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

Effects of electric utility residential conservation programs on hourly load profiles  

SciTech Connect

This paper discusses the potential of using hourly energy simulation models to determine load shape changes resulting from energy conservation activities. It is determined that shifts in the time and the day of the monthly peak demand may occur as the level of conservation increases. The shifting of the peak was from weather-sensitive periods to less-weather-sensitive periods. Seasonal load profile changes resulting from energy conservation were demonstrated. A statistically significant quadratic relationship was identified between the annual percent reduction and annual percent energy conserved for the different distribution systems examined. The relationships are examined between different levels of residential energy conservation from weatherization and heat pumps on the hourly load profiles of different power distribution systems within the TVA power service area.

Harper, J.P.; Sieber, R.E.

1983-01-01T23:59:59.000Z

4

load profile | OpenEI Community  

Open Energy Info (EERE)

load profile Home Sfomail's picture Submitted by Sfomail(48) Member 17 May, 2013 - 13:03 Commercial and Residential Hourly Load Data Now Available on OpenEI building load building...

5

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

6

Load Profiling and Settlement for Retail Markets Methods Assessment Study  

Science Conference Proceedings (OSTI)

Retail electric competition requires estimation of hourly loads for each retail supplier. Load profiling is the means by which loads for customers who do not have hourly metering are accounted for. This report presents an assessment of alternative load profiling and settlement methods for retail electric markets and provides a framework for evaluating costs and benefits of potential improvements to profiling and settlement systems. This report is available only to funders of Program 101A or 101.001. Fund...

1999-06-01T23:59:59.000Z

7

Impact of Wind Energy on Hourly Load Following Requirements: An Hourly and Seasonal Analysis; Preprint  

Science Conference Proceedings (OSTI)

The impacts of wind energy on the power system grid can be decomposed into several time scales that include regulation, load following, and unit commitment. Techniques for evaluating the impacts on these time scales are still evolving, and as wind energy becomes a larger part of the electricity supply, valuable experience will be gained that will help refine these methods. Studies that estimated the impact of wind in the load following time scale found differing results and costs, ranging from near zero to approximately $2.50/megawatt-hour (MWh). Part of the reason for these differences is the different interpretation of the impacts that would be allocated to this ancillary service. Because of the low correlation between changes in load and wind, long-term analyses of the load following impact of wind may find low impacts. During the daily load cycle, there is a tremendous variability in load following requirements in systems without wind. When significant levels of wind generation are added to the resource mix, relatively small changes in wind output can complicate the task of balancing the system during periods of large load swings. This paper analyzes the load following impacts of wind by segregating these critical time periods of the day and separating the analysis by season. The analysis compares wind generation at geographically dispersed sites to wind generation based primarily at a single site, and for a large penetration of wind (more than 20% wind capacity to peak load).

Krich, A.; Milligan, M.

2005-05-01T23:59:59.000Z

8

Load Scheduling with Profile Information  

E-Print Network (OSTI)

. Within the past five years, many manufactures have added hardware performance counters to their microprocessors to generate profile data cheaply. We show how to use Compaq's DCPI tool to determine load latencies which are at a fine, instruction granularity and use them as fodder for improving instruction scheduling. We validate our heuristic for using DCPI latency data to classify loads as hits and misses against simulation numbers. We map our classification into the Multiflow compiler's intermediate representation, and use a locality sensitive Balanced scheduling algorithm. Our experiments illustrate that our algorithm improves run times by 1% on average, but up to 10% on a Compaq Alpha. 1 Introduction This paper explores how to use hardware performance counters to produce fine grain latency information to improve compiler scheduling. We use this information to hide latencies with any available instruction level parallelism (ILP). (ILP for an instruction is the number of o...

