analysis. Berkeley Lab experimented with several alternative approaches, including modifying the CAC efficiency level, but determined that these did not sufficiently improve the robustness of the method or results to warrant their implementation. Work in this area will continue in preparation for upcoming rulemakings for the other peak coincident end uses, commercial air conditioning and distribution transformers.

Hamachi LaCommare, Kristina; Marnay, Chris; Gumerman, Etan; Chan, Peter; Rosenquist, Greg; Osborn, Julie

2002-05-01T23:59:59.000Z

228

Electrical and Production Load Factors  

E-Print Network (OSTI)

, Texas Abstract Load factors and operating hours of small and medium-sized industrial plants are analyzed to classify shift-work patterns and develop energy conservation diagnostic tools. This paper discusses two types of electric load factors... for each shift classification within major industry groups. The load factor based on billing hours (ELF) increases with operating hours from about 0.4 for a nominal one shift operation, to about 0.7 for around-the-clock operation. On the other hand...

Sen, T.; Heffington, W. M.

229

Estimating Demand Response Load Impacts: Evaluation of BaselineLoad Models for Non-Residential Buildings in California  

SciTech Connect

Both Federal and California state policymakers areincreasingly interested in developing more standardized and consistentapproaches to estimate and verify the load impacts of demand responseprograms and dynamic pricing tariffs. This study describes a statisticalanalysis of the performance of different models used to calculate thebaseline electric load for commercial buildings participating in ademand-response (DR) program, with emphasis onthe importance of weathereffects. During a DR event, a variety of adjustments may be made tobuilding operation, with the goal of reducing the building peak electricload. In order to determine the actual peak load reduction, an estimateof what the load would have been on the day of the event without any DRactions is needed. This baseline load profile (BLP) is key to accuratelyassessing the load impacts from event-based DR programs and may alsoimpact payment settlements for certain types of DR programs. We testedseven baseline models on a sample of 33 buildings located in California.These models can be loosely categorized into two groups: (1) averagingmethods, which use some linear combination of hourly load values fromprevious days to predict the load on the event, and (2) explicit weathermodels, which use a formula based on local hourly temperature to predictthe load. The models were tested both with and without morningadjustments, which use data from the day of the event to adjust theestimated BLP up or down.Key findings from this study are: - The accuracyof the BLP model currently used by California utilities to estimate loadreductions in several DR programs (i.e., hourly usage in highest 3 out of10 previous days) could be improved substantially if a morning adjustmentfactor were applied for weather-sensitive commercial and institutionalbuildings. - Applying a morning adjustment factor significantly reducesthe bias and improves the accuracy of all BLP models examined in oursample of buildings. - For buildings with low load variability, all BLPmodels perform reasonably well in accuracy. - For customer accounts withhighly variable loads, we found that no BLP model produced satisfactoryresults, although averaging methods perform best in accuracy (but notbias). These types of customers are difficult to characterize withstandard BLP models that rely on historic loads and weather data.Implications of these results for DR program administrators andpolicymakersare: - Most DR programs apply similar DR BLP methods tocommercial and industrial sector customers. The results of our study whencombined with other recent studies (Quantum 2004 and 2006, Buege et al.,2006) suggests that DR program administrators should have flexibility andmultiple options for suggesting the most appropriate BLP method forspecific types of customers.

Coughlin, Katie; Piette, Mary Ann; Goldman, Charles; Kiliccote,Sila

2008-01-01T23:59:59.000Z

230

Performance profiles style sheet  

Gasoline and Diesel Fuel Update (EIA)

Performance Profiles of Major Energy Producers 2009 Performance Profiles of Major Energy Producers 2009 vii Major Findings This edition of Performance Profiles reviews financial and operating data for the calendar year 2009 and discusses important trends and emerging issues relevant to U.S. energy company operations. Major U.S.-based oil and natural gas producers and petroleum refiners submit the data in this report annually on Form EIA-28, the Financial Reporting System (FRS). FRS companies' net income declined to the lowest level since 2002.  Net income fell 66 percent (in constant 2009 dollars) to $30 billion in 2009 from $88 billion in 2008. Substantial reductions in oil and natural gas prices in 2009 slowed revenue growth. FRS companies cut operating costs but by less than the decline in revenue, resulting in a 69-percent drop in operating income.

231

State Nuclear Profiles 2010  

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

State Nuclear Profiles 2010 State Nuclear Profiles 2010 April 2012 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies. U.S. Energy Information Administration | State Nuclear Profiles 2010 i Contacts This report was prepared by the staff of the Renewables and Uranium Statistics Team, Office of Electricity,

232

electric load data | OpenEI Community  

Open Energy Info (EERE)

load data Home Sfomail's picture Submitted by Sfomail(48) Member 17 May, 2013 - 12:03 Commercial and Residential Hourly Load Data Now Available on OpenEI building load building...

233

FINAL PROJECT REPORT LOAD MODELING TRANSMISSION RESEARCH  

E-Print Network (OSTI)

BulkSystemLoad ModelinGEPSLFTMforInvestigatingthea Bulk System Load Model in GE PSLF TM for Investigating thecompositeloadmodelin thePSLFsimulationsoftware;the

Lesieutre, Bernard

2013-01-01T23:59:59.000Z

234

The elimination of liquid loading problems in low productivity gas wells  

E-Print Network (OSTI)

investigated. The Beggs and Brill multiphase pressure drop correlation was programmed and used as a basis to generate tubing performance curves and to study the effects of various parameters on long term gas production. Turner's method for predicting... the known methods of analyzing liquid loading problems in gas wells. A computer program will be developed to aid in generating tubing performance curves along with calculated gas velocity profiles. The calculated gas velocity profile...

Neves, Toby Roy

1987-01-01T23:59:59.000Z

235

Determining Electric Motor Load and Efficiency  

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

To compare the operating costs of an existing standard motor with an appropriately-sized energy-efficient replacement, you need to determine operating hours, efficiency improvement values, and load. Part-load is a term used to describe the actual load served by the motor as compared to the rated full-load capability of the motor. Motor part-loads may be estimated through using input power, amperage, or speed measurements. This fact sheet briefly discusses several load estimation techniques.

236

CFD-based design load analysis of 5MW offshore wind turbine  

Science Journals Connector (OSTI)

The structure and aerodynamic loads acting on NREL 5MW reference wind turbine blade are calculated and analyzed based on advanced Computational Fluid Dynamics (CFD) and unsteady Blade Element Momentum (BEM). A detailed examination of the six force components has been carried out (three force components and three moment components). Structure load (gravity and inertia load) and aerodynamic load have been obtained by additional structural calculations (CFD or BEM respectively ). In CFD method the Reynolds Average Navier-Stokes approach was applied to solve the continuity equation of mass conservation and momentum balance so that the complex flow around wind turbines was modeled. Written in C programming language a User Defined Function (UDF) code which defines transient velocity profile according to the Extreme Operating Gust condition was compiled into commercial FLUENT package. Furthermore the unsteady BEM with 3D stall model has also adopted to investigate load components on wind turbine rotor. The present study introduces a comparison between advanced CFD and unsteady BEM for determining load on wind turbine rotor. Results indicate that there are good agreements between both present methods. It is importantly shown that six load components on wind turbine rotor is significant effect under Extreme Operating Gust (EOG) condition. Using advanced CFD and additional structural calculations this study has succeeded to construct accuracy numerical methodology to estimate total load of wind turbine that compose of aerodynamic load and structure load.

T. T. Tran; G. J. Ryu; Y. H. Kim; D. H. Kim

2012-01-01T23:59:59.000Z

237

Influence of loading rate on axially loaded piles in clay  

E-Print Network (OSTI)

, Haas and Saxe Yong and Japp. Arulanandan and Shen 4 ~ ~ ~ ~ ~ ~ 4 5 5 6 6 13 13 21 21 22 22 23 23 24 24 Ladd, Hi11iams, Connell and Edgars Berre and Bjerrum. Stevenson. King Vaid and Campanella. Lacasse. Rigqins. CHAPTER V... of the Gain in Strength versus Shearing Rate Plots 4. Select Regression, PI, LI, W, SO(REF) 76 Cases for 152 Laboratory Tests 5. Collected Data for Pile Load Test Results. 6. Data Set References for Pile Load Tests. Page 14 36 54 61 7. Semi...

Garland Ponce, Enrique Eduardo

2012-06-07T23:59:59.000Z

238

EIA - State Nuclear Profiles  

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

Florida Nuclear Profile 2010 Florida profile Florida Nuclear Profile 2010 Florida profile Florida total electric power industry, summer capacity and net generation, by energy source, 2010 Primary Energy Source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 3,924 6.6 23,936 10.4 Coal 9,975 16.9 59,897 26.1 Hydro and Pumped Storage 55 0.1 177 0.1 Natural Gas 31,563 53.4 128,634 56.1 Other1 544 0.9 2,842 1.2 Other Renewable1 1,053 1.8 4,487 2.0 Petroleum 12,033 20.3 9,122 4.0 Total 59,147 100.0 229,096 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

239

EIA - State Nuclear Profiles  

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

North Carolina Nuclear Profile 2010 North Carolina profile North Carolina Nuclear Profile 2010 North Carolina profile North Carolina total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 4,958 17.9 40,740 31.7 Coal 12,766 46.1 71,951 55.9 Hydro and Pumped Storage 2,042 7.4 4,757 3.7 Natural Gas 6,742 24.4 8,447 6.6 Other 1 50 0.2 407 0.3 Other Renewable1 543 2.0 2,083 1.6 Petroleum 573 2.1 293 0.2 Total 27,674 100.0 128,678 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

240

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

California Nuclear Profile 2010 California profile California Nuclear Profile 2010 California profile California total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 4,390 6.5 32,201 15.8 Coal 374 0.6 2,100 1.0 Hydro and Pumped Storage 13,954 20.7 33,260 16.3 Natural Gas 41,370 61.4 107,522 52.7 Other 1 220 0.3 2,534 1.2 Other Renewable1 6,319 9.4 25,450 12.5 Petroleum 701 1.0 1,059 0.5 Total 63,328 100.0 204,126 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

Note: This page contains sample records for the topic "kwh load profiles" 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

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Georgia Nuclear Profile 2010 Georgia profile Georgia Nuclear Profile 2010 Georgia profile Georgia total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 4,061 11.1 33,512 24.6 Coal 13,230 36.1 73,298 54.0 Hydro and Pumped Storage 3,851 10.5 3,044 2.7 Natural Gas 12,668 34.6 23,884 15.9 Other 1 - - 18 * Other Renewable1 637 1.7 3,181 2.2 Petroleum 2,189 6.0 641 0.5 Total 36,636 100.0 128,698 100 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05.

242

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Mississippi Nuclear Profile 2010 Mississippi profile Mississippi Nuclear Profile 2010 Mississippi profile Mississippi total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,251 8.0 9,643 17.7 Coal 2,526 16.1 13,629 25.0 Natural Gas 11,640 74.2 29,619 54.4 Other 1 4 * 10 * Other Renewable1 235 1.5 1,504 2.8 Petroleum 35 0.2 18 0.1 Total 15,691 100.0 54,487 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05. Notes: Totals may not equal sum of components due to independent rounding.

243

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Connecticut Nuclear Profile 2010 Connecticut profile Connecticut Nuclear Profile 2010 Connecticut profile Connecticut total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 2,103 25.4 16,750 50.2 Coal 564 6.8 2,604 7.8 Hydro and Pumped Storage 151 1.8 400 1.2 Natural Gas 2,292 27.7 11,716 35.1 Other 1 27 0.3 730 2.2 Other Renewable1 159 1.9 740 2.2 Petroleum 2,989 36.1 409 1.2 Total 8,284 100.0 33,350 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

244

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Massachusetts Nuclear Profile 2010 Massachusetts profile Massachusetts Nuclear Profile 2010 Massachusetts profile Massachusetts total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 685 5.0 5,918 13.8 Coal 1,669 12.2 8,306 19.4 Hydro and Pumped Storage 1,942 14.2 659 1.5 Natural Gas 6,063 44.3 25,582 59.8 Other 1 3 * 771 1.8 Other Renewable1 304 2.2 1,274 3.0 Petroleum 3,031 22.1 296 0.7 Total 13,697 100.0 42,805 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

245

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Michigan Nuclear Profile 2010 Michigan profile Michigan Nuclear Profile 2010 Michigan profile Michigan total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 3,947 13.2 29,625 26.6 Coal 11,531 38.7 65,604 58.8 Hydro and Pumped Storage 2,109 7.1 228 0.2 Natural Gas 11,033 37.0 12,249 11.0 Other 1 - - 631 0.6 Other Renewable1 571 1.9 2,832 2.5 Petroleum 640 2.1 382 0.3 Total 29,831 100.0 111,551 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

246

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Florida Nuclear Profile 2010 Florida profile Florida Nuclear Profile 2010 Florida profile Florida total electric power industry, summer capacity and net generation, by energy source, 2010 Primary Energy Source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 3,924 6.6 23,936 10.4 Coal 9,975 16.9 59,897 26.1 Hydro and Pumped Storage 55 0.1 177 0.1 Natural Gas 31,563 53.4 128,634 56.1 Other1 544 0.9 2,842 1.2 Other Renewable1 1,053 1.8 4,487 2.0 Petroleum 12,033 20.3 9,122 4.0 Total 59,147 100.0 229,096 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

247

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Missouri Nuclear Profile 2010 Missouri profile Missouri Nuclear Profile 2010 Missouri profile Missouri total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,190 5.5 8,996 9.7 Coal 12,070 55.5 75,047 81.3 Hydro and Pumped Storage 1,221 5.6 2,427 2.6 Natural Gas 5,579 25.7 4,690 5.1 Other 1 - - 39 * Other Renewable1 466 2.1 988 1.1 Petroleum 1,212 5.6 126 0.1 Total 21,739 100.0 92,313 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05.

248

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Alabama Nuclear Profile 2010 Alabama profile Alabama Nuclear Profile 2010 Alabama profile Alabama total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 5,043 15.6 37,941 24.9 Coal 11,441 35.3 63,050 41.4 Hydro and Pumped Storage 3,272 10.1 8,704 5.7 Natural Gas 11,936 36.8 39,235 25.8 Other1 100 0.3 643 0.4 Other Renewable1 583 1.8 2,377 1.6 Petroleum 43 0.1 200 0.1 Total 32,417 100.0 152,151 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

249

EIA - State Nuclear Profiles  

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

Arizona Nuclear Profile 2010 Arizona profile Arizona Nuclear Profile 2010 Arizona profile Arizona total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,937 14.9 31,200 27.9 Coal 6,233 23.6 43,644 39.1 Hydro and Pumped Storage 2,937 11.1 6,831 6.1 Natural Gas 13,012 49.3 29,676 26.6 Other 1 - - 15 * Other Renewable1 181 0.7 319 0.3 Petroleum 93 0.4 66 0.1 Total 26,392 100.0 111,751 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05.

250

EIA - State Nuclear Profiles  

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

Minnesota Nuclear Profile 2010 Minnesota profile Minnesota Nuclear Profile 2010 Minnesota profile Minnesota total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,549 10.8 13,478 25.1 Coal 4,789 32.5 28,083 52.3 Hydro and Pumped Storage 193 1.3 840 1.6 Natural Gas 4,936 33.5 4,341 8.1 Other 1 13 0.1 258 0.5 Other Renewable1 2,395 16.3 6,640 12.4 Petroleum 795 5.4 31 0.1 Total 14,715 100.0 53,670 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

251

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Pennsylvania Nuclear Profile 2010 Pennsylvania profile Pennsylvania Nuclear Profile 2010 Pennsylvania profile Pennsylvania total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 9,540 20.9 77,828 33.9 Coal 18,481 40.6 110,369 48.0 Hydro and Pumped Storage 2,268 5.0 1,624 0.7 Natural Gas 9,415 20.7 33,718 14.7 Other 1 100 0.2 1,396 0.6 Other Renewable1 1,237 2.7 4,245 1.8 Petroleum 4,534 9.9 571 0.2 Total 45,575 100.0 229,752 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

252

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Hampshire Nuclear Profile 2010 New Hampshire profile Hampshire Nuclear Profile 2010 New Hampshire profile New Hampshire total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,247 29.8 10,910 49.2 Coal 546 13.1 3,083 13.9 Hydro and Pumped Storage 489 11.7 1,478 6.7 Natural Gas 1,215 29.1 5,365 24.2 Other 1 - - 57 0.3 Other Renewable1 182 4.4 1,232 5.6 Petroleum 501 12.0 72 0.3 Total 4,180 100.0 22,196 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

253

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

North Carolina Nuclear Profile 2010 North Carolina profile North Carolina Nuclear Profile 2010 North Carolina profile North Carolina total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 4,958 17.9 40,740 31.7 Coal 12,766 46.1 71,951 55.9 Hydro and Pumped Storage 2,042 7.4 4,757 3.7 Natural Gas 6,742 24.4 8,447 6.6 Other 1 50 0.2 407 0.3 Other Renewable1 543 2.0 2,083 1.6 Petroleum 573 2.1 293 0.2 Total 27,674 100.0 128,678 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

254

EIA - State Nuclear Profiles  

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

Hampshire Nuclear Profile 2010 New Hampshire profile Hampshire Nuclear Profile 2010 New Hampshire profile New Hampshire total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,247 29.8 10,910 49.2 Coal 546 13.1 3,083 13.9 Hydro and Pumped Storage 489 11.7 1,478 6.7 Natural Gas 1,215 29.1 5,365 24.2 Other 1 - - 57 0.3 Other Renewable1 182 4.4 1,232 5.6 Petroleum 501 12.0 72 0.3 Total 4,180 100.0 22,196 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

255

EIA - State Nuclear Profiles  

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

Georgia Nuclear Profile 2010 Georgia profile Georgia Nuclear Profile 2010 Georgia profile Georgia total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 4,061 11.1 33,512 24.6 Coal 13,230 36.1 73,298 54.0 Hydro and Pumped Storage 3,851 10.5 3,044 2.7 Natural Gas 12,668 34.6 23,884 15.9 Other 1 - - 18 * Other Renewable1 637 1.7 3,181 2.2 Petroleum 2,189 6.0 641 0.5 Total 36,636 100.0 128,698 100 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05.

256

EIA - State Nuclear Profiles  

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

Michigan Nuclear Profile 2010 Michigan profile Michigan Nuclear Profile 2010 Michigan profile Michigan total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 3,947 13.2 29,625 26.6 Coal 11,531 38.7 65,604 58.8 Hydro and Pumped Storage 2,109 7.1 228 0.2 Natural Gas 11,033 37.0 12,249 11.0 Other 1 - - 631 0.6 Other Renewable1 571 1.9 2,832 2.5 Petroleum 640 2.1 382 0.3 Total 29,831 100.0 111,551 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

257

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Louisiana Nuclear Profile 2010 Louisiana profile Louisiana Nuclear Profile 2010 Louisiana profile Louisiana total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (nw) Share of State total (percent) Net generation (thousand nwh) Share of State total (percent) Nuclear 2,142 8.0 18,639 18.1 Coal 3,417 12.8 23,924 23.3 Hydro and Pumped Storage 192 0.7 1,109 1.1 Natural Gas 19,574 73.2 51,344 49.9 Other 1 213 0.8 2,120 2.1 Other Renewable1 325 1.2 2,468 2.4 Petroleum 881 3.3 3,281 3.2 Total 26,744 100.0 102,885 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

258

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Illinois Nuclear Profile 2010 Illinois profile Illinois Nuclear Profile 2010 Illinois profile Illinois total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 11,441 25.9 96,190 47.8 Coal 15,551 35.2 93,611 46.5 Hydro and Pumped Storage 34 0.1 119 0.1 Natural Gas 13,771 31.2 5,724 2.8 Other 1 145 0.3 461 0.2 Other Renewable1 2,078 4.7 5,138 2.6 Petroleum 1,106 2.5 110 0.1 Total 44,127 100.0 201,352 100 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

259

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Jersey Nuclear Profile 2010 New Jersey profile Jersey Nuclear Profile 2010 New Jersey profile New Jersey total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 4,108 22.3 32,771 49.9 Coal 2,036 11.1 6,418 9.8 Hydro and Pumped Storage 404 2.2 -176 -0.3 Natural Gas 10,244 55.6 24,902 37.9 Other 1 56 0.3 682 1.0 Other Renewable1 226 1.2 850 1.3 Petroleum 1,351 7.3 235 0.4 Total 18,424 100.0 65,682 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

260

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Iowa Nuclear Profile 2010 Iowa profile Iowa Nuclear Profile 2010 Iowa profile Iowa total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 601 4.1 4,451 7.7 Coal 6,956 47.7 41,283 71.8 Hydro and Pumped Storage 144 1.0 948 1.6 Natural Gas 2,299 15.8 1,312 2.3 Other Renewable1 3,584 24.6 9,360 16.3 Petroleum 1,007 6.9 154 .0.3 Total 14,592 100.0 57,509 100 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. Notes: Totals may not equal sum of components due to independent rounding.

Note: This page contains sample records for the topic "kwh load profiles" 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

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Minnesota Nuclear Profile 2010 Minnesota profile Minnesota Nuclear Profile 2010 Minnesota profile Minnesota total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,549 10.8 13,478 25.1 Coal 4,789 32.5 28,083 52.3 Hydro and Pumped Storage 193 1.3 840 1.6 Natural Gas 4,936 33.5 4,341 8.1 Other 1 13 0.1 258 0.5 Other Renewable1 2,395 16.3 6,640 12.4 Petroleum 795 5.4 31 0.1 Total 14,715 100.0 53,670 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

262

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Arkansas Nuclear Profile 2010 Arkansas profile Arkansas Nuclear Profile 2010 Arkansas profile Arkansas total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State ttal (percent) Nuclear 1,835 11.5 15,023 24.6 Coal 4,535 28.4 28,152 46.2 Hydro and Pumped Storage 1,369 8.6 3,658 6.0 Natural Gas 7,894 49.4 12,469 20.4 Other 1 - - 28 * Other Renewable1 326 2.0 1,624 2.7 Petroleum 22 0.1 45 0.1 Total 15,981 100.0 61,000 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable * = Absolute percentage less than 0.05.

