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


1

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

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

2

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.

3

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

4

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...

5

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.

6

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

7

Mirant: Case 67a: Units 3 & 4 & 5 at Max Load for 12 hours and at Min Load  

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

Mirant: Case 67a: Units 3 & 4 & 5 at Max Load for 12 hours and at Mirant: Case 67a: Units 3 & 4 & 5 at Max Load for 12 hours and at Min Load for 12 hours Mirant: Case 67a: Units 3 & 4 & 5 at Max Load for 12 hours and at Min Load for 12 hours Docket No. EO-05-01. Mirant: Case 67a: Units 3 & 4 & 5 at Max Load for 12 hours and at Min Load for 12 hours. Arial photograph showing plant and location of predicted SO2 violations, predicted in 2000. Mirant: Case 67a: Units 3 & 4 & 5 at Max Load for 12 hours and at Min Load for 12 hours More Documents & Publications Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 3, 1, 2 SO2 Case Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 4, 1, 2 SO2 Case Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by

8

Short Term Hourly Load Forecasting Using Abductive Networks R. E. Abdel-Aal  

E-Print Network [OSTI]

Short Term Hourly Load Forecasting Using Abductive Networks R. E. Abdel-Aal Center for Applied for this purpose. This paper proposes using the alternative technique of abductive networks, which offers with statistical and empirical models. Using hourly temperature and load data for five years, 24 dedicated models

Abdel-Aal, Radwan E.

9

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...

10

After-hours Power Status of Office Equipment and Inventory of Miscellaneous Plug-Load Equipment  

E-Print Network [OSTI]

LBNL-53729 After-hours Power Status of Office Equipment and Inventory of Miscellaneous Plug-Load To download this paper and related data go to: http://enduse.lbl.gov/Projects/OffEqpt.html The work described.................................................................................................................................................5 Office Equipment Data Collection

11

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

12

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

13

Impact of realistic hourly emissions profiles on air pollutants concentrations modelled with CHIMERE  

E-Print Network [OSTI]

Impact of realistic hourly emissions profiles on air pollutants concentrations modelled Keywords: Atmospheric composition European air quality Anthropogenic emissions a b s t r a c t Regional inputs data like anthropogenic surface emissions of NOx, VOCs and particulate matter. These emissions

Menut, Laurent

14

Building Energy Software Tools Directory: Prophet Load Profiler  

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

15

hourly | OpenEI  

Open Energy Info (EERE)

hourly hourly 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 (7 months ago) Date Updated July 02nd, 2013 (5 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

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

17

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...

Véronique Cariou

2006-01-01T23:59:59.000Z

18

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

19

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

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

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 ? GË?otz Lindenmaier 1 , Kathryn S. M c Kinley 2, UniversitË?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

Note: This page contains sample records for the topic "hourly load profile" 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 | 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

22

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

23

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

24

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

25

Estimation of Hourly Solar Loads on the Surfaces of Moving Refrigerated Tractor Trailers Outfitted with Phase Change Materials (PCMs) for Several Routes across the Continental U.S.  

E-Print Network [OSTI]

The primary objective of this thesis was to calculate solar loads, wind chill temperatures on the surfaces of moving refrigerated tractor trailers outfitted with phase change materials (PCMs) for several routes across the Continental United States...

Varadarajan, Krupasagar

2011-08-31T23:59:59.000Z

26

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

27

Relative Short-Range Forecast Impact from Aircraft, Profiler, Radiosonde, VAD, GPS-PW, METAR, and Mesonet Observations via the RUC Hourly Assimilation Cycle  

Science Journals Connector (OSTI)

An assessment is presented on the relative forecast impact on the performance of a numerical weather prediction model from eight different observation data types: aircraft, profiler, radiosonde, velocity azimuth display (VAD), GPS-derived ...

Stanley G. Benjamin; Brian D. Jamison; William R. Moninger; Susan R. Sahm; Barry E. Schwartz; Thomas W. Schlatter

2010-04-01T23:59:59.000Z

28

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 Kolmogorov–Smirnov 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 Rydén; Joakim Widén

2014-01-01T23:59:59.000Z

29

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

30

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

31

Differentiated long term projections of the hourly electricity consumption in local areas. The case of Denmark West  

Science Journals Connector (OSTI)

Abstract Assessing grid developments the spatial distribution of the electricity consumption is important. In Denmark the electricity grid consists of transmission – and local distribution grids with different voltages that are connected via transformer stations each covering a local area with between 10.000 and 100.000 customers. Data for the hourly electricity consumption at transformer stations shows that the profile of consumption differs considerably between local areas, and this is partly due to a different weight of categories of customers in the different areas. Categories of customers have quite distinct consumption profiles and contribute quite differently to the aggregated load profile. In forecasts, demand by categories of customers is expected to develop differently implying that both the level and the profile of consumption at each transformer stations are expected to change differently. Still, in the previous planning of the transmission grid in Denmark specific local conditions have not been considered. As a first step towards differentiated local load forecasts, the paper presents a new model for long term projections of consumption in local areas and illustrates a first use of the model related to the transmission grid planning by the Danish TSO Energinet.dk. The model is a distribution system that distributes hourly consumption in an aggregated area to hourly consumption at each transformer station. Using econometrics, the model is estimated on national statistics for the hourly consumption by categories of customers and data for the hourly consumption at each transformer station for the years 2009–2011. Applying the model for load forecasts, a major conclusion is that different transformer stations will experience different changes both in the level - and in the hourly profile of load.

F.M. Andersen; H.V. Larsen; N. Juul; R.B. Gaardestrup

2014-01-01T23:59:59.000Z

32

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

SciTech Connect (OSTI)

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

33

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

34

Common Help Room Hours  

E-Print Network [OSTI]

Common Help Room Hours for Spring 2015. Monday, Tuesday, Wednesday, Thursday, Friday. 10:30 am. 11:30 am. MA 16200 - MATH 205 - Nathanael Cox ...

35

Common Help Room Hours  

E-Print Network [OSTI]

Common Help Room Hours for Spring 2015. Monday, Tuesday, Wednesday, Thursday, Friday. 10:30 am. 11:30 am. MA 16010 - MATH 205 - Alessandra ...

36

Contacts / Hours - Hanford Site  

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

Station Real Time Met Data from Around the Site Current HMS Observations Daily HMS Extremes in Met Data Met and Climate Data Summary Products Contacts Hours Current NWS...

37

LIBRARY SERVICES LIBRARY HOURS  

E-Print Network [OSTI]

LIBRARY SERVICES LIBRARY HOURS Up-to-date library hours are posted at http Wesleyan ID that is linked to the library circulation database is needed to charge out library materials to visit the Circulation Office in Olin Library 115 to set up their borrowing privileges. If you have

Royer, Dana

38

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:

39

NERSC Edison Hours Used Report  

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

Hours Used Edison Hours Used 2014 Edison Usage Chart Edison Usage Chart 2013 Edison Usage Chart Edison Usage Chart 2014 Date Hours Used (in millions) Percent of Maximum Possible...

40

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...

Note: This page contains sample records for the topic "hourly load profile" 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

FALL AND SPRING Per Hour # Hours # Semesters Total  

E-Print Network [OSTI]

$4,060.00 FALL AND SPRING Per Hour # Hours # Semesters Total Tuition $765.00 15 2 $22,950.00 ISS, Engineering, Journalism & Mass Communications, Music and Social Welfare fees. These amounts do NOT include to complete at least 12 hours each fall and spring semester. Calculations are based on 15 hours (an average

42

hourly emission factors | OpenEI  

Open Energy Info (EERE)

60 60 Varnish cache server Browse Upload data GDR 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2142278660 Varnish cache server hourly emission factors Dataset Summary Description Emissions from energy use in buildings are usually estimated on an annual basis using annual average multipliers. Using annual numbers provides a reasonable estimation of emissions, but it provides no indication of the temporal nature of the emissions. Therefore, there is no way of understanding the impact on emissions from load shifting and peak shaving technologies such as thermal energy storage, on-site renewable energy, and demand control. Source NREL Date Released April 11th, 2011 (3 years ago) Date Updated April 11th, 2011 (3 years ago)

43

NERSC Hopper Hours Used Report  

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

Hours Used Hopper Hours Used 2014 Hopper Usage Chart Hopper Usage Chart 2013 Hopper Usage Chart Hopper Usage Chart 2012 Hopper Usage Chart Hopper Usage Chart 2011 Hopper Usage...

44

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.

45

FALL AND SPRING Per Hour # Hours # Semesters Total  

E-Print Network [OSTI]

$4,060.00 FALL AND SPRING Per Hour # Hours # Semesters Total Tuition $828.00 15 2 $24,840.00 ISS Living Expenses Please see reverse side for Architecture, Arts, Business, Design & Planning, Engineering to change. Tuition will be guaranteed through spring 2018; however, expect approximately a 5% increase each

46

NERSC Franklin Hours Used Report  

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

Franklin Hours Used Franklin Hours Used Franklin Hours Used 2011 Franklin Usage in Hours 2011 Franklin Usage in Hours 2010 2010 Franklin Usage in Hours 2009 2009 Franklin Usage in Hours 2007-2008 2008 Franklin Usage in Hours 2008 Franklin Usage in Hours Date Hours Used (in thousands) Percentage of Maximum Possible (24 hours/day) 04/28/2012 0.00 0.00 04/27/2012 272.62 29.40 04/26/2012 692.81 74.71 04/25/2012 841.60 90.75 04/24/2012 53.86 5.81 04/23/2012 432.01 46.59 04/22/2012 823.23 88.77 04/21/2012 473.95 51.11 04/20/2012 173.75 18.74 04/19/2012 449.22 48.44 04/18/2012 816.23 88.02 04/17/2012 754.35 81.34 04/16/2012 648.89 69.97 04/15/2012 812.25 87.59 04/14/2012 843.46 90.95 04/13/2012 737.46 79.52 04/12/2012 711.97 76.77 04/11/2012 734.65 79.22 04/10/2012 815.65 87.95 04/09/2012 897.25 96.75

47

Determining Electric Motor Load and Efficiency  

Broader source: Energy.gov [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.

48

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

SciTech Connect (OSTI)

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

49

EIA-930 Hourly and Daily Balancing ...  

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

not change from day-to-day or hour-to-hour, as specified in the immediately preceding section. For each hour of the day, hourly integrated demand is to be posted within ten...

50

NERSC Carver Hours Used Report  

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

Carver Hours Carver Hours Used Carver Hours Used Hopper Usage Chart Hopper Usage Chart Date Hours Used (in millions) Percent of Maximum Possible (24 hours/day) 01/05/2014 170.00 89.35 01/04/2014 174.38 91.65 01/03/2014 174.15 91.53 01/02/2014 179.72 94.45 01/01/2014 173.76 91.32 12/31/2013 172.25 90.53 12/30/2013 169.62 89.14 12/29/2013 164.72 86.57 12/28/2013 177.92 93.51 12/27/2013 171.61 90.19 12/26/2013 172.74 90.79 12/25/2013 172.13 90.46 12/24/2013 173.48 91.18 12/23/2013 174.92 91.93 12/22/2013 175.26 92.11 12/21/2013 173.58 91.23 12/20/2013 174.50 91.71 12/19/2013 170.02 89.36 12/18/2013 178.25 93.68 12/17/2013 176.17 92.59 12/16/2013 162.03 85.16 12/15/2013 157.09 82.56 12/14/2013 173.40 91.13 12/13/2013 185.02 97.24 12/12/2013 150.91 79.31 12/11/2013 31.67 16.64 12/10/2013 92.44 48.58

51

Location and Hours | ornl.gov  

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

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

52

hourly data | OpenEI  

Open Energy Info (EERE)

data data Dataset Summary Description (Abstract): Each data file is a set of hourly values of solar radiation and meteorological elements for a 1-year period. Solar radiation is modeled using the NREL METSTAT model, with surface observed cloud cover being the principal model input. Each container file contains up to 30 yearly files for one station, plus the Typical Meteorological Year (TMY) file for the selected station, plus documentation files and a TMY data reader file for use with Microsoft Excel. Source U.S. National Renewable Energy Laboratory (NREL) Date Released May 03rd, 2005 (9 years ago) Date Updated November 01st, 2007 (7 years ago) Keywords DNI GHI hourly data NREL solar Sri Lanka SWERA TILT TMY UNEP Data application/zip icon Download TMY data (zip, 67.5 MiB)

53

Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water...  

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

Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production...

54

Definition: Kilowatt-hour | Open Energy Information  

Open Energy Info (EERE)

Kilowatt-hour Kilowatt-hour Jump to: navigation, search Dictionary.png Kilowatt-hour A unit of measure for energy, typically applied to electricity usage; equal to the amount of energy used at a rate of 1,000 watts over the course of one hour. One kWh is equivalent to 3,412 Btu, or 3,600 kJ.[1][2] View on Wikipedia Wikipedia Definition The kilowatt hour, or kilowatt-hour, (symbol kW·h, kW h or kWh) is a unit of energy equal to 1000 watt hours or 3.6 megajoules. For constant power, energy in watt hours is the product of power in watts and time in hours. The kilowatt hour is most commonly known as a billing unit for energy delivered to consumers by electric utilities. Also Known As kWh Related Terms British thermal unit, Electricity, Energy, Kilowatt, energy, electricity generation

55

Investigation of residential central air conditioning load shapes in NEMS  

SciTech Connect (OSTI)

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

56

Hourly Energy Emission Factors for Electricity Generation in the United  

Open Energy Info (EERE)

Hourly Energy Emission Factors for Electricity Generation in the United Hourly Energy Emission Factors for Electricity Generation in the United States Dataset Summary Description Emissions from energy use in buildings are usually estimated on an annual basis using annual average multipliers. Using annual numbers provides a reasonable estimation of emissions, but it provides no indication of the temporal nature of the emissions. Therefore, there is no way of understanding the impact on emissions from load shifting and peak shaving technologies such as thermal energy storage, on-site renewable energy, and demand control. This project utilized GridViewTM, an electric grid dispatch software package, to estimate hourly emission factors for all of the eGRID subregions in the continental United States. These factors took into account electricity imports and exports

57

Plug Load  

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

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

58

Load Control  

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

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

59

Information and Instructions for Your Office Hours  

E-Print Network [OSTI]

Aug 7, 2014 ... INFORMATION on OFFICE HOURS and INSTRUCTIONS for TAOH. Please view rather than print this information. Current dates can be found ...