Götz Lindenmaier; Kathryn S. McKinley; Olivier Temam

2000-01-01T23:59:59.000Z

9

Load Scheduling with Profile Information  

E-Print Network (OSTI)

Abstract Within the past five years, many manufactureshave added hardware performance counters to their microprocessors to generate profile data cheaply.Translating aggregate data such as basic block execution frequencies from the executable to the com-piler intermediate representation is fairly straightforward. In this paper, we show how to use Com-paq's DCPI tool to determine load latencies which are at a fine, instruction granularity and then usethem to provide fodder for improving instruction scheduling. We validate our heuristic for usingDCPI latency data to classify loads as hits and misses against simulation numbers, demonstratingthat we can gather correct latencies cheaply at runtime. We map our classification into the Multiflowcompiler's intermediate representation, and use a locality sensitive Balanced scheduling algorithm. Ourexperiments illustrate that our algorithm has the potential to improve run times by up to 10 % on a Com-paq Alpha when compared to Balanced scheduling, but that a variety of pitfalls make consistent im-provements difficult to attain. 1 Introduction In this paper, we explore how to use hardware per-formance counters to produce fine grain latency information to improve compiler scheduling. We usethis information to hide latencies with any avail\\Lambda The authors

unknown authors

1999-01-01T23:59:59.000Z

10

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

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

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

11

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

12

Load Scheduling with Profile Information  

E-Print Network (OSTI)

Within the past five years, many manufactures have added hardware performance counters to their microprocessors to generate profile data cheaply.

Gotz Lindenmaier Kathryn; Kathryn S. M C Kinley; Olivier Temam

2000-01-01T23:59:59.000Z

13

Analysis Methodology for Industrial Load Profiles  

E-Print Network (OSTI)

A methodology is provided for evaluating the impact of various demand-side management (DSM) options on industrial customers. The basic approach uses customer metered load profile data as a basis for the customer load shape. DSM technologies are represented as load shapes and are used as a basis for altering the customers existing measured load shape. The impact of load shape changes on the customer is evaluated in terms of a change in the electric bill by using a software analytical tool called LOADEXPERT™. The software calculates the customer's bill for a particular rate structure and a given load shape. The output data from LOADEXPERT™ are used to calculate the rate of return on the DSM technology investment. Other uses of load profile data are provided.

Reddoch, T. W.

1991-06-01T23:59:59.000Z

14

Profile Guided Load Marking for Memory Renaming  

E-Print Network (OSTI)

Memory operations remain a significant bottleneck in dynamically scheduled pipelined processors, due in part to the inability to statically determine the existence of memory address dependencies. Hardware memory renaming techniques have been proposed which predict which stores a load might be dependent upon. These prediction techniques can be used to speculatively forward a value from a predicted store dependency to a load through a value prediction table; however, these techniques require large and time-consuming hardware tables. In this paper we propose a software-guided approach for identifying dependencies between store and load instructions and the Load Marking (LM) architecture to communicate these dependencies to the hardware. Compiler analysis and profiles are used to find important store/load relationships, and these relationships are identified during execution via hints or an n-bit tag. For those loads that are not marked for renaming, we then use additional profiling inform...

Glenn Reinman; Brad Calder; Dean Tullsen; Gary Tyson; Todd Austin

1998-01-01T23:59:59.000Z

15

Building Energy Software Tools Directory: Prophet Load Profiler  

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

Shots Keywords energy analysis, load profiling, cost comparison, energy budgeting, rate analysis, data collection, real-time monitoring, load shedding ValidationTesting NA...

16

Regression Models for Demand Reduction based on Cluster Analysis of Load Profiles  

E-Print Network (OSTI)

on Cluster Analysis of Load Profiles Nobuyuki Yamaguchi,on Cluster Analysis of Load Profiles Nobuyuki Yamaguchi,regressions, using actual load profile data of Pacific Gas

Kiliccote, Sila

2010-01-01T23:59:59.000Z

17

Load Profiling Based Routing for Guaranteed Bandwidth Flows  

E-Print Network (OSTI)

. To support the stringent Quality of Service (QoS) requirements of real-time (e.g. audio/video) applications in integrated services networks, several routing algorithms that allow for the reservation of the needed bandwidth over a Virtual Circuit (VC), established on one of several candidate routes, have been proposed. Traditionally, such routing is done using the least-loaded concept, and thus results in balancing the load across the set of candidate routes. In this paper, we propose the use of load profiling as an attractive alternative to load balancing for routing guaranteed bandwidth VCs (flows). Load profiling techniques allow the distribution of "available" bandwidth across a set of candidate routes to match the characteristics of incoming VC QoS requests. We thoroughly characterize the performance of VC routing using load profiling and contrast it to routing using load balancing and load packing. We do so both analytically and via extensive simulations of multi-class traffic r...