263

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Nebraska Nuclear Profile 2010 Nebraska profile Nebraska Nuclear Profile 2010 Nebraska profile Nebraska total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,245 15.8 11,054 30.2 Coal 3,932 50.0 23,368 63.8 Hydro and Pumped Storage 278 3.5 1,314 3.6 Natural Gas 1,864 23.5 375 1.0 Other Renewable1 165 2.1 493 1.3 Petroleum 387 4.9 31 0.1 Total 7,857 100.0 36,630 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. Notes: Totals may not equal sum of components due to independent rounding.

264

EIA - State Nuclear Profiles  

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

Mississippi Nuclear Profile 2010 Mississippi profile Mississippi Nuclear Profile 2010 Mississippi profile Mississippi total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,251 8.0 9,643 17.7 Coal 2,526 16.1 13,629 25.0 Natural Gas 11,640 74.2 29,619 54.4 Other 1 4 * 10 * Other Renewable1 235 1.5 1,504 2.8 Petroleum 35 0.2 18 0.1 Total 15,691 100.0 54,487 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05. Notes: Totals may not equal sum of components due to independent rounding.

265

EIA - State Nuclear Profiles  

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

Arkansas Nuclear Profile 2010 Arkansas profile Arkansas Nuclear Profile 2010 Arkansas profile Arkansas total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State ttal (percent) Nuclear 1,835 11.5 15,023 24.6 Coal 4,535 28.4 28,152 46.2 Hydro and Pumped Storage 1,369 8.6 3,658 6.0 Natural Gas 7,894 49.4 12,469 20.4 Other 1 - - 28 * Other Renewable1 326 2.0 1,624 2.7 Petroleum 22 0.1 45 0.1 Total 15,981 100.0 61,000 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable * = Absolute percentage less than 0.05.

266

EIA - State Nuclear Profiles  

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

Kansas Nuclear Profile 2010 Kansas profile Kansas Nuclear Profile 2010 Kansas profile Kansas total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,160 9.2 9,556 19.9 Coal 5,179 41.3 32,505 67.8 Hydro and Pumped Storage 3 * 13 * Natural Gas 4,573 36.5 2,287 4.8 Other Renewable1 1,079 8.6 3,459 7.2 Petroleum 550 4.4 103 0.2 Total 12,543 100.0 47,924 100 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05. Notes: Totals may not equal sum of components due to independent rounding.

267

EIA - State Nuclear Profiles  

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

Pennsylvania Nuclear Profile 2010 Pennsylvania profile Pennsylvania Nuclear Profile 2010 Pennsylvania profile Pennsylvania total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 9,540 20.9 77,828 33.9 Coal 18,481 40.6 110,369 48.0 Hydro and Pumped Storage 2,268 5.0 1,624 0.7 Natural Gas 9,415 20.7 33,718 14.7 Other 1 100 0.2 1,396 0.6 Other Renewable1 1,237 2.7 4,245 1.8 Petroleum 4,534 9.9 571 0.2 Total 45,575 100.0 229,752 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

268

EIA - State Nuclear Profiles  

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

Ohio Nuclear Profile 2010 Ohio profile Ohio Nuclear Profile 2010 Ohio profile Ohio total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 2,134 6.5 15,805 11.0 Coal 21,360 64.6 117,828 82.1 Hydro and Pumped Storage 101 0.3 429 0.3 Natural Gas 8,203 24.8 7,128 5.0 Other 1 123 0.4 266 0.2 Other Renewable1 130 0.4 700 0.5 Petroleum 1,019 3.1 1,442 1.0 Total 33,071 100.0 143,598 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. Notes: Totals may not equal sum of components due to independent rounding.

269

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Arizona Nuclear Profile 2010 Arizona profile Arizona Nuclear Profile 2010 Arizona profile Arizona total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,937 14.9 31,200 27.9 Coal 6,233 23.6 43,644 39.1 Hydro and Pumped Storage 2,937 11.1 6,831 6.1 Natural Gas 13,012 49.3 29,676 26.6 Other 1 - - 15 * Other Renewable1 181 0.7 319 0.3 Petroleum 93 0.4 66 0.1 Total 26,392 100.0 111,751 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05.

270

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Kansas Nuclear Profile 2010 Kansas profile Kansas Nuclear Profile 2010 Kansas profile Kansas total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,160 9.2 9,556 19.9 Coal 5,179 41.3 32,505 67.8 Hydro and Pumped Storage 3 * 13 * Natural Gas 4,573 36.5 2,287 4.8 Other Renewable1 1,079 8.6 3,459 7.2 Petroleum 550 4.4 103 0.2 Total 12,543 100.0 47,924 100 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05. Notes: Totals may not equal sum of components due to independent rounding.

271

EIA - State Nuclear Profiles  

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

Jersey Nuclear Profile 2010 New Jersey profile Jersey Nuclear Profile 2010 New Jersey profile New Jersey total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 4,108 22.3 32,771 49.9 Coal 2,036 11.1 6,418 9.8 Hydro and Pumped Storage 404 2.2 -176 -0.3 Natural Gas 10,244 55.6 24,902 37.9 Other 1 56 0.3 682 1.0 Other Renewable1 226 1.2 850 1.3 Petroleum 1,351 7.3 235 0.4 Total 18,424 100.0 65,682 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

272

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Maryland Nuclear Profile 2010 Maryland profile Maryland Nuclear Profile 2010 Maryland profile Maryland total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (Percent) Nuclear 1,705 13.6 13,994 32.1 Coal 4,886 39.0 23,668 54.3 Hydro and Pumped Storage 590 4.7 1,667 3.8 Natural Gas 2,041 16.3 2,897 6.6 Other 1 152 1.2 485 1.1 Other Renewable1 209 1.7 574 1.3 Petroleum 2,933 23.4 322 0.7 Total 12,516 100.0 43,607 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

273

EIA - State Nuclear Profiles  

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

Alabama Nuclear Profile 2010 Alabama profile Alabama Nuclear Profile 2010 Alabama profile Alabama total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 5,043 15.6 37,941 24.9 Coal 11,441 35.3 63,050 41.4 Hydro and Pumped Storage 3,272 10.1 8,704 5.7 Natural Gas 11,936 36.8 39,235 25.8 Other1 100 0.3 643 0.4 Other Renewable1 583 1.8 2,377 1.6 Petroleum 43 0.1 200 0.1 Total 32,417 100.0 152,151 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

274

EIA - State Nuclear Profiles  

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

Missouri Nuclear Profile 2010 Missouri profile Missouri Nuclear Profile 2010 Missouri profile Missouri total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,190 5.5 8,996 9.7 Coal 12,070 55.5 75,047 81.3 Hydro and Pumped Storage 1,221 5.6 2,427 2.6 Natural Gas 5,579 25.7 4,690 5.1 Other 1 - - 39 * Other Renewable1 466 2.1 988 1.1 Petroleum 1,212 5.6 126 0.1 Total 21,739 100.0 92,313 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05.

275

EIA - State Nuclear Profiles  

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

California Nuclear Profile 2010 California profile California Nuclear Profile 2010 California profile California total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 4,390 6.5 32,201 15.8 Coal 374 0.6 2,100 1.0 Hydro and Pumped Storage 13,954 20.7 33,260 16.3 Natural Gas 41,370 61.4 107,522 52.7 Other 1 220 0.3 2,534 1.2 Other Renewable1 6,319 9.4 25,450 12.5 Petroleum 701 1.0 1,059 0.5 Total 63,328 100.0 204,126 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

276

EIA - State Nuclear Profiles  

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

Maryland Nuclear Profile 2010 Maryland profile Maryland Nuclear Profile 2010 Maryland profile Maryland total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (Percent) Nuclear 1,705 13.6 13,994 32.1 Coal 4,886 39.0 23,668 54.3 Hydro and Pumped Storage 590 4.7 1,667 3.8 Natural Gas 2,041 16.3 2,897 6.6 Other 1 152 1.2 485 1.1 Other Renewable1 209 1.7 574 1.3 Petroleum 2,933 23.4 322 0.7 Total 12,516 100.0 43,607 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

277

EIA - State Nuclear Profiles  

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

Connecticut Nuclear Profile 2010 Connecticut profile Connecticut Nuclear Profile 2010 Connecticut profile Connecticut total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 2,103 25.4 16,750 50.2 Coal 564 6.8 2,604 7.8 Hydro and Pumped Storage 151 1.8 400 1.2 Natural Gas 2,292 27.7 11,716 35.1 Other 1 27 0.3 730 2.2 Other Renewable1 159 1.9 740 2.2 Petroleum 2,989 36.1 409 1.2 Total 8,284 100.0 33,350 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

278

EIA - State Nuclear Profiles  

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

York Nuclear Profile 2010 New York profile York Nuclear Profile 2010 New York profile New York total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 5,271 13.4 41,870 30.6 Coal 2,781 7.1 13,583 9.9 Hydro and Pumped Storage 5,714 14.5 24,942 18.2 Natural Gas 17,407 44.2 48,916 35.7 Other 1 45 0.1 832 0.6 Other Renewable1 1,719 4.4 4,815 3.5 Petroleum 6,421 16.3 2,005 1.5 Total 39,357 100.0 136,962 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable.

279

EIA - State Nuclear Profiles  

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

Nebraska Nuclear Profile 2010 Nebraska profile Nebraska Nuclear Profile 2010 Nebraska profile Nebraska total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,245 15.8 11,054 30.2 Coal 3,932 50.0 23,368 63.8 Hydro and Pumped Storage 278 3.5 1,314 3.6 Natural Gas 1,864 23.5 375 1.0 Other Renewable1 165 2.1 493 1.3 Petroleum 387 4.9 31 0.1 Total 7,857 100.0 36,630 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. Notes: Totals may not equal sum of components due to independent rounding.

280

Cooling load design tool for UFAD systems.  

E-Print Network (OSTI)

Underfloor Air Distribution (UFAD) Design Guide. Atlanta:Load Design Tool for Underfloor Air Distribution Systems. for design cooling loads in underfloor air distribution (

Bauman, Fred; Schiavon, Stefano; Webster, Tom; Lee, Kwang Ho

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "kwh load profiles" 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

Self-aligning biaxial load frame  

DOE Patents (OSTI)

An self-aligning biaxial loading apparatus for use in testing the strength of specimens while maintaining a constant specimen centroid during the loading operation. The self-aligning biaxial loading apparatus consists of a load frame and two load assemblies for imparting two independent perpendicular forces upon a test specimen. The constant test specimen centroid is maintained by providing elements for linear motion of the load frame relative to a fixed crosshead, and by alignment and linear motion elements of one load assembly relative to the load frame.

Ward, Michael B. (Idaho Falls, ID); Epstein, Jonathan S. (Idaho Falls, ID); Lloyd, W. Randolph (Idaho Falls, ID)

1994-01-01T23:59:59.000Z

282

Self-aligning biaxial load frame  

DOE Patents (OSTI)

An self-aligning biaxial loading apparatus for use in testing the strength of specimens while maintaining a constant specimen centroid during the loading operation. The self-aligning biaxial loading apparatus consists of a load frame and two load assemblies for imparting two independent perpendicular forces upon a test specimen. The constant test specimen centroid is maintained by providing elements for linear motion of the load frame relative to a fixed cross head, and by alignment and linear motion elements of one load assembly relative to the load frame. 3 figures.

Ward, M.B.; Epstein, J.S.; Lloyd, W.R.

1994-01-18T23:59:59.000Z

283

Peak load management: Potential options  

SciTech Connect

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

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

1989-10-01T23:59:59.000Z

284

EIA - State Electricity Profiles  

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

Tennessee Electricity Profile 2010 Tennessee full report Tennessee Electricity Profile 2010 Tennessee full report Table 1. 2010 Summary Statistics (Tennessee) Item Value U.S. Rank NERC Region(s) RFC/SERC Primary Energy Source Coal Net Summer Capacity (megawatts) 21,417 19 Electric Utilities 20,968 11 Independent Power Producers & Combined Heat and Power 450 49 Net Generation (megawatthours) 82,348,625 19 Electric Utilities 79,816,049 15 Independent Power Producers & Combined Heat and Power 2,532,576 45 Emissions (thousand metric tons) Sulfur Dioxide 138 13 Nitrogen Oxide 33 31 Carbon Dioxide 48,196 18 Sulfur Dioxide (lbs/MWh) 3.7 14 Nitrogen Oxide (lbs/MWh) 0.9 40 Carbon Dioxide (lbs/MWh) 1,290 26 Total Retail Sales (megawatthours) 103,521,537 13 Full Service Provider Sales (megawatthours) 103,521,537 10

285

Performance profiles style sheet  

Gasoline and Diesel Fuel Update (EIA)

06) 06) Distribution Category UC-950 Performance Profiles of Major Energy Producers 2006 December 2007 Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the U.S. Department of Energy. The information contained herein should be attributed to the Energy Information Administration and should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. Contacts Performance Profiles of Major Energy Producers 2006 is prepared by the Energy Information Administration, Office of Energy Markets and End Use, Energy Markets and Contingency Information Division, Financial

286

EIA - State Electricity Profiles  

Gasoline and Diesel Fuel Update (EIA)

Tennessee Electricity Profile 2010 Tennessee full report Tennessee Electricity Profile 2010 Tennessee full report Table 1. 2010 Summary Statistics (Tennessee) Item Value U.S. Rank NERC Region(s) RFC/SERC Primary Energy Source Coal Net Summer Capacity (megawatts) 21,417 19 Electric Utilities 20,968 11 Independent Power Producers & Combined Heat and Power 450 49 Net Generation (megawatthours) 82,348,625 19 Electric Utilities 79,816,049 15 Independent Power Producers & Combined Heat and Power 2,532,576 45 Emissions (thousand metric tons) Sulfur Dioxide 138 13 Nitrogen Oxide 33 31 Carbon Dioxide 48,196 18 Sulfur Dioxide (lbs/MWh) 3.7 14 Nitrogen Oxide (lbs/MWh) 0.9 40 Carbon Dioxide (lbs/MWh) 1,290 26 Total Retail Sales (megawatthours) 103,521,537 13 Full Service Provider Sales (megawatthours) 103,521,537 10

287

Chemical profiles of switchgrass  

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

profiles profiles of switchgrass Zhoujian Hu a,b , Robert Sykes a,c , Mark F. Davis a,c , E. Charles Brummer a,d , Arthur J. Ragauskas a,b,e, * a BioEnergy Science Center, USA b School of Chemistry and Biochemistry, Institute of Paper Science and Technology, Georgia Institute of Technology, Atlanta, GA 30332, USA c National Renewable Energy Laboratory, 1617 Cole Blvd., Golden, CO 80401, USA d Institute for Plant Breeding, Genetics, and Genomics, Department of Crop and Soil Sciences, University of Georgia, Athens, GA 30602, USA e Forest Products and Chemical Engineering Department, Chemical and Biological Engineering, Chalmers University of Technology, SE-412 96 Göteborg, Sweden a r t i c l e i n f o Article history: Received 15 April 2009 Received in revised form 10 December 2009 Accepted 10 December 2009 Available online 13 January 2010 Keywords: Switchgrass Morphological components Chemical

288

Temperature profile detector  

DOE Patents (OSTI)

Disclosed is a temperature profile detector shown as a tubular enclosure surrounding an elongated electrical conductor having a plurality of meltable conductive segments surrounding it. Duplicative meltable segments are spaced apart from one another along the length of the enclosure. Electrical insulators surround these elements to confine molten material from the segments in bridging contact between the conductor and a second electrical conductor, which might be the confining tube. The location and rate of growth of the resulting short circuits between the two conductors can be monitored by measuring changes in electrical resistance between terminals at both ends of the two conductors. Additional conductors and separate sets of meltable segments operational at differing temperatures can be monitored simultaneously for measuring different temperature profiles. 8 figs.

Tokarz, R.D.

1983-10-11T23:59:59.000Z

289

{Control of Residential Load Management Networks Using Real Time Pricing  

E-Print Network (OSTI)

loads to deliver load following and regulation, withproducts like load following and spinning reserve.following of constant power references. Chapter 7 Implications of Load

Burke, William Jerome

2010-01-01T23:59:59.000Z

290

Web-crippling of GFRP pultruded profiles. Part 1: Experimental study  

Science Journals Connector (OSTI)

Abstract There is evidence that glass fibre reinforced polymer (GFRP) pultruded profiles are particularly susceptible to transverse compressive loads, owing to the much lower mechanical properties in the direction transverse to the pultrusion axis. Although very relevant, the understanding about the web-crippling phenomenon in GFRP pultruded profiles is still very limited, as attested by the lack of information available in design codes and guidelines. This paper reports an experimental study about the web-crippling phenomenon in GFRP pultruded profiles with I-section. The experimental programme included comprehensive material characterization tests (tension, compression, flexure and shear), and full-scale web-crippling tests on four different I-profiles, with heights ranging from 100mm to 400mm, thus covering the vast majority of structural profiles currently available in the market. In the web-crippling experiments, two load configurations were tested: interior two flanges (ITF); and end two flanges (ETF). In addition, tests were performed with three different bearing lengths: 15mm, 50mm, and 100mm. The experimental results confirmed the susceptibility of GFRP pultruded profiles to transverse compressive loads, outlining the influence of both the load configuration and the bearing length on the web-crippling phenomenon in terms of strength, stiffness, and failure modes.

Loureno Almeida Fernandes; Jos Gonilha; Joo R. Correia; Nuno Silvestre; Francisco Nunes

2015-01-01T23:59:59.000Z

291

NOTES ON NEUTRON DEPTH PROFILING  

E-Print Network (OSTI)

NOTES ON NEUTRON DEPTH PROFILING by J.K. Shultis Department of Mechanical and Nuclear Engineering College of Engineering Kansas State University Manhattan, Kansas 66506 Dec. 2003 #12;Notes on Neutron Depth Profiling J. Kenneth Shultis December 2003 1 Introduction The purpose of neutron depth profiling

Shultis, J. Kenneth

292

Macro Data Load: An Efficient Mechanism for Enhancing Loaded Data Reuse  

E-Print Network (OSTI)

Macro Data Load: An Efficient Mechanism for Enhancing Loaded Data Reuse Lei Jin and Sangyeun Cho, Member, IEEE Abstract--This paper presents a study on macro data load, a novel mechanism to increase the amount of loaded data reuse within a processor. A macro data load brings into the processor a maximum

Cho, Sangyeun

293

Project Cost Profile Spreadsheet | Department of Energy  

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

Project Cost Profile Spreadsheet Project Cost Profile Spreadsheet Project Cost Profile Spreadsheet.xlsx More Documents & Publications Statement of Work (SOW) Template (Combined...

294

Texas Crop Profile: Potatoes  

E-Print Network (OSTI)

175 pounds of nitrogen, 80 pounds of phosphorus, and 80 pounds of potassium. Potassium is generally not needed in the High Plains, although many growers apply it. Texas Crop Profile P O T A T O E S E-19 3-00 Prepared by Kent D. Hall, Rodney L. Holloway..., following drag-off or after potato plants have fully emerged. Controls weeds by disrupting growth process during germination. Does not control established weeds. State Contacts Rodney L. Holloway Extension Specialist 2488 TAMU College Station, Texas 77843...

Hall, Kent D.; Holloway, Rodney L.; Smith, Dudley

2000-04-12T23:59:59.000Z

295

PASSIVE DETECTION OF VEHICLE LOADING  

SciTech Connect

The Digital Imaging and Remote Sensing Laboratory (DIRS) at the Rochester Institute of Technology, along with the Savannah River National Laboratory is investigating passive methods to quantify vehicle loading. The research described in this paper investigates multiple vehicle indicators including brake temperature, tire temperature, engine temperature, acceleration and deceleration rates, engine acoustics, suspension response, tire deformation and vibrational response. Our investigation into these variables includes building and implementing a sensing system for data collection as well as multiple full-scale vehicle tests. The sensing system includes; infrared video cameras, triaxial accelerometers, microphones, video cameras and thermocouples. The full scale testing includes both a medium size dump truck and a tractor-trailer truck on closed courses with loads spanning the full range of the vehicle's capacity. Statistical analysis of the collected data is used to determine the effectiveness of each of the indicators for characterizing the weight of a vehicle. The final sensing system will monitor multiple load indicators and combine the results to achieve a more accurate measurement than any of the indicators could provide alone.

Garrett, A.

2012-01-03T23:59:59.000Z

296

EIA - State Nuclear Profiles  

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

Virginia profile Virginia profile Virginia total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 3,501 14.5 26,572 36.4 Coal 5,868 24.3 25,459 34.9 Hydro and Pumped Storage 4,107 17.0 10 * Natural Gas 7,581 31.4 16,999 23.3 Other 1 - - 414 0.6 Other Renewable1 621 2.6 2,220 3.0 Petroleum 2,432 10.1 1,293 1.8 Total 24,109 100.0 72,966 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05.

297

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Wisconsin profile Wisconsin profile Wisconsin total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,584 8.9 13,281 20.7 Coal 8,063 45.2 40,169 62.5 Hydro and Pumped Storage 492 2.8 2,112 3.3 Natural Gas 6,110 34.3 5,497 8.5 Other 1 21 0.1 63 0.1 Other Renewable1 775 4.3 2,474 3.8 Petroleum 790 4.4 718 1.1 Total 17,836 100.0 64,314 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. Notes: Totals may not equal sum of components due to independent rounding.