Dominic Naughton

2014-08-07T23:59:59.000Z

60

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

Note: This page contains sample records for the topic "hourly load profile" 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

Bradbury Science Museum announces winter opening hours  

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

Bradbury Science Museum winter hours Bradbury Science Museum winter hours Bradbury Science Museum announces winter opening hours Museum will be closed on Christmas Day (December 25) and New Year's Day (January 1, 2011). December 21, 2010 Bradbury Science Museum Bradbury Science Museum Contact Communications Office (505) 667-7000 Often called "a window to the Laboratory," the museum annually attracts thousands of visitors from all over the world. LOS ALAMOS, New Mexico, December 21, 2010-Los Alamos National Laboratory's Bradbury Science Museum will be closed on Christmas Day (December 25) and New Year's Day (January 1, 2011). On all other days, the museum will observe regular opening hours: from 10 a.m. to 5 p.m. Tuesdays to Saturdays, and from 1 to 5 p.m. Sundays and Mondays. Often called "a window to the Laboratory," the museum annually attracts

62

MARKETING DEPARTMENT Office Hours Fall 2014  

E-Print Network [OSTI]

MARKETING DEPARTMENT Office Hours Fall 2014 NAME OFFICE HOURS COURSE # COURSE TITLE DAY TIME ROOM MKTG 470.2 MKTG 496.1 Marketing Research Marketing & Sales Analytics MW MW 1000-1150 1400-1550 SSW 3620-1400 and by appointment MKTG 498.1-3 MKTG 779.1 MKTG 790.1 MKTG 797.1 MKTG 798.1-3 Investigation & Report Ad. Marketing

Gallo, Linda C.

63

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

64

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

65

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

66

Peak load management: Potential options  

SciTech Connect (OSTI)

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

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

1989-10-01T23:59:59.000Z

67

hourly solar radiation | OpenEI  

Open Energy Info (EERE)

solar radiation solar radiation Dataset Summary Description (Abstract): A need for predicting hourly global radiation exists for many locations particularly in Bangladesh for which measured values are not available and daily values have to be estimated from sunshine data. The CPRG model has been used to predict values of hourly Gh for Dhaka (23.770N, 90.380E), Chittagong (22.270N, 91.820E) and Bogra (24.850N, 89.370E) for = ±7.50, ±22.50, ±37.50, ±52.50, ±67.50, ±82.50 and ±97.50 i.e., for ±1/2, ±3/2, ±5/2, ±7/2, ±9/2, ±11/2, ±13/2 hours before and after solar noon and the computed values for Source Renewable Energy Research Centre Date Released October 22nd, 2003 (11 years ago) Date Updated Unknown Keywords Bangladesh documentation hourly solar radiation SWERA

68

Ethics and Public Health 3 credit hours  

E-Print Network [OSTI]

PUB H Ethics and Public Health 3 credit hours Summer, 2009 Instructor: Ann Cook, PhD, MPA, Research U.S. public health policies. The course begins with a rationale for studying the ethical dimensions of public health and then examines ethical decisonmaking in arenas such as policy development, research

Vonessen, Nikolaus

69

Credit Based; Beginning Swimming Credit/Hour  

E-Print Network [OSTI]

the pool. To be able to swim at least 50 yards with one of the learned strokes. Required Materials: Swim. Make-Ups: Only two make-ups allowed by swimming laps during open swim/lap swim at MSU pool. Lap swimCredit Based; Beginning Swimming Credit/Hour s Class Title Lead Instructo r Phone Email Office

Maxwell, Bruce D.

70

Project Management Foundation 21 hours, $895  

E-Print Network [OSTI]

Project Management Foundation 21 hours, $895 The fundamental project management processes. In group exercises, participants gain an understanding of how the project management processes are used during each phase of a project to build a better, more effective project plan. Topics Include

Alabama in Huntsville, University of

71

2009-2010 Advertising Curriculum Hours PREREQUISITES  

E-Print Network [OSTI]

2009-2010 Advertising Curriculum Hours PREREQUISITES First Year English 101, 102 6 or satisfactory placement test score Second Year Advertising 250 3 ___ Public Relations 270 3 ___ 3 History 241 ___ Statistics 201 3 ___ Math 125 or Math 141 Accounting 200 3 ___ Advertising 310 3 ___ Advertising 250 TOTAL 31

Grissino-Mayer, Henri D.

72

2007-2008 Advertising Curriculum Hours PREREQUISITES  

E-Print Network [OSTI]

2007-2008 Advertising Curriculum Hours PREREQUISITES First Year English 101, 102 6-4 ___ Math 119 or 123 or satisfactory placement test score TOTAL 32-33 Second Year Advertising 250 3 ___ Advertising 310 3 ___ Adv 250 and admission to the major TOTAL 31 Third Year Psychology 110 3 ___ Business

Grissino-Mayer, Henri D.

73

2011-12 Advertising Curriculum Hours PREREQUISITES  

E-Print Network [OSTI]

2011-12 Advertising Curriculum Hours PREREQUISITES First Year English 101, 102 6-33 Math 141: Math 130 or placement level Second Year Advertising 250 3 ___ Public Relations 270 3 ___ 3 Economics 201 4 ___ Statistics 201 3 ___ Math 125 or Math 141 Accounting 200 3 ___ Advertising 310 3

Grissino-Mayer, Henri D.

74

2010-11 Advertising Curriculum Hours PREREQUISITES  

E-Print Network [OSTI]

2010-11 Advertising Curriculum Hours PREREQUISITES First Year English 101, 102 6-33 Math 141: Math 130 or placement level Second Year Advertising 250 3 ___ Public Relations 270 3 ___ 3 Economics 201 4 ___ Statistics 201 3 ___ Math 125 or Math 141 Accounting 200 3 ___ Advertising 310 3

Grissino-Mayer, Henri D.

75

2012-13 Advertising Curriculum Hours PREREQUISITES  

E-Print Network [OSTI]

2012-13 Advertising Curriculum Hours PREREQUISITES First Year English 101*, 102* 6 Advertising 250 3 ___ Public Relations 270 3 ___ 3 History 241*, 242* or 261*, 262* 6 ___ ___ 4 English or Math 141 Accounting 200 3 ___ Advertising 310 3 ___ Advertising 250 TOTAL 31 Third Year Psychology 110

Grissino-Mayer, Henri D.

76

NERSC Edison Phase I Hours Used Report  

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

Edison Phase I Hours Used Edison Phase I Hours Used Edison Phase I Hours Used Edison Usage Chart Edison Usage Chart Date Hours Used (in millions) Percent of Maximum Possible (24 hours/day) 06/23/2013 0.226 88.6 06/22/2013 0.239 93.9 06/21/2013 0.248 97.1 06/20/2013 0.240 94.0 06/19/2013 0.233 91.3 06/18/2013 0.245 96.0 06/17/2013 0.251 98.4 06/16/2013 0.243 95.3 06/15/2013 0.245 95.9 06/14/2013 0.246 96.5 06/13/2013 0.240 94.1 06/12/2013 0.128 50.4 06/11/2013 0.215 84.5 06/10/2013 0.225 88.4 06/09/2013 0.228 89.6 06/08/2013 0.225 88.3 06/07/2013 0.121 47.5 06/06/2013 0.223 87.4 06/05/2013 0.250 98.0 06/04/2013 0.234 91.6 06/03/2013 0.218 85.5 06/02/2013 0.246 96.4 06/01/2013 0.230 90.0 05/31/2013 0.215 84.5 05/30/2013 0.212 83.1 05/29/2013 0.223 87.3 05/28/2013 0.237 93.0 05/27/2013 0.226 88.5 05/26/2013 0.229 89.9

77

Health Promotion Graduate Student Coordinator 15-20 hours/week $18/hour (pending approval)  

E-Print Network [OSTI]

Health Promotion Graduate Student Coordinator 15-20 hours/week $18/hour (pending approval year. The Graduate Student Coordinator for Health Promotion is responsible for assisting the Fitness & Health Promotion Coordinator in the development, promotion, management and implementation of Campus Rec

Lafferriere, Gerardo

78

Society, Technology and the Environment-3credit hours Spanish for Engineering-6 credit hours  

E-Print Network [OSTI]

Society, Technology and the Environment- 3credit hours Spanish for Engineering- 6 credit hours 21st May to 22nd June 2012 The University of Alabama College of Engineering in collaboration with Pamplona for any student interested in technology and the environment; students will have the opportunity to study

Simaan, Nabil

79

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

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

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

80

Faculty Office Hours Fall 2014 Aberle, James  

E-Print Network [OSTI]

Faculty Office Hours Fall 2014 Aberle, James GWC 326 01:30 PM 02:45 PMM T W F to Tuesday is through:30 AMR to Coleman, James BYENG 450 08:45 AM 09:45 AMT R to By Appointment Cotter, Jeff GWC 424 03:15 PM:00 AM 09:30 AMF to Or at a time arranged via e-mail to reisslein@asu.edu Rodriguez, Armando GWC 352 10

Zhang, Yanchao

Note: This page contains sample records for the topic "hourly load profile" 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

Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production  

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

Hour-by-Hour Cost Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production Genevieve Saur (PI), Chris Ainscough (Presenter), Kevin Harrison, Todd Ramsden National Renewable Energy Laboratory January 17 th , 2013 This presentation does not contain any proprietary, confidential, or otherwise restricted information 2 Acknowledgements * This work was made possible by support from the U.S. Department of Energy's Fuel Cell Technologies Office within the Office of Energy Efficiency and Renewable Energy (EERE). http://www.eere.energy.gov/topics/hydrogen_fuel_cells.html * NREL would like to thank our DOE Technology Development Managers for this project, Sara Dillich, Eric Miller, Erika Sutherland, and David Peterson. * NREL would also like to acknowledge the indirect

82

People Profiles  

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

83

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

SciTech Connect (OSTI)

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

Katipamula, Srinivas; Hatley, Darrel D.

2004-12-22T23:59:59.000Z

84

20140430_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 April to 30 April 2014.

Thibedeau, Joe

2014-05-05T23:59:59.000Z

85

Green Machine Florida Canyon Hourly Data 20130731  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 7/1/13 to 7/31/13.

Vanderhoff, Alex

2013-08-30T23:59:59.000Z

86

20130416_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 4/16/13.

Vanderhoff, Alex

2013-04-24T23:59:59.000Z

87

Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 6/1/13 to 6/30/13

Vanderhoff, Alex

2013-07-15T23:59:59.000Z

88

Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 6/1/13 to 6/30/13

Vanderhoff, Alex

89

20130416_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 4/16/13.

Vanderhoff, Alex

90

20140430_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 April to 30 April 2014.

Thibedeau, Joe

91

Green Machine Florida Canyon Hourly Data 20130731  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 7/1/13 to 7/31/13.

Vanderhoff, Alex

92

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

93

Cleanroom After-Hours Policy Original: 11/04  

E-Print Network [OSTI]

Cleanroom After-Hours Policy Original: 11/04 Revised: 2//05 CAMD strives to maintain and improve laboratory and User safety along with User efficiency. After- Hours work inside the cleanroom (CR + all hours of LSU Staff holidays. After-Hours Access Request · Cleanroom-trained Users can apply for CR

94

Guidelines for Use MIT Libraries' 24 Hour Study Space  

E-Print Network [OSTI]

Guidelines for Use MIT Libraries' 24 Hour Study Space Access to and use of the MIT Libraries' 24://libguides.mit.edu/hours)). The following principles guide access to 24-hour spaces for all users of the MIT Libraries: Expectations Library policies Behavior Library users in the 24-hour study spaces are expected to refrain from: � Behaviors

95

The Temperature Sensitivity of the Residential Load and Commercial Building Load  

SciTech Connect (OSTI)

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

96

Building Energy Software Tools Directory: HAP System Design Load  

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

97

Estimation of hourly global and diffuse solar radiation from hourly sunshine duration  

SciTech Connect (OSTI)

A statistical procedure has been employed to develop correlations of monthly-mean-hourly global and diffuse solar radiation on a horizontal surface to hourly sunshine duration. Several years of measured data on solar radiation and sunshine duration, reported in the literature for two stations in the southern African region, is employed for this purpose. The applicability of the developed correlations is tested by estimating solar radiation for a new location. The excellent agreement between the measured and estimated data for that station the wide applicability of the method.

Gopinathan, K.K (National Univ. of Lesotho, Roma (South Africa))

1992-01-01T23:59:59.000Z

98

Reliability analysis of solar photovoltaic system using hourly mean solar radiation data  

SciTech Connect (OSTI)

This paper presents the hourly mean solar radiation and standard deviation as inputs to simulate the solar radiation over a year. Monte Carlo simulation (MCS) technique is applied and MATLAB program is developed for reliability analysis of small isolated power system using solar photovoltaic (SPV). This paper is distributed in two parts. Firstly various solar radiation prediction methods along with hourly mean solar radiation (HMSR) method are compared. The comparison is carried on the basis of predicted electrical power generation with actual power generated by SPV system. Estimation of solar photovoltaic power using HMSR method is close to the actual power generated by SPV system. The deviation in monsoon months is due to the cloud cover. In later part of the paper various reliability indices are obtained by HMSR method using MCS technique. Load model used is IEEE-RTS. Reliability indices, additional load hours (ALH) and additional power (AP) reduces exponentially with increase in load indicates that a SPV source will offset maximum fuel when all of its generated energy is utilized. Fuel saving calculation is also investigated. Case studies are presented for Sagardeep Island in West Bengal state of India. (author)

Moharil, Ravindra M. [Department of Electrical Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, Maharashtra (India); Kulkarni, Prakash S. [Department of Electrical Engineering, Visvesvaraya National Institute of Technology, South Ambazari Road, Nagpur 440011, Maharashtra (India)

2010-04-15T23:59:59.000Z

99

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

100

An Improved Procedure for Developing a Calibrated Hourly Simulation Model of an Electrically Heated and Cooled Commercial Buildling  

E-Print Network [OSTI]

, this thesis presents new calibration methods including temperature binned box-whisker-mean analysis to improve x-y scatter plots, 24-hour weather-daytype box-whisker-mean graphs to show IV hourly temperature-dependent energy use profiles, and 52-week box... using a case study building located in Washington, D.C. In the case study building, nine months of hourly whole-building electricity data and site-specific weather data were measured and used with the D0E-2.1D building simulation program to test the new...

Bou-Saada, Tarek Edmond

Note: This page contains sample records for the topic "hourly load profile" 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

Also visit my online sites on Facebook www.facebook.com/ceceiliajill or LinkedIn www.linkedin.com/in/ceceilia about 20 hours ago via web  

E-Print Network [OSTI]

.linkedin.com/in/ceceilia about 20 hours ago via web Love the online Profile that ShannonKelly did in PennCareerServices @PennCareerDay http://ulife.vpul.upenn.edu/careerservices/blog/?cat=92 about 20 hours ago via web Looong drive out starting point. about 20 hours ago via web Time to go out and have fun but will continue to tweet

Plotkin, Joshua B.

102

1991 Pacific Northwest Loads and Resources Study.  

SciTech Connect (OSTI)

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

103

BNL | Center for Functional Nanomaterials Hours of Operation  

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

CFN Hours of Operation CFN Hours of Operation Normal working hours at the CFN are 8 a.m. to 6 p.m. Working Outside of Normal Hours CFN scientific and technical personnel, as well as external users, may need to work outside of normal operating hours, during which time support is limited and many colleagues may not be around. Therefore, working outside the 8 a.m. to 6 p.m. envelope on weekdays, or anytime on weekends and holidays, requires special precautions, especially if working in a laboratory. CFN users are expected to work at the CFN during normal working hours. Users with extensive experience working at the CFN may be granted permission by the appropriate facility leader and ES&H Coordinator to work after hours. Users first must complete the Request to Work After-Hours at

104

Mentee Profile  

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

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?