Ibrahim Matta; Azer Bestavros; Marwan Krunz

1999-01-01T23:59:59.000Z

18

Does EIA publish data on peak or hourly electricity ...  

U.S. Energy Information Administration (EIA)

Financial market analysis and financial ... load (or demand) data in our Electric Power Annual ... hourly load/demand profiles for some Independent ...

19

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

Science Conference Proceedings (OSTI)

This research was conducted in support of two branches of the EPA ENERGY STAR program, whose overall goal is to reduce, through voluntary market-based means, the amount of carbon dioxide emitted in the U.S. The primary objective was to collect data for the ENERGY STAR Office Equipment program on the after-hours power state of computers, monitors, printers, copiers, scanners, fax machines, and multi-function devices. We also collected data for the ENERGY STAR Commercial Buildings branch on the types and amounts of ''miscellaneous'' plug-load equipment, a significant and growing end use that is not usually accounted for by building energy managers. This data set is the first of its kind that we know of, and is an important first step in characterizing miscellaneous plug loads in commercial buildings. The main purpose of this study is to supplement and update previous data we collected on the extent to which electronic office equipment is turned off or automatically enters a low power state when not in active use. In addition, it provides data on numbers and types of office equipment, and helps identify trends in office equipment usage patterns. These data improve our estimates of typical unit energy consumption and savings for each equipment type, and enables the ENERGY STAR Office Equipment program to focus future effort on products with the highest energy savings potential. This study expands our previous sample of office buildings in California and Washington DC to include education and health care facilities, and buildings in other states. We report data from twelve commercial buildings in California, Georgia, and Pennsylvania: two health care buildings, two large offices (> 500 employees each), three medium offices (50-500 employees), four education buildings, and one ''small office'' that is actually an aggregate of five small businesses. Two buildings are in the San Francisco Bay area of California, five are in Pittsburgh, Pennsylvania, and five are in Atlanta, Georgia.

Roberson, Judy A.; Webber, Carrie A.; McWhinney, Marla C.; Brown, Richard E.; Pinckard, Margaret J.; Busch, John F.

2004-01-22T23:59:59.000Z

20

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

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


21

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

22

Building Energy Software Tools Directory: Prophet Load Profiler  

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

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

23

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

E-Print Network (OSTI)

Using measured equipment load profiles to “right-size” HVAClighting and occupancy load profiles in all the spaces wereintensity” equipment load profile, while the remaining zones

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

2008-01-01T23:59:59.000Z

24

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

E-Print Network (OSTI)

--Congestion forecasting, price forecasting, wholesale power market, locational marginal price, load partitioning, convex for system planning.1 Many studies have focused on electricity price forecasting based on statistical tools distributed loads and DC-OPF system variable solutions was identified and applied to forecast congestion

Abdel-Aal, Radwan E.

25

Climatic-related Evaluations of the Summer Peak-Hours' Electric Load in Israel  

Science Conference Proceedings (OSTI)

The interrelationship between the Summer peak electric load in Israel and pertinent meteorological parameters, including the commonly used outdoor biometeorological comfort index, is evaluated conceptually and statistically. Linear regression ...

M. Segal; H. Shafir; M. Mandel; P. Alpert; Y. Balmor

1992-12-01T23:59:59.000Z

26

Load Data Analysis and PowerShape Training: Strategic Load Research and Advanced Topics in Load Profiling for Settlements  

Science Conference Proceedings (OSTI)

Load shapes, representing usage patterns in the electric and gas industry, are a key factor in energy company operations and management. In the emerging restructured energy market, retail energy suppliers market energy to final customers and must arrange for electricity generation or gas delivery to meet their customers' needs. EPRI and Primen sponsored a workshop in September 2000 that addressed a range of issues associated with load shapes, including modeling, profiling for retail market settlement, re...