298

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Texas profile Texas profile Texas total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 4,966 4.6 41,335 10.0 Coal 22,335 20.6 150,173 36.5 Hydro and Pumped Storage 689 0.6 1,262 0.3 Natural Gas 69,291 64.0 186,882 45.4 Other 1 477 0.4 3,630 0.9 Other Renewable1 10,295 9.5 27,705 6.7 Petroleum 204 0.2 708 0.2 Total 108,258 100.0 411,695 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. Notes: Totals may not equal sum of components due to independent rounding.

299

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Vermont profile Vermont profile Vermont total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 620 55.0 4,782 72.2 Hydro and Pumped Storage 324 28.7 1,347 20.3 Natural Gas - - 4 0.1 Other Renewable1 84 7.5 482 7.3 Petroleum 100 8.9 5 0.1 Total 1,128 100.0 6,620 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. - = No data reported. Notes: Totals may not equal sum of components due to independent rounding. Other Renewable: Wood, black liquor, other wood waste, biogenic municipal solid waste, landfill gas, sludge waste, agriculture byproducts, other biomass, geothermal, solar thermal, photovoltaic energy, and wind.

300

EIA - State Nuclear Profiles  

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

Vermont profile Vermont profile Vermont total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 620 55.0 4,782 72.2 Hydro and Pumped Storage 324 28.7 1,347 20.3 Natural Gas - - 4 0.1 Other Renewable1 84 7.5 482 7.3 Petroleum 100 8.9 5 0.1 Total 1,128 100.0 6,620 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. - = No data reported. Notes: Totals may not equal sum of components due to independent rounding. Other Renewable: Wood, black liquor, other wood waste, biogenic municipal solid waste, landfill gas, sludge waste, agriculture byproducts, other biomass, geothermal, solar thermal, photovoltaic energy, and wind.

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


301

EIA - State Nuclear Profiles  

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

Tennessee profile Tennessee profile Tennessee total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 3,401 15.9 27,739 33.7 Coal 8,805 41.1 43,670 53.0 Hydro and Pumped Storage 4,277 20.0 7,416 9.0 Natural Gas 4,655 21.7 2,302 2.8 Other 1 - - 16 * Other Renewable1 222 1.0 988 1.2 Petroleum 58 0.3 217 0.3 Total 21,417 100.0 82,349 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05.

302

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Virginia profile Virginia profile Virginia total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 3,501 14.5 26,572 36.4 Coal 5,868 24.3 25,459 34.9 Hydro and Pumped Storage 4,107 17.0 10 * Natural Gas 7,581 31.4 16,999 23.3 Other 1 - - 414 0.6 Other Renewable1 621 2.6 2,220 3.0 Petroleum 2,432 10.1 1,293 1.8 Total 24,109 100.0 72,966 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05.

303

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

South Carolina profile South Carolina profile South Carolina total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 6,486 27.0 51,988 49.9 Coal 7,230 30.1 37,671 36.2 Hydro and Pumped Storage 4,006 16.7 1,442 1.4 Natural Gas 5,308 22.1 10,927 10.5 Other 1 - - 61 0.1 Other Renewable1 284 1.2 1,873 1.8 Petroleum 670 2.8 191 0.2 Total 23,982 100.0 104,153 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. - = No data reported.

304

EIA - State Nuclear Profiles  

Gasoline and Diesel Fuel Update (EIA)

Washington profile Washington profile Washington total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,097 3.6 9,241 8.9 Coal 1,340 4.4 8,527 8.2 Hydro and Pumped Storage 21,495 70.5 68,342 66.0 Natural Gas 3,828 12.6 10,359 10.0 Other 1 - - 354 0.3 Other Renewable1 2,703 8.9 6,617 6.4 Petroleum 15 * 32 * Total 30,478 100.0 103,473 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05.

305

EIA - State Nuclear Profiles  

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

Washington profile Washington profile Washington total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,097 3.6 9,241 8.9 Coal 1,340 4.4 8,527 8.2 Hydro and Pumped Storage 21,495 70.5 68,342 66.0 Natural Gas 3,828 12.6 10,359 10.0 Other 1 - - 354 0.3 Other Renewable1 2,703 8.9 6,617 6.4 Petroleum 15 * 32 * Total 30,478 100.0 103,473 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. * = Absolute percentage less than 0.05.

306

EIA - State Nuclear Profiles  

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

South Carolina profile South Carolina profile South Carolina total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 6,486 27.0 51,988 49.9 Coal 7,230 30.1 37,671 36.2 Hydro and Pumped Storage 4,006 16.7 1,442 1.4 Natural Gas 5,308 22.1 10,927 10.5 Other 1 - - 61 0.1 Other Renewable1 284 1.2 1,873 1.8 Petroleum 670 2.8 191 0.2 Total 23,982 100.0 104,153 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. - = No data reported.

307

EIA - State Nuclear Profiles  

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

Wisconsin profile Wisconsin profile Wisconsin total electric power industry, summer capacity and net generation, by energy source, 2010 Primary energy source Summer capacity (mw) Share of State total (percent) Net generation (thousand mwh) Share of State total (percent) Nuclear 1,584 8.9 13,281 20.7 Coal 8,063 45.2 40,169 62.5 Hydro and Pumped Storage 492 2.8 2,112 3.3 Natural Gas 6,110 34.3 5,497 8.5 Other 1 21 0.1 63 0.1 Other Renewable1 775 4.3 2,474 3.8 Petroleum 790 4.4 718 1.1 Total 17,836 100.0 64,314 100.0 1Municipal Solid Waste net generation is allocated according to the biogenic and non-biogenic components of the fuel; however, all Municipal Solid Waste summer capacity is classified as Renewable. Notes: Totals may not equal sum of components due to independent rounding.

308

Online Load Balancing for Related Machines 1 Piotr Berman  

E-Print Network (OSTI)

), the load of a machine i in schedule s and Load(s), the load of entire schedule s as follows: load(s; i) = 1On­line Load Balancing for Related Machines 1 Piotr Berman The Pennsylvania State University of randomized algorithms for this problem. Key Words: on­line algorithm, load balancing, related machines

Charikar, Moses

309

Price-Responsive Load (PRL) Program - Framing Paper No.1  

SciTech Connect

By definition, effective and efficient competitive markets need a supply side and a demand side. One criticism of electric restructuring efforts in many states is that most of the attention has been focused on the supply side, in a market focused on the short term. In general, the demand side of the market has been under-addressed. The objective of the New England Demand Response Initiative (NEDRI) is to develop a comprehensive, coordinated set of demand response programs for the New England regional power markets. NEDRI aims to maximize the capability of demand response to compete in the wholesale market and to improve the economic efficiency and environmental profile of the electric sector. To those ends, NEDRI is focusing its efforts in four interrelated areas: (1) ISO-level reliability programs, (2) Market-based price-responsive load programs, (3) Demand response at retail through pricing, rate design, and advanced metering, and (4) End-use energy efficiency resources as demand response. The fourth area, energy efficiency, is the subject of this framing paper. Energy efficiency reduces the energy used by specific end-use devices and systems, typically without affecting the level of service and without loss of amenity. Energy savings and peak load reductions are achieved by substituting technically more advanced equipment, processes, or operational strategies to produce the same or an improved level of end-use service with less electricity. In contrast, load management programs lower peak demand during specific, limited time periods by either (1) influencing the timing of energy use by shifting load to another time period, or (2) reducing the level of energy use by curtailing or interrupting the load, typically with some loss of service or amenity.

Goldman, Charles A.

2002-03-01T23:59:59.000Z

310

Approximate Stokes Drift Profiles in Deep Water  

Science Journals Connector (OSTI)

A deep-water approximation of the Stokes drift velocity profile is explored as an alternative to the monochromatic profile. The alternative profile investigated relies on the same two quantities required for the monochromatic profile, namely, the ...

yvind Breivik; Peter A. E. M. Janssen; Jean-Raymond Bidlot

2014-09-01T23:59:59.000Z

311

5 Year Financial Profile -Charts 5 Year Financial Profile Charts  

E-Print Network (OSTI)

. Income Expenditure Assets Liabilities http://www.fin.mmu.ac.uk/f18_001b.htm06/07/2004 13:02:41 #12;5 Year Financial Profile - Charts - Income 5 Year Financial Profile Charts Income Back http://www.fin.mmu.ac.uk/f18 Profile Charts Expenditure Back http://www.fin.mmu.ac.uk/f18_001d.htm06/07/2004 13:02:52 #12;5 Year

312

5 Year Financial Profile -Charts 5 Year Financial Profile Charts  

E-Print Network (OSTI)

. Income Expenditure Assets Liabilities http://www.fin.mmu.ac.uk/f18_0029.htm06/07/2004 13:01:23 #12;5 Year Financial Profile - Charts - Income 5 Year Financial Profile Charts Income Back http://www.fin.mmu.ac.uk/f18 Profile Charts Expenditure Back http://www.fin.mmu.ac.uk/f18_002d.htm06/07/2004 13:01:34 #12;5 Year

313

5 Year Financial Profile -Charts 5 Year Financial Profile Charts  

E-Print Network (OSTI)

. Income Expenditure Assets Liabilities & Reserves http://www.fin.mmu.ac.uk/f18_0067.htm06/07/2004 13 Profile Charts Expenditure Back http://www.fin.mmu.ac.uk/f18_006b.htm06/07/2004 13:04:46 #12;5 Year Financial Profile - Charts - Assets 5 Year Financial Profile Charts Assets Back http://www.fin.mmu.ac.uk/f18

314

5 Year Financial Profile -Charts 5 Year Financial Profile Charts  

E-Print Network (OSTI)

. Income Expenditure Assets Liabilities & Reserves http://www.fin.mmu.ac.uk/f18_0079.htm06/07/2004 13 Profile Charts Expenditure Back http://www.fin.mmu.ac.uk/f18_007b.htm06/07/2004 13:05:59 #12;5 Year Financial Profile - Charts - Assets 5 Year Financial Profile Charts Assets Back http://www.fin.mmu.ac.uk/f18

315

2012 ENVIRONMENTAL PERFORMANCE INDEX 61 Appendix I: Indicator Profiles  

E-Print Network (OSTI)

emissions per electricity generation CO2KWH Ecosystem Vitality Climate change Renewable electricity RENEW if it is private or shared (but not public) and if hygienically separates human excreta

Columbia University

316

Beam Profile Monitor With Accurate Horizontal And Vertical Beam Profiles  

DOE Patents (OSTI)

A widely used scanner device that rotates a single helically shaped wire probe in and out of a particle beam at different beamline positions to give a pair of mutually perpendicular beam profiles is modified by the addition of a second wire probe. As a result, a pair of mutually perpendicular beam profiles is obtained at a first beamline position, and a second pair of mutually perpendicular beam profiles is obtained at a second beamline position. The simple modification not only provides more accurate beam profiles, but also provides a measurement of the beam divergence and quality in a single compact device.

Havener, Charles C [Knoxville, TN; Al-Rejoub, Riad [Oak Ridge, TN

2005-12-26T23:59:59.000Z

317

Residential Load Management Program and Pilot  

E-Print Network (OSTI)

In 1986 LCRA embarked on residential load management to control peak summer loads. At that time, LCRA was considered a summer peaking utility, and residential air conditioning and water heating systems were selected for control. The program...

Haverlah, D.; Riordon, K.

1994-01-01T23:59:59.000Z

318

1994 Pacific Northwest Loads and Resources Study.  

SciTech Connect

The 1994 Pacific Northwest Loads and Resources Study presented herein establishes a picture of how the agency is positioned today in its loads and resources balance. It is a snapshot of expected resource operation, contractual obligations, and rights. This study does not attempt to present or analyze future conservation or generation resource scenarios. What it does provide are base case assumptions from which scenarios encompassing a wide range of uncertainties about BPA`s future may be evaluated. The Loads and Resources Study is presented in two documents: (1) this summary of Federal system and Pacific Northwest region loads and resources and (2) a technical appendix detailing the loads and resources for each major Pacific Northwest generating utility. This analysis updates the 1993 Pacific Northwest Loads and Resources Study, published in December 1993. In this loads and resources study, resource availability is compared with a range of forecasted electricity consumption. The Federal system and regional analyses for medium load forecast are presented.

United States. Bonneville Power Administration.

1994-12-01T23:59:59.000Z

319

Helicase Loading at Chromosomal Origins of Replication  

E-Print Network (OSTI)

Loading of the replicative DNA helicase at origins of replication is of central importance in DNA replication. As the first of the replication fork proteins assemble at chromosomal origins of replication, the loaded helicase ...

Bell, Stephen P.

320

A Novel Approach to Determining Motor Load  

E-Print Network (OSTI)

A NOVEL APPROACH TO DETERMINING MOTOR LOAD by Michael Brown Georgia Tech Research Institute Atlanta, Georgia ABSTRACf Properly sized electric motors are essential if industrial plant efficiency is to be optimized and energy costs... minimized. Because of the difficully in making power measurements on three phase motors, loading is rarely, if ever, checked. A simple indication of motor load can be achieved by measuring operating speed because speed and load are almost linearly...

Brown, M.

Note: This page contains sample records for the topic "kwh load profiles" 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

Chapter 6 - Stage 3: Data Load  

Science Journals Connector (OSTI)

Summary This chapter discusses the Data Load stage of the Guerrilla Analytics workflow. Data Load involves getting data from a receipt location (generally the file system) and loading it into the Data Manipulation Environment (DME). In this chapter, you will learn about the various activities that take place at Data Load. You will learn about the pitfalls and risks in these activities. You will then learn a number of practice tips to mitigate those risks.

Enda Ridge

2015-01-01T23:59:59.000Z

322

FINAL PROJECT REPORT LOAD MODELING TRANSMISSION RESEARCH  

E-Print Network (OSTI)

BPA), the basic requirements for an improved load model were determined. These requirements included modeling the substation

Lesieutre, Bernard

2013-01-01T23:59:59.000Z

323

Test profiles for stationary energy storage applications  

SciTech Connect

Evaluation of battery and other energy storage technologies for stationary uses is progressing rapidly toward application-specific testing that uses computer-based data acquisition and control equipment, active electronic loads and power supplies, and customized software, to enable sophisticated test regimes that simulate actual use conditions. These simulated-use tests provide more accurate performance and life evaluations than simple constant resistance or current testing regimes. Some of the tests use stepped constant-power charge and discharge regimes to simulate conditions created by electric utility applications such as frequency regulation and spinning reserve. Other test profiles under development simulate conditions for the energy storage component of Remote Area Power Supplies (RAPS) that include renewable and/or fossil-fueled generators. Various RAPS applications have unique sets of service conditions that require specialized test profiles. However, almost all RAPS tests and many tests that represent other stationary applications need to simulate significant time periods during which storage devices operate at low-to-medium states-of-charge without full recharge. Consideration of these and similar issues in simulated-use test regimes is necessary to effectively predict the responses of the various types of batteries in specific stationary applications. This paper describes existing and evolving stationary applications for energy storage technologies and test regimes that are designed to simulate them. The paper also discusses efforts to develop international testing standards.

Butler, P.C. [Sandia National Labs., Albuquerque, NM (United States); Cole, J.F. [International Lead Zinc Research Organization, Research Triangle Park, NC (United States); Taylor, P.A. [Energetics, Inc., Columbia, MD (United States)

1998-09-01T23:59:59.000Z

324

Structures buckling under tensile dead load  

Science Journals Connector (OSTI)

...the load measured with a load cell Gefran OC-K2D-C3...PY-2-F-100 (Gefran Spa). Data have been acquired with...elementsAmsterdamElsevier Data Supplement Data Supplement Structures buckling under tensile dead load. A movie of the experiments...

2011-01-01T23:59:59.000Z

325

Flow Duration Curve Load Duration Curve  

E-Print Network (OSTI)

and concentration data--select appropriate conversion factors 3. Develop Load Duration Curve 4. Plot observed data there has been no flow at this site #12;Gather daily flow rate data Load data into a spreasheet Sort largest, etc) Calculate percentage of days flow was exceeded: How do you estimate load with given data

326

Flow Duration Curve Load Duration Curve  

E-Print Network (OSTI)

given flow and concentration data--select appropriate conversion factors 3. Develop Load Duration Curve 4. Plot observed data with Load Duration Curve #12;What are they? How do you make one? #12;DescribesRangeFlows LowFlows 40 % of the time there has been no flow at this site #12;Gather daily flow rate data Load

327

Scholarship Search Profile Personal Information  

E-Print Network (OSTI)

Scholarship Search Profile Personal Information Name: ____________________________________ Address) ________________________________________________________________________ ________________________________________________________________________ ________________________________________________________________________ Work Experience: List most recent job first Employer/Company Name _______________________________________________________________ Reference: Name and telephone _____________________________________________ Employer/Company Name

Mather, Patrick T.

328

Evaluate Greenhouse Gas Emissions Profile  

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

Evaluating a Federal agency's greenhouse gas (GHG) emissions profile means getting a solid understanding of the organization's largest emission categories, largest emission sources, and its potential for improvement.

329

Low reflectance radio frequency load  

DOE Patents (OSTI)

A load for traveling microwave energy has an absorptive volume defined by cylindrical body enclosed by a first end cap and a second end cap. The first end cap has an aperture for the passage of an input waveguide with a rotating part that is coupled to a reflective mirror. The inner surfaces of the absorptive volume consist of a resistive material or are coated with a coating which absorbs a fraction of incident RF energy, and the remainder of the RF energy reflects. The angle of the reflector and end caps is selected such that reflected RF energy dissipates an increasing percentage of the remaining RF energy at each reflection, and the reflected RF energy which returns to the rotating mirror is directed to the back surface of the rotating reflector, and is not coupled to the input waveguide. Additionally, the reflector may have a surface which generates a more uniform power distribution function axially and laterally, to increase the power handling capability of the RF load. The input waveguide may be corrugated for HE11 mode input energy.

Ives, R. Lawrence; Mizuhara, Yosuke M

2014-04-01T23:59:59.000Z

330

APS high heat load monochromator  

SciTech Connect

This document contains the design specifications of the APS high heat load (HHL) monochromator and associated accessories as of February 1993. It should be noted that work is continuing on many parts of the monochromator including the mechanical design, crystal cooling designs, etc. Where appropriate, we have tried to add supporting documentation, references to published papers, and calculations from which we based our decisions. The underlying philosophy behind performance specifications of this monochromator was to fabricate a device that would be useful to as many APS users as possible, that is, the design should be as generic as possible. In other words, we believe that this design will be capable of operating on both bending magnet and ID beamlines (with the appropriate changes to the cooling and crystals) with both flat and inclined crystal geometries and with a variety of coolants. It was strongly felt that this monochromator should have good energy scanning capabilities over the classical energy range of about 4 to 20 keywith Si (111) crystals. For this reason, a design incorporating one rotation stage to drive both the first and second crystals was considered most promising. Separate rotary stages for the first and second crystals can sometimes provide more flexibility in their capacities to carry heavy loads (for heavily cooled first crystals or sagittal benders of second crystals), but their tuning capabilities were considered inferior to the single axis approach.

Lee, W.K.; Mills, D.

1993-02-01T23:59:59.000Z

331

System and method employing a minimum distance and a load feature database to identify electric load types of different electric loads  

DOE Patents (OSTI)

A method identifies electric load types of a plurality of different electric loads. The method includes providing a load feature database of a plurality of different electric load types, each of the different electric load types including a first load feature vector having at least four different load features; sensing a voltage signal and a current signal for each of the different electric loads; determining a second load feature vector comprising at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the different electric loads; and identifying by a processor one of the different electric load types by determining a minimum distance of the second load feature vector to the first load feature vector of the different electric load types of the load feature database.

Lu, Bin; Yang, Yi; Sharma, Santosh K; Zambare, Prachi; Madane, Mayura A

2014-12-23T23:59:59.000Z

332

1993 Pacific Northwest Loads and Resources Study.  

SciTech Connect

The Loads and Resources Study is presented in three documents: (1) this summary of Federal system and Pacific Northwest region loads and resources; (2) a technical appendix detailing forecasted Pacific Northwest economic trends and loads, and (3) a technical appendix detailing the loads and resources for each major Pacific Northwest generating utility. In this loads and resources study, resource availability is compared with a range of forecasted electricity consumption. The forecasted future electricity demands -- firm loads -- are subtracted from the projected capability of existing and {open_quotes}contracted for{close_quotes} resources to determine whether Bonneville Power Administration (BPA) and the region will be surplus or deficit. If resources are greater than loads in any particular year or month, there is a surplus of energy and/or capacity, which BPA can sell to increase revenues. Conversely, if firm loads exceed available resources, there is a deficit of energy and/or capacity, and additional conservation, contract purchases, or generating resources will be needed to meet load growth. The Pacific Northwest Loads and Resources Study analyzes the Pacific Northwest`s projected loads and available generating resources in two parts: (1) the loads and resources of the Federal system, for which BPA is the marketing agency; and (2) the larger Pacific Northwest regional power system, which includes loads and resource in addition to the Federal system. The loads and resources analysis in this study simulates the operation of the power system under the Pacific Northwest Coordination Agreement (PNCA) produced by the Pacific Northwest Coordinating Group. This study presents the Federal system and regional analyses for five load forecasts: high, medium-high, medium, medium-low, and low. This analysis projects the yearly average energy consumption and resource availability for Operating Years (OY) 1994--95 through 2003--04.

United States. Bonneville Power Administration.