105

Mentor Profile  

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

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?

106

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

107

IPM Profiling Tool at NERSC  

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

108

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

109

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.

110

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

111

Partnership with Industries- A Successful "Conservation and Load Management Program"  

E-Print Network [OSTI]

WAS THE EXISTENCE OF FAVORABLE TIME-OF-USE "RATES. THE OPERATIONAL PLANT LOAD IS 10,000 KW. OF THIS, ONE PROCESS WILL REQUIRE 5,000 KW E'OR HEATI NG. THE INITIAL WORK WEEK WILL BE 40 HOURS, AND IS EXPECTED TO INCREASE TO 80 HOURS WITHIN THE NEXT TWO YEARS...P~RTNERSHIPS WITH INDUSTRY '" NT PROGRAM" A SUCCESSFUL "CONSERVATION AND LOAD MANAGEME Walter E. Johnston Carolina power & Light Co. Raleigh, North Carolina INTRODUCTION CAROLINA POWER AND LIGHT PROVIDES ELECTRIC SERVICE TO ABOUT 3 MILLION...

Johnston, W. E.

112

Identifying Challenging Operating Hours for Solar Intergration in the NV Energy System  

SciTech Connect (OSTI)

Abstract-- In this paper, the ability of the Nevada (NV) Energy generation fleet to meet its system balancing requirements under different solar energy penetration scenarios is studied. System balancing requirements include capacity, ramp rate, and ramp duration requirements for load following and regulation. If, during some operating hours, system capability is insufficient to meet these requirements, there is certain probability that the balancing authority’s control and reliability performance can be compromised. These operating hours are considered as “challenging” hours. Five different solar energy integration scenarios have been studied. Simulations have shown that the NV Energy system will be potentially able to accommodate up to 942 MW of solar photovoltaic (PV) generation. However, the existing generation scheduling procedure should be adjusted to make it happen. Fast-responsive peaker units need to be used more frequently to meet the increasing ramping requirements. Thus, the NV Energy system operational cost can increase. Index Terms—Solar Generation, Renewables Integration, Balancing Process, Load Following, Regulation.

Etingov, Pavel V.; Lu, Shuai; Guo, Xinxin; Ma, Jian; Makarov, Yuri V.; Chadliev, Vladimir; Salgo, Richard

2012-05-09T23:59:59.000Z

113

Future energy loads for a large-scale adoption of electric vehicles in the city of Los Angeles: Impacts on greenhouse gas (GHG) emissions  

Science Journals Connector (OSTI)

Abstract Using plug-in electric vehicles (PEVs) has become an important component of greenhouse gas (GHG) emissions reduction strategy in the transportation sector. Assessing the net effect of \\{PEVs\\} on GHG emissions, however, is dependent on factors such as type and scale of electricity generation sources, adoption rate, and charging behavior. This study creates a comprehensive model that estimates the energy load and GHG emissions impacts for the years 2020 and 2030 for the city of Los Angeles. For 2020, model simulations show that the PEV charging loads will be modest with negligible effects on the overall system load profile. Contrary to previous study results, the average marginal carbon intensity is higher if PEV charging occurs during off-peak hours. These results suggest that current economic incentives to encourage off-peak charging result in greater GHG emissions. Model simulations for 2030 show that PEV charging loads increase significantly resulting in potential generation shortages. There are also significant grid operation challenges as the region?s energy grid is required to ramp up and down rapidly to meet PEV loads. For 2030, the average marginal carbon intensity for off-peak charging becomes lower than peak charging mainly due to the removal of coal from the power generation portfolio.

Jae D. Kim; Mansour Rahimi

2014-01-01T23:59:59.000Z

114

NV Energy Large-Scale Photovoltaic Integration Study: Intra-Hour Dispatch and AGC Simulation  

SciTech Connect (OSTI)

The uncertainty and variability with photovoltaic (PV) generation make it very challenging to balance power system generation and load, especially under high penetration cases. Higher reserve requirements and more cycling of conventional generators are generally anticipated for large-scale PV integration. However, whether the existing generation fleet is flexible enough to handle the variations and how well the system can maintain its control performance are difficult to predict. The goal of this project is to develop a software program that can perform intra-hour dispatch and automatic generation control (AGC) simulation, by which the balancing operations of a system can be simulated to answer the questions posed above. The simulator, named Electric System Intra-Hour Operation Simulator (ESIOS), uses the NV Energy southern system as a study case, and models the system’s generator configurations, AGC functions, and operator actions to balance system generation and load. Actual dispatch of AGC generators and control performance under various PV penetration levels can be predicted by running ESIOS. With data about the load, generation, and generator characteristics, ESIOS can perform similar simulations and assess variable generation integration impacts for other systems as well. This report describes the design of the simulator and presents the study results showing the PV impacts on NV Energy real-time operations.

Lu, Shuai; Etingov, Pavel V.; Meng, Da; Guo, Xinxin; Jin, Chunlian; Samaan, Nader A.

2013-01-02T23:59:59.000Z

115

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

116

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

117

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

118

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

119

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

120

Hospital Triage in First Hours After Nuclear or Radiological...  

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

Hospital Triage in the First 24 Hours after a Nuclear or Radiological Disaster Medical professionals with the Radiation Emergency Assistance CenterTraining Site (REACTS) at the...

Note: This page contains sample records for the topic "hourly load profile" 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

Delayed Start or Cancellation of Business Hours | Argonne National...  

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

if you have questions. When regular business hours are suspended The laboratory may not conduct regular operations because of inclement weather. In this case, employees are not...

122

Predicting pipeline frost load  

SciTech Connect (OSTI)

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

123

Credit Based; Beginning Swimming Credit/Hours Class  

E-Print Network [OSTI]

Center Pool Course Description: Beginning swimming skills and water safety. Prerequisites: Must about experience at the meet. 3) Swim laps during open swim/lap swim at MSU pool. A sheet will be postedCredit Based; Beginning Swimming Credit/Hours Class Title Lead Instructor Phone Email Office Hours

Maxwell, Bruce D.

124

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

125

General Education and Major Coursework: Credit Hours General Education and Major Coursework: Credit Hours ENGN 110 2 ECE 111 2  

E-Print Network [OSTI]

: 128 ** Meets philosophy and ethics general education requirement. Electrical engineering majors mustGeneral Education and Major Coursework: Credit Hours General Education and Major Coursework: Credit (C or better required) 3 PHYS 231N 4 COMM 101R 3 General Education and Major Coursework: Credit Hours

126

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

127

Building Energy Software Tools Directory: TRACE Load 700  

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

Load 700 Load 700 TRACE Load 700 logo. Use TRACE Load 700 software - the building and load design modules of TRACE 700, Trane Air Conditioning Economics - to evaluate the effect of building orientation, size, shape, and mass based on hourly weather data and the resulting heat-transfer characteristics of air and moisture. To assure calculation integrity, the program uses algorithms recommended by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). Choose from eight different ASHRAE cooling and heating methodologies, including the Exact Transfer Function. The program encourages "what if" analyses, allowing the user to enter construction details in any order and then easily change the resulting building model as the design progresses. Multiple project views and "drag-and-drop"

128

HLW Glass Waste Loadings  

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

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

129

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

130

Composite Load Model Evaluation  

SciTech Connect (OSTI)

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

131

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...

132

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)...

133

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...

134

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...

135

Team Surpasses 1 Million Hours Safety Milestone | Department of Energy  

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

Team Surpasses 1 Million Hours Safety Milestone Team Surpasses 1 Million Hours Safety Milestone Team Surpasses 1 Million Hours Safety Milestone October 30, 2013 - 12:00pm Addthis The Separations Process Research Unit Demolition Project Safety Committee meets regularly with employees and supervisors to discuss safety issues and reinforce safe work habits. The Separations Process Research Unit Demolition Project Safety Committee meets regularly with employees and supervisors to discuss safety issues and reinforce safe work habits. NISKAYUNA, N.Y. - Vigilance and dedication to safety led the EM program's disposition project team at the Separations Process Research Unit (SPRU) to achieve a milestone of one million hours - over two-and-a-half-years - without injury or illness resulting in time away from work.

136

Team Surpasses 1 Million Hours Safety Milestone | Department of Energy  

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

Team Surpasses 1 Million Hours Safety Milestone Team Surpasses 1 Million Hours Safety Milestone Team Surpasses 1 Million Hours Safety Milestone October 30, 2013 - 12:00pm Addthis The Separations Process Research Unit Demolition Project Safety Committee meets regularly with employees and supervisors to discuss safety issues and reinforce safe work habits. The Separations Process Research Unit Demolition Project Safety Committee meets regularly with employees and supervisors to discuss safety issues and reinforce safe work habits. NISKAYUNA, N.Y. - Vigilance and dedication to safety led the EM program's disposition project team at the Separations Process Research Unit (SPRU) to achieve a milestone of one million hours - over two-and-a-half-years - without injury or illness resulting in time away from work.

137

DOE Awards Over a Billion Supercomputing Hours to Address Scientific  

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

Over a Billion Supercomputing Hours to Address Over a Billion Supercomputing Hours to Address Scientific Challenges DOE Awards Over a Billion Supercomputing Hours to Address Scientific Challenges January 26, 2010 - 12:00am Addthis Washington, DC. - The U.S. Department of Energy announced today that approximately 1.6 billion supercomputing processor hours have been awarded to 69 cutting-edge research projects through the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. The INCITE program provides powerful resources to enable scientists and engineers to conduct cutting-edge research in just weeks or months rather than the years or decades needed previously. This facilitates scientific breakthroughs in areas such as climate change, alternative energy, life sciences, and materials science.

138

DOE Awards Over a Billion Supercomputing Hours to Address Scientific  

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

DOE Awards Over a Billion Supercomputing Hours to Address DOE Awards Over a Billion Supercomputing Hours to Address Scientific Challenges DOE Awards Over a Billion Supercomputing Hours to Address Scientific Challenges January 26, 2010 - 12:00am Addthis Washington, DC. - The U.S. Department of Energy announced today that approximately 1.6 billion supercomputing processor hours have been awarded to 69 cutting-edge research projects through the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. The INCITE program provides powerful resources to enable scientists and engineers to conduct cutting-edge research in just weeks or months rather than the years or decades needed previously. This facilitates scientific breakthroughs in areas such as climate change, alternative energy, life

139

Balancing Authority Cooperation Concepts - Intra-Hour Scheduling  

SciTech Connect (OSTI)

The overall objective of this study was to understand, on an Interconnection-wide basis, the effects intra-hour scheduling compared to hourly scheduling. Moreover, the study sought to understand how the benefits of intra-hour scheduling would change by altering the input assumptions in different scenarios. This report describes results of three separate scenarios with differing key assumptions and comparing the production costs between hourly scheduling and 10-minute scheduling performance. The different scenarios were chosen to provide insight into how the estimated benefits might change by altering input assumptions. Several key assumptions were different in the three scenarios, however most assumptions were similar and/or unchanged among the scenarios.

Hunsaker, Matthew; Samaan, Nader; Milligan, Michael; Guo, Tao; Liu, Guangjuan; Toolson, Jacob

2013-03-29T23:59:59.000Z

140

DOE's Office of Science Awards 18 Million Hours of Supercomputing...  

Office of Environmental Management (EM)

Supercomputing Time to 15 Teams for Large-Scale Scientific Computing DOE's Office of Science Awards 18 Million Hours of Supercomputing Time to 15 Teams for Large-Scale Scientific...

Note: This page contains sample records for the topic "hourly load profile" 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

SunShot Announces 24-Hour Solar Data Hackathon  

Broader source: Energy.gov [DOE]

SunShot will host a 24-hour solar data hackathon at the 2014 SunShot Grand Challenge Summit. Learn more over at the EERE blog and register here. 

142

Pay and Leave Administration and Hours of Duty  

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

This Order establishes requirements and responsibilities for the management of pay, including overtime and compensatory time, leave administration, and hours of duty. Cancels DOE O 322.1A. Canceled by DOE O 322.1C.

2005-01-14T23:59:59.000Z

143

Pay and Leave Administration and Hours of Duty  

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

The order establishes requirements and responsibilities for the management of pay, including overtime pay and compensatory time, leave administration, time and attendance reporting, and hours of duty. Cancels DOE O 322.1B and DOE O 535.1

2011-01-19T23:59:59.000Z

144

Load Monitoring CEC/LMTF Load Research Program  

SciTech Connect (OSTI)

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

145

Truck loading rack blending  

SciTech Connect (OSTI)

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

146

User_TalentProfile  

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

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

147

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

SciTech Connect (OSTI)

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

148

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

149

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

150

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

151

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

152

Form EIA-930 HOURLY AND DAILY BALANCING AUTHORITY OPERATIONS REPORT  

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

930 930 HOURLY AND DAILY BALANCING AUTHORITY OPERATIONS REPORT INSTRUCTIONS Due Date: mm/dd/yyyy Approved: OMB No. 1905-0129 Approval Expires: 10/31/2016 Burden: 0.19 hours Page 1 Draft for Discussion only PURPOSE Form EIA-930 requires Internet posting of hourly balancing authority operating data. The posted data are used to monitor the current status and trends of the electric power industry, and to support enhancement of electric system operations. REQUIRED RESPONDENTS For the contiguous United States: all entities that are listed in NERC's Compliance Registry as a balancing authority must post balancing authority operating information required by this survey. Other than the Midwest ISO (MISO), registered balancing authorities that are parties

153

INCITE Program Doles Out Hours on Supercomputers | Department of Energy  

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

INCITE Program Doles Out Hours on Supercomputers INCITE Program Doles Out Hours on Supercomputers INCITE Program Doles Out Hours on Supercomputers November 5, 2012 - 1:30pm Addthis Mira, the 10-petaflop IBM Blue Gene/Q system at Argonne National Laboratory, is capable of carrying out 10 quadrillion calculations per second. Each year researchers apply to the INCITE program to get to use this machine's incredible computing power. | Photo courtesy of Argonne National Lab. Mira, the 10-petaflop IBM Blue Gene/Q system at Argonne National Laboratory, is capable of carrying out 10 quadrillion calculations per second. Each year researchers apply to the INCITE program to get to use this machine's incredible computing power. | Photo courtesy of Argonne National Lab. Charles Rousseaux Charles Rousseaux Senior Writer, Office of Science

154

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

155

Helium Refrigerator Design for Pulsed Heat Load in Tokamaks  

SciTech Connect (OSTI)

Nuclear fusion reactors of the Tokamak type will be operated in a pulsed mode requiring the helium refrigerator to remove periodically large heat loads in time steps of approximately one hour. What are the necessary steps for a refrigerator to cope with such load variations?A series of numerical simulations has been performed indicating the possibility of an active refrigerator control with low exergetic losses. A basic comparison is made between the largest existing refrigerator sizes and the size required to service for example the ITER requirements.