2000-12-20T23:59:59.000Z

27

Remote Area Power Supply (RAPS) load and resource profiles.  

SciTech Connect

In 1997, an international team interested in the development of Remote Area Power Supply (RAPS) systems for rural electrification projects around the world was organized by the International Lead Zinc Research Organization (ILZRO) with the support of Sandia National Laboratories (SNL). The team focused on defining load and resource profiles for RAPS systems. They identified single family homes, small communities, and villages as candidates for RAPS applications, and defined several different size/power requirements for each. Based on renewable energy and resource data, the team devised a ''strawman'' series of load profiles. A RAPS system typically consists of a renewable and/or conventional generator, power conversion equipment, and a battery. The purpose of this report is to present data and information on insolation levels and load requirements for ''typical'' homes, small communities, and larger villages around the world in order to facilitate the development of robust design practices for RAPS systems, and especially for the storage battery component. These systems could have significant impact on areas of the world that would otherwise not be served by conventional electrical grids.

Giles, Lauren (Energetics, Inc., Washington, DC); Skolnik, Edward G. (Energetics, Inc., Washington, DC); Marchionini, Brian (Energetics, Inc., Washington, DC); Fall, Ndeye K. (Energetics, Inc., Washington, DC)

2007-07-01T23:59:59.000Z

28

Remote Area Power Supply (RAPS) load and resource profiles.  

SciTech Connect

In 1997, an international team interested in the development of Remote Area Power Supply (RAPS) systems for rural electrification projects around the world was organized by the International Lead Zinc Research Organization (ILZRO) with the support of Sandia National Laboratories (SNL). The team focused on defining load and resource profiles for RAPS systems. They identified single family homes, small communities, and villages as candidates for RAPS applications, and defined several different size/power requirements for each. Based on renewable energy and resource data, the team devised a ''strawman'' series of load profiles. A RAPS system typically consists of a renewable and/or conventional generator, power conversion equipment, and a battery. The purpose of this report is to present data and information on insolation levels and load requirements for ''typical'' homes, small communities, and larger villages around the world in order to facilitate the development of robust design practices for RAPS systems, and especially for the storage battery component. These systems could have significant impact on areas of the world that would otherwise not be served by conventional electrical grids.

Giles, Lauren (Energetics, Inc., Washington, DC); Skolnik, Edward G. (Energetics, Inc., Washington, DC); Marchionini, Brian (Energetics, Inc., Washington, DC); Fall, Ndeye K. (Energetics, Inc., Washington, DC)

2007-07-01T23:59:59.000Z

29

Classification of total load demand profiles for war-ships based on pattern recognition methods  

Science Conference Proceedings (OSTI)

The classification of total load demand profiles for every type of war-ships is crucial information, because it is the necessary base for a series of studies and operations, such as load estimation, load shedding and power management systems. In this ... Keywords: adequacy measures, clustering algorithms, load profiles, pattern recognition, warship

G. J. Tsekouras; I. S. Karanasiou; F. D. Kanellos

2011-07-01T23:59:59.000Z

30

A new classification pattern recognition methodology for power system typical load profiles  

Science Conference Proceedings (OSTI)

In this paper a new pattern recognition methodology is described for the classification of the daily chronological load curves of power systems, in order to estimate their respective representative daily load profiles, which can be mainly used for load ... Keywords: adaptive vector quantization, adequacy measures, clustering algorithms, fuzzy k-means, hierarchical clustering, k-means, load profiles, pattern recognition, self-organized maps

G. J. Tsekouras; F. D. Kanellos; V. T. Kontargyri; I. S. Karanasiou; A. D. Salis; N. E. Mastorakis

2008-12-01T23:59:59.000Z

31

After-hours power status of office equipment and energy use of miscellaneous plug-load equipment  

Science Conference Proceedings (OSTI)