1993-12-01T23:59:59.000Z

333

Park Load Reduction by Preconditioning of Buildings at Night  

E-Print Network (OSTI)

arounde50%. The local utility charges approximately p - 10 $/kWe per month for demand and pc - 0.05 $$?h and Pw - 0.07 $/kwh for energy, off and on $eak respectively - nihbers that are representative. If pc/Pw were greater than r), night cooling...

Rabl, A.; Norford, L. K.

1988-01-01T23:59:59.000Z

334

High payload six-axis load sensor  

DOE Patents (OSTI)

A repairable high-payload six-axis load sensor includes a table, a base, and at least three shear-pin load transducers removably mounted between the table and the base. Removable mounting permits easy replacement of damaged shear pins. Preferably, the shear-pin load transducers are responsive to shear forces imparted along the two axes perpendicular to an axis of minimum sensitivity characteristic of the transducer. Responsive to an applied shear force, each shear-pin load transducer can produce an electrical signal proportional to the reaction force. The load sensor can further include a structure for receiving the proportional electrical signals and computing the applied load corresponding to the proportional electrical signals. The computed load can be expressed in terms of a three-dimensional XYZ Cartesian coordinate system.

Jansen, John F. (Knoxville, TN); Lind, Randall F. (Knoxville, TN)

2003-01-01T23:59:59.000Z

335

Statistical Analysis of Baseline Load Models for Non-Residential Buildings  

SciTech Connect

Policymakers are encouraging the development of standardized and consistent methods to quantify the electric load impacts of demand response programs. For load impacts, an essential part of the analysis is the estimation of the baseline load profile. In this paper, we present a statistical evaluation of the performance of several different models used to calculate baselines for commercial buildings participating in a demand response program in California. In our approach, we use the model to estimate baseline loads for a large set of proxy event days for which the actual load data are also available. Measures of the accuracy and bias of different models, the importance of weather effects, and the effect of applying morning adjustment factors (which use data from the day of the event to adjust the estimated baseline) are presented. Our results suggest that (1) the accuracy of baseline load models can be improved substantially by applying a morning adjustment, (2) the characterization of building loads by variability and weather sensitivity is a useful indicator of which types of baseline models will perform well, and (3) models that incorporate temperature either improve the accuracy of the model fit or do not change it.

Coughlin, Katie; Piette, Mary Ann; Goldman, Charles; Kiliccote, Sila

2008-11-10T23:59:59.000Z

336

High voltage load resistor array  

DOE Patents (OSTI)

A high voltage resistor comprising an array of a plurality of parallel electrically connected resistor elements each containing a resistive solution, attached at each end thereof to an end plate, and about the circumference of each of the end plates, a corona reduction ring. Each of the resistor elements comprises an insulating tube having an electrode inserted into each end thereof and held in position by one or more hose clamps about the outer periphery of the insulating tube. According to a preferred embodiment, the electrode is fabricated from stainless steel and has a mushroom shape at one end, that inserted into the tube, and a flat end for engagement with the end plates that provides connection of the resistor array and with a load.

Lehmann, Monty Ray (Smithfield, VA)

2005-01-18T23:59:59.000Z

337

Downstream Heat Flux Profile vs. Midplane T Profile in Tokamaks  

SciTech Connect

The relationship between the midplane scrape-off-layer electron temperature profile and the parallel heat flux profile at the divertor in tokamaks is investigated. A model is applied which takes into account anisotropic thermal diffusion, in a rectilinear geometry with constant density. Eigenmode analysis is applied to the simplified problem with constant thermal diffusivities. A self-similar nonlinear solution is found for the more realistic problem with anisotropically temperature-dependent thermal diffusivities. Numerical solutions are developed for both cases, with spatially dependent heat flux emerging from the plasma. For both constant and temperature-dependent thermal diffusivities it is found that, below about one-half of its peak, the heat flux profile shape at the divertor, compared with the midplane temperature profile shape, is robustly described by the simplest two-point model. However the physical processes are not those assumed in the simplest two-point model, nor is the numerical coefficient relating q||div to Tmp ?||mp/L|| as predicted. For realistic parameters the peak in the heat flux, moreover, can be reduced by a factor of two or more from the two-point model scaling which fits the remaining profile. For temperature profiles in the SOL region above the x-point set by marginal stability, the heat flux profile to the divertor can be largely decoupled from the prediction of the two-point model. These results suggest caveats for data interpretation, and possibly favorable outcomes for divertor configurations with extended field lines.

Robert J. Goldston

2009-08-20T23:59:59.000Z

338

Methods for Analyzing Electric Load Shape and its Variability  

E-Print Network (OSTI)

graphical displays of load data. We then define someAlthough simply overlaying load data from different timeprovide a good fit to load data in most buildings; their

Price, Philip

2010-01-01T23:59:59.000Z

339

5 Year Financial Profile -Charts 5 Year Financial Profile Charts  

E-Print Network (OSTI)

Charts Income Back http://www.fin.mmu.ac.uk/f18_004b.htm06/07/2004 12:57:08 #12;5 Year Financial Profile - Charts - zoom 5 Year Financial Profile Charts Expenditure Back http://www.fin.mmu.ac.uk/f18_004c.htm06 http://www.fin.mmu.ac.uk/f18_004d.htm06/07/2004 12:57:19 #12;5 Year Financial Profile - Charts - zoom 5

340

5 Year Financial Profile -Charts 5 Year Financial Profile Charts  

E-Print Network (OSTI)

Charts Income Back http://www.fin.mmu.ac.uk/f18_008b.htm06/07/2004 12:51:21 #12;5 Year Financial Profile - Charts - zoom 5 Year Financial Profile Charts Expenditure Back http://www.fin.mmu.ac.uk/f18_008c.htm06 http://www.fin.mmu.ac.uk/f18_008d.htm06/07/2004 12:51:31 #12;5 Year Financial Profile - Charts - zoom 5

Note: This page contains sample records for the topic "kwh load profiles" 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

5 Year Financial Profile -Charts 5 Year Financial Profile Charts  

E-Print Network (OSTI)

Charts Income Back http://www.fin.mmu.ac.uk/f18_010b.htm06/07/2004 10:57:23 #12;5 Year Financial Profile - Charts - zoom 5 Year Financial Profile Charts Expenditure Back http://www.fin.mmu.ac.uk/f18_010c.htm06 http://www.fin.mmu.ac.uk/f18_010d.htm06/07/2004 12:40:15 #12;5 Year Financial Profile - Charts - zoom 5

342

Estimating Demand Response Load Impacts: Evaluation of Baseline Load Models for Non-Residential Buildings in California  

E-Print Network (OSTI)

electric interval load data are available throughdetails, eachuseselectricloaddatafromaperiodbeforeusing customer load data [KEMA 2003, Quantum 2004,

Coughlin, Katie; Piette, Mary Ann; Goldman, Charles; Kiliccote, Sila

2008-01-01T23:59:59.000Z

343

5 Year Financial Profile -Charts 5 Year Financial Profile Charts  

E-Print Network (OSTI)

. Income Expenditure Assets Liabilities Income Breakdown Expenditure Breakdown http://www.fin.mmu.ac.uk/f18 Charts Income Back http://www.fin.mmu.ac.uk/f18_005b.htm06/07/2004 13:00:29 #12;5 Year Financial Profile - Charts - zoom 5 Year Financial Profile Charts Expenditure Back http://www.fin.mmu.ac.uk/f18_005c.htm06

344

Reservoir compaction loads on casings and liners  

SciTech Connect

Pressure drawdown due to production from a reservoir causes compaction of the reservoir formation which induces axial and radial loads on the wellbore. Reservoir compaction loads increase during the production life of a well, and are greater for deviated wells. Presented here are casing and liner loads at initial and final pressure drawdowns for a particular reservoir and at well deviation angles of 0 to 45 degrees.

Wooley, G.R.; Prachner, W.

1984-09-01T23:59:59.000Z

345

Preliminary Evaluation of Load Management for Electricity End Users  

E-Print Network (OSTI)

The planning, design and implementation of load management is complex and expensive. The results of a load management program are subject to numerous uncertainties related to load characteristics, power cost savings, load management costs...

Collier, S. E.

1984-01-01T23:59:59.000Z

346

Loads Providing Ancillary Services: Review of International Experience  

E-Print Network (OSTI)

In PJM for example, loads and generators that can follow theto generators and loads, who can follow operators second bya reflection of the loads inability to follow minute-by-

Heffner, Grayson

2008-01-01T23:59:59.000Z

347

Building Technologies Office Load Control Strategies  

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

BTO researches and implements load control strategies, which support the Sustainable and Holistic IntegratioN of Energy storage and Solar PV (SHINES) FOA.

348

Discovering and Loading Data with Power Query  

Science Journals Connector (OSTI)

Discovering, loading, cleaning, and modifying source data is where Power Query comes in. Using this, the... Data DiscoveryFind and connect to a myriad of data sources ...

Adam Aspin

2014-01-01T23:59:59.000Z

349

Online Load Balancing for Related Machines 1 (Revised Piotr Berman  

E-Print Network (OSTI)

s as follows: load(s; i) = 1 v i X s(j)=i p j ; Load(s) = max i load(s; i) It is easy to observe that findingOn­line Load Balancing for Related Machines 1 (Revised Version) Piotr Berman The Pennsylvania State of randomized algorithms for this problem. Key Words: on­line algorithm, load balancing, related machines

Karpinski, Marek

350

Loads Providing Ancillary Services: Review of International Experience  

E-Print Network (OSTI)

Load Following)Imbalance Management (Load Following) Energy Imbalanceload participation in ancillary service markets, we offer the following

Heffner, Grayson

2008-01-01T23:59:59.000Z

351

SPEAK UP, EPPING! COMMUNITY PROFILE  

E-Print Network (OSTI)

SPEAK UP, EPPING! COMMUNITY PROFILE REPORT Epping, New Hampshire April 14, 2007 #12;TABLE ............................................................................................. 21 6. Community Services, Facilities and Utilities........................................................................................................................... 38 1. Natural Resources & Environment 2. Communication 3. Infrastructure & Public Safety 4

New Hampshire, University of

352

Profile of Alec J. Jeffreys  

Science Journals Connector (OSTI)

Profile of Alec J. Jeffreys 10.1073/pnas.0603953103 Nick Zagorski As one of the great contributors to modern genetics...the forensic sciences. That achievement alone is worthy of merit, contributing to Jeffreys' receiving three high distinctions...

Nick Zagorski

2006-01-01T23:59:59.000Z

353

Neuropsychological Profile of Stuttering Children  

Science Journals Connector (OSTI)

The purpose of this study was to analyze the cognitive profile of stuttering children. A sample of 290 children was ... classified as stutterers. In general, performance in stuttering children was similar to the ...

Alfredo Ardila; Mnica Rosselli

2000-06-01T23:59:59.000Z

354

Energy Consumption Profile for Energy  

E-Print Network (OSTI)

317 Chapter 12 Energy Consumption Profile for Energy Harvested WSNs T. V. Prabhakar, R Venkatesha.............................................................................................318 12.2 Energy Harvesting ...................................................................................318 12.2.1 Motivations for Energy Harvesting...............................................319 12

Langendoen, Koen

355

Vibration of Tethered Microstructure Profilers  

Science Journals Connector (OSTI)

Although loosely tethered turbulence profilers have many advantages, they are prone to resonant vibrations at frequencies in the dissipation range when they are falling rapidly or when the tether is strummed. Using the Advanced Microstructure ...

Jack B. Miller; M. C. Gregg; Vernon W. Miller; Gordon L. Welsh

1989-12-01T23:59:59.000Z

356

JOBAID-ACCESSING AND MODIFYING TALENT PROFILE  

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

The purpose of this job aid is to guide users through the step-by-step process of accessing their talent profiles, adding information to their profiles, and editing existing talent profile...

357

The Promise of Load Balancing the Parameterization of Moist Convection Using a Model Data Load Index  

Science Journals Connector (OSTI)

The parameterization of physical processes in atmospheric general circulation models contributes to load imbalances among individual processors of message-passing distributed-multiprocessor systems. Load imbalances increase the overall time to ...

S. P. Muszala; D. A. Connors; J. J. Hack; G. Alaghband

2006-04-01T23:59:59.000Z

358

Load Forecast For use in Resource Adequacy  

E-Print Network (OSTI)

p g Monthly employment data for 1995-2012 from Bureau of Labor Statistics. H l Di S i I d l d d f Loads 1995-2012 employment 7) Estimate 84 sets of Daily Temperature Sensitive Loads Using 1928 regional employment 8) Adjust for Embedded and Target Conservation amounts Factor s for each day #12;Input

359

Load Management DSM: Past, Present & Future  

E-Print Network (OSTI)

Load Management has grown in acceptance over the past several decades as a reliable means to provide a demand-side resource of demand capacity. This paper first reviews the significant break-throughs of load management technology then sets the stage...

Gardner, E.

1994-01-01T23:59:59.000Z

360

Thermionic converter in load-switching mode  

SciTech Connect

An electrical equivalent circuit is proposed for a thermionic electrogenerating element. It is suitable for calculation of transients in load-switching mode. Formulas are given for estimating circuit parameters. A sample numerical calculation is given for the transient between no-load and short-circuit regimes. The results may be employed to identify experimental data in the frequency domain.

Mendel'baum, M.A.; Es'kov, V.D.

1983-01-01T23:59:59.000Z

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


361

1997 Pacific Northwest Loads and Resources Study.  

SciTech Connect

The 1997 White Book is presented in two documents: (1) this summary of Federal system and Pacific Northwest region loads and resources; and (2) a technical appendix detailing the loads and resources for each major Pacific Northwest generating utility. Data detailing Pacific Northwest non-utility generating (NUG) resources is also available upon request. This analysis updates the 1996 pacific Northwest Loads and Resources Study, published in December 1996. In this loads and resources study, resource availability is compared with a medium forecast of electricity consumption. This document analyzes the Pacific Northwest`s projected loads and available generating resources in two parts: (1) the loads and resources of the Federal system, for which BPA is the marketing agency; and (2) the larger Pacific Northwest regional power system which includes loads and resources in addition to the Federal system. This study presents the Federal system and regional analyses for the medium load forecast. This analysis projects the yearly average energy consumption and resource availability for Operating Years (OY) 1998--99 through 2007--08.

United States. Bonneville Power Administration.

1997-12-01T23:59:59.000Z

362

Effects of dynamic conditions and sheave efficiency on hook load, derrick load, and line tension  

E-Print Network (OSTI)

EFFECTS OF DYNAMIC CONDITIONS AND SHEAVE EFFICIENCY ON HOOK LOAD, DERRICK LOAD, AND LINE TENSION A Thesis by GREGORY ROBERT LUKE Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... for the degree of MASTER OF SCIENCE May 1991 Major Subject: Petroleum Engineering EFFECTS OF DYNAMIC CONDITIONS AND SHEAVE EFFICIENCY ON HOOK LOAD, DERRICK LOAD, AND LINE TENSION A Thesis by GREGORY ROBERT LUKE Approved as to style and content by: Hans...

Luke, Gregory Robert

1991-01-01T23:59:59.000Z

363

Appears in Computer Architecture Letters, Volume 12 (2010) SMT-Directory: Efficient Load-Load Ordering for SMT  

E-Print Network (OSTI)

-thread "read" bit to every data cache line. When a load executes, it sets the bit corresponding to its threadAppears in Computer Architecture Letters, Volume 12 (2010) SMT-Directory: Efficient Load-Load, TSO, and PC enforce load-load ordering, requiring that loads from any single thread appear to occur

Roth, Amir

364

Combi Systems for Low Load homes  

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

text styles text styles Combi Systems for Low Load Homes Center for Energy and Environment, NorthernSTAR, Ben Schoenbauer * Low load homes are more common than ever. * Typical space heating and DHW equipment have capacities larger than necessary * A single heating plant could provide high efficiency heat at lower costs, increased durability and improved combustion safety Context Technical Approach * A condensing water heater and hydronic air handler will used to provide space and water heating loads in almost 300 weatherized homes. * System specifications, sizing, and installation optimization guidelines were all developed. * Contractor capability was developed in MN market, but may not be developed in all local. 4 Recommended Guidance * Determine peak load on system: - Space heating design load (ie 40,000 Btu/hr)

365

Scaling of load in communications networks  

Science Journals Connector (OSTI)

We show that the load at each node in a preferential attachment network scales as a power of the degree of the node. For a network whose degree distribution is p(k)?k??, we show that the load is l(k)?k? with ?=??1, implying that the probability distribution for the load is p(l)?1/l2 independent of ?. The results are obtained through scaling arguments supported by finite size scaling studies. They contradict earlier claims, but are in agreement with the exact solution for the special case of tree graphs. Results are also presented for real communications networks at the IP layer, using the latest available data. Our analysis of the data shows relatively poor power-law degree distributions as compared to the scaling of the load versus degree. This emphasizes the importance of the load in network analysis.

Onuttom Narayan and Iraj Saniee

2010-09-02T23:59:59.000Z

366

Time and Cognitive Load 1 Time and Cognitive Load in Working Memory  

E-Print Network (OSTI)

Time and Cognitive Load 1 Time and Cognitive Load in Working Memory Pierre Barrouillet*, Sophie Bourgogne Running head: Time and Cognitive Load Corresponding author: Pierre Barrouillet Pierre manuscript, published in "Journal of Experimental Psychology: Learning, Memory, and Cognition 33, 3 (2007

Paris-Sud XI, Université de

367

Blinded by the load: attention, awareness and the role of perceptual load  

Science Journals Connector (OSTI)

...while including novel data that demonstrate...between perceptual load and the fundamental...effects of perceptual load on visual detection...response gain, the data from each participant...Konstantinou, N. 2014 Data from: blinded by the load: attention, awareness...

2014-01-01T23:59:59.000Z

368

A literature survey on measuring energy usage for miscellaneous electric loads in offices and commercial buildings  

Science Journals Connector (OSTI)

Abstract This paper presents the current state of the art regarding work performed related to the electric energy consumption for Information and Communication Technologies (ICTs) and Miscellaneous Electric Loads (MELs), in office and commercial buildings. Techniques used for measuring the energy consumption of office plug loads, and efforts for saving energy by using this equipment more rationally and efficiently are identified and categorized. Popular methods and techniques for energy metering are discussed, together with efforts to classify and benchmark office equipment. Our study reveals that many issues are still open in this domain, including more accurate, diverse and meaningful energy audits for longer time periods, taking into account device profiles, occupant behavior and environmental context. Finally, there is a need for a global consensus on benchmarking and performance metrics, as well as a need for a coordinated worldwide activity for gathering, sharing, analyzing, visualizing and exposing all the silos of information relating to plug loads in offices and commercial buildings.

Andreas Kamilaris; Balaji Kalluri; Sekhar Kondepudi; Tham Kwok Wai

2014-01-01T23:59:59.000Z

369

IGFC response to initial fuel cell load for various syngas compositions  

SciTech Connect

The system response to an initial electric load of the fuel cell during the startup of a direct-fired fuel cell turbine power system was studied using the Hybrid Performance (Hyper) project hardware-based simulation facility at the U.S. Department of Energy, National Energy Technology Laboratory for a range of input fuel compositions. The facility was brought to a steady condition at a temperature deemed adequate to minimize stress on the fuel cell during the initial load transient. A 1D distributed fuel cell model operating in real-time was used to produce individual cell transient temperature profiles during the course of the load change. The process was conducted with humidified hydrogen, and then repeated with various syngas compositions representative of different gasifier technologies. The results provide insight into control strategy requirements for mitigation of expected fuel cell failure modes relevant to available gasifier technology.

Tucker, David [U.S DOE; Hughes, Dimitri O. [Georgia Institute of Technology; Haynes, Comas L. [Georgia Institute of Technology

2012-01-01T23:59:59.000Z

370

Modeling and life prediction methodology for titanium matrix composites subjected to mission profiles  

SciTech Connect

Titanium matrix composites (TMCs) are being evaluated as structural materials for elevated temperature applications in future generation hypersonic vehicles. In such applications, TMC components are subjected to complex thermomechanical loading profiles at various elevated temperatures. Therefore, thermomechanical fatigue (TMF) testing, using a simulated mission profile, is essential for evaluation and development of life prediction methodologies. The objective of the research presented in this paper was to evaluate the TMF response of the [0/90]{sub 2s} SCS-6/TIMETAL-21S subjected to a generic hypersonic flight profile and its portions with a temperature ranging from {minus}130 to 816 C. It was found that the composite modulus, prior to rapid degradation, had consistent values for all the profiles tested. The accumulated minimum strain was also found to be the same for all the profiles tested. A micromechanics-based analysis was used to predict the stress-strain response of the laminate and of the constituents in each ply during thermomechanical loading conditions by using only constituent properties as input. The fiber was modeled as elastic with transverse orthotropic and temperature-dependent properties. The matrix was modeled using a thermoviscoplastic constitutive relationship. In the analysis, the composite modulus degradation was assumed to result from matrix cracking and was modeled by reducing the matrix modulus. Fatigue lives of the composite subjected to the complex generic hypersonic flight profiles were well correlated using the predicted stress in 0{degree} fibers.

Mirdamadi, M. [Analytical Services and Materials Inc., Hampton, VA (United States); Johnson, W.S. [Georgia Inst. of Tech., Atlanta, GA (United States). School of Materials Science and Engineering

1996-12-31T23:59:59.000Z

371

Calculation of bed load based on the measured data of suspended load  

Science Journals Connector (OSTI)

This paper proposes a method for establishing both the velocity profile and concentration profile for suspended sediment based on measured data consisting of average velocity and average suspended ... addition, a...