Kuendig, A.; Schoenfeld, H. [Linde Kryotechnik AG, Dattlikonerstrasse 5, CH-8422 Pfungen (Switzerland)

2006-04-27T23:59:59.000Z

156

BIOLOGY 650 (credit 2 hours) Animal Physiology LABORATORY  

E-Print Network [OSTI]

BIOLOGY 650 (credit 2 hours) Animal Physiology LABORATORY Spring 2011 Instructor: ROBIN COOPER , Ph role of ion channels and transporters in regulation of the membrane potential will be covered in great-neuron communication through electrical and chemical synapses will be examined in live preparations. The historical

Cooper, Robin L.

157

Aegis Combat and Weapon Systems Overview 24 hours, $1495  

E-Print Network [OSTI]

Aegis Combat and Weapon Systems Overview 24 hours, $1495 Launched from the Advanced Surface Missile that led to the initiation of Aegis. Topics Include: · AegisOverviewandHistory · AegisBMD · AegisWeaponSEprocessensuresthatsystemsaredevelopedtomeet affordable, operationally effective, and timely mission objectives. FocusonengineeringtheWeapon

Fork, Richard

158

BRASENOSE COLLEGE 8-HOUR STIPENDIARY LECTURERSHIP IN PHILOSOPHY  

E-Print Network [OSTI]

BRASENOSE COLLEGE OXFORD 8-HOUR STIPENDIARY LECTURERSHIP IN PHILOSOPHY FURTHER PARTICULARS in Philosophy at Brasenose College, Oxford. The post is tenable from 1 October 2013 (finishing date: 31st information about the College can be found at www.bnc.ox.ac.uk. Brasenose has a strong tradition in Philosophy

Oxford, University of

159

Folding Proteins at 500 ns/hour with Work Queue  

E-Print Network [OSTI]

in part to the unbiased nature of these simulations: the low-energy regions of the free-energy landscape to achieve an aggregate sampling rate of over 500 ns/hour. As a comparison, a single process typically are oversampled while the (arguably more interesting) high-energy tran- sition regions are rarely observed

Thain, Douglas

160

Credit Based; Intermediate Swimming Credit/Hours Class  

E-Print Network [OSTI]

Center Pool Course Description: Intermediate stroke and swimming skills Prerequisites: Must have by swimming laps during open swim/lap swim at MSU pool. Lap swim times are available online or at the frontCredit Based; Intermediate Swimming Credit/Hours Class Title Lead Instructor Phone Email Office

Maxwell, Bruce D.

Note: This page contains sample records for the topic "hourly load profile" 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

Credit Based; Intermediate Swimming Credit/Hours Class  

E-Print Network [OSTI]

at the meet. 3) Swim laps during open swim/lap swim at MSU pool. A sheet will be posted on D2l that you. Emergency phone B. Pool Rules C key swimming skills 1. Breathing 2. Floating/body position 3. Treading waterCredit Based; Intermediate Swimming Credit/Hours Class Title Lead Instructor Phone Email Office

Maxwell, Bruce D.

162

Pay and Leave Administration and Hours of Duty  

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

The order establishes requirements and responsibilities for the management of pay, including overtime pay and compensatory time, leave administration, time and attendance reporting, and hours of duty. Cancels DOE O 322.1B and DOE O 535.1. Admin Chg 1, dated 5-10-12, cancels DOE O 322.1C.

2011-01-19T23:59:59.000Z

163

Open Automated Demand Response Communications in Demand Response for Wholesale Ancillary Services  

E-Print Network [OSTI]

shows how the actual load profile follows the hourly bidscriteria were as follows: Low load variability – enhancesloads, the actual loads do not closely follow the forecasted

Kiliccote, Sila

2010-01-01T23:59:59.000Z

164

Regression Models for Demand Reduction based on Cluster Analysis of Load  

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

165

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

166

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

167

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

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

168

MTS Table Top Load frame  

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

169

PWR AXIAL BURNUP PROFILE ANALYSIS  

SciTech Connect (OSTI)

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

170

LANSCE | News & Media | Profiles  

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

171

EIA - State Electricity Profiles  

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

172

Management's Discussion & Analysis Profile  

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

173

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...

174

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

175

20140301-0331_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Mar to 31 Mar 2014.

Thibedeau, Joe

2014-04-07T23:59:59.000Z

176

20140601-0630_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 June to 30 June 2014.

Thibedeau, Joe

2014-06-30T23:59:59.000Z

177

20140701-0731_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 July to 31 July 2014.

Thibedeau, Joe

2014-07-31T23:59:59.000Z

178

20131201-1231_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Dec to 31 Dec 2013.

Thibedeau, Joe

2014-01-08T23:59:59.000Z

179

20140201-0228_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Feb to 28 Feb 2014.

Thibedeau, Joe

2014-03-03T23:59:59.000Z

180

20140501-0531_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 May to 31 May 2014.

Thibedeau, Joe

2014-06-02T23:59:59.000Z

Note: This page contains sample records for the topic "hourly load profile" 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

20131101-1130_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Nov to 30 Nov 2013.

Thibedeau, Joe

2013-12-02T23:59:59.000Z

182

20130801-0831_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 8/1/13 to 8/31/13.

Vanderhoff, Alex

2013-09-10T23:59:59.000Z

183

20130901-0930_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 1 September 2013 to 30 September 2013.

Thibedeau, Joe

2013-10-25T23:59:59.000Z

184

20131001-1031_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 1 Oct 2013 to 31 Oct 2013.

Thibedeau, Joe

2013-11-05T23:59:59.000Z

185

20140101-0131_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Jan to 31 Jan 2014.

Thibedeau, Joe

2014-02-03T23:59:59.000Z

186

20130501-20130531_Green Machine Florida Canyon Hourly Data  

SciTech Connect (OSTI)

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from May 2013

Vanderhoff, Alex

2013-06-18T23:59:59.000Z

187

20140201-0228_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Feb to 28 Feb 2014.

Thibedeau, Joe

188

20131101-1130_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Nov to 30 Nov 2013.

Thibedeau, Joe

189

20140301-0331_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Mar to 31 Mar 2014.

Thibedeau, Joe

190

20131001-1031_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 1 Oct 2013 to 31 Oct 2013.

Thibedeau, Joe

191

20140601-0630_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 June to 30 June 2014.

Thibedeau, Joe

192

20131201-1231_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Dec to 31 Dec 2013.

Thibedeau, Joe

193

20130801-0831_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 8/1/13 to 8/31/13.

Vanderhoff, Alex

194

20130501-20130531_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from May 2013

Vanderhoff, Alex

195

20140701-0731_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 July to 31 July 2014.

Thibedeau, Joe

196

20140101-0131_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Jan to 31 Jan 2014.

Thibedeau, Joe

197

20140501-0531_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 May to 31 May 2014.

Thibedeau, Joe

198

20130901-0930_Green Machine Florida Canyon Hourly Data  

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

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 1 September 2013 to 30 September 2013.

Thibedeau, Joe

199

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Cuba from NREL Cuba from NREL Dataset Summary Description (Abstract): Each data file is a set of hourly values of solar radiation and meteorological elements for a 1-year period. Solar radiation is modeled using the NREL METSTAT model, with surface observed cloud cover being the principal model input. Each container file contains up to 30 yearly files for one station, plus the Typical Meteorological Year (TMY) file for the selected station, plus documentation files and a TMY data reader file for use with Microsoft Excel. (Purpose): Simulations (Supplemental Information): The intended use of these data files is for computer simulations of solar energy conversion systems and building systems. The yearly data may be suitable for designing systems and their components to meet the worst-case conditions occurring at a location, if enough years of data are present. The TMY consists of months selected from individual years and concatenated to form a complete year.. Because of the selection criteria, these TMYs are not appropriate for simulations of wind energy conversion systems. A TMY provides a standard for hourly data for solar radiation and other meteorological elements that permit performance comparisons of system types and configurations for one or more locations. A TMY is not necessarily a good indicator of conditions over the next year, or even the next 5 years. Rather, it represents conditions judged to be typical over a long period of time, such as 30 years.

200

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Nepal from NREL Nepal from NREL Dataset Summary Description (Abstract): Each data file is a set of hourly values of solar radiation and meteorological elements for a 1-year period. Solar radiation is modeled using the NREL METSTAT model, with surface observed cloud cover being the principal model input. Each container file contains up to 30 yearly files for one station, plus the Typical Meteorological Year (TMY) file for the selected station, plus documentation files and a TMY data reader file for use with Microsoft Excel. (Purpose): Simulations (Supplemental Information): The intended use of these data files is for computer simulations of solar energy conversion systems and building systems. The yearly data may be suitable for designing systems and their components to meet the worst-case conditions occurring at a location, if enough years of data are present. The TMY consists of months selected from individual years and concatenated to form a complete year.. Because of the selection criteria, these TMYs are not appropriate for simulations of wind energy conversion systems. A TMY provides a standard for hourly data for solar radiation and other meteorological elements that permit performance comparisons of system types and configurations for one or more locations. A TMY is not necessarily a good indicator of conditions over the next year, or even the next 5 years. Rather, it represents conditions judged to be typical over a long period of time, such as 30 years.

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


201

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Kenya from NREL Kenya from NREL Dataset Summary Description (Abstract): Each data file is a set of hourly values of solar radiation and meteorological elements for a 1-year period. Solar radiation is modeled using the NREL METSTAT model, with surface observed cloud cover being the principal model input. Each container file contains up to 30 yearly files for one station, plus the Typical Meteorological Year (TMY) file for the selected station, plus documentation files and a TMY data reader file for use with Microsoft Excel. (Purpose): Simulations (Supplemental Information): The intended use of these data files is for computer simulations of solar energy conversion systems and building systems. The yearly data may be suitable for designing systems and their components to meet the worst-case conditions occurring at a location, if enough years of data are present. The TMY consists of months selected from individual years and concatenated to form a complete year.. Because of the selection criteria, these TMYs are not appropriate for simulations of wind energy conversion systems. A TMY provides a standard for hourly data for solar radiation and other meteorological elements that permit performance comparisons of system types and configurations for one or more locations. A TMY is not necessarily a good indicator of conditions over the next year, or even the next 5 years. Rather, it represents conditions judged to be typical over a long period of time, such as 30 years.

202

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

China from NREL China from NREL Dataset Summary Description (Abstract): Each data file is a set of hourly values of solar radiation and meteorological elements for a 1-year period. Solar radiation is modeled using the NREL METSTAT model, with surface observed cloud cover being the principal model input. Each container file contains up to 30 yearly files for one station, plus the Typical Meteorological Year (TMY) file for the selected station, plus documentation files and a TMY data reader file for use with Microsoft Excel. (Purpose): Simulations (Supplemental Information): The intended use of these data files is for computer simulations of solar energy conversion systems and building systems. The yearly data may be suitable for designing systems and their components to meet the worst-case conditions occurring at a location, if enough years of data are present. The TMY consists of months selected from individual years and concatenated to form a complete year. Because of the selection criteria, these TMYs are not appropriate for simulations of wind energy conversion systems. A TMY provides a standard for hourly data for solar radiation and other meteorological elements that permit performance comparisons of system types and configurations for one or more locations. A TMY is not necessarily a good indicator of conditions over the next year, or even the next 5 years. Rather, it represents conditions judged to be typical over a long period of time, such as 30 years.

203

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Bangladesh stations from NREL Bangladesh stations from NREL Dataset Summary Description (Abstract): Each data file is a set of hourly values of solar radiation and meteorological elements for a 1-year period. Solar radiation is modeled using the NREL METSTAT model, with surface observed cloud cover being the principal model input. Each container file contains up to 30 yearly files for one station, plus the Typical Meteorological Year (TMY) file for the selected station, plus documentation files and a TMY data reader file for use with Microsoft Excel. (Purpose): Simulations (Supplemental Information): The intended use of these data files is for computer simulations of solar energy conversion systems and building systems. The yearly data may be suitable for designing systems and their components to meet the worst-case conditions occurring at a location, if enough years of data are present. The TMY consists of months selected from individual years and concatenated to form a complete year.. Because of the selection criteria, these TMYs are not appropriate for simulations of wind energy conversion systems. A TMY provides a standard for hourly data for solar radiation and other meteorological elements that permit performance comparisons of system types and configurations for one or more locations. A TMY is not necessarily a good indicator of conditions over the next year, or even the next 5 years. Rather, it represents conditions judged to be typical over a long period of time, such as 30 years.

204

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

205

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

206

FINAL PROJECT REPORT LOAD MODELING TRANSMISSION RESEARCH  

E-Print Network [OSTI]

at PSE is to collect load data for validating dynamic and approach 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

207

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

208

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

209

Examination of shaped charge liner shock loading  

SciTech Connect (OSTI)

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

210

High efficiency motor program impact assessment: Load analysis  

SciTech Connect (OSTI)

Incentive programs that encourage customers to purchase new or replacement high efficiency motors (HEM) are an element of many utilities DSM efforts. Such a program has been in place at Ontario Hydro since late 1989. The program was expected to rebate up to 800,000 HP over its five year duration. This paper reports on the results of a recently completed load analysis study to assess the load impacts of the program. The findings are based on field metering of integral HP, three-phase induction motors up to 500HP in size, at thirty industrial sites. Using a database of manufacturers`reported effiiencies, loadings and operating times for each of 181 standard and high efficiency motors are estimated. The results will be used as part of program impact evaluation. They indicate lower motor loadings and longer operating hours than had been assumed for interim evaluation. The paper provides detailed estimates of loading by HP group, industrial segment, and end-use. Issues in sample design, field metering and extrapolation to the rebated motor population are also discussed.

Whiting, R. Sr.