This research was conducted in support of two branches of the EPA ENERGY STAR program, whose overall goal is to reduce, through voluntary market-based means, the amount of carbon dioxide emitted in the U.S. The primary objective was to collect data for the ENERGY STAR Office Equipment program on the after-hours power state of computers, monitors, printers, copiers, scanners, fax machines, and multi-function devices. We also collected data for the ENERGY STAR Commercial Buildings branch on the types and amounts of miscellaneous plug-load equipment, a significant and growing end use that is not usually accounted for by building energy managers. For most types of miscellaneous equipment, we also estimated typical unit energy consumption in order to estimate total energy consumption of the miscellaneous devices within our sample. This data set is the first of its kind that we know of, and is an important first step in characterizing miscellaneous plug loads in commercial buildings. The main purpose of this study is to supplement and update previous data we collected on the extent to which electronic office equipment is turned off or automatically enters a low power state when not in active use. In addition, it provides data on numbers and types of office equipment, and helps identify trends in office equipment usage patterns. These data improve our estimates of typical unit energy consumption and savings for each equipment type, and enables the ENERGY STAR Office Equipment program to focus future effort on products with the highest energy savings potential. This study expands our previous sample of office buildings in California and Washington DC to include education and health care facilities, and buildings in other states. We report data from sixteen commercial buildings in California, Georgia, and Pennsylvania: four education buildings, two medical buildings, two large offices (> 500 employees each), three medium offices (50-500 employees each), and five small business offices (< 50 employees each). Two buildings are in the San Francisco Bay are a of California, nine (including the five small businesses) are in Pittsburgh, Pennsylvania, and five are in Atlanta, Georgia.

Roberson, Judy A.; Webber, Carrie A.; McWhinney, Marla C.; Brown, Richard E.; Pinckard, Marageret J.; Busch, John F.

2004-05-27T23:59:59.000Z

32

Observed Temperature Effects on Hourly Residential Electric Load Reduction in Response to an Experimental Critical Peak Pricing Tariff  

E-Print Network (OSTI)

changes to retail electricity rates on an hourly or dailyweekdays 2004 [6] Most electricity rates in use today arerates with control technologies use 30- 40% less electricity

Herter, Karen B.; McAuliffe, Patrick K.; Rosenfeld, Arthur H.

2005-01-01T23:59:59.000Z

33

Analytical and demonstration experience with changing load profile. Final report  

SciTech Connect

A bibliography of load management and supply management projects, sponsored by EPRI, was developed. Summaries of project scope and results were made for a selection of these projects already completed. Finally, summaries of six utility load management demonstration projects were made, including project descriptions and presentation of selected results.

Isaksen, L.; Khan, S.; Ma, F.S.

1979-12-01T23:59:59.000Z

34

Regional load-curve models: QUERI's model long-run forecasts and sensitivity analysis. Volume 4. Final report. [Hourly demand in 32 US regions  

SciTech Connect

This report presents detailed forecasts of the hourly demand for electricity in 32 regions of the US through the year 2000. The forecasts are generated by a load curve model estimated by QUERI and described in Volume II of this report. Two primary sets of input assumptions for this model are utilized: one based on DRI's macro, regional and sectoral models is called the Baseline Scenario while the other, which is a projection of historical trends, is the Extrapolation Scenario. Under both assumptions, the growth rates of electricity are forecast to slow from historical levels. Load factors are generally projected to continue to decline; most regions are forecast to remain Summer peaking but this is rather sensitive to the choice of scenario. By considering other scenarios which are small perturbations of the Baseline assumptions, elasticities of average, peak and hourly loads are calculated. Different weather assumptions are also examined for the sensitivity of the load shapes to changes in the weather.

Engle, R.F.; Granger, C.W.J.; Ramanathan, R.

1981-09-01T23:59:59.000Z

35

ZigBee Smart Energy Application Profile for Demand Response/Load...  

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

ZigBee Smart Energy Application Profile for Demand ResponseLoad Control and its implementation on a JAVA-based platform Speaker(s): John Lin Date: April 23, 2009 - 12:00pm...