Chang-Tai Tsai; Chih-Heng Tsai; Chun-Hung Weng

2010-12-01T23:59:59.000Z

372

Project Profile: Maintenance-Free Stirling Engine for High-Performance Dish CSP  

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

Infinia, under the CSP R&D FOA, is developing a 30 kW CSP system that utilizes a multi-cylinder, free-piston Stirling engine to achieve the goal LCOE of $0.07$0.10/kWh by 2015 and $0.05$0.07/kWh by 2020.

373

Variability of Load and Net Load in Case of Large Scale Distributed Wind Power  

SciTech Connect

Large scale wind power production and its variability is one of the major inputs to wind integration studies. This paper analyses measured data from large scale wind power production. Comparisons of variability are made across several variables: time scale (10-60 minute ramp rates), number of wind farms, and simulated vs. modeled data. Ramp rates for Wind power production, Load (total system load) and Net load (load minus wind power production) demonstrate how wind power increases the net load variability. Wind power will also change the timing of daily ramps.

Holttinen, H.; Kiviluoma, J.; Estanqueiro, A.; Gomez-Lazaro, E.; Rawn, B.; Dobschinski, J.; Meibom, P.; Lannoye, E.; Aigner, T.; Wan, Y. H.; Milligan, M.

2011-01-01T23:59:59.000Z

374

Dehumidification and cooling loads from ventilation air  

SciTech Connect

The importance of controlling humidity in buildings is cause for concern, in part, because of indoor air quality problems associated with excess moisture in air-conditioning systems. But more universally, the need for ventilation air has forced HVAC equipment (originally optimized for high efficiency in removing sensible heat loads) to remove high moisture loads. To assist cooling equipment and meet the challenge of larger ventilation loads, several technologies have succeeded in commercial buildings. Newer technologies such as subcool/reheat and heat pipe reheat show promise. These increase latent capacity of cooling-based systems by reducing their sensible capacity. Also, desiccant wheels have traditionally provided deeper-drying capacity by using thermal energy in place of electrical power to remove the latent load. Regardless of what mix of technologies is best for a particular application, there is a need for a more effective way of thinking about the cooling loads created by ventilation air. It is clear from the literature that all-too-frequently, HVAC systems do not perform well unless the ventilation air loads have been effectively addressed at the original design stage. This article proposes an engineering shorthand, an annual load index for ventilation air. This index will aid in the complex process of improving the ability of HVAC systems to deal efficiently with the amount of fresh air the industry has deemed useful for maintaining comfort in buildings. Examination of typical behavior of weather shows that latent loads usually exceed sensible loads in ventilation air by at least 3:1 and often as much as 8:1. A designer can use the engineering shorthand indexes presented to quickly assess the importance of this fact for a given system design. To size those components after they are selected, the designer can refer to Chapter 24 of the 1997 ASHRAE Handbook--Fundamentals, which includes separate values for peak moisture and peak temperature.

Harriman, L.G. III [Mason-Grant, Portsmouth, NH (United States); Plager, D. [Quantitative Decision Support, Portsmouth, NH (United States); Kosar, D. [Gas Research Inst., Chicago, IL (United States)

1997-11-01T23:59:59.000Z

375

Phenotype MicroArray Profiling  

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

MicroArray MicroArray Profiling of Zymomonas mobilis ZM4 Barry Bochner & Vanessa Gomez & Michael Ziman & Shihui Yang & Steven D. Brown Received: 22 May 2009 / Accepted: 26 October 2009 # The Author(s) 2009. This article is published with open access at Springerlink.com Abstract In this study, we developed a Phenotype MicroArray(tm) (PM) protocol to profile cellular phenotypes in Zymomonas mobilis, which included a standard set of nearly 2,000 assays for carbon, nitrogen, phosphorus and sulfur source utilization, nutrient stimulation, pH and osmotic stresses, and chemical sensitivities with 240 inhibitory chemicals. We observed two positive assays for C-source utilization (fructose and glucose) using the PM screen, which uses redox chemistry and cell respiration as a universal reporter to profile growth phenotypes in a high-throughput 96-well plate-based format.

376

Industry Profile | Department of Energy  

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

Industry Profile Industry Profile Industry Profile November 1, 2013 - 11:40am Addthis The largest energy consuming industrial sectors account for the largest share of CHP capacity; namely: Chemicals (30%), Petroleum Refining (17%), and Paper Products (14%). Other industrial sectors include: Commercial/Institutional (12%), Food (8%), Primary Metals (5%), Other Manufacturing (8%), and Other Industrial (6%). Combined heat and power (CHP)-sometimes referred to as cogeneration-involves the sequential process of producing and utilizing electricity and thermal energy from a single fuel. CHP is widely recognized to save energy and costs, while reducing carbon dioxide (CO2) and other pollutants. CHP is a realistic, near-term option for large energy efficiency improvements and significant CO2 reductions.

377

Mean and peak wind loads on heliostats  

SciTech Connect

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

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

1989-05-01T23:59:59.000Z

378

Synthesis of polyoxometalate-loaded epoxy composites  

DOE Patents (OSTI)

The synthesis of a polyoxometalate-loaded epoxy uses a one-step cure by applying an external stimulus to release the acid from the polyoxometalate and thereby catalyze the cure reaction of the epoxy resin. Such polyoxometalate-loaded epoxy composites afford the cured epoxy unique properties imparted by the intrinsic properties of the polyoxometalate. For example, polyoxometalate-loaded epoxy composites can be used as corrosion resistant epoxy coatings, for encapsulation of electronics with improved dielectric properties, and for structural applications with improved mechanical properties.

Anderson, Benjamin J

2014-10-07T23:59:59.000Z

379

gprof Profiling Tools | Argonne Leadership Computing Facility  

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

Tuning MPI on BG/Q Tuning and Analysis Utilities (TAU) HPCToolkit HPCTW mpiP gprof Profiling Tools Darshan PAPI BG/Q Performance Counters BGPM Openspeedshop Scalasca BG/Q DGEMM Performance Software & Libraries IBM References Intrepid/Challenger/Surveyor Tukey Eureka / Gadzooks Policies Documentation Feedback Please provide feedback to help guide us as we continue to build documentation for our new computing resource. [Feedback Form] gprof Profiling Tools Contents Introduction Profiling on the Blue Gene Enabling Profiling Collecting Profile Information Profiling Threaded Applications Using gprof Routine Level Flat Profile Line Level Flat Profile Call Graph Analysis Routine Execution Count List Annotated Source Listing Issues in Interpreting Profile Data Profiling Concepts Programs in Memory

380

Definition: Base Load | Open Energy Information  

Open Energy Info (EERE)

Load Load Jump to: navigation, search Dictionary.png Base Load The minimum amount of electric power delivered or required over a given period at a constant rate.[1] View on Wikipedia Wikipedia Definition Baseload (also base load, or baseload demand) is the minimum amount of power that a utility or distribution company must make available to its customers, or the amount of power required to meet minimum demands based on reasonable expectations of customer requirements. Baseload values typically vary from hour to hour in most commercial and industrial areas. Related Terms electricity generation, power, smart grid References ↑ Glossary of Terms Used in Reliability Standards An in Like Like You like this.Sign Up to see what your friends like. line Glossary Definition Retrieved from

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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

S-Band Loads for SLAC Linac  

SciTech Connect

The S-Band loads on the current SLAC linac RF system were designed, in some cases, 40+ years ago to terminate 2-3 MW peak power into a thin layer of coated Kanthal material as the high power absorber [1]. The technology of the load design was based on a flame-sprayed Kanthal wire method onto a base material. During SLAC linac upgrades, the 24 MW peak klystrons were replaced by 5045 klystrons with 65+ MW peak output power. Additionally, SLED cavities were introduced and as a result, the peak power in the current RF setup has increased up to 240 MW peak. The problem of reliable RF peak power termination and RF load lifetime required a careful study and adequate solution. Results of our studies and three designs of S-Band RF load for the present SLAC RF linac system is discussed. These designs are based on the use of low conductivity materials.

Krasnykh, A.; Decker, F.-J.; /SLAC; LeClair, R.; /INTA Technologies, Santa Clara

2012-08-28T23:59:59.000Z

382

Advancements in rapid load test data regression.  

E-Print Network (OSTI)

??Rate-dependent effects introduced during rapid and/or dynamic events have typically been oversimplified to compensate for deficiencies in present analyses. As load test results are generally (more)

Stokes, Michael Jeffrey

2006-01-01T23:59:59.000Z

383

LOAD SHEDDING IN DATA STREAM MANAGEMENT SYSTEMS  

Science Journals Connector (OSTI)

In this chapter, we focus on a fundamental problem that is central to a DSMS. Namely, we investigate the problem of load shedding during temporary overload periods. This problem... ...

Sharma Chakravarthy; Qingchun Jiang

2009-01-01T23:59:59.000Z

384

AMTEC Response to Changes in Resistive Loading  

Science Journals Connector (OSTI)

An important aspect of electric power supply systems is their inherent response time to rapid changes in loading demands. This presentation reviews the experimental response of an Alkali Metal Thermal Electric Converter (AMTEC) system when switched from open circuit to stable resistive loads. Our data show a nominal 35?Watt AMTEC converter responded rapidly throughout the power curve. Response times from open circuit to delivering 90% of peak DC current were within 0.25 milliseconds to 0.85 milliseconds for a range of electrically resistive loads at several typical AMTEC operational temperatures. Such response times to load changes suggest that AMTEC may be suitable as a primary power supply or backup power supply for critical space applications.

Robert W. Fletcher; Thomas K. Hunt

2003-01-01T23:59:59.000Z

385

Reducing Cache Traffic and Energy with Macro Data Load  

E-Print Network (OSTI)

Reducing Cache Traffic and Energy with Macro Data Load Lei Jin Sangyeun Cho Department of Computer data load, an efficient mechanism to enhance loaded value reuse. A macro data load brings (MVRT) shows the significantly increased reuse opportunities provided by macro data load. We also

Cho, Sangyeun

386

Load apparatus and method for bolt-loaded compact tension test specimen  

DOE Patents (OSTI)

A bolt-loaded compact tension test specimen load apparatus includes: (a) a body having first and second opposing longitudinal ends, the first end comprising an externally threaded portion sized to be threadedly received within the test specimen threaded opening; (b) a longitudinal loading rod having first and second opposing longitudinal ends, the loading rod being slidably received in a longitudinal direction within the body internally through the externally threaded portion and slidably extending longitudinally outward of the body first longitudinal end; (c) a force sensitive transducer slidably received within the body and positioned to engage relative to the loading rod second longitudinal end; and (d) a loading bolt threadedly received relative to the body, the loading bolt having a bearing end surface and being positioned to bear against the transducer to forcibly sandwich the transducer between the loading bolt and loading rod. Also disclosed is a method of in situ determining applied force during crack propagation in a bolt-loaded compact tension test specimen. 6 figs.

Buescher, B.J. Jr.; Lloyd, W.R.; Ward, M.B.; Epstein, J.S.

1997-02-04T23:59:59.000Z

387

Load apparatus and method for bolt-loaded compact tension test specimen  

DOE Patents (OSTI)

A bolt-loaded compact tension test specimen load apparatus includes: a) a body having first and second opposing longitudinal ends, the first end comprising an externally threaded portion sized to be threadedly received within the test specimen threaded opening; b) a longitudinal loading rod having first and second opposing longitudinal ends, the loading rod being slidably received in a longitudinal direction within the body internally through the externally threaded portion and slidably extending longitudinally outward of the body first longitudinal end; c) a force sensitive transducer slidably received within the body and positioned to engage relative to the loading rod second longitudinal end; and d) a loading bolt threadedly received relative to the body, the loading bolt having a bearing end surface and being positioned to bear against the transducer to forcibly sandwich the transducer between the loading bolt and loading rod. Also disclosed is a method of in situ determining applied force during crack propagation in a bolt-loaded compact tension test specimen.

Buescher, Jr., Brent J. (Idaho Falls, ID); Lloyd, W. Randolph (Idaho Falls, ID); Ward, Michael B. (Idaho Falls, ID); Epstein, Jonathan S. (Idaho Falls, ID)

1997-01-01T23:59:59.000Z

388

Central Appalachia: Coal industry profile  

SciTech Connect

Central Appalachia, the most complex and diverse coal-producing region in the United States, is also the principal source of very low sulfur coal in the East. This report provides detailed profiles of companies and facilities responsible for about 90% of the area's production, conveying a unique view of the aggregate industry as well as its many parts.

McMahan, R.L.; Kendall, L.K. (Resource Data International, Inc., Boulder, CO (USA))

1991-05-01T23:59:59.000Z

389

Microfluidics and Nanoscale Research Profile  

E-Print Network (OSTI)

Microfluidics and Nanoscale Science Research Profile Our research group is engaged in a broad range of activities in the general area of microfluidics and nanoscale science. At a primary level, our interest that when compared to macroscale tech- nology, microfluidic systems engender a number of distinct advantages

390

Turfgrass Disease Profiles Brown Patch  

E-Print Network (OSTI)

Turfgrass Disease Profiles Brown Patch Richard Latin, Professor of Plant Pathology Brown patch to algae and moss infestation. Even mild brown patch outbreaks can spoil the appearance of golf greens and perennial ryegrass) also may sustain damage from brown patch infection. Disease Characteristics and Symptom

391

MODELING OF CHANGING ELECTRODE PROFILES  

SciTech Connect

A model for simulating the transient behavior of solid electrodes undergoing deposition or dissolution has been developed. The model accounts for ohmic drop, charge transfer overpotential, and mass transport limitations. The finite difference method, coupled with successive overrelaxation, was used as the basis of the solution technique. An algorithm was devised to overcome the computational instabilities associated with the calculations of the secondary and tertiary current distributions. Simulations were performed on several model electrode profiles: the sinusoid, the rounded corner, and the notch. Quantitative copper deposition data were obtained in a contoured rotating cylinder system, Sinusoidal cross-sections, machined on stainless steel cylinders, were used as model geometries, Kinetic parameters for use in the simulation were determined from polarization curves obtained on copper rotating cylinders, These parameters, along with other physical property and geometric data, were incorporated in simulations of growing sinusoidal profiles. The copper distributions on the sinusoidal cross-sections were measured and found to compare favorably with the simulated results. At low Wagner numbers the formation of a slight depression at the profile peak was predicted by the simulation and observed on the profile. At higher Wagner numbers, the simulated and experimental results showed that the formation of a depression was suppressed. This phenomenon was shown to result from the competition between ohmic drop and electrode curvature.

Prentice, Geoffrey Allen

1980-12-01T23:59:59.000Z

392

PO. 254 Control of Power Train Loads  

E-Print Network (OSTI)

Abstract summary Variable loads along the power train are the primary cause attributed to the failure of gears, bearings, and other mechanical components. The concept of anticipatory control applied to a wind power train is presented. This new approach to power train load management is based on the data reflecting the current status of the power train. The model driving the optimization of the power train loads considers four different objectives, including minimization of the torque variability and power maximization. A software tool for power train load management is presented. This new approach to power train load control is based on the data reflecting the current status of the power train. Such data is collected by a typical SCADA system. The model driving the optimization of the power train loads considers four different objectives, including minimization of the torque variability and power maximization. Details of the model that is applicable to different turbines are presented Objectives Goal: Transform a wind a farm into a wind power plant Example objectives: ? Minimization of the torque ramp rate ? Maximization of the power produced ? Maximization of the power quality Modify the shape of the power curve Methods Data mining/Knowledge discovery

Andrew Kusiak

393

The engineering of doxorubicin-loaded liposome-quantum dot hybrids for cancer theranostics  

Science Journals Connector (OSTI)

Many studies have recently attempted to develop multifunctional nanoconstructs by integrating the superior fluorescence properties of quantum dots (QD) with therapeutic capabilities into a single vesicle for cancer theranostics. Liposome-quantum dot (L-QD) hybrid vesicles have shown promising potential for the construction of multifunctional nanoconstructs for cancer imaging and therapy. To fulfil such a potential, we report here the further functionalization of L-QD hybrid vesicles with therapeutic capabilities by loading anticancer drug doxorubicin (Dox) into their aqueous core. L-QD hybrid vesicles are first engineered by the incorporation of TOPO-capped, CdSe/ZnS QD into the lipid bilayers of DSPC:Chol:DSPE-PEG2000, followed by Dox loading using the pH-gradient technique. The loading efficiency of Dox into L-QD hybrid vesicles is achieved up to 97%, comparable to liposome control. All these evidences prove that the incorporation of QD into the lipid bilayer does not affect Dox loading through the lipid membrane of liposomes using the pH-gradient technique. Moreover, the release study shows that Dox release profile can be modulated simply by changing lipid composition. In conclusion, the Dox-loaded L-QD hybrid vesicles presented here constitute a promising multifunctional nanoconstruct capable of transporting combinations of therapeutic and diagnostic modalities.

Bowen Tian (???); Wafa' T. Al-Jamal; Kostas Kostarelos

2014-01-01T23:59:59.000Z

394

Modeling and life prediction methodology for Titanium Matrix Composites subjected to mission profiles  

SciTech Connect

Titanium matrix composites (TMC) are being evaluated as structural materials for elevated temperature applications in future generation hypersonic vehicles. In such applications, TMC components are subjected to complex thermomechanical loading profiles at various elevated temperatures. Therefore, thermomechanical fatigue (TMF) testing, using a simulated mission profile, is essential for evaluation and development of life prediction methodologies. The objective of the research presented in this paper was to evaluate the TMF response of the (0/90)2s SCS-6/Timetal-21S subjected to a generic hypersonic flight profile and its portions with a temperature ranging from -130 C to 816 C. It was found that the composite modulus, prior to rapid degradation, had consistent values for all the profiles tested. A micromechanics based analysis was used to predict the stress-strain response of the laminate and of the constituents in each ply during thermomechanical loading conditions by using only constituent properties as input. The fiber was modeled as elastic with transverse orthotropic and temperature dependent properties. The matrix was modeled using a thermoviscoplastic constitutive relation. In the analysis, the composite modulus degradation was assumed to result from matrix cracking and was modeled by reducing the matrix modulus. Fatigue lives of the composite subjected to the complex generic hypersonic flight profile were well correlated using the predicted stress in 0 degree fibers.

Mirdamadi, M.; Johnson, W.S.

1994-08-01T23:59:59.000Z

395

Power System Load Forecasting Based on EEMD and ANN  

Science Journals Connector (OSTI)

In order to fully mine the characteristics of load data and improve the accuracy of power system load forecasting, a load forecasting model based on Ensemble Empirical Mode ... is proposed in this paper. Firstly,...

Wanlu Sun; Zhigang Liu; Wenfan Li

2011-01-01T23:59:59.000Z

396

Effect of palladium loaded activated carbons on hydrogen storage  

Science Journals Connector (OSTI)

Pd-loaded high surface area activated carbon (BAC-Pd) was produced from bamboo by carbonization and activation using potassium hydroxide with subsequent loading of palladium. The palladium loaded onto BACs appear...

Masaki Ohno; Nami Okamura; Tomohiro Kose; Takashi Asada

2012-12-01T23:59:59.000Z

397

General solutions for thermopiezoelectrics with various holes under thermal loading  

E-Print Network (OSTI)

induced by thermal loads. The loads may be uniform remote heat ¯ow, point heat source and temperature elastic plate with an hole of various shapes subjected to remote uniform mechanical loading. For plane

Qin, Qinghua

398

Definition: Electrical Profiling Configurations | Open Energy Information  

Open Energy Info (EERE)

Profiling Configurations Profiling Configurations Jump to: navigation, search Dictionary.png Electrical Profiling Configurations Electrical profiling is a DC resistivity survey which aims to trace lateral variations in the apparent resistivity structure of the subsurface. Traditionally, electrical profiling provides qualitative information of relative apparent resistivity values in order to detect anomalous geological features.[1] Also Known As Electrical mapping References ↑ http://www.amazon.com/Principles-Electric-Borehole-Geophysics-Geochemistry/dp/0444529942 Ret LikeLike UnlikeLike You like this.Sign Up to see what your friends like. rieved from "http://en.openei.org/w/index.php?title=Definition:Electrical_Profiling_Configurations&oldid=596184" Category: Definitions

399

The derivation of structural usage profiles for vehicles from failure statistics  

Science Journals Connector (OSTI)

A methodology is presented to derive a statistical fatigue loading profile of the total population of users of a vehicle model, from failure data recorded on the same or a previous model. The method is based on fitting a bivariate probability density function on normalised failure data. This is radically more economic than existing methods. Reasonable accuracy could be achieved, even if the failures represent only a small fraction of the total population. The two-parameter usage profile determined in this way offers a powerful approach to predict failures or derive statistically based durability test or design requirements.

Johann Wannenburg; P. Stephan Heyns

2008-01-01T23:59:59.000Z

400

Local Soot Loading Distribution in Cordierite Diesel Particulate...  

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

Local Soot Loading Distribution in Cordierite Diesel Particulate Filters by Dynamic Neutron Radiography Local Soot Loading Distribution in Cordierite Diesel Particulate Filters by...

Note: This page contains sample records for the topic "kwh load profiles" 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

Thermal Cycling Combined with Dynamic Mechanical Load: Preliminary...  

Office of Environmental Management (EM)

Load: Preliminary Report This PowerPoint presentation summarizes the efforts of the team led by ESPEC Corp. to investigate thermal cycling combined with dynamic mechanical load, a...

402

Load Shedding in Data Stream Management Systems Using Application Semantics  

Science Journals Connector (OSTI)

Data Stream Management Systems (DSMSs) process highly ... literature, including capacity planning, scheduling, and load shedding. Existing load shedding approaches drop tuples either randomly or based on the char...

Raman Adaikkalavan

2012-01-01T23:59:59.000Z

403

Characterization of Dynamic Loads on Solar Modules with Respect...  