1995-12-31T23:59:59.000Z

211

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Honduras from SUNY Honduras from SUNY Dataset Summary Description (Abstract): Zip file contains year-site specific files including time series of global, direct and diffuse irradiance (Purpose): The time series are useful for performing site specific simulation of customized solar energy systems (Supplemental Information): Each file's name identifies year and location, by listing Country_City_latitude-longitude_year, e.g., EL_SALVADOR_San_Salvador_13.75-89.15_98.out is for the city of San Salvador, in El Salvador, latitude 13.75 degrees, longitude -89.15 degrees, year 1998. The content of each file includes A one line header, listing latitude, longitude and ground elevation in meters,Hourly records including, year, month, day, time (GMT), global irradiance, direct irradiance and

212

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Brazil from NREL Brazil from NREL Dataset Summary Description (Abstract): Each data file is a set of hourly values of solar radiation and meteorological elements for a 1-year period. Solar radiation is modeled using the NREL METSTAT model, with surface observed cloud cover being the principal model input. Each container file contains up to 30 yearly files for one station, plus the Typical Meteorological Year (TMY) file for the selected station, plus documentation files and a TMY data reader file for use with Microsoft Excel. (Purpose): Simulations (Supplemental Information): The intended use of these data files is for computer simulations of solar energy conversion systems and building systems. The yearly data may be suitable for designing systems and their components to meet the worst-case conditions occurring at a

213

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Nicaragua from SUNY Nicaragua from SUNY Dataset Summary Description (Abstract): Zip file contains year-site specific files including time series of global, direct and diffuse irradiance (Purpose): The time series are useful for performing site specific simulation of customized solar energy systems (Supplemental Information): Each file's name identifies year and location, by listing Country_City_latitude-longitude_year, e.g., EL_SALVADOR_San_Salvador_13.75-89.15_98.out is for the city of San Salvador, in El Salvador, latitude 13.75 degrees, longitude -89.15 degrees, year 1998. The content of each file includes A one line header, listing latitude, longitude and ground elevation in meters,Hourly records including, year, month, day, time (GMT), global irradiance, direct irradiance and

214

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Central America from NREL Central America from NREL Dataset Summary Description (Abstract): Each data file is a set of hourly values of solar radiation and meteorological elements for a 1-year period. Solar radiation is modeled using the NREL METSTAT model, with surface observed cloud cover being the principal model input. Each container file contains up to 30 yearly files for one station, plus the Typical Meteorological Year (TMY) file for the selected station, plus documentation files and a TMY data reader file for use with Microsoft Excel. (Purpose): Simulations (Supplemental Information): The intended use of these data files is for computer simulations of solar energy conversion systems and building systems. The yearly data may be suitable for designing systems and their components to meet the worst-case conditions occurring at a

215

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Guatemala from SUNY Guatemala from SUNY Dataset Summary Description (Abstract): Zip file contains year-site specific files including time series of global, direct and diffuse irradiance (Purpose): The time series are useful for performing site specific simulation of customized solar energy systems (Supplemental Information): Each file's name identifies year and location, by listing Country_City_latitude-longitude_year, e.g., EL_SALVADOR_San_Salvador_13.75-89.15_98.out is for the city of San Salvador, in El Salvador, latitude 13.75 degrees, longitude -89.15 degrees, year 1998. The content of each file includes A one line header, listing latitude, longitude and ground elevation in meters,Hourly records including, year, month, day, time (GMT), global irradiance, direct irradiance and

216

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Cuba sites from SUNY Cuba sites from SUNY Dataset Summary Description (Abstract): Zip file contains year-site specific files including time series of global, direct and diffuse irradiance (Purpose): The time series are useful for performing site specific simulation of customized solar energy systems (Supplemental Information): Each file's name identifies year and location, by listing Country_City_latitude-longitude_year, e.g., EL_SALVADOR_San_Salvador_13.75-89.15_98.out is for the city of San Salvador, in El Salvador, latitude 13.75 degrees, longitude -89.15 degrees, year 1998. The content of each file includes A one line header, listing latitude, longitude and ground elevation in meters,Hourly records including, year, month, day, time (GMT), global irradiance, direct irradiance and

217

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Ghana from NREL Ghana from NREL Dataset Summary Description (Abstract): Each data file is a set of hourly values of solar radiation and meteorological elements for a 1-year period. Solar radiation is modeled using the NREL METSTAT model, with surface observed cloud cover being the principal model input. Each container file contains up to 30 yearly files for one station, plus the Typical Meteorological Year (TMY) file for the selected station, plus documentation files and a TMY data reader file for use with Microsoft Excel. (Purpose): Simulations (Supplemental Information): The intended use of these data files is for computer simulations of solar energy conversion systems and building systems. The yearly data may be suitable for designing systems and their components to meet the worst-case conditions occurring at a

218

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Sri Lanka from NREL Sri Lanka from NREL Dataset Summary Description (Abstract): Each data file is a set of hourly values of solar radiation and meteorological elements for a 1-year period. Solar radiation is modeled using the NREL METSTAT model, with surface observed cloud cover being the principal model input. Each container file contains up to 30 yearly files for one station, plus the Typical Meteorological Year (TMY) file for the selected station, plus documentation files and a TMY data reader file for use with Microsoft Excel. (Purpose): Simulations (Supplemental Information): The intended use of these data files is for computer simulations of solar energy conversion systems and building systems. The yearly data may be suitable for designing systems and their components to meet the worst-case conditions occurring at a

219

A stochastic technique for synthesis of hourly precipitation  

E-Print Network [OSTI]

STATES DURING SIX PFRIODS WHEN THE LAST PERIOD IS DRY t-5 t-4 State t-3 During T 11M t-2 t-1 D D D D W W W W D D W W D D W W D W D W D W D W D W D W D W D W 19 fearures and of the daily precipitation record of the... 124 10 80 TABLE 5 FREQUENCIES OF 2-HR SEQUENCES State During Hour (t) 1 2 3 4 5 6 7 8 9 10 136, 330 338 311 198 171 138 65 38 52 30 2 3 416 220 142 68 30 380 170 189 102 50 21 7 6 42 8 7 4 3 9 2 4 0 5 Zl 7 4J 9 209 146 112 29...

Huddle, John Paul

2012-06-07T23:59:59.000Z

220

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

El Salvador sites from SUNY El Salvador sites from SUNY Dataset Summary Description (Abstract): Zip file contains year-site specific files including time series of global, direct and diffuse irradiance (Purpose): The time series are useful for performing site specific simulation of customized solar energy systems (Supplemental Information): Each file's name identifies year and location, by listing Country_City_latitude-longitude_year, e.g., EL_SALVADOR_San_Salvador_13.75-89.15_98.out is for the city of San Salvador, in El Salvador, latitude 13.75 degrees, longitude -89.15 degrees, year 1998. The content of each file includes A one line header, listing latitude, longitude and ground elevation in meters,Hourly records including, year, month, day, time (GMT), global irradiance, direct irradiance and

Note: This page contains sample records for the topic "hourly load profile" 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

Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and  

Open Energy Info (EERE)

Ethiopia from NREL Ethiopia from NREL Dataset Summary Description (Abstract): Each data file is a set of hourly values of solar radiation and meteorological elements for a 1-year period. Solar radiation is modeled using the NREL METSTAT model, with surface observed cloud cover being the principal model input. Each container file contains up to 30 yearly files for one station, plus the Typical Meteorological Year (TMY) file for the selected station, plus documentation files and a TMY data reader file for use with Microsoft Excel. (Purpose): Simulations (Supplemental Information): The intended use of these data files is for computer simulations of solar energy conversion systems and building systems. The yearly data may be suitable for designing systems and their components to meet the worst-case conditions occurring at a

222

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

223

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

224

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

225

Identify Employee Commuting Clusters for Greenhouse Gas Profile |  

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

Identify Employee Commuting Clusters for Greenhouse Gas Profile Identify Employee Commuting Clusters for Greenhouse Gas Profile Identify Employee Commuting Clusters for Greenhouse Gas Profile October 7, 2013 - 1:53pm Addthis YOU ARE HERE: Step 2 For evaluating a greenhouse gas profile for employee commuting, use survey data on employee home location and arrival/departure times to identify geographic areas to target for vanpool and carpool ride-matching efforts. Those who live in close proximity or en route to the workplace and with similar hours may be clustered to determine which locations might represent the best candidates for ride-share matching. As illustrated in Figure 1, areas with higher concentrations of employees that live farther from the worksite might be good candidate locations for targeted carpool and vanpool

226

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

227

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

228

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

229

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

230

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

231

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

232

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

233

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

234

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

235

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

236

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

237

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

238

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

239

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

240

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

Note: This page contains sample records for the topic "hourly load profile" from the National Library of EnergyBeta (NLEBeta).
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We encourage you to perform a real-time search of NLEBeta
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241

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

242

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

243

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

244

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

245

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

246

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

247

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

248

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

249

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

250

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

251

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

252

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

253

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

254

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

255

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

256

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

257

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

258

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

259

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

260

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

Note: This page contains sample records for the topic "hourly load profile" 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 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

262

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

263

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

264

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

265

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

266

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

267

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

268

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

269

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

270

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

271

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

272

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

273

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

274

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

275

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

276

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

277

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

278

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

279

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

280

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

Note: This page contains sample records for the topic "hourly load profile" 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

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

282

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

283

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

284

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

285

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

286

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

287

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

288

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

289

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

290

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

291

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

292

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

293

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

294

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

295

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

296

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

297

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

298

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

299

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

300

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...

Note: This page contains sample records for the topic "hourly load profile" 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 Electricity Profiles  

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

302

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

303

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

304

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

305

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

306

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

307

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

308

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

309

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

310

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

311

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

312

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

313

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

314

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

315

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

ScienceCinema (OSTI)

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

Piette, Mary Ann

2011-04-28T23:59:59.000Z

316

Retrieval of hourly records of surface hydrometeorological variables using satellite remote sensing data  

Science Journals Connector (OSTI)

A new algorithm is formulated for retrieving hourly time-series of surface hydrometeorological variables including net radiation, sensible heat flux, and near-surface air temperature aided by hourly visible images from the Geostationary ...

Sanaz Moghim; Andrew Jay Bowen; Sepideh Sarachi; Jingfeng Wang

317

EPA ENERGY STAR Webcast: Portfolio Manager Office Hours, Focus Topic: Sharing Forward and Transfer Ownership  

Broader source: Energy.gov [DOE]

Portfolio Manager "Office Hours" is a live webinar that gives all users an opportunity to ask their questions directly to EPA in an open forum. In 2014, Office Hours will be held once a month. We...

318

TESTING FORM Please deliver exams with envelope & testing form at least 24 hours in advance to  

E-Print Network [OSTI]

TESTING FORM Please deliver exams with envelope & testing form at least 24 hours in advance to: _________________________________ Class Time: __________ - __________ _________ Test Date: _______________________________ Time allotted): ____________________________ INSTRUCTOR PROCEDURES: 1. Please deliver tests to WYLY TOWER 318 at least 24 hours PRIOR to test time

Selmic, Sandra

319

Insights from Smart Meters: The Potential for Peak-Hour Savings from Behavior-Based Programs  

E-Print Network [OSTI]

top graph) as a percent of the total average energy usage ofgraph) as a percentage of each hour’s average energy usagegraph: first, kWh savings; second, normalized savings as a percent of the total average energy usage

Todd, Annika

2014-01-01T23:59:59.000Z

320

EPA ENERGY STAR Webcast- Portfolio Manager Office Hours, Focus Topic: Weather Data and Metrics  

Broader source: Energy.gov [DOE]

Portfolio Manager "Office Hours" is a live webinar that gives all users an opportunity to ask their questions directly to EPA in an open forum. In 2014, Office Hours will be held once a month. We...

Note: This page contains sample records for the topic "hourly load profile" 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

Fuel Cell Stacks Still Going Strong After 5,000 Hours | Department...  

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

Fuel Cell Stacks Still Going Strong After 5,000 Hours Fuel Cell Stacks Still Going Strong After 5,000 Hours March 24, 2009 - 1:00pm Addthis Washington, DC -- Two fuel cell stacks...

322

A new approach to estimate commercial sector end-use load shapes and energy use intensities  

SciTech Connect (OSTI)

We discuss the application of an end-use load shape estimation technique to develop annual energy use intensities (EUIs) and hourly end-use load shapes (LSs) for commercial buildings in the Pacific Gas and Electric Company (PG&E) service territory. Results will update inputs for the commercial sector energy and peak demand forecasting models used by PG&E and the California Energy Commission (CEC). EUIs were estimated for 11 building types, up to 10 end uses, 3 fuel types, 2 building vintages, and up to 5 climate regions. The integrated methodology consists of two major parts. The first part is the reconciliation of initial end-use load-shape estimates with measured whole-building load data to produce intermediate EUIs and load shapes, using LBL`s End-use Disaggregation Algorithm, EDA. EDA is a deterministic hourly algorithm that relies on the observed characteristics of the measured hourly whole-building electricity use and disaggregates it into major end-use components. The end-use EUIs developed through the EDA procedure represent a snap-shot of electricity use by building type and end-use for two regions of the PG&E service territory, for the year that disaggregation is performed. In the second part of the methodology, we adjust the EUIs for direct application to forecasting models based on factors such as climatic impacts on space-conditioning EUIs, fuel saturation effects, building and equipment vintage, and price impacts. Core data for the project are detailed on-site surveys for about 800 buildings, mail surveys ({approximately}6000), load research data for over 1000 accounts, and hourly weather data for five climate regions.

Akbari, H.; Eto, J.; Konopacki, S.; Afzal, A.; Heinemeier, K.; Rainer, L.

1994-08-01T23:59:59.000Z

323

Minor in Psychology The minor in Psychology requires 18 hours of Psychology coursework as shown below. At least 6 hours of the  

E-Print Network [OSTI]

Minor in Psychology The minor in Psychology requires 18 hours of Psychology coursework as shown on this minor check sheet may be counted toward the Psychology minor. Research Methods/Critical Thinking Skills 1 PSYC Course - 3 hours Term Grade Hrs Qpts General Psychology Lecture (PSYC 1101) with a C

Raja, Anita

324

Dependence of offshore wind turbine fatigue loads on atmospheric stratification  

Science Journals Connector (OSTI)

The stratification of the atmospheric boundary layer (ABL) is classified in terms of the M-O length and subsequently used to determine the relationship between ABL stability and the fatigue loads of a wind turbine located inside an offshore wind farm. Recorded equivalent fatigue loads, representing blade-bending and tower bottom bending, are combined with the operational statistics from the instrumented wind turbine as well as with meteorological statistics defining the inflow conditions. Only a part of all possible inflow conditions are covered through the approximately 8200 hours of combined measurements. The fatigue polar has been determined for an (almost) complete 360° inflow sector for both load sensors, representing mean wind speeds below and above rated wind speed, respectively, with the inflow conditions classified into three different stratification regimes: unstable, neutral and stable conditions. In general, impact of ABL stratification is clearly seen on wake affected inflow cases for both blade and tower fatigue loads. However, the character of this dependence varies significantly with the type of inflow conditions – e.g. single wake inflow or multiple wake inflow.

K S Hansen; G C Larsen; S Ott

2014-01-01T23:59:59.000Z

325

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.