36

Observed Temperature Effects on Hourly Residential Electric LoadReduction in Response to an Experimental Critical Peak PricingTariff  

SciTech Connect

The goal of this investigation was to characterize themanual and automated response of residential customers to high-price"critical" events dispatched under critical peak pricing tariffs testedin the 2003-2004 California Statewide Pricing Pilot. The 15-monthexperimental tariff gave customers a discounted two-price time-of-userate on 430 days in exchange for 27 critical days, during which the peakperiod price (2 p.m. to 7 p.m.) was increased to about three times thenormal time-of-use peak price. We calculated response by five-degreetemperature bins as the difference between peak usage on normal andcritical weekdays. Results indicatedthat manual response to criticalperiods reached -0.23 kW per home (-13 percent) in hot weather(95-104.9oF), -0.03 kW per home (-4 percent) in mild weather (60-94.9oF),and -0.07 kW per home (-9 percent) during cold weather (50-59.9oF).Separately, we analyzed response enhanced by programmable communicatingthermostats in high-use homes with air-conditioning. Between 90oF and94.9oF, the response of this group reached -0.56 kW per home (-25percent) for five-hour critical periods and -0.89 kW/home (-41 percent)for two-hour critical periods.

Herter, Karen B.; McAuliffe, Patrick K.; Rosenfeld, Arthur H.

2005-11-14T23:59:59.000Z

37

Plug-In Electric Vehicle Charging Load Profile Forecasts for the Salt River Project Service Area  

Science Conference Proceedings (OSTI)

As plug-in electric vehicles (PEVs) enter the marketplace, it is important to understand the impacts of the potentially significant new load caused by PEV charging. Time-of-use (TOU) electricity pricing will help shift PEV charging loads to off-peak hours, mitigating the potential problem of raising the system peak load. However, there is a potential for a secondary peak to develop if the TOU plan causes a large PEV load to appear on the grid at a specific time in the evening. So-called smart chargingbid...

2011-06-30T23:59:59.000Z

38

Low profile, high load vertical rolling positioning stage  

DOE Patents (OSTI)

A stage or support platform assembly for use in a synchrotron accurately positions equipment to be used in the beam line of the synchrotron. The support platform assembly includes an outer housing in which is disposed a lifting mechanism having a lifting platform or stage at its upper extremity on which the equipment is mounted. A worm gear assembly is located in the housing and is adapted to raise and lower a lifting shaft that is fixed to the lifting platform by an anti-binding connection. The lifting platform is moved vertically as the lifting shaft is moved vertically. The anti-binding connection prevents the shaft from rotating with respect to the platform, but does permit slight canting of the shaft with respect to the lifting platform so as to eliminate binding and wear due to possible tolerance mismatches. In order to ensure that the lifting mechanism does not move in a horizontal direction as it is moved vertically, at least three linear roller bearing assemblies are arranged around the outer-periphery of the lifting mechanism. One of the linear roller bearing assemblies can be adjusted so that the roller bearings apply a loading force against the lifting mechanism. Alternatively, a cam mechanism can be used to provide such a loading force.

Shu, Deming (Darien, IL); Barraza, Juan (Aurora, IL)

1996-01-01T23:59:59.000Z

39

Regression Models for Demand Reduction based on Cluster Analysis of Load Profiles  

Science Conference Proceedings (OSTI)

This paper 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. The proposed models examined their performances from the viewpoint of validity of explanatory variables and fitness of regressions, using actual load profile data of Pacific Gas and Electric Company's commercial and industrial customers who participated in the 2008 Critical Peak Pricing program including Manual and Automated Demand Response.

Yamaguchi, Nobuyuki; Han, Junqiao; Ghatikar, Girish; Piette, Mary Ann; Asano, Hiroshi; Kiliccote, Sila

2009-06-28T23:59:59.000Z

40

Analysis of industrial load management  

SciTech Connect

Industrial Load Management, ILM, has increased the possibilities of changing load profiles and raising load factors. This paper reports on load profile measurements and feasible load management applications that could be implemented in industry e.g. bivalent systems for heating of premises and processes, load priority systems, energy storage and rescheduling processes or parts of processes due to differential electricity rates. Industrial load variations on hourly, daily and seasonal basis are treated as well as the impact by load management on load curves e g peak clipping, valley filling and increased off-peak electricity usage.

Bjork, C.O.; Karlsson, B.G.