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

Characterization of Dynamic Loads on Solar Modules with Respect to Fracture of Solar Cells Characterization of Dynamic Loads on Solar Modules with Respect to Fracture of Solar...

404

The Development of a Small Engine Based Accelerated Ash Loading...  

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

Accelerated Ash Loading Protocol The Development of a Small Engine Based Accelerated Ash Loading Protocol Presentation given at DEER 2006, August 20-24, 2006, Detroit, Michigan....

405

Transmission Reliability "Load as a Resource" Peer Review Materials...  

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

Transmission Reliability "Load as a Resource" Peer Review Materials Now Available Transmission Reliability "Load as a Resource" Peer Review Materials Now Available September 25,...

406

Used Nuclear Fuel Loading and Structural Performance Under Normal...  

Office of Environmental Management (EM)

Used Nuclear Fuel Loading and Structural Performance Under Normal Conditions of Transport - Modeling, Simulation and Experimental Integration RD&D Plan Used Nuclear Fuel Loading...

407

A stochastic framework for the grid integration of wind power using flexible load approach  

Science Journals Connector (OSTI)

Abstract Wind power integration has always been a key research area due to the green future power system target. However, the intermittent nature of wind power may impose some technical and economic challenges to Independent System Operators (ISOs) and increase the need for additional flexibility. Motivated by this need, this paper focuses on the potential of Demand Response Programs (DRPs) as an option to contribute to the flexible operation of power systems. On this basis, in order to consider the uncertain nature of wind power and the reality of electricity market, a Stochastic Network Constrained Unit Commitment associated with DR (SNCUCDR) is presented to schedule both generation units and responsive loads in power systems with high penetration of wind power. Afterwards, the effects of both price-based and incentive-based \\{DRPs\\} are evaluated, as well as DR participation levels and electricity tariffs on providing a flexible load profile and facilitating grid integration of wind power. For this reason, novel quantitative indices for evaluating flexibility are defined to assess the success of \\{DRPs\\} in terms of wind integration. Sensitivity studies indicate that DR types and customer participation levels are the main factors to modify the system load profile to support wind power integration.

E. Heydarian-Forushani; M.P. Moghaddam; M.K. Sheikh-El-Eslami; M. Shafie-khah; J.P.S. Catalo

2014-01-01T23:59:59.000Z

408

A comparison of measured wind park load histories with the WISPER and WISPERX load spectra  

SciTech Connect

The blade-loading histories from two adjacent Micon 65/13 wind turbines are compared with the variable-amplitude test-loading histories known as the WISPER and WISPERX spectra. These standardized loading sequences were developed from blade flapwise load histories taken from nine different horizontal-axis wind turbines operating under a wide range of conditions in Europe. The subject turbines covered a broad spectrum of rotor diameters, materials, and operating environments. The final loading sequences were developed as a joint effort of thirteen different European organizations. The goal was to develop a meaningful loading standard for horizontal-axis wind turbine blades that represents common interaction effects seen in service. In 1990, NREL made extensive load measurements on two adjacent Micon 65/13 wind turbines in simultaneous operation in the very turbulent environment of a large wind park. Further, before and during the collection of the loads data, comprehensive measurements of the statistics of the turbulent environment were obtained at both the turbines under test and at two other locations within the park. The trend to larger but lighter wind turbine structures has made an understanding of the expected lifetime loading history of paramount importance. Experience in the US has shown that the turbulence-induced loads associated with multi-row wind parks in general are much more severe than for turbines operating individually or within widely spaced environments. Multi-row wind parks are much more common in the US than in Europe. In this paper we report on our results in applying the methodology utilized to develop the WISPER and WISPERX standardized loading sequences using the available data from the Micon turbines. While the intended purpose of the WISPER sequences were not to represent a specific operating environment, we believe the exercise is useful, especially when a turbine design is likely to be installed in a multi-row wind park.

Kelley, N.D.

1995-01-01T23:59:59.000Z

409

Sonic Load History Recorder. I. Feasibility Study  

Science Journals Connector (OSTI)

The acoustic loads to which an aircraft is subjected during its lifetime must be known for structural?fatigue analysis in aircraft design. The Sonic Load History Recorder senses filters smooths and records some measure of the length of time the sound pressure has spent in a given level band. Sound?pressure?level distributions over long periods of time are calculated for a present?day aircraft from engine?operating parameters operational characteristics of the aircraft and from ambient atmospheric conditions. The requirements for a device which is designed to provide a useful description of acoustic loads at a point on an operational aircraft are developed on the basis of the SPL histories and fatigue criteria. [This work was supported under U. S. Air Force Contract AF 33(616)?7789.

N. Doelling; D. Noiseux

1962-01-01T23:59:59.000Z

410

Independent review of estimated load reductions for PJM's small customer load response pilot project  

E-Print Network (OSTI)

water heater (EWH) load control program operated as part of PJM Interconnections Demand ResponseDemand Response Economic and Emergency Load Response Programs Electric Thermal Storage Electric Water Heaterwater pumps and electric thermal storage space heaters. The CSP is also participating in PJMs pilot Demand Response

Heffner, G.; Moezzi, M.; Goldman, C.

2004-01-01T23:59:59.000Z

411

Reconstruction of a wind turbine's endured load spectrum using a short-time load measurement  

E-Print Network (OSTI)

Reconstruction of a wind turbine's endured load spectrum using a short-time load measurement Abstract Wind turbines (WT) are normally designed for a service life (SL) of 20 years. In Germany, over safety. 1 Introduction A wind turbine (WT) is normally designed, tested and certified for a design life

Berlin,Technische Universität

412

Modality Effects on Cognitive Load and Performance in High-Load Information Presentation  

E-Print Network (OSTI)

INTRODUCTION Intelligent human-computer interfaces are often multimodal, i.e. the human-computer communications into the modality planning procedure for systems that support high-load human-computer interaction. Author Keywords-load information presenta- tion scenario. Mainly based on modality-related psychology theories, we selected five

Theune, Mariët

413

Benchmarking optimization software with performance profiles  

E-Print Network (OSTI)

Abstract: We propose performance profiles -- probability distribution functions for a performance metric -- as a tool for benchmarking and comparing optimization...

Elizabeth Dolan

414

Taking a Bite out of Lighting Loads  

E-Print Network (OSTI)

Take a Bite Out of Lighting Loads With LEDs Stephen Williams Toshiba Sales Support Manager ESL-KT-13-12-34 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 Some LED Advantages Less electricity ? 18w LED... = 100w PAR38 No maintenance for years ? 50,000 LED vs.10,000 CFL Improved light quality ? 80 CRI LED vs. 25 CRI HPS Reduce HVAC cooling load Advanced control options ESL-KT-13-12-34 CATEE 2013: Clean Air Through Energy Efficiency Conference, San...

Williams, S.

2013-01-01T23:59:59.000Z

415

On-line Load Balancing for Related Machines 1 Piotr Berman  

E-Print Network (OSTI)

s and Load(s), the load of entire schedule s as follows: load(s;i) = 1 vi X s(j)=i pj; Load(s) = maxi loadOn-line Load Balancing for Related Machines 1 (Revised Version) Piotr Berman The Pennsylvania State for this problem. Key Words: on-line algorithm, load balancing, related machines, competitive ratio 1A preliminary

Eckmiller, Rolf

416

Duet: Cloud Scale Load Balancing with Hardware and Rohan Gandhi  

E-Print Network (OSTI)

that scale using a distributed data plane that runs on commodity servers. Software load balancers offer low overlooked resource in the data center networks � the switches themselves. We show how to embed the load-DC traffic. This traffic volume induces heavy load on both data plane and control plane of the load balancer

Zhang, Ming

417

Randomized Load Balancing by Joining and Splitting Bins James Aspnes  

E-Print Network (OSTI)

Consider the following load balancing scenario: a certain amount of work load is distributed among a setRandomized Load Balancing by Joining and Splitting Bins James Aspnes Yitong Yin § 1 Introduction, one of the existing machines gives some of its load to the new machine; and upon a departure

Aspnes, James

418

Stochastic service load simulation for engineering structures  

Science Journals Connector (OSTI)

...at the design stage of an engineering structure, both global and...is relevant to other core engineering industry sectors. This paper...simulated Jack-up offshore load history (JOSH) developed for use...fatigue|fracture mechanics|engineering structures|

2001-01-01T23:59:59.000Z

419

Economic load dispatch using improved harmony search  

Science Journals Connector (OSTI)

This paper presents the use of the improved harmony search method for solving economic load dispatch problems. The harmony search method mimics a jazz improvisation process by musicians in order to seek a fantastic state of harmony. To assess the searching ... Keywords: adaptive tabu search, economic dispatch, evolutionary programming, genetic algorithms, particle swarm optimization

T. Ratniyomchai; A. Oonsivilai; P. Pao-La-Or; T. Kulworawanichpong

2010-04-01T23:59:59.000Z

420

Load Tilt and Body Tilt at Bidston  

Science Journals Connector (OSTI)

......to Tidal Load,Memoirs of the Imperial Marine Observatory, 1, No. 1, 1922 June...that the possibilities of error due to wear in the cone and cup should be made known...1932 September. Memoirs of the Imperial Marine Observatory, I, No. I, 1922June. the......

A. T. Doodson; R. H. Corkan

1934-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "kwh load profiles" 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

1995 Pacific Northwest Loads and Resources Study.  

SciTech Connect

The study establishes the planning basis for supplying electricity to customers. The study presents projections of regional and Federal system load and resource capabilities, and serves as a benchmark for annual BPA determinations made pursuant to the 1981 regional power sales contracts.

United States. Bonneville Power Administration.

1995-12-01T23:59:59.000Z

422

Valve for fuel pin loading system  

DOE Patents (OSTI)

A cyclone valve surrounds a wall opening through which cladding is projected. An axial valve inlet surrounds the cladding. Air is drawn through the inlet by a cyclone stream within the valve. An inflatable seal is included to physically engage a fuel pin subassembly during loading of fuel pellets.

Christiansen, D.W.

1984-01-01T23:59:59.000Z

423

Valve for fuel pin loading system  

DOE Patents (OSTI)

A cyclone valve surrounds a wall opening through which cladding is projected. An axial valve inlet surrounds the cladding. Air is drawn through the inlet by a cyclone stream within the valve. An inflatable seal is included to physically engage a fuel pin subassembly during loading of fuel pellets.

Christiansen, David W. (Kennewick, WA)

1985-01-01T23:59:59.000Z

424

EQPT: Ecological Quality Profiling Tool  

SciTech Connect

EQPT uses"Habitat Value Units" to assess the ecological quality of selected areas. A Habitat Value Unit is equal to one unit area of pristine or desired habitat. The proximity of waste reduces the value of the habitat. The GIS uses a proximity-based iterative algorithm to aggregate similarly classified waste sites. A variable size buffering algorithm is then used to approximate the effects of the waste on the environmental quality of the surrounding areas. The user designated areas are analyzed, and the resulting quality profiles are presented quantitatively in tabular summaries and graphically as grids on vector base maps.

Tzemos, Spyridon (BATTELLE (PACIFIC NW LAB)); Sackschewsky, Michael R. (BATTELLE (PACIFIC NW LAB)); Bilyard, Gordon R. (BATTELLE (PACIFIC NW LAB))

2002-08-21T23:59:59.000Z

425

Texas Crop Profile: Sweet Potatoes  

E-Print Network (OSTI)

is between 120 to 135 days. Texas Crop Profile S W E E T P O T A T O E S E-22 3-00 Prepared by Rodney L. Holloway, Kent D. Hall and Dudley T. Smith 1 In collaboration with James V. Robinson, George Philley and Marvin Baker 2 1 Extension Specialist, Extension... Command will not. Rodney L. Holloway Extension Specialist 2488 TAMU College Station, Texas 77843-2488 979-845-3849 rholloway@tamu.edu Kent D. Hall Extension Associate 2488 TAMU College Station, Texas 77843-2488 979-845-3849 kd-hall@tamu.edu Dudley Smith...

Hall, Kent D.; Holloway, Rodney L.; Smith, Dudley

2000-04-12T23:59:59.000Z

426

2003 Pacific Northwest Loads and Resources Study.  

SciTech Connect

The Pacific Northwest Loads and Resources Study (White Book), which is published annually by the Bonneville Power Administration (BPA), establishes one of the planning bases for supplying electricity to customers. The White Book contains projections of regional and Federal system load and resource capabilities, along with relevant definitions and explanations. The White Book also contains information obtained from formalized resource planning reports and data submittals including those from individual utilities, the Northwest Power and Conservation Council (Council), and the Pacific Northwest Utilities Conference Committee (PNUCC). The White Book is not an operational planning guide, nor is it used for determining BPA revenues, although the database that generates the data for the White Book analysis contributes to the development of BPA's inventory and ratemaking processes. Operation of the Federal Columbia River Power System (FCRPS) is based on a set of criteria different from that used for resource planning decisions. Operational planning is dependent upon real-time or near-term knowledge of system conditions that include expectations of river flows and runoff, market opportunities, availability of reservoir storage, energy exchanges, and other factors affecting the dynamics of operating a power system. In this loads and resources study, resource availability is compared to an expected level of total retail electricity consumption. The forecasted annual energy electricity retail load plus contract obligations are subtracted from the sum of the projected annual energy capability of existing resources and contract purchases to determine whether BPA and/or the region will be surplus or deficit. Surplus energy is available when resources are greater than loads. This energy could be marketed to increase revenues. Deficits occur when resources are less than loads. Energy deficits could be met by any combination of the following: better-than-critical water conditions, demand-side management and conservation programs, permanent loss of a load (i.e., due to economic conditions or closures), additional contract purchases, and/or new generating resources. The loads and resources analysis in this study simulates the operation of the power system under the Pacific Northwest Coordination Agreement (PNCA). The PNCA defines the planning and operation of seventeen U.S. Pacific Northwest utilities and other parties with generating facilities within the region's hydroelectric (hydro) system. The hydroregulation study used for the 2003 White Book incorporates measures from the National Oceanographic and Atmospheric Administration Fisheries (NOAA Fisheries) Biological Opinion dated December 2000, and the U.S. Fish and Wildlife Service's 2000 Biological Opinion (2000 FCRPS BiOps) for the Snake River and Columbia River projects. These measures include: (1) Increased flow augmentation for juvenile fish migrations in the Snake and Columbia rivers in the spring and summer; (2) Mandatory spill requirements at the Lower Snake and Columbia dams to provide for non-turbine passage routes for juvenile fish migrants; and (3) Additional flows for Kootenai River white sturgeon in the spring. The hydroregulation criteria for this analysis includes: an updated Detailed Operation Plan for Treaty reservoirs for Operating Year (OY) 2004, updated PNCA planning criteria for OY 2003, and revised juvenile fish bypass spill levels for 2000 FCRPS BiOps implementation. The 2003 White Book is presented in two documents: (1) this summary document of Federal system and PNW region loads and resources, and (2) a technical appendix which presents regional loads, grouped by major PNW utility categories, and detailed contract and resource information. The technical appendix is available only in electronic form. Individual customer information regarding marketer contracts is not detailed due to confidentiality agreements. The 2003 White Book analysis updates the December 2002 White Book. This analysis projects the yearly average energy consumption and resource availability

United States. Bonneville Power Administration.

2003-12-01T23:59:59.000Z

427

Independent review of estimated load reductions for PJM's small customer load response pilot project  

SciTech Connect

This study describes the results of a low-cost approach used to measure reported load reductions from a residential electric water heater (EWH) load control program operated as part of PJM Interconnection's Demand Response small customer pilot program. Lawrence Berkeley National Laboratory (LBNL) conducted this independent review of the engineering estimates for EWH load control reported by a Curtailment Service Provider (CSP) at PJM's request. LBNL employed low-cost measurement and verification (M&V) approaches that utilized existing interval metering equipment to monitor results for a series of load control tests. The CSP collected hourly load data for two substations and several hundred households over a six-week period in October and November 2003. During this time period, the CSP operated its electric water heater load control program during pre-specified test periods in the morning, afternoon and early evening. LBNL then analyzed substation and premise-level data from these tests in order to verify the diversified demand reductions claimed by the CSP for customers participating in the EWH load control program. We found that the observed load reductions for the premise-level data aggregated over all households in the two participating electric cooperatives were, respectively, 40 percent-60 percent less and 3 percent less-10 percent higher than the estimated diversified demand reduction values assumed by the CSP, depending on whether observed or normalized results are considered. We also analyzed sub-station level data and found that the observed load reductions during the test periods were significantly lower than expected, although confounding influences and operational problems signifiogram during pre-specified test periods in the morning, afternoon and early evening. LBNL then analyzed substation and premise-level data from these tests in order to verify the diversified demand reductions claimed by the CSP for customers participating in the EWH load control program. We found that the observed load reductions for the premise-level data aggregated over all households in the two participating electric cooperatives were, respectively, 40 percent-60 percent less and 3 percent less-10 percent higher than the estimated diversified demand reduction values assumed by the CSP, depending on whether observed or normalized results are considered. We also analyzed sub-station level data and found that the observed load reductions during the test periods were significantly lower than expected, although confounding influences and operational problems significantly limit our ability to differentiate between control-related and non-control related differences in substation-level load shape data. The usefulness and accuracy of the results were hampered by operational problems encountered during the measurement period as well as in sufficient number of load research grade interval meters at one cooperative. Given the larger sample size at one electric cooperative and more statistically-robust results, there is some basis to suggest that the Adjusted Diversified Demand Factor (ADDF) values used by the CSP somewhat over-state the actual load reductions. Given the results and limitations of the M&V approach as implemented, we suggest several options for PJM to consider: (1) require load aggregators participating in ISODR programs to utilize formal PURPA-compliant load research samples in their M&V plans, and (2) continue developing lower cost M&V approaches for mass market load control programs that incorporate suggested improvements described in this study.

Heffner, G.; Moezzi, M.; Goldman, C.

2004-06-01T23:59:59.000Z

428

Radiation Tests for a Single-GEM Loaded Gaseous Detector  

E-Print Network (OSTI)

We report on the systematic study of a single-gas-electron-multiplication (GEM) loaded gaseous detector developed for precision measurements of high-energy particle beams and dose-verification measurements. In the present study, a 256-channel prototype detector with an active area of 16$\\times$16 cm$^{2}$, operated in a continuous current-integration-mode signal-processing method, was manufactured and tested with x rays emitted from a 70-kV x-ray generator and 43-MeV protons provided by the MC50 proton cyclotron at the Korea Institute of Radiological and Medical Science (KIRAMS). The amplified detector response was measured for the x rays with an intensity of about 5$\\times$10$^{6}$ Hz cm$^{-2}$. The linearity of the detector response to the particle flux was examined and validated by using 43-MeV proton beams. The non-uniform development of the amplification for the gas electrons in space was corrected by applying proper calibration to the channel responses of the measured beam-profile data. We concluded fro...

Lee, Kyong Sei; Kim, Sang Yeol; Park, Sung Keun

2014-01-01T23:59:59.000Z

429

Fuel loading and homogeneity analysis of HFIR design fuel plates loaded with uranium silicide fuel  

SciTech Connect

Twelve nuclear reactor fuel plates were analyzed for fuel loading and fuel loading homogeneity by measuring the attenuation of a collimated X-ray beam as it passed through the plates. The plates were identical to those used by the High Flux Isotope Reactor (HFIR) but were loaded with uranium silicide rather than with HFIR`s uranium oxide fuel. Systematic deviations from nominal fuel loading were observed as higher loading near the center of the plates and underloading near the radial edges. These deviations were within those allowed by HFIR specifications. The report begins with a brief background on the thermal-hydraulic uncertainty analysis for the Advanced Neutron Source (ANS) Reactor that motivated a statistical description of fuel loading and homogeneity. The body of the report addresses the homogeneity measurement techniques employed, the numerical correction required to account for a difference in fuel types, and the statistical analysis of the resulting data. This statistical analysis pertains to local variation in fuel loading, as well as to ``hot segment`` analysis of narrow axial regions along the plate and ``hot streak`` analysis, the cumulative effect of hot segment loading variation. The data for all twelve plates were compiled and divided into 20 regions for analysis, with each region represented by a mean and a standard deviation to report percent deviation from nominal fuel loading. The central regions of the plates showed mean values of about +3% deviation, while the edge regions showed mean values of about {minus}7% deviation. The data within these regions roughly approximated random samplings from normal distributions, although the chi-square ({chi}{sup 2}) test for goodness of fit to normal distributions was not satisfied.

Blumenfeld, P.E.

1995-08-01T23:59:59.000Z

430

A Note on Online Load Balancing for Related Machines  

E-Print Network (OSTI)

(j) that will execute it. We define the load of a machine i and the load of entire schedule s as follows: load(s; i) = 1A Note on On­line Load Balancing for Related Machines Piotr Berman \\Lambda Marek Karpinski y that differ in speed but are related in the following sence: a job of size p requires time p=v on a machine

Eckmiller, Rolf

431

Field Trial of a Low-Cost, Distributed Plug Load Monitoring System  

SciTech Connect

Researchers have struggled to inventory and characterize the energy use profiles of the ever-growing category of so-called miscellaneous electric loads (MELs) because plug-load monitoring is cost-prohibitive to the researcher and intrusive to the homeowner. However, these data represent a crucial missing link to our understanding of how homes use energy, and we cannot control what we do not understand. Detailed energy use profiles would enable the nascent automated home energy management (AHEM) industry to develop effective control algorithms that target consumer electronics and other plug loads. If utility and other efficiency programs are to incent AHEM devices, they need large-scale datasets that provide statistically meaningful justification of their investments by quantifying the aggregate energy savings achievable. To address this need, we have investigated a variety of plug-load measuring devices available commercially and tested them in the laboratory to identify the most promising candidates for field applications. The scope of this report centers around the lessons learned from a field validation of one proof-of-concept system, called Smartenit (formerly SimpleHomeNet). The system was evaluated based on the rate of successful data queries, reliability over a period of days to weeks, and accuracy. This system offers good overall performance when deployed with up to ten end nodes in a residential environment, although deployment with more nodes and in a commercial environment is much less robust. We conclude that the current system is useful in selected field research projects, with the recommendation that system behavior is observed over time.