326

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,

327

FINAL PROJECT REPORT LOAD MODELING TRANSMISSION RESEARCH  

E-Print Network [OSTI]

Bulk System Load  Model in GE PSLF TM for Investigating the a Bulk System Load Model in GE PSLF TM for Investigating thecomposite load model in  the PSLF simulation software; the 

Lesieutre, Bernard

2013-01-01T23:59:59.000Z

328

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

329

Question of the Week: How Are You Observing Earth Hour? | Department of  

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

Are You Observing Earth Hour? Are You Observing Earth Hour? Question of the Week: How Are You Observing Earth Hour? March 26, 2009 - 12:16pm Addthis This Saturday, March 28th, people around the world will observe Earth Hour at 8:30 p.m. local time-whatever the local time zone happens to be-by switching off their lights for one hour. While many people are taking part by simply shutting off their lights and lighting some candles, some communities are hosting gatherings or events around Earth Hour. How are you observing Earth Hour? Each Thursday, you have the chance to share your thoughts on a topic related to energy efficiency or renewable energy for consumers. Please e-mail your responses to the Energy Saver team at consumer.webmaster@nrel.gov. Addthis Related Articles Question of the Week: How Will You Save Energy this Spring?

330

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

331

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

332

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.

333

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.

334

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.

335

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.

336

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.

337

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.

338

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.

339

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.

340

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.

Note: This page contains sample records for the topic "hourly load profile" from the National Library of EnergyBeta (NLEBeta).
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341

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.

342

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.

343

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.

344

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.

345

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.

346

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.

347

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.

348

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.

349

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.

350

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.

351

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.

352

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.

353

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.

354

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.

355

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.

356

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.

357

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.

358

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.

359

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.

360

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.

Note: This page contains sample records for the topic "hourly load profile" 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

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.

362

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.

363

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.

364

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.

365

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.

366

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.

367

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.

368

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.

369

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.

370

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.

371

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.

372

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.

373

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.

374

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

375

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

376

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

377

Renewable RFP on behalf of the Navy  

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

price. Please include all factors related to pricing. For an estimated average hourly load profile by month of the aggregated various loads related to this RFP, read the...

378

Puget Sound Area Electric Reliability Plan. Appendix D, Conservation, Load Management and Fuel Switching Analysis : Draft Environmental Impact Statement.  

SciTech Connect (OSTI)

Various conservation, load management, and fuel switching programs were considered as ways to reduce or shift system peak load. These programs operate at the end-use level, such as residential water heat. Figure D-1a shows what electricity consumption for water heat looks like on normal and extreme peak days. Load management programs, such as water heat control, are designed to reduce electricity consumption at the time of system peak. On the coldest day in average winter, system load peaks near 8:00 a.m. In a winter with extremely cold weather, electricity consumption increases fr all hours, and the system peak shifts to later in the morning. System load shapes in the Puget Sound area are shown in Figure D-1b for a normal winter peak day (February 2, 1988) and extreme peak day (February 3, 1989). Peak savings from any program are calculated to be the reduction in loads on the entire system at the hour of system peak. Peak savings for all programs are measured at 8:00 a.m. on a normal peak day and 9:00 a.m. on an extreme peak day. On extremely cold day, some water heat load shifts to much later in the morning, with less load available for shedding at the time of system peak. Models of hourly end-use consumption were constructed to simulate the impact of conservation, land management, and fuel switching programs on electricity consumption. Javelin, a time-series simulating package for personal computers, was chosen for the hourly analysis. Both a base case and a program case were simulated. 15 figs., 7 tabs.

United States. Bonneville Power Administration.

1991-09-01T23:59:59.000Z

379

End-Use Load and Consumer Assessment Program: Analysis of residential refrigerator/freezer performance  

SciTech Connect (OSTI)

The Bonneville Power Administration (Bonneville) is conducting a large end-use data acquisition program in an effort to understand how energy is utilized in buildings with permanent electric space heating equipment in the Pacific Northwest. The initial portion of effort, known as the End-Use Load and Consumer Assessment Program (ELCAP), was conducted for Bonneville by the Pacific Northwest Laboratory (PNL). The collection of detailed end-use data provided an opportunity to analyze the amount of energy consumed by both refrigerators and separate freezers units located in residential buildings. By obtaining this information, the uncertainty of long- term regional end-use forecasting can be improved and potential utility marketing programs for new appliances with a reduced overall energy demand can be identified. It was found that standby loads derived from hourly averages between 4 a.m. and 5 a.m. reflected the minimum consumption needed to maintain interior refrigerator temperatures at a steady-state condition. Next, an average 24-hour consumption that included cooling loads from door openings and cooling food items was also determined. Later, analyses were conducted to develop a model capable of predicting refrigerator standby loads and 24-hour consumption for comparison with national refrigerator label ratings. Data for 140 residential sites with a refrigeration end-use were screened to develop a sample of 119 residences with pure refrigeration for use in this analysis. To identify those refrigerators that were considered to be pure (having no other devices present on the circuit) in terms of their end-use classification, the screening procedure used a statistical clustering technique that was based on standby loads with 24-hour consumption. 5 refs., 18 figs., 4 tabs.

Ross, B.A.

1991-09-01T23:59:59.000Z

380

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

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


381

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

382

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

383

Chemical profiles of switchgrass  

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

384

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

385

{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

386

Earth Hour 2009: March 28, 8:30-9:30 PM Local Time | Department of Energy  

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

Earth Hour 2009: March 28, 8:30-9:30 PM Local Time Earth Hour 2009: March 28, 8:30-9:30 PM Local Time Earth Hour 2009: March 28, 8:30-9:30 PM Local Time March 27, 2009 - 6:00am Addthis John Lippert The city of Greenbelt, Maryland, where I live, is living up to its "green" name by participating in Earth Hour. This global event asks everyone to "go dark" for an hour to make a powerful statement of concern about climate change. The city will be turning off all non-essential lights in municipal buildings. Residents are requested to turn off their lights (and other energy-consuming appliances). The Greenbelt Advisory Committee on Environmental Sustainability, which advises the mayor and city council and which I chair, will be sponsoring a flashlight walk around Old Greenbelt during Earth Hour. My wife and I will

387

Earth Hour 2009: March 28, 8:30-9:30 PM Local Time | Department of Energy  

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

Earth Hour 2009: March 28, 8:30-9:30 PM Local Time Earth Hour 2009: March 28, 8:30-9:30 PM Local Time Earth Hour 2009: March 28, 8:30-9:30 PM Local Time March 27, 2009 - 6:00am Addthis John Lippert The city of Greenbelt, Maryland, where I live, is living up to its "green" name by participating in Earth Hour. This global event asks everyone to "go dark" for an hour to make a powerful statement of concern about climate change. The city will be turning off all non-essential lights in municipal buildings. Residents are requested to turn off their lights (and other energy-consuming appliances). The Greenbelt Advisory Committee on Environmental Sustainability, which advises the mayor and city council and which I chair, will be sponsoring a flashlight walk around Old Greenbelt during Earth Hour. My wife and I will

388

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 100 mm to 400 mm, 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: 15 mm, 50 mm, and 100 mm. 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.

Lourenço Almeida Fernandes; José Gonilha; João R. Correia; Nuno Silvestre; Francisco Nunes

2015-01-01T23:59:59.000Z

389

Recreation Pool Hours and Availability for Rochester INDIVIDUAL GUEST FEES WILL APPLY AT FACILITIES LISTED  

E-Print Network [OSTI]

Recreation Pool Hours and Availability for Rochester INDIVIDUAL GUEST FEES WILL APPLYSp_aquatic.pdf Perinton http://www.perinton.org/Departments/Recreation/PCC Pittsford Pages 1012 http

Portman, Douglas

390

Intra-hour wind power variability assessment using the conditional range metric : quantification, forecasting and applications.  

E-Print Network [OSTI]

??The research presented herein concentrates on the quantification, assessment and forecasting of intra-hour wind power variability. Wind power is intrinsically variable and, due to the… (more)

Boutsika, Thekla

2013-01-01T23:59:59.000Z

391

E-Print Network 3.0 - after-hours care instructions Sample Search...  

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

after hours access? yes no AUP Number... Supervisor's Signature Submitted Occupational Health Form to Animal Care and Use 608 Boyd Graduate Studied... Building ... Source:...

392

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

393

An assessment of electrical load forecasting using artificial neural network  

Science Journals Connector (OSTI)

The forecasting of electricity demand has become one of the major research fields in electrical engineering. The supply industry requires forecasts with lead times, which range from the short term (a few minutes, hours, or days ahead) to the long term (up to 20 years ahead). The major priority for an electrical power utility is to provide uninterrupted power supply to its customers. Long term peak load forecasting plays an important role in electrical power systems in terms of policy planning and budget allocation. This paper presents a peak load forecasting model using artificial neural networks (ANN). The approach in the paper is based on multi-layered back-propagation feed forward neural network. For annual forecasts, there should be 10 to 12 years of historical monthly data available for each electrical system or electrical buss. A case study is performed by using the proposed method of peak load data of a state electricity board of India which maintain high quality, reliable, historical data providing the best possible results. Model's quality is directly dependent upon data integrity.

V. Shrivastava; R.B. Misra; R.C. Bansal

2012-01-01T23:59:59.000Z

394

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

395

Project Cost Profile Spreadsheet | Department of Energy  

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

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

396

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

397

PASSIVE DETECTION OF VEHICLE LOADING  

SciTech Connect (OSTI)

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

398

Sample 8 Semester Plan for NRES Students need 130 hours to graduate.  

E-Print Network [OSTI]

resource systems with emphasis on the ecology, biology, conservation, and management of fish and wildlifeSample 8 Semester Plan for NRES Students need 130 hours to graduate. Year 11 Fall Semester ACES 101 Public Speaking2 IB 103 Intro to Plant Biology Statistics3 or Cultural Studies4 Total Hours Hrs 3 1 3-4 4

Kent, Angela

399

Optimal Multi-scale Capacity Planning under Hourly Varying Electricity Prices  

E-Print Network [OSTI]

1 Optimal Multi-scale Capacity Planning under Hourly Varying Electricity Prices Sumit Mitra Ignacio;2 Motivation of this work · Deregulation of the electricity markets caused electricity prices to be highly? (retrofit) · Challenge: Multi-scale nature of the problem! Hourly varying electricity prices vs. 10-15 years

Grossmann, Ignacio E.

400

STUDENT HOURLY OFFICE ASSISTANT Position available with the History of Cartography Project  

E-Print Network [OSTI]

STUDENT HOURLY OFFICE ASSISTANT Position available with the History of Cartography Project Hours · Must be enrolled UW student; work study funding accepted · Experience with Word, Excel, database To apply, submit a detailed letter of application and resume to Beth Freundlich at: History of Cartography

Wisconsin at Madison, University of

Note: This page contains sample records for the topic "hourly load profile" 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

A Seven-Year Wind Profiler–Based Climatology of the Windward Barrier Jet along California’s Northern Sierra Nevada  

Science Journals Connector (OSTI)

This wind profiler–based study highlights key characteristics of the barrier jet along the windward slope of California’s Sierra Nevada. Between 2000 and 2007 roughly 10% of 100 000 hourly wind profiles, recorded at two sites, satisfied the ...

Paul J. Neiman; Ellen M. Sukovich; F. Martin Ralph; Mimi Hughes

2010-04-01T23:59:59.000Z

402

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.

403

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.

404

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.

405

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.

406

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.

407

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.

408

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.

409

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.

410

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.

411

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.

412

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.

413

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.

414

Derivation of 24-Hour Average SO2, Background for the Update 1 Report |  

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

Derivation of 24-Hour Average SO2, Background for the Update 1 Derivation of 24-Hour Average SO2, Background for the Update 1 Report Derivation of 24-Hour Average SO2, Background for the Update 1 Report Docket No. EO-05-01. As supporting documentation for "Update 1 to: A Dispersion Modeling Analysis of Downwash from Mirant's Potomac River Power Plant: Modeling Unit 1 Emissions in a Cycling Mode" this memo documents the fact that the observed 24-hour SO2 background concentrations during periods when meteorological conditions produce the highest impacts from Unit 1. Derivation of 24-Hour Average SO2, Background for the Update 1 Report More Documents & Publications Review of the ENSR Report Titled "Update 1 to: A Dispersion Modeling Analysis of Downwash from Mirant's Potomac River Power Plant"

415

Mirant: Ambient 24 Hour SO2 Values: Model vs Monitor | Department of Energy  

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

Mirant: Ambient 24 Hour SO2 Values: Model vs Monitor Mirant: Ambient 24 Hour SO2 Values: Model vs Monitor Mirant: Ambient 24 Hour SO2 Values: Model vs Monitor Docket No. EO-05-01: Mirant: Ambient 24 Hour SO2 Values: Model vs Monitor, March 2002 to November 2004, showing the model overprediction Mirant: Ambient 24 Hour SO2 Values: Model vs Monitor More Documents & Publications Comments on Department of Energy's Emergency Order To Resume Limited Operation at Mirant's Potomac River Generating Station and Proposed Mirant Compliance Plan Answer of Potomac Electric Power Company and PJM lnterconnection, L.L.C. to the October 6, 2005 motion filed by the Virginia Department of Environmental Quality Special Environmental Analysis For Actions Taken under U.S. Department of Energy Emergency Orders Regarding Operation of the Potomac River Generating

416

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

417

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

SciTech Connect (OSTI)

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

418

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 ...

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

2014-09-01T23:59:59.000Z

419

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

420

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

Note: This page contains sample records for the topic "hourly load profile" 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

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

422

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

423

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

424

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

425

1994 Pacific Northwest Loads and Resources Study.  

SciTech Connect (OSTI)

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

426

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.

427

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.

428

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

429

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

430

Test profiles for stationary energy storage applications  

SciTech Connect (OSTI)

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

431

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

432

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

433

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

434

Average Data for Each Choke Setting (before 24-May 2010 06:00), 6-hour average (  

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

Average Data for Each Choke Setting (before 24-May 2010 06:00), 6-hour average (after 24-May 2010 06:00):" Average Data for Each Choke Setting (before 24-May 2010 06:00), 6-hour average (after 24-May 2010 06:00):" ,,"Choke","Average","Average","Fluid","Methanol","Water","Oil","Gas","Hyd. Eq.","Gas" ,"Choke","Setting","Upstream","Upstream","Recovery","Recovery","Recovery","Recovery","Recovery","Recovery","Recovery" "Date and Time","Setting","Duration","Pressure","Temp.","Rate","Rate","Rate","Rate","Rate","Rate","Portion" "dd-mmm-yy","(64ths)","(hours)","(psia)","(degF)","(bfpd)","(bfpd)","(bwpd)","(bopd)","(mmcfpd)","(boepd)","(%)"

435

Calibration of Predicted Hourly Zone-Level Supply Air Flows with Measurements  

E-Print Network [OSTI]

the chemical composition, then sends a signal to the control system to increase the ventilation rate, if necessary. This system cannot be modeled in eQuest. The null hypothesis H0 is true only if the t-value is less than tcritical; if t-value is greater..., daily and monthly calibration analysis: CV-RMSE[%] vs. t-test CV-RMSE [%] Zone Interval Time step t t,cr 2.1 NE Summer Hourly 18.8 Daily 9.5 Monthly 4.2 3 days Hourly 24.2 2.4 SW Summer Hourly 28.4 Daily 12.7 Monthly 4...

Mihai, A.; Zmeureanu, R.