Auchter, B.; Cautley, D.; Ahl, D.; Earle, L.; Jin, X.

2014-03-01T23:59:59.000Z

432

The Temperature Sensitivity of the Residential Load and Commercial Building Load  

SciTech Connect

This paper presents a building modeling approach to quickly quantify climate change impacts on energy consumption, peak load, and load composition of residential and commercial buildings. This research focuses on addressing the impact of temperature changes on the building heating and cooling load in 10 major cities across the Western United States and Canada. A building simulation software are first used to quantify the hourly energy consumption of different building types by end-use and by vintage. Then, the temperature sensitivities are derived based on the climate data inputs.

Lu, Ning; Taylor, Zachary T.; Jiang, Wei; Correia, James; Leung, Lai R.; Wong, Pak C.

2009-07-26T23:59:59.000Z

433

City of Hubbard, Ohio (Utility Company) | Open Energy Information  

Open Energy Info (EERE)

Hubbard Hubbard Place Ohio Utility Id 8949 Utility Location Yes Ownership M NERC Location RFC NERC RFC Yes ISO MISO Yes Activity Buying Transmission Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Commercial General Service-Large Commercial Commercial General Service-Small Commercial Industrial General Service-Large Industrial Industrial General Service-Small Industrial Residential Load Management Residential Residential Non load management Residential Average Rates Residential: $0.0802/kWh Commercial: $0.0760/kWh Industrial: $0.0932/kWh References

434

Detailed heat balance analysis of the thermal load variations depending on the blind location and glazing type  

Science Journals Connector (OSTI)

Abstract Nowadays, curtain wall is the norm, due to which there is an increase in direct solar gain and heat loss through the window inside the building, causing massive thermal load. Use of blinds has been one of the best counter measures for this. In this study, EnergyPlus modeling has been used to measure the effect of reflectance of blind on heating and cooling load when the blind is located inside or outside for winter and summer condition. Modeling showed that in summer, as blind reflectance increased, cooling load decreased in case of internal blind and increased in case of external blind whereas in winter, the opposite was true for heating load. However, solar energy transmittance increased proportionately with the increase in reflectance of blind irrespective of position in either season. In addition, the heating load profiles under different window material compositions were determined mainly by the U-value variations, which were directly connected to the infrared and convective heat flows from the window into the space. SHGC also showed effect on the heating load to some extent by affecting the solar transmittance and convective and radiant heat flows from the blind into the space.

Yeo Beom Yoon; Dong Soo Kim; Kwang Ho Lee

2014-01-01T23:59:59.000Z

435

Interval analysis applied to the maximum loading point of electric power systems considering load data uncertainties  

Science Journals Connector (OSTI)

Abstract This paper proposes a simple and efficient power flow method to calculate, in an interval manner, the main variables corresponding to the maximum loading point, under load data uncertainties. The resulting interval nonlinear system of equations is solved using Krawczyk method. The proposed methodology is implemented in the Matlab environment using the Intlab toolbox. Results are compared with those obtainable by Monte Carlo simulations. IEEE 30 bus system and a South-southeastern Brazilian network are used to validate the proposed methodology.

L.E.S. Pereira; V.M. da Costa

2014-01-01T23:59:59.000Z

436

Project Profile: Innovative Application of Maintenance-Free Phase-Change Thermal Energy Storage for Dish Systems  

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

Infinia, under the Thermal Storage FOA, is developing a thermal energy storage (TES) system that, when combined with Infinia's dish-Stirling system, can achieve DOE's CSP cost goals of $0.07/kWh by 2015 for intermediate power and 5/kWh by 2020 for baseload power.

437

1996 Pacific Northwest Loads and Resources Study.  

SciTech Connect

The Pacific Northwest Loads and Resources Study (White Book) is published annually by BPA and establishes the planning basis for supplying electricity to customers. It serves a dual purpose. First, the White Book presents projections of regional and Federal system load and resource capabilities, along with relevant definitions and explanations. Second, the White Book serves as a benchmark for annual BPA determinations made pursuant to the 1981 regional power sales contracts. Specifically, BPA uses the information in the White Book for determining the notice required when customers request to increase or decrease the amount of power purchased from BPA. Aside from these purposes, the White Book is used for input to BPA`s resource planning process. The White Book compiles information obtained from several formalized resource planning reports and data submittals, including those from the Northwest Power Planning Council (Council) and the Pacific Northwest Utilities Conference Committee (PNUCC). 11 figs., 12 tabs.

United States. Bonneville Power Administration.

1996-12-01T23:59:59.000Z

438

NREL: Vehicle Ancillary Loads Reduction - Integrated Modeling  

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

Integrated Modeling Integrated Modeling NREL's Vehicle Ancillary Loads Reduction (VALR) team predicts the impact of advanced vehicle cooling technologies before testing by using an integrated modeling process. Evaluating the heat load on a vehicle under real world conditions is a difficult task. An accepted method to evaluate passenger compartment airflow and heat transfer is computational fluid dynamics. (CFD). Combining analytical models with CFD provides a powerful tool to assist industry both on current vehicles and on future design studies. Flow chart showing the vehicle integrated modeling process which considers solar radiation, air conditioning, and vehicles with CAD, glazing, cabin thermal/fluid, and thermal comfort modeling tools. Results are provided for fuel economy, tailpipe emissions and occupant thermal comfort.

439

Definition: Direct Load Control Device | Open Energy Information  

Open Energy Info (EERE)

Load Control Device Load Control Device Jump to: navigation, search Dictionary.png Direct Load Control Device A remotely controllable switch that can turn power to a load or appliance on or off. Such a device could also be used to regulate the amount of power that a load can consume. Direct load control devices can be operated by a utility or third party energy provider to reduce a customer's energy demand at certain times.[1] Related Terms power, load References ↑ https://www.smartgrid.gov/category/technology/direct_load_control_device [[Ca LikeLike UnlikeLike You like this.Sign Up to see what your friends like. tegory: Smart Grid Definitionssmart grid,smart grid, |Template:BASEPAGENAME]]smart grid,smart grid, Retrieved from "http://en.openei.org/w/index.php?title=Definition:Direct_Load_Control_Device&oldid=502631

440

Seismic considerations in the evaluation of temporary loads  

SciTech Connect

Temporary loads in nuclear power facilities can result from a number of activities including special one time operating conditions, repair and upgrade conditions, and ALARA requirements for operation, inspection and maintenance. Many times evaluation of these loadings includes their consideration in conjunction with other design basis loadings such as normal loads and extreme event loads including earthquake loadings. At times this combination with design basis extreme loads, such as earthquake, results in predicted structural demands which exceed the design basis capacity. Many times a major contributor to this demand prediction is the earthquake loadings. Discussed in this paper are analytical methods, probabilistic considerations, and earthquake experienced based evaluations which can be applied to reduce the earthquake demand for short term temporary loadings.

Adams, T.M. [Stevenson and Associates, Cleveland, OH (United States); Stevenson, J.D.

1996-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "kwh load profiles" 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

SHOCKWAVE PROFILE AND BAUSCHINGER EFFECT IN DEPLETED URANIUM  

Science Journals Connector (OSTI)

Dynamic damage evolution in materials is of growing interest in particular the role of defect structure on material strength during a dynamic experiment. Many studies in the past have seen strong correlations between the shockwave profile and the defect structure during dynamic experiments such as quasi?elastic release behavior. Bauschinger effect is a microstructurally controlled process in which a material displays a change in stress?strain characterisitics due to a change in the defect structure. Studies on depleted uranium have revealed indications of Bauschinger effect being a mechanism present during quasi?static experiments which could be a result of the large amount of twinning observed in these materials. As work continues to improve strength models it becomes imperitive to understand the role of defect structure on the properties of materials under dynamic conditions. The study reported here is an observation of the release wave behavior in depleted uranium that first undergoes compressive shock loading followed by a reversal of the loading direction upon release.

D. D. Koller; G. T. Gray III; R. S. Hixson

2007-01-01T23:59:59.000Z

442

ARM - Campaign Instrument - s-band-profiler  

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

govInstrumentss-band-profiler govInstrumentss-band-profiler Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign Instrument : NOAA S-band (2835 Mhz) Profiler (S-BAND-PROFILER) Instrument Categories Cloud Properties, Atmospheric Profiling Campaigns CRYSTAL-FACE [ Download Data ] Off Site Campaign : various, including non-ARM sites, 2002.06.26 - 2002.08.01 Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers [ Download Data ] Southern Great Plains, 2011.04.22 - 2011.06.06 Tropical Warm Pool - International Cloud Experiment (TWP-ICE) [ Download Data ] Tropical Western Pacific, 2006.01.21 - 2006.02.13 Primary Measurements Taken The following measurements are those considered scientifically relevant. Refer to the datastream (netcdf) file headers for the list of all available

443

Methods for Analyzing Electric Load Shape and its Variability  

SciTech Connect

Current methods of summarizing and analyzing electric load shape are discussed briefly and compared. Simple rules of thumb for graphical display of load shapes are suggested. We propose a set of parameters that quantitatively describe the load shape in many buildings. Using the example of a linear regression model to predict load shape from time and temperature, we show how quantities such as the load?s sensitivity to outdoor temperature, and the effectiveness of demand response (DR), can be quantified. Examples are presented using real building data.

Price, Philip

2010-05-12T23:59:59.000Z

444

Definition: Electromagnetic Profiling Techniques | Open Energy Information  

Open Energy Info (EERE)

Electromagnetic Profiling Techniques Electromagnetic Profiling Techniques Jump to: navigation, search Dictionary.png Electromagnetic Profiling Techniques Electromagnetic profiling techniques map lateral variations in subsurface resistivity.[1] View on Wikipedia Wikipedia Definition Exploration geophysics is the applied branch of geophysics which uses surface methods to measure the physical properties of the subsurface Earth, along with the anomalies in these properties, in order to detect or infer the presence and position of ore minerals, hydrocarbons, geothermal reservoirs, groundwater reservoirs, and other geological structures. Exploration geophysics is the practical application of physical methods (such as seismic, gravitational, magnetic, electrical and electromagnetic) to measure the physical properties of rocks, and in particular, to detect

445

Project Profile: Forecasting and Influencing Technological Progress...  

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

Forecasting and Influencing Technological Progress in Solar Energy Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Logos of the University of...

446

Project Profile: Regenerative Carbonate-Based Thermochemical...  

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

Regenerative Carbonate-Based Thermochemical Energy Storage System for Concentrating Solar Power Project Profile: Regenerative Carbonate-Based Thermochemical Energy Storage System...

447

Project Profile: Concentrated Solar Thermoelectric Power | Department...  

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

Solar Thermoelectric Power Project Profile: Concentrated Solar Thermoelectric Power MIT logo The Rohsenow-Kendall Heat Transfer Lab at Massachusetts Institute of...

448

Plant Energy Profiler | Department of Energy  

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

Energy Profiler Pumping System Assessment Tool Process Heating Assessment and Survey Tool Steam System Modeler Advanced Manufacturing Home Key Activities Research &...

449

TAU Portable Performance Profiling Tools Sameer Shende  

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

Laboratory, Los Alamos National Laboratory sameer@cs.uoregon.edu Tuning and Analysis Utilities http:www.acl.lanl.govtau TAU Profiling Team Members (In alphabetical order) Peter...

450

SLUDGE TREATMENT PROJECT COST COMPARISON BETWEEN HYDRAULIC LOADING AND SMALL CANISTER LOADING CONCEPTS  

SciTech Connect

The Sludge Treatment Project (STP) is considering two different concepts for the retrieval, loading, transport and interim storage of the K Basin sludge. The two design concepts under consideration are: (1) Hydraulic Loading Concept - In the hydraulic loading concept, the sludge is retrieved from the Engineered Containers directly into the Sludge Transport and Storage Container (STSC) while located in the STS cask in the modified KW Basin Annex. The sludge is loaded via a series of transfer, settle, decant, and filtration return steps until the STSC sludge transportation limits are met. The STSC is then transported to T Plant and placed in storage arrays in the T Plant canyon cells for interim storage. (2) Small Canister Concept - In the small canister concept, the sludge is transferred from the Engineered Containers (ECs) into a settling vessel. After settling and decanting, the sludge is loaded underwater into small canisters. The small canisters are then transferred to the existing Fuel Transport System (FTS) where they are loaded underwater into the FTS Shielded Transfer Cask (STC). The STC is raised from the basin and placed into the Cask Transfer Overpack (CTO), loaded onto the trailer in the KW Basin Annex for transport to T Plant. At T Plant, the CTO is removed from the transport trailer and placed on the canyon deck. The CTO and STC are opened and the small canisters are removed using the canyon crane and placed into an STSC. The STSC is closed, and placed in storage arrays in the T Plant canyon cells for interim storage. The purpose of the cost estimate is to provide a comparison of the two concepts described.

GEUTHER J; CONRAD EA; RHOADARMER D

2009-08-24T23:59:59.000Z

451

Stochastic model for electrical loads in Mediterranean residential buildings: Validation and applications  

Science Journals Connector (OSTI)

Abstract A major issue in modelling the electrical load of residential building is reproducing the variability between dwellings due to the stochastic use of different electrical equipment. In that sense and with the objective to reproduce this variability, a stochastic model to obtain load profiles of household electricity is developed. The model is based on a probabilistic approach and is developed using data from the Mediterranean region of Spain. A detailed validation of the model has been done, analysing and comparing the results with Spanish and European data. The results of the validation show that the model is able to reproduce the most important features of the residential electrical consumption, especially the particularities of the Mediterranean countries. The final part of the paper is focused on the potential applications of the models, and some examples are proposed. The model is useful to simulate a cluster of buildings or individual households. The model allows obtaining synthetic profiles representing the most important characteristics of the mean dwelling, by means of a stochastic approach. The inputs of the proposed model are adapted to energy labelling information of the electric devices. An example case is presented considering a dwelling with high performance equipment.

Joana Ortiz; Francesco Guarino; Jaume Salom; Cristina Corchero; Maurizio Cellura

2014-01-01T23:59:59.000Z

452

Controlling a rabbet load and air/oil seal temperatures in a turbine  

SciTech Connect

During a standard fired shutdown of a turbine, a loaded rabbet joint between the fourth stage wheel and the aft shaft of the machine can become unloaded causing a gap to occur due to a thermal mismatch at the rabbet joint with the bearing blower turned on. An open or unloaded rabbet could cause the parts to move relative to each other and therefore cause the rotor to lose balance. If the bearing blower is turned off during a shutdown, the forward air/oil seal temperature may exceed maximum design practice criterion due to "soak-back." An air/oil seal temperature above the established maximum design limits could cause a bearing fire to occur, with catastrophic consequences to the machine. By controlling the bearing blower according to an optimized blower profile, the rabbet load can be maintained, and the air/oil seal temperature can be maintained below the established limits. A blower profile is determined according to a thermodynamic model of the system.

Schmidt, Mark Christopher (Niskayuna, NY)

2002-01-01T23:59:59.000Z

453

Parent and Teacher Report: Comparing Results from the Sensory Profile and the Sensory Profile School Companion  

E-Print Network (OSTI)

OBJECTIVE. This study investigated the similarities and differences between parent and teacher report on the Sensory Profile and the Sensory Profile School Companion (School Companion). METHOD. Using data gathered during ...

Clark, Jessica Saiter

2008-08-13T23:59:59.000Z

454

Building Energy Software Tools Directory: HAP System Design Load  

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

HAP System Design Load HAP System Design Load HAP System Design Load logo. Provides the load estimating and system design features found in its popular cousin � Carrier�s Hourly Analysis Program (HAP). By focusing on system design features, the HAP System Design Load program serves as a simpler, more efficient tool for those users only interested in system design; energy simulation features are omitted. Like the HAP program, HAP System Design Load provides the ease of use of a Windows-based graphical user interface and the computing power of modern 32-bit software. HAP System Design Load uses a system-based approach to HVAC load estimating. This approach tailors sizing procedures and results to the specific type of system being considered. A wide variety of equipment types

455

Power Load Forecasting Using Data Mining and Knowledge Discovery Technology  

Science Journals Connector (OSTI)

Considering the importance of the peak load to the dispatching and management of the system, the error of peak load is proposed in this paper as criteria ... proposes a systemic framework that attempts to used data

Yongli Wang; Dongxiao Niu; Yakun Wang

2010-01-01T23:59:59.000Z

456

Data Mining in Load Forecasting of Power System  

Science Journals Connector (OSTI)

This project applies Data Mining technology to the prediction of electric power system load forecast. It proposes a mining program of electric power load forecasting data based on the similarity of time series .....

Guang Yu Zhao; Yan Yan; Chun Zhou Zhao

2013-01-01T23:59:59.000Z

457

Data dependence path reduction with tunneling load instructions  

Science Journals Connector (OSTI)

The technique for reducing the length of the data dependence path is presented. This technique,...tunneling-load..., utilizes the register specifier buffer in order to hide the load latency, and thus reduces the ...

Toshinori Sato

1997-01-01T23:59:59.000Z

458

Data Management with Load Balancing in Distributed Computing  

Science Journals Connector (OSTI)

This paper reviews existing data management schemes and presents a design and development of a data management scheme with load balancing in a distributed computing. This scheme defines a variety of degree of load

Jong Sik Lee

2004-01-01T23:59:59.000Z

459

Bed load equation evaluation based on alluvial river data, India  

Science Journals Connector (OSTI)

The rate of bed load transport in weight per unit width for ... material has been computed by collecting the field data of Tapi River, in the monsoon season ... of this paper is to estimate the bed load carried b...

S. M. Yadav; B. K. Samtani

2008-11-01T23:59:59.000Z

460

Critical loads of acid deposition on Scottish soils  

Science Journals Connector (OSTI)

The impact of acid deposition, attributable to sulphur and nitrogen pollutants, on the soils of Scotland has been analysed using a critical loads approach. The critical load of a soil (as an indicator of ecolo...

Simon J. Langan; M. J. Wilson

1994-05-01T23:59:59.000Z

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


461

Laboratory testing of structures under dynamic loads: an introductory review  

Science Journals Connector (OSTI)

...research-article Theme Issue Dynamic testing of structures compiled by M. S. Williams Laboratory testing of structures under dynamic loads: an...introduces and reviews the theme of laboratory testing of structures under dynamic loads. The...

2001-01-01T23:59:59.000Z

462

Effective Load Management for the City of College Station  

E-Print Network (OSTI)

specifications for a computer controlled system called Supervisory Control and Data Acquisition (SCADA), which will be utilized in automatic system control to achieve maximum pos- sible load reduction during peak load periods. THE TOP TEN COFIIIERCIAL...

Hecox, O. D.; Bauer, V.

1985-01-01T23:59:59.000Z

463

Modeling and Estimating Current Harmonics of Variable Electronic Loads  

E-Print Network (OSTI)

This paper develops a model for relating input current harmonic content to real power consumption for variable electronic loads, specifically for loads' actively controlled inverters energized by an uncontrolled rectification ...

Wichakool, Warit

464

Y-12 Finishes Initial HEUMF Loading Ahead of Schedule | National...  

National Nuclear Security Administration (NNSA)

Production Office NPO News Releases Y-12 Finishes Initial HEUMF Loading Ahead of Schedule Y-12 Finishes Initial HEUMF Loading Ahead of Schedule applicationmsword icon NR-01-10...

465

Load Management and Houston Lighting and Power Co.  

E-Print Network (OSTI)

Defining Load Management as influencing of customer loads in order to shift the time use of electric power and energy, encompasses a broad spectrum of activities at Houston Lighting & Power Company. This paper describes those activities by directing...

Drawe, R. G.; Ramsay, I. M.

1984-01-01T23:59:59.000Z

466

44-BWR WASTE PACKAGE LOADING CURVE EVALUATION  

SciTech Connect

The objective of this calculation is to evaluate the required minimum burnup as a function of initial boiling water reactor (BWR) assembly enrichment that would permit loading of spent nuclear fuel into the 44 BWR waste package configuration as provided in Attachment IV. This calculation is an application of the methodology presented in ''Disposal Criticality Analysis Methodology Topical Report'' (YMP 2003). The scope of this calculation covers a range of enrichments from 0 through 5.0 weight percent (wt%) U-235, and a burnup range of 0 through 40 GWd/MTU. This activity supports the validation of the use of burnup credit for commercial spent nuclear fuel applications. The intended use of these results will be in establishing BWR waste package configuration loading specifications. Limitations of this evaluation are as follows: (1) The results are based on burnup credit for actinides and selected fission products as proposed in YMP (2003, Table 3-1) and referred to as the ''Principal Isotopes''. Any change to the isotope listing will have a direct impact on the results of this report. (2) The results of 100 percent of the current BWR projected waste stream being able to be disposed of in the 44-BWR waste package with Ni-Gd Alloy absorber plates is contingent upon the referenced waste stream being sufficiently similar to the waste stream received for disposal. (3) The results are based on 1.5 wt% Gd in the Ni-Gd Alloy material and having no tuff inside the waste package. If the Gd loading is reduced or a process to introduce tuff inside the waste package is defined, then this report would need to be reevaluated based on the alternative materials.

J.M. Scaglione

2004-08-25T23:59:59.000Z

467

Application of release rate data to hazard load calculations  

Science Journals Connector (OSTI)

The author illustrates methods of applying heat, smoke and toxic gas release rate data to calculating fire hazard loading values.

Edwin E. Smith

1974-08-01T23:59:59.000Z

468

Liquefaction through expander for base load LNG  

SciTech Connect

New natural gas liquefaction process using turbo expander has been developed to improve process thermal efficiency. The new process consists of precooling section which uses refrigerant with shell and tube heat exchangers or brazed aluminum plate-fin exchangers or spool wound heat exchanger and liquefaction section by iso-entropic expander. As a result of design study, thermal efficiency of the new liquefaction process has been confirmed to be in the highest level compared with other liquefaction processes. Also, since the new liquefaction process is constructed with commonly available equipment in industry, it can be readily adapted to base load LNG plants of any capacity without requiring expensive and specially designed equipment.

Nakamura, Moritaka; Kikkawa, Yoshitsugi [Chiyoda Corp., Yokohama (Japan)

1998-12-31T23:59:59.000Z

469

A framework for nonparametric profile monitoring  

Science Journals Connector (OSTI)

Control charts have been widely used for monitoring the functional relationship between a response variable and some explanatory variable(s) (called profile) in various industrial applications. In this article, we propose an easy-to-implement framework ... Keywords: B-spline, Block bootstrap, Confidence band, Curve depth, Nonparametric profile monitoring

Shih-Chung Chuang; Ying-Chao Hung; Wen-Chi Tsai; Su-Fen Yang

2013-01-01T23:59:59.000Z

470

Research profiling for `standardization and innovation'  

Science Journals Connector (OSTI)

This paper addresses the profiling of research papers on `standardization and innovation'--exploring major topics and arguments in this field. Drawing on 528 papers retrieved from the database, Web of Science, we employed trend, factor, and clustering ... Keywords: Bibliometrics, Clustering analysis, Innovation, Publication analysis, Research profiling, Standardization, Taxonomy

Dong Geun Choi; Heesang Lee; Tae-Kyung Sung

2011-07-01T23:59:59.000Z

471

A PROFILE OF KENTUCKY MEDICAID MENTAL HEALTH  

E-Print Network (OSTI)

can be advanced--among patients, health care providers, and the community at large. This workA PROFILE OF KENTUCKY MEDICAID MENTAL HEALTH DIAGNOSES, 2000-2010 #12; #12; i A Profile of Kentucky Medicaid Mental Health Diagnoses, 20002010 BY Michael T. Childress

Hayes, Jane E.

472

Sibling competition and hunger increase allostatic load in spotted hyaenas  

Science Journals Connector (OSTI)

...probably increasing allostatic load in dominants [3]. Within-brood...competition [11] on allostatic load in twins of a free-ranging...reasons, we expect allostatic load measured by faecal glucocorticoid...males and 19 females). These data (see electronic supplementary...

2013-01-01T23:59:59.000Z

473

Chimaeric load among sympatric social bacteria increases with genotype richness  

Science Journals Connector (OSTI)

...contribute more to chimaeric load during development than...across chimaera treatments (data not shown). In some treatments...and C suffer chimaeric load (data not shown). This result...C to increase chimaeric load in the three-way mix...

2014-01-01T23:59:59.000Z

474

Dietary Insulin Load, Dietary Insulin Index, and Colorectal Cancer  

Science Journals Connector (OSTI)

...using national dietary data and the nutrient database...index and glycemic load values in the NIH-AARP...multivariate models (data not shown). After...intake of glycemic load did not change our...Management Service for data management. 1 Gapstur...status and post-load plasma glucose concentration...

Ying Bao; Katharina Nimptsch; Jeffrey A. Meyerhardt; Andrew T. Chan; Kimmie Ng; Dominique S. Michaud; Jennie C. Brand-Miller; Walter C. Willett; Edward Giovannucci; and Charles S. Fuchs

2010-12-01T23:59:59.000Z

475

Reduced Study Load Application Form International Students on Student Visa  

E-Print Network (OSTI)

in a standard load for the following reasons: Continued on next page #12;CRICOS Provider No. 00300K (NTReduced Study Load Application Form International Students on Student Visa CRICOS Provider No. 00300K (NT/VIC) | CRICOS Provider No. 03286A (NSW) Study Load Requirements International students

476

On the Minimum Load Coloring Problem --Extended Abtract--  

E-Print Network (OSTI)

# such that the maximum load, l # := max{r# , b #}, is minimized. In the following we shall skip the term ``maximumOn the Minimum Load Coloring Problem --Extended Abtract-- Nitin Ahuja 1 , Andreas Baltz 2 Abstract. Given a graph G = (V, E) with n vertices, m edges and maximum vertex degree #, the load

Doerr, Benjamin

477

Exploiting Home Automation Protocols for Load Monitoring in Smart Buildings  

E-Print Network (OSTI)

load con- sumes, e.g., to enable automated demand response. Al- though load monitoring and control, Sean Barker, Aditya Mishra, Prashant Shenoy, and Jeannie Albrecht University of Massachusetts Amherst@cs.williams.edu Abstract Monitoring and controlling electrical loads is crucial for demand-side energy management in smart

Massachusetts at Amherst, University of

478

Numerical Simulation of Wave Loads on Static Offshore Structures  

E-Print Network (OSTI)

Numerical Simulation of Wave Loads on Static Offshore Structures Hrvoje Jasak, Inno Gatin, Vuko Workshop, Cambridge, 30 July 2014 Numerical Simulation of Wave Loads on Static Offshore Structures ­ p. #12 of Wave Loads on Static Offshore Structures ­ p. #12;VOF Free Surface Flow Model Modelling of Free Surface

479

Asymptotics of cellular buckling close to the Maxwell load  

Science Journals Connector (OSTI)

...bifurcation parameter (load) and frequency are scaled in powers of , which then...solution at the Maxwell load. From the derivatives...coefficients of like powers of : O() : Lu1...and the Maxwell load PM is excellent...above numerical data leads us to make...

2001-01-01T23:59:59.000Z

480

Scaling of load in communications networks Onuttom Narayan1  

E-Print Network (OSTI)

that the load at each node in a preferential attachment network scales as a power of the degree of the node power-law degree distributions as compared to the scaling of the load versus degree. This emphasizes that the probability distribution for the load scales as p(l) 1/l with = 2.2. Subsequently, data for net- works

California at Santa Cruz, University of

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


481

Dynamic versus Static Load Balancing in a Pipeline Computation \\Lambda  

E-Print Network (OSTI)

­ ber of data sets is pipelined through a series of tasks and load balancing is performed­ mance and fully utilize the power of parallel machines the load of the computations must be distributedDynamic versus Static Load Balancing in a Pipeline Computation \\Lambda Anna Brunstrom brunstro

Simha, Rahul

482

PARAMETRIC MODELS FOR ESTIMATING WIND TURBINE FATIGUE LOADS FOR DESIGN  

E-Print Network (OSTI)

loads. #12;2 INTRODUCTION Design constraints for wind turbine structures fall into either extreme load1 PARAMETRIC MODELS FOR ESTIMATING WIND TURBINE FATIGUE LOADS FOR DESIGN Lance Manuel1 Paul S, TX 78712 2 Sandia National Laboratories, Wind Energy Technology Department, Albuquerque, NM 87185

Sweetman, Bert

483

TOF Profile function used at POWGEN  

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

TOF Profile function used at POWGEN: TOF Profile function used at POWGEN: Powgen uses a TOF profile function which is a variation on the standard profile function originally derived by VonDreele, Jorgensen and Windsor (VonDreele RB, Jorgensen JD and Windsor CG, "Rietveld Refinement with Spallation Neutron Powder Diffraction Data", J. Appl. Cryst. 15, 581 (1982). This function is implemented in GSAS (profile function 3, 4 & 5) and Fullprof NPROF 9 and is most applicable to diffractometers viewing ambient polyethylene or water moderators. The POWGEN diffractometer, however, views a poisoned cryogenic H 2 (liquid) moderator. The variation in peak shape and peak position with TOF (or d-spacing d) is calculated using a more complex function related to thermal and epithermal components of the neutron spectrum that was

484

Estimating the Effect of Domestic Load and Renewable Supply Variability on Battery Capacity Requirements for Decentralized Microgrids  

Science Journals Connector (OSTI)

Abstract Large battery banks are a commonly considered alternative for local storage of volatile energy supply in decentralized grid management. In this paper the hypothetical case of an isolated community of 15 houses with direct access to a nearby set of wind turbines and a backup grid connection (e.g. ex-urban hamlet) is being considered. The question arises as to what size of battery, relative to household average daily consumption, should be installed in order to avoid excessively fast aging of said battery bank, i.e. to avoid the need to replace it faster than standard expected battery lifetime. The basic technology of the batteries addressed in this study is lithium ion phosphate. A dynamic modeling process of aging is implemented, along with realistic wind power data and a stochastic model of domestic load, with variable morning/evening peaks, weekend and seasonal effects. It was found that simulations using domestic load profiles and variability predict a significant reduction in expected battery state of health, for comparable average loads, than standard load cycles used for industrial testing, and that increased variability in average domestic load has a minor effect on the speed of state of health reduction. Furthermore a region of high sensitivity to overall battery bank size can be observed, which subsides over approx. 200 hours of average household consumption.

Malte Thomann; Florin Popescu

2014-01-01T23:59:59.000Z

485

Dry coating of micronized API powders for improved dissolution of directly compacted tablets with high drug loading  

Science Journals Connector (OSTI)

Motivated by our recent study showing improved flow and dissolution rate of the active pharmaceutical ingredient (API) powders (20?m) produced via simultaneous micronization and surface modification through continuous fluid energy milling (FEM) process, the performance of blends and direct compacted tablets with high drug loading is examined. Performance of 50?m API powders dry coated without micronization is also considered for comparison. Blends of micronized, non-micronized, dry coated or uncoated API powders at 30, 60 and 70% drug loading, are examined. The results show that the blends containing dry coated API powders, even micronized ones, have excellent flowability and high bulk density compared to the blends containing uncoated API, which are required for direct compaction. As the drug loading increases, the difference between dry coated and uncoated blends is more pronounced, as seen in the proposed bulk density-FFC phase map. Dry coating led to improved tablet compactibility profiles, corresponding with the improvements in blend compressibility. The most significant advantage is in tablet dissolution where for all drug loadings, the t80 for the tablets with dry coated \\{APIs\\} was well under 5min, indicating that this approach can produce nearly instant release direct compacted tablets at high drug loadings.

Xi Han; Chinmay Ghoroi; Rajesh Dav

2013-01-01T23:59:59.000Z

486

SAPHIRE 8 Volume 7 - Data Loading  

SciTech Connect

The Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) is a software application developed for performing a complete probabilistic risk assessment (PRA) using a personal computer. SAPHIRE Version 8 is funded by the U.S. Nuclear Regulatory Commission and developed by the Idaho National Laboratory. This report is intended to assist the user to enter PRA data into the SAPHIRE program using the built-in MAR-D ASCII-text file data transfer process. Towards this end, a small sample database is constructed and utilized for demonstration. Where applicable, the discussion includes how the data processes for loading the sample database relate to the actual processes used to load a larger PRA models. The procedures described herein were developed for use with SAPHIRE Version 8. The guidance specified in this document will allow a user to have sufficient knowledge to both understand the data format used by SAPHIRE and to carry out the transfer of data between different PRA projects.

K. J. Kvarfordt; S. T. Wood; C. L. Smith; S. R. Prescott

2011-03-01T23:59:59.000Z

487

Experimental investigation and model validation of the heat flux profile in a 300MW CFB boiler  

Science Journals Connector (OSTI)

Abstract In this paper, systematic experimental investigation on the heat flux distribution inside the furnace of a 300MW CFB boiler was presented. Detailed experimental setup and measurement techniques were presented and a finite element method approach was applied to determine the heat flux. The heat flux profile on the rear wall along the horizontal direction shows a significant imbalance at different boiler loads. As a result of the non-uniform layout of the heating surfaces, which is the essential reason, as well as the imbalance and deviation of the temperature field, solid suspension density and solid flow rate, the central section of the furnace possesses higher heat flux distribution compared to the side sections. The heat flux is also found to increase with the increasing boiler load and decrease as the height increases. Heat flux near the roof, where the solid suspension density is rather small, is found to decrease remarkably revealing less heat absorption in this area. In addition, an empirical model of heat transfer coefficient is revised using the average data at different boiler loads. A mechanism heat transfer model based on the membrane water-wall configuration is proposed and validated with the heat flux profile obtained from the measurement. The model provides good accuracy for correlating 85% of the data within 10%.

Ruiqing Zhang; Hairui Yang; Nan Hu; Junfu Lu; Yuxin Wu

2013-01-01T23:59:59.000Z

488

Rotordynamic coefficients for a load-between-pad, flexible-pivot tilting pad bearing at high loads  

E-Print Network (OSTI)

The dynamic and static performance of a flexure-pivot tilting pad bearing is presented at a load between pad configuration for various load and speed combinations. A similar work performed on the same bearing at lower loads ranging from 0-1 MPa (0...

Hensley, John Eric

2006-10-30T23:59:59.000Z

489

A new generation of load sharing algorithms: the semi-adaptive load sharing algorithm  

E-Print Network (OSTI)

: Wael, Omar, Tamer, Ashraf and Hazem, who were always there for me. Your support and comfort have given me the strength to go through all the bad times. TABLE OF CONTENTS CHAPTER Page INTRODUCTION A. What is Load Sharing? B. Thesis Outline 2 4...

Morsy, Hazem Kamal

1997-01-01T23:59:59.000Z

490

Long-term Analysis of Gear Loads in Fixed Offshore Wind Turbines Considering Ultimate Operational Loadings  

Science Journals Connector (OSTI)

Abstract The long-term extreme value analysis of gear transmitted load due to the main shaft torque is presented. Two methods, the multibody simulations (MBS) and a simplified method, are demonstrated for the gear transmitted load calculation. The simplified method is verified by the MBS results. The long-term extreme value of the gear transmitted load for wind speeds from the cut-in to the cut-out values is calculated by the simplified method from the long-term distribution of the main shaft torque. Three statistical methods for long-term extreme value analysis of the main shaft torque in the offshore wind turbines are presented. They are then used to predict the extreme value of the gear transmitted load. An alternative approach, the design state or the environmental contour method is proposed and verified by the full long-term results. The methods are exemplified by a 5 MW gearbox case study. The results of this paper are the basis for further work in Ultimate Limit State (ULS) gear design.

Amir R. Nejad; Zhen Gao; Torgeir Moan

2013-01-01T23:59:59.000Z

491

Building Energy Software Tools Directory: QwickLoad  

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

QwickLoad QwickLoad QwickLoad logo QwickLoad uses the ASHRAE TFM (Transfer Function Method) algorithms combined with a screen interface that provides building load calculations. It includes a Duct Sizing Program and supports IP and SI units. QwickLoad Residential 7.0 provides heat gain and heat loss calculations for up to 10 zones. QwickLoad Commercial 7.0 provides heat gain and heat loss calculations for up to 500 zones. Zones and plenums can be added or deleted with one button click. Intuitive screens for entering building information. Default is automatically displayed. Construction types for roofs, walls, partitions, windows, shade types, and scheduling control. Complete air-conditioning and heating system control and supply, return, heating and cooling duct static pressure specification. Energy recovery ventilator can

492

Technical Assistance to ISO's and Grid Operators For Loads Providing  

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

Technical Assistance to ISO's and Grid Operators For Loads Technical Assistance to ISO's and Grid Operators For Loads Providing Ancillary Services To Enhance Grid Reliability Technical Assistance to ISO's and Grid Operators For Loads Providing Ancillary Services To Enhance Grid Reliability Project demonstrates and promotes the use of responsive load to provide ancillary services; helps ISOsand grid operators understand the resource and how best to apply it. Technical Assistance to ISO's and Grid Operators For Loads Providing Ancillary Services To Enhance Grid Reliability More Documents & Publications Loads Providing Ancillary Services: Review of International Experience 2012 Load as a Resource Program Peer Review New York Independent System Operator, Smart Grid RFI: Addressing Policy and Logistical Challenges.

493

The Load Distribution Problem in a Processor Ring Francis C.M. Lau  

E-Print Network (OSTI)

the load balancing procedure into the following phases: load measurement, calculation of load averageThe Load Distribution Problem in a Processor Ring Francis C.M. Lau Department of Computer Science picture of the system load and the average load, the load distribution problem is to find a suitable

Lau, Francis C.M.

494

The effects of shockwave profile shape and shock obliquity on spallation in Cu and Ta: kinetic and stress-state effects on damage evolution(u)  

SciTech Connect

Widespread research over the past five decades has provided a wealth of experimental data and insight concerning shock hardening and the spallation response of materials subjected to square-topped shock-wave loading profiles. Less quantitative data have been gathered on the effect of direct, in-contact, high explosive (HE)-driven Taylor wave (or triangular-wave) loading profile shock loading on the shock hardening, damage evolution, or spallation response of materials. Explosive loading induces an impulse dubbed a 'Taylor Wave'. This is a significantly different loading history than that achieved by a square-topped impulse in terms of both the pulse duration at a fixed peak pressure, and a different unloading strain rate from the peak Hugoniot state achieved. The goal of this research is to quantify the influence of shockwave obliquity on the spallation response of copper and tantalum by subjecting plates of each material to HE-driven sweeping detonation-wave loading and quantify both the wave propagation and the post-mortem damage evolution. This talk will summarize our current understanding of damage evolution during sweeping detonation-wave spallation loading in Cu and Ta and show comparisons to modeling simulations. The spallation responses of Cu and Ta are both shown to be critically dependent on the shockwave profile and the stress-state of the shock. Based on variations in the specifics of the shock drive (pulse shape, peak stress, shock obliquity) and sample geometry in Cu and Ta, 'spall strength' varies by over a factor of two and the details of the mechanisms of the damage evolution is seen to vary. Simplistic models of spallation, such as P{sub min} based on 1-D square-top shock data lack the physics to capture the influence of kinetics on damage evolution such as that operative during sweeping detonation loading. Such considerations are important for the development of predictive models of damage evolution and spallation in metals and alloys.

Gray, George T [Los Alamos National Laboratory

2010-12-14T23:59:59.000Z

495

Performance Profiles of Major Energy Producers 1993  

Gasoline and Diesel Fuel Update (EIA)

3) 3) Distribution Category UC-950 Performance Profiles of Major Energy Producers 1993 Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 Energy Information Administration/ Performance Profiles of Major Energy Producers 1993 ii This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. The information contained herein should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. Energy Information Administration/ Performance Profiles of Major Energy Producers 1993 iii The Financial Reporting System, 1977-1993 diskette is available from the Energy Information Administration.

496

Electromagnetic Profiling Techniques | Open Energy Information  

Open Energy Info (EERE)

Electromagnetic Profiling Techniques Electromagnetic Profiling Techniques Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Technique: Electromagnetic Profiling Techniques Details Activities (0) Areas (0) Regions (0) NEPA(0) Exploration Technique Information Exploration Group: Geophysical Techniques Exploration Sub Group: Electrical Techniques Parent Exploration Technique: Ground Electromagnetic Techniques Information Provided by Technique Lithology: Rock composition, mineral and clay content Stratigraphic/Structural: Detection of permeable pathways, fracture zones, faults Hydrological: Resistivity influenced by porosity, grain size distribution, permeability, fluid saturation, fluid type and phase state of the pore water Thermal: Resistivity influenced by temperature

497

Vertical Seismic Profiling | Open Energy Information  

Open Energy Info (EERE)

Vertical Seismic Profiling Vertical Seismic Profiling Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Technique: Vertical Seismic Profiling Details Activities (4) Areas (3) Regions (1) NEPA(0) Exploration Technique Information Exploration Group: Downhole Techniques Exploration Sub Group: Borehole Seismic Techniques Parent Exploration Technique: Borehole Seismic Techniques Information Provided by Technique Lithology: Rock unit density influences elastic wave velocities. Stratigraphic/Structural: Structural geology- faults, folds, grabens, horst blocks, sedimentary layering, discontinuities, etc. Hydrological: Combining compressional and shear wave results can indicate the presence of fluid saturation in the formation. Thermal: High temperatures and pressure impact the compressional and shear wave velocities.

498

Electrical Profiling Configurations | Open Energy Information  

Open Energy Info (EERE)

Electrical Profiling Configurations Electrical Profiling Configurations Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Technique: Electrical Profiling Configurations Details Activities (0) Areas (0) Regions (0) NEPA(0) Exploration Technique Information Exploration Group: Geophysical Techniques Exploration Sub Group: Electrical Techniques Parent Exploration Technique: Direct-Current Resistivity Survey Information Provided by Technique Lithology: Rock composition, mineral and clay content Stratigraphic/Structural: Detection of permeable pathways, fracture zones, faults Hydrological: Resistivity influenced by porosity, grain size distribution, permeability, fluid saturation, fluid type and phase state of the pore water Thermal: Resistivity influenced by temperature

499

Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection  

E-Print Network (OSTI)

demand response participation, including customer fatigue (reduced willingness to respond to events in quick succession to previous events) and price elasticity (demand response participation, including customer fatigue (reduced willingness to respond to events in close proximity to previous events) and price elasticity (

Olsen, Daniel J.

2014-01-01T23:59:59.000Z

500

Minimizing State-of-Health Degradation in Hybrid Electrical Energy Storage Systems with Arbitrary Source and Load Profiles  

E-Print Network (OSTI)

elements and hide their weaknesses for achieving a combination of superior performance metrics. The cycle. The cycle life is directly related to the state-of-health (SoH), which is defined as the ratio of full of battery in the previous literature can only be applied to charging/discharging cycles with the same state

Pedram, Massoud