2013-01-01T23:59:59.000Z

436

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.

437

Evaluate Greenhouse Gas Emissions Profile  

Broader source: Energy.gov [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.

438

Effect of load-sharing operation strategy on the aggregate performance of existed multiple-chiller systems  

Science Journals Connector (OSTI)

Abstract This paper examines the effect of load-sharing operation strategies on the aggregate performance for existing multiple-chiller system under different partial loads and environmental conditions. The various tested load-sharing operation strategies obtain aggregate performance from 1.64 to 2.18 during the day hours and from 1.06 to 1.41 for the full day indicating significant effect of the operation strategies on the aggregate performance. The conventional (same part load ratio) strategies attain aggregate performance that is lower than the best strategy by 22–33%. At very low system partial load, the performance of the multiple-chiller system falls to less than quarter its value at large load whereas the performance of individual chiller drops to about one sixth of its large load value. The load sharing strategy is influenced by many parameters such as the condition of the chillers and compressors, the piping arrangement, and the heat loss from the chilled water piping where these parameters may overwhelm the individual chiller performance. Accordingly, the load-sharing operation strategy may vary from case to another and should be periodically examined to verify proper system operation, rectify the existing chiller performance and identify chiller faults. Therefore, the need for maintenance can be predicted and the standby chiller may be eliminated.

Hosny Z. Abou-Ziyan; Ali F. Alajmi

2014-01-01T23:59:59.000Z

439

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

440

APS high heat load monochromator  

SciTech Connect (OSTI)

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

Note: This page contains sample records for the topic "hourly load profile" 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

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

442

1993 Pacific Northwest Loads and Resources Study.  

SciTech Connect (OSTI)

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

443

Titanium tritide radioisotope heat source development : palladium-coated titanium hydriding kinetics and tritium loading tests.  

SciTech Connect (OSTI)

We have found that a 180 nm palladium coating enables titanium to be loaded with hydrogen isotopes without the typical 400-500 C vacuum activation step. The hydriding kinetics of Pd coated Ti can be described by the Mintz-Bloch adherent film model, where the rate of hydrogen absorption is controlled by diffusion through an adherent metal-hydride layer. Hydriding rate constants of Pd coated and vacuum activated Ti were found to be very similar. In addition, deuterium/tritium loading experiments were done on stacks of Pd coated Ti foil in a representative-size radioisotope heat source vessel. The experiments demonstrated that such a vessel could be loaded completely, at temperatures below 300 C, in less than 10 hours, using existing department-of-energy tritium handling infrastructure.

Van Blarigan, Peter; Shugard, Andrew D.; Walters, R. Tom (Savannah River National Labs, Aiken, SC)

2012-01-01T23:59:59.000Z

444

Integrated estimation of commercial sector end-use load shapes and energy use intensities  

SciTech Connect (OSTI)

The Southern California Edison Company (SCE) and the California Energy Commission (CEC) have contracted with Energy Analysis Program of the Applied Science Division at the Lawrence Berkeley Laboratory (LBL) to develop an integrated set of commercial sector load shapes (LS) and energy utilization indices (EUI) for use in forecasting electricity demand. The overall objectives of this project are to conduct detailed analyses of SCE data on commercial building characteristics, energy use, and whole-building load shapes, and, in conjunction with other data, to develop, test, and apply an integrated approach for the estimation of end-use LSs and EUIs. The project is one of the first attempts ever to combine simulation-based, prototypical building analyses with direct reconciliation to measured hourly load data.

Akbari, H.; Eto, J.; Turiel, I.; Heinemeier, K.; Lebot, B.; Nordman, B.; Rainer, L.

1989-01-01T23:59:59.000Z

445

An Evaluation of the Water Heater Load Potential for Providing Regulation Service  

SciTech Connect (OSTI)

This paper investigates the possibility of providing aggregated regulation services with small loads, such as water heaters or air conditioners. A direct-load control algorithm is presented to aggregate the water heater load for the purpose of regulation. A dual-element electric water heater model is developed, which accounts for both thermal dynamics and users’ water consumptions. A realistic regulation signal was used to evaluate the number of water heaters needed and the operational characteristics of a water heater when providing 2-MW regulation service. Modeling results suggest that approximately 33,333 water heaters are needed to provide a 2-MW regulation service 24 hours a day. However, if water heaters only provide regulation from 6:00 to 24:00, approximately 20,000 will be needed. Because the control algorithm has considered the thermal setting of the water heater, the customer comfort is obstructed little. Therefore, the aggregated regulation service provided by water heater loads can become a major source of revenue for load-service entities when the smart grid enables the direct load control.

Kondoh, Junji; Lu, Ning; Hammerstrom, Donald J.

2011-08-31T23:59:59.000Z

446

Analysis of combined cooling, heating, and power systems under a compromised electric–thermal load strategy  

Science Journals Connector (OSTI)

Abstract Following the electric load (FE) and following the thermal load (FT) strategies both have advantages and disadvantages for combined cooling, heating and power (CCHP) systems. In this paper, the performance of different strategies is evaluated under operation cost (OC), carbon dioxide emission (CDE) and exergy efficiency (EE). Analysis of different loads in one hour is conducted under the assumption that the additional electricity is not allowed to be sold back to the grid. The results show that FE produces less OC, less CDE, and FT produces higher EE when the electric load is larger. However, FE produces less OC, less CDE and higher EE when the thermal load is larger. Based on a hybrid electric–thermal load (HET) strategy, compromised electric–thermal (CET) strategies are innovatively proposed using the efficacy coefficient method. Additional, the CCHP system of a hotel in Tianjin is analyzed for all of the strategies. The results for an entire year indicate the first CET strategy is the optimal one when dealing with OC, CDE and EE. And the second CET is the optimal one when dealing with OC and EE. Moreover, the laws are strictly correct for different buildings in qualitative terms.

Gang Han; Shijun You; Tianzhen Ye; Peng Sun; Huan Zhang

2014-01-01T23:59:59.000Z

447

DOE Awards 265 Million Hours of Supercomputing Time to Advance Leading  

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

265 Million Hours of Supercomputing Time to Advance 265 Million Hours of Supercomputing Time to Advance Leading Scientific Research Projects DOE Awards 265 Million Hours of Supercomputing Time to Advance Leading Scientific Research Projects January 17, 2008 - 10:38am Addthis WASHINGTON, DC -The U.S. Department of Energy's (DOE) Office of Science today announced that 265 million processor-hours were awarded to 55 scientific projects, the largest amount of supercomputing resource awards donated in the Department's history and three times that of last year's award. The projects-with applications from aeronautics to astrophysics, and from climate change to combustion research-were chosen based on their potential breakthroughs in the science and engineering research and their suitability of the project for using supercomputers. These awards will

448

Oak Ridge: Approaching 4 Million Safe Work Hours | Department of Energy  

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

Ridge: Approaching 4 Million Safe Work Hours Ridge: Approaching 4 Million Safe Work Hours Oak Ridge: Approaching 4 Million Safe Work Hours March 11, 2013 - 12:03pm Addthis Safety inspections are a key element in a nuclear cleanup environment with large pieces of cleanup equipment. Inspections are essential to continuing safety success and reaching new milestones.| Photo courtesy of Oak Ridge Safety inspections are a key element in a nuclear cleanup environment with large pieces of cleanup equipment. Inspections are essential to continuing safety success and reaching new milestones.| Photo courtesy of Oak Ridge David Sheeley Editor/Writer for Environmental Management's Office of External Affairs Workers at URS | CH2M Oak Ridge (UCOR), the prime contractor for EM's Oak Ridge cleanup, are approaching a milestone of 4 million safe work hours

449

Solar: hourly global horizontal (GHI) and direct normal (DNI) data for  

Open Energy Info (EERE)

Ethiopia from DLR Ethiopia from DLR Dataset Summary Description (Abstract): Hourly time series of GHI and DNI for the years 2000, 2001 and 2002 for selected sites in Ethiopia. The hourly data are stored in ASCII files for each station. Please read the documentation file for additional information. (Purpose): For the selected sites, the hourly time series can be used for the simulation of Photovoltaic (PV)-systems or Concentrating Solar Power (CSP)-systems. Source DLR - Deutsches Zentrum für Luft- und Raumfahrt Date Released October 31st, 2004 (10 years ago) Date Updated November 01st, 2007 (7 years ago) Keywords DLR DNI GHI hourly data solar SWERA TILT UNEP Data application/zip icon Download data (zip, 2.1 MiB) Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage

450

WIPP Workers Reach Two Million Man-Hours Without a Lost-Time Accident  

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

Workers Reach Two Million Man-Hours Workers Reach Two Million Man-Hours Without a Lost-Time Accident CARLSBAD, N.M., February 22, 2001 - Workers at the U.S. Department of Energy's (DOE) Waste Isolation Pilot Plant (WIPP) reached a safety milestone Feb. 19 by working two million man-hours without a lost-time accident. According to the National Safety Council, facilities with the same industry code as WIPP lose an average of 20.6 workdays (or 164.8 man-hours) a year to accidents. "Safety is at the core of all WIPP operations," said Dr. Inés Triay, Manager of DOE's Carlsbad Field Office. "We are particularly pleased that WIPP workers reached the two million mark during the time in which they mined a new panel and increased shift work." "To make safety a number one priority means more than creating a safe

451

Solar: hourly global horizontal (GHI) and direct normal (DNI) data for  

Open Energy Info (EERE)

Kenya from DLR Kenya from DLR Dataset Summary Description (Abstract): Hourly time series of GHI and DNI for the years 2000, 2001 and 2002 for selected sites in Kenya. The hourly data are stored in ASCII files for each station. Please read the documentation file for additional information. (Purpose): For the selected sites, the hourly time series can be used for the simulation of Photovoltaic (PV)-systems or Concentrating Solar Power (CSP)-systems. Source DLR - Deutsches Zentrum für Luft- und Raumfahrt Date Released October 31st, 2004 (10 years ago) Date Updated November 01st, 2007 (7 years ago) Keywords DLR DNI GEF GHI hourly data Kenya solar SWERA TILT UNEP Data application/zip icon Download data (zip, 3.9 MiB) Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage

452

DOE's Office of Science Awards 95 Million Hours of Supercomputing Time to  

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

95 Million Hours of Supercomputing 95 Million Hours of Supercomputing Time to Advance Research in Science, Academia and Industry DOE's Office of Science Awards 95 Million Hours of Supercomputing Time to Advance Research in Science, Academia and Industry January 8, 2007 - 9:59am Addthis WASHINGTON, D.C. - The U.S. Department of Energy's (DOE) Office of Science announced today that 45 projects were awarded a total of 95 million hours of computing time on some of the world's most powerful supercomputers as part of its 2007 Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. DOE's Under Secretary for Science Dr. Raymond Orbach presented the awards at the Council on Competitiveness in Washington, DC. Supercomputers are playing an increasingly important role in scientific

453

Nonprofit Organizations: Have Your Los Alamos Employees/Retirees Log Hours  

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

Nonprofit Organizations: Have Your Los Alamos Employees/Retirees Log Nonprofit Organizations: Have Your Los Alamos Employees/Retirees Log Hours in VolunteerMatch Community Connections: Our link to Northern New Mexico Communities Latest Issue:Dec. 2013 - Jan. 2014 All Issues » submit Nonprofit Organizations: Have Your Los Alamos Employees/Retirees Log Hours in VolunteerMatch Lab employees and retirees should log their VolunteerMatch hours to benefit local nonprofits. March 1, 2013 Volunteers help fill sandbags during flood season Volunteers help in many different roles including in healthcare. Contacts Editor Linda Anderman Email Community Programs Office Kurt Steinhaus Email So far, employees and retirees have volunteered more than 1.2 million volunteer hours. If you are a nonprofit organization that has Lab employees or retirees as

454

Solar: hourly global horizontal (GHI) and direct normal (DNI) data for  

Open Energy Info (EERE)

Nepal from DLR Nepal from DLR Dataset Summary Description (Abstract): Hourly time series of GHI and DNI for the years 2000, 2002 and 2003 for selected sites in Nepal. The hourly data are stored in ASCII files for each station. Please read the documentation file for additional information. (Purpose): For the selected sites, the hourly time series can be used for the simulation of Photovoltaic (PV)-systems or Concentrating Solar Power (CSP)-systems. Source DLR - Deutsches Zentrum für Luft- und Raumfahrt Date Released October 31st, 2004 (10 years ago) Date Updated November 01st, 2007 (7 years ago) Keywords DLR DNI GEF GHI hourly data Nepal NREL solar SWERA TILT UNEP Data application/zip icon Download data (zip, 1.2 MiB) Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage

455

DOE Awards 265 Million Hours of Supercomputing Time to Advance Leading  

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

DOE Awards 265 Million Hours of Supercomputing Time to Advance DOE Awards 265 Million Hours of Supercomputing Time to Advance Leading Scientific Research Projects DOE Awards 265 Million Hours of Supercomputing Time to Advance Leading Scientific Research Projects January 17, 2008 - 10:38am Addthis WASHINGTON, DC -The U.S. Department of Energy's (DOE) Office of Science today announced that 265 million processor-hours were awarded to 55 scientific projects, the largest amount of supercomputing resource awards donated in the Department's history and three times that of last year's award. The projects-with applications from aeronautics to astrophysics, and from climate change to combustion research-were chosen based on their potential breakthroughs in the science and engineering research and their suitability of the project for using supercomputers. These awards will

456

Thirty states sign ITER nuclear fusion plant deal 1 hour, 28 minutes ago  

E-Print Network [OSTI]

Thirty states sign ITER nuclear fusion plant deal 1 hour, 28 minutes ago Representatives of more than 30 countries signed a deal on Tuesday to build the world's most advanced nuclear fusion reactor

457

Workers at EM's West Valley Site Surpass 1 Million Hours without...  

Office of Environmental Management (EM)

Achieving 1 million work hours without a lost-time accident is a true indication of the safety culture that we embrace at the West Valley Demonstration Project," EM WVDP Director...

458

Univariate forecasting of day-ahead hourly electricity demand in the northern grid of India  

Science Journals Connector (OSTI)

Short-term electricity demand forecasts (minutes to several hours ahead) have become increasingly important since the rise of the competitive energy markets. The issue is particularly important for India as it has recently set up a power exchange (PX), which has been operating on day-ahead hourly basis. In this study, an attempt has been made to forecast day-ahead hourly demand of electricity in the northern grid of India using univariate time-series forecasting techniques namely multiplicative seasonal ARIMA and Holt-Winters multiplicative exponential smoothing (ES). In-sample forecasts reveal that ARIMA models, except in one case, outperform ES models in terms of lower RMSE, MAE and MAPE criteria. We may conclude that linear time-series models works well to explain day-ahead hourly demand forecasts in the northern grid of India. The findings of the study will immensely help the players in the upcoming power market in India.

Sajal Ghosh

2009-01-01T23:59:59.000Z

459

Building Technologies Program: Tax Deduction Qualified Software- Hourly Analysis Program (HAP) version 4.41  

Broader source: Energy.gov [DOE]

Provides required documentation that Hourly Analysis Program (HAP) version 4.41 meets Internal Revenue Code §179D, Notice 2006-52, dated April 10, 2009, for calculating commercial building energy and power cost savings.

460

ANTH 376: GENOMICS & ANTHROPOLOGY 4 credit hours (satisfies an SC requirement)  

E-Print Network [OSTI]

1 ANTH 376: GENOMICS & ANTHROPOLOGY 4 credit hours (satisfies an SC variation, health and evolution. Extended Course Description The Human Genome Project and recent advances in genome sequencing techniques have made it possible

Note: This page contains sample records for the topic "hourly load profile" 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

EPA ENERGY STAR Webcast- Portfolio Manager® Office Hours, Focus Topic: Portfolio Manager 2015 Priorities  

Broader source: Energy.gov [DOE]

Portfolio Manager "Office Hours" is a live webinar that gives all users an opportunity to ask their questions directly to EPA in an open forum. We will plan to spend the first 20-30 minutes of each...

462

MAST/GEOG 667: Wind Power Meteorology Fall 2013, 3 credit hours  

E-Print Network [OSTI]

to understand onshore, offshore, and airborne wind power. Topics include: forces affecting and energy from turbines; and wind measurement technologies. Textbooks (not requiredMAST/GEOG 667: Wind Power Meteorology Fall 2013, 3 credit hours 1

Delaware, University of

463

Workers at Paducah Site Exceed 1.5 Million Hours Without Lost-Time Injury, Illness  

Broader source: Energy.gov [DOE]

PADUCAH, Ky. – Workers with Paducah site infrastructure contractor Swift & Staley, Inc. recently exceeded 1.5 million hours without lost time away from work due to injury or illness, representing nine years of safe performance.

464

DOE's Office of Science Awards 18 Million Hours of Supercomputing Time to  

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

Office of Science Awards 18 Million Hours of Supercomputing Office of Science Awards 18 Million Hours of Supercomputing Time to 15 Teams for Large-Scale Scientific Computing DOE's Office of Science Awards 18 Million Hours of Supercomputing Time to 15 Teams for Large-Scale Scientific Computing February 1, 2006 - 11:14am Addthis WASHINGTON, D.C. - Secretary of Energy Samuel W. Bodman announced today that DOE's Office of Science has awarded a total of 18.2 million hours of computing time on some of the world's most powerful supercomputers to help researchers in government labs, universities, and industry working on projects ranging from designing more efficient engines to better understanding Parkinson's disease. The allocations of computing time are made under DOE's Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program, now in its

465

Solar: hourly global horizontal (GHI) and direct normal (DNI) data for  

Open Energy Info (EERE)

Sri Lanka sites from DLR Sri Lanka sites from DLR Dataset Summary Description (Abstract): Hourly time series of GHI and DNI for the years 2000, 2002 and 2003 for selected sites in Sri Lanka. The hourly data are stored in ASCII files for each station. Please read the documentation file for additional information. (Purpose): For the selected sites, the hourly time series can be used for the simulation of Photovoltaic (PV)-systems or Concentrating Solar Power (CSP)-systems. Source DLR - Deutsches Zentrum für Luft- und Raumfahrt Date Released October 31st, 2004 (10 years ago) Date Updated November 01st, 2007 (7 years ago) Keywords DLR DNI GHI hourly data solar Sri Lanka SWERA TILT UNEP Data application/zip icon Download data (zip, 368.2 KiB) Quality Metrics Level of Review Some Review Comment

466

Solar: hourly global horizontal (GHI) and direct normal (DNI) data for  

Open Energy Info (EERE)

Ghana from DLR Ghana from DLR Dataset Summary Description (Abstract): Hourly time series of GHI and DNI for the years 2000, 2001 and 2002 for selected sites in Ghana. The hourly data are stored in ASCII files for each station. Please read the documentation file for additional information. (Purpose): For the selected sites, the hourly time series can be used for the simulation of Photovoltaic (PV)-systems or Concentrating Solar Power (CSP)-systems. Source DLR - Deutsches Zentrum für Luft- und Raumfahrt Date Released October 31st, 2004 (10 years ago) Date Updated November 01st, 2007 (7 years ago) Keywords DLR DNI Ghana GHI hourly data solar SWERA TILT TMY UNEP Data application/zip icon ghanaDLRtimeseries_103.zip (zip, 2.7 MiB) Quality Metrics Level of Review Some Review Comment

467

Solar: hourly global horizontal (GHI) and direct normal (DNI) data for  

Open Energy Info (EERE)

Bangladesh sites from DLR Bangladesh sites from DLR Dataset Summary Description (Abstract): Hourly time series of GHI and DNI for the years 2000, 2002 and 2003 for selected sites in Bangladesh. The hourly data are stored in ASCII files for each station. Please read the documentation file for additional information. (Purpose): For the selected sites, the hourly time series can be used for the simulation of Photovoltaic (PV)-systems or Concentrating Solar Power (CSP)-systems. Source DLR - Deutsches Zentrum für Luft- und Raumfahrt Date Released October 31st, 2004 (10 years ago) Date Updated November 01st, 2007 (7 years ago) Keywords Bangladesh DLR DNI GHI hourly data solar SWERA UNEP Data application/zip icon Download Data (zip, 1.2 MiB) Quality Metrics Level of Review Some Review Comment

468

Pantex celebrates three million hours without a lost time injury | National  

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

three million hours without a lost time injury | National three million hours without a lost time injury | National Nuclear Security Administration Our Mission Managing the Stockpile Preventing Proliferation Powering the Nuclear Navy Emergency Response Recapitalizing Our Infrastructure Continuing Management Reform Countering Nuclear Terrorism About Us Our Programs Our History Who We Are Our Leadership Our Locations Budget Our Operations Media Room Congressional Testimony Fact Sheets Newsletters Press Releases Speeches Events Social Media Video Gallery Photo Gallery NNSA Archive Federal Employment Apply for Our Jobs Our Jobs Working at NNSA Blog Home > NNSA Blog > Pantex celebrates three million hours without a ... Pantex celebrates three million hours without a lost time injury Posted By Office of Public Affairs NNSA Blog NNSA Blog

469

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

470

Computer Code Gives Astrophysicists First Full Simulation of Star's Final Hours  

ScienceCinema (OSTI)

The precise conditions inside a white dwarf star in the hours leading up to its explosive end as a Type Ia supernova are one of the mysteries confronting astrophysicists studying these massive stellar explosions. But now, a team of researchers, composed of three applied mathematicians at the U.S. Department of Energy's (DOE) Lawrence Berkeley National Laboratory and two astrophysicists, has created the first full-star simulation of the hours preceding the largest thermonuclear explosions in the universe.

Andy Nonaka

2010-01-08T23:59:59.000Z

471

Synthesis of hourly rainfall by a Monte Carlo method using a sixth-order Markov chain  

E-Print Network [OSTI]

the modeling scheme that reproduces the historical sequences. Hudlow (1967) and the author designed a model for producing synthetic rainfall sequences based on these probabilities. Hudlow us d the model to generate three selected storms of the stationary... - or ? Dry Hour (t-29) 30 complete scheme of operating the two Narkov chains to produce each synthetic hourly value. CHAPTER IV TESTING OF THE I'1ODEL Parameter Test Applications The purpose of testing a model for rainfall synthesis is to ensure...

Dale, Walter Marvin

2012-06-07T23:59:59.000Z

472

Statistical Analysis of Baseline Load Models for Non-Residential Buildings  

SciTech Connect (OSTI)

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

473

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

474

Effect of sun’s orientation on boot thermal load  

Science Journals Connector (OSTI)

Abstract Cabin thermal loads are largely affected by transient solar radiation. One critical situation is when a car has been parked in the sun for several hours; the average temperature inside the car and the boot becomes very high. These high temperatures can affect the performance of infotainment systems (amplifier, GPS/Navigation system, etc.) inside the cabin and boot. In the current paper, a 3D CAE model is developed to predict the cabin and boot temperatures for different solar loads using commercial software RadTherm (ThermoAnalytics Inc). Two different cases have been simulated: (i) fixed sun position - representing the Climate Wind Tunnel (CWT) and (ii) moving sun position - representing the real life scenario. The numerical results were validated against the experimental data and a comparison between these two cases has been presented. The predicted results showed good agreement against the test data with some discrepancies. Comparison of fixed sun and moving sun position results showed that latter had low temperatures in boot and cabin. The findings of this study would help the designer to detect any issues and optimise the design and package quite early in the programme. The application of this model will save development time and wind tunnel shifts. Thus, reducing the cost and carbon print during the product development process.

A Q Shaik; W Jansen

2013-01-01T23:59:59.000Z

475

Utilization of Heat Pump Water Heaters for Load Management  

SciTech Connect (OSTI)

The Energy Conservation Standards for Residential Water Heaters require residential electric storage water heaters with volumes larger than 55 gallons to have an energy factor greater than 2.0 after April 2015. While this standard will significantly increase the energy efficiency of water heaters, large electric storage water heaters that do not use heat pump technologies may no longer be available. Since utilities utilize conventional large-volume electric storage water heaters for thermal storage in demand response programs, there is a concern that the amended standard will significantly limit demand response capacity. To this end, Oak Ridge National Laboratory partnered with the Tennessee Valley Authority to investigate the load management capability of heat pump water heaters that meet or exceed the forthcoming water heater standard. Energy consumption reduction during peak periods was successfully demonstrated, while still meeting other performance criteria. However, to minimize energy consumption, it is important to design load management strategies that consider the home s hourly hot water demand so that the homeowner has sufficient hot water.

Boudreaux, Philip R [ORNL; Jackson, Roderick K [ORNL; Munk, Jeffrey D [ORNL; Gehl, Anthony C [ORNL; Lyne, Christopher T [ORNL

2014-01-01T23:59:59.000Z

476

Downstream Heat Flux Profile vs. Midplane T Profile in Tokamaks  

SciTech Connect (OSTI)

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

477

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

478

Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production - DOE Hydrogen and Fuel Cells Program FY 2012 Annual Progress Report  

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

3 3 FY 2012 Annual Progress Report DOE Hydrogen and Fuel Cells Program Genevieve Saur (Primary Contact), Chris Ainscough. National Renewable Energy Laboratory (NREL) 15013 Denver West Parkway Golden, CO 80401-3305 Phone: (303) 275-3783 Email: genevieve.saur@nrel.gov DOE Manager HQ: Erika Sutherland Phone: (202) 586-3152 Email: Erika.Sutherland@ee.doe.gov Project Start Date: October 1, 2010 Project End Date: Project continuation and direction determined annually by DOE Fiscal Year (FY) 2012 Objectives Corroborate recent wind electrolysis cost studies using a * more detailed hour-by-hour analysis. Examine consequences of different system configuration * and operation for four scenarios, at 42 sites in five

479

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

480

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

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481

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

482

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  through details,  each uses electric load data from a period before using  customer  load  data  [KEMA  2003,  Quantum  2004, 

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

2008-01-01T23:59:59.000Z

483

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

484

Reservoir compaction loads on casings and liners  

SciTech Connect (OSTI)

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

485

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

486

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 operator’s second bya reflection of the load’s inability to follow minute-by-

Heffner, Grayson

2008-01-01T23:59:59.000Z

487

Building Technologies Office Load Control Strategies  

Broader source: Energy.gov [DOE]

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

488

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 Discovery—Find and connect to a myriad of data sources ...

Adam Aspin

2014-01-01T23:59:59.000Z

489

Prediction of clock time hourly global radiation from daily values over  

Open Energy Info (EERE)

Prediction of clock time hourly global radiation from daily values over Prediction of clock time hourly global radiation from daily values over Bangladesh Dataset Summary Description (Abstract): A need for predicting hourly global radiation exists for many locations particularly in Bangladesh for which measured values are not available and daily values have to be estimated from sunshine data. The CPRG model has been used to predict values of hourly Gh for Dhaka (23.770N, 90.380E), Chittagong (22.270N, 91.820E) and Bogra (24.850N, 89.370E) for = ±7.50, ±22.50, ±37.50, ±52.50, ±67.50, ±82.50 and ±97.50 i.e., for ±1/2, ±3/2, ±5/2, ±7/2, ±9/2, ±11/2, ±13/2 hours before and after solar noon and the computed values for different months are symmetrical about solar noon whereas for many months experimental data show a clear asymmetry. To obtain improved

490

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

491

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

492

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

493

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

494

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; Mónica Rosselli…

2000-06-01T23:59:59.000Z

495

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

496

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

497

Statistical correlation between hourly and daily values of solar radiation on horizontal surface at sea level in the Italian climate  

E-Print Network [OSTI]

219- Statistical correlation between hourly and daily values of solar radiation on horizontal- nalières du rayonnement solaire. Abstract. 2014 The knowledge of hourly data of solar radiation is required data measured in Italian stations and propose a method to estimate hourly solar radiation

Boyer, Edmond

498

JOBAID-ACCESSING AND MODIFYING TALENT PROFILE  

Broader source: Energy.gov [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...

499

Oak Ridge: Approaching 4 Million Safe Work Hours | Department of Energy  

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

Oak Ridge: Approaching 4 Million Safe Work Hours Oak Ridge: Approaching 4 Million Safe Work Hours Oak Ridge: Approaching 4 Million Safe Work Hours February 27, 2013 - 12:00pm Addthis Mike Tidwell performs a leak check and inspection on propane tanks Mike Tidwell performs a leak check and inspection on propane tanks Inspections ensure hoisting and rigging equipment performs correctly so employees can safely complete their tasks Inspections ensure hoisting and rigging equipment performs correctly so employees can safely complete their tasks Mike Tidwell performs a leak check and inspection on propane tanks Inspections ensure hoisting and rigging equipment performs correctly so employees can safely complete their tasks OAK RIDGE, Tenn. - Workers at URS | CH2M Oak Ridge (UCOR), the prime contractor for EM's Oak Ridge cleanup, are approaching a milestone of 4

500

On a QUEST to Save Oakland 8.4 Gigawatt Hours | Department of Energy  

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

On a QUEST to Save Oakland 8.4 Gigawatt Hours On a QUEST to Save Oakland 8.4 Gigawatt Hours On a QUEST to Save Oakland 8.4 Gigawatt Hours August 13, 2010 - 3:38pm Addthis Lorelei Laird Writer, Energy Empowers Derrick Rebello wants to make the downtown corridor of Oakland, California, one of the greenest in the nation. Through the new Downtown Oakland Targeted Measure Saturation Project, he and his company, Quantum Energy Services and Technologies (QUEST), are targeting the city's 120-block business district to make as many buildings as possible highly energy efficient. "The goal is to really leave no stone unturned," said Rebello, president of QUEST. "We are trying to achieve 80 percent participation. And of those participating buildings, we are focusing on getting a 20 percent reduction