1986-04-01T23:59:59.000Z

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


41

Abstract--This paper analyzes a distribution system load time series through autocorrelation coefficient, power spectral density,  

E-Print Network (OSTI)

models [7], [8]. The load model developed in [7] provides different 24-hour load profiles for different seasons. The 24-hour load profile is obtained by a weighted sum of peak loads from different types1 Abstract--This paper analyzes a distribution system load time series through autocorrelation

Bak-Jensen, Birgitte

42

FINAL PROJECT REPORT LOAD MODELING TRANSMISSION RESEARCH  

E-Print Network (OSTI)

composition: The total load profile obtained from  load individual load types if  load profiles of individual load composition validation: Load profiles generated by the load 

Lesieutre, Bernard

2013-01-01T23:59:59.000Z

43

Using Utility Load Data to Estimate Demand for Space Cooling and Potential for Shiftable Loads  

SciTech Connect

This paper describes a simple method to estimate hourly cooling demand from historical utility load data. It compares total hourly demand to demand on cool days and compares these estimates of total cooling demand to previous regional and national estimates. Load profiles generated from this method may be used to estimate the potential for aggregated demand response or load shifting via cold storage.

Denholm, P.; Ong, S.; Booten, C.

2012-05-01T23:59:59.000Z

44

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

E-Print Network (OSTI)

load profiles to “right-size” HVAC systems and reduce energyGeorgia. ASHRAE [1999]. HVAC Applications Handbook 1999.Inefficiency of a Common Lab HVAC System,” presented at the

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

2008-01-01T23:59:59.000Z

45

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

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

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

46

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

47

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

48

G&T adds versatile load management system  

SciTech Connect

Wolverine`s load management system was designed in response to the need to reduce peak demand. The Energy Management System (EMS) prepares short term (seven day) load forecasts, based on a daily peak demand forecst, augmented by a similar day profile based on weather conditions. The software combines the similar day profile with the daily peak demand forecast to yield an hourly load forecast for an entire week. The software uses the accepted load forecast case in many application functions, including interchange scheduling, unit commitment, and transaction evaluation. In real time, the computer updates the accepted forecast hourly, based in actual changes in the weather and load. The load management program executes hourly. The program uses impact curves to calculate a load management strategy that reduces the load forecast below a desired load threshold.

Nickel, J.R.; Baker, E.D.; Holt, J.W.; Chan, M.L.

1995-04-01T23:59:59.000Z

49

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

50

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

51

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

Science Conference Proceedings (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

52

Regression Models for Demand Reduction based on Cluster Analysis of Load Profiles  

E-Print Network (OSTI)

Methods for Customer and Demand Response Policies SelectionC. McParland,“Open Automated Demand Response Communicationset al, “Estimating Demand Response Load Impacts: Evaluation

Kiliccote, Sila

2010-01-01T23:59:59.000Z

53

The Load Leveling Approach to Removing Appliance Features from Home Electricity Usage Profiles.  

E-Print Network (OSTI)

??For the past twenty years, researchers have developed a class of algorithms that are capable of disaggregating a residential electric load into its set of… (more)

McLaughlin, Stephen

2011-01-01T23:59:59.000Z

54

Regression Models for Demand Reduction based on Cluster Analysis of Load Profiles  

E-Print Network (OSTI)

ESCRIPTIVE S TATISTICS Maximum Demand (kW) Num. of Obs. Meanrate and customer’s maximum demand. C’ i, t : a constant, Arate and customer’s maximum demand. The load sensitivity to

Kiliccote, Sila

2010-01-01T23:59:59.000Z

55

Teach Yourself in 24 Hours  

E-Print Network (OSTI)

"ations .................................................. 302 Reclaiming Memory with the kill Command .................................. 303 Getting System Load in a retrieval system, or transmitted by any means, electronic, mechanical, photo- copying, recording 1 Hour 1 Preparing to Install Linux 3 2 Installing Linux 11 3 Configuring the X Window System 31

Eckmiller, Rolf

56

The influence of a variable volume water heater on the domestic load profile  

SciTech Connect

In this paper a variable volume water heater and a load impact model is presented. The variable volume water heater is a unique system that can be implemented as a residential demand-side management tool. The variable volume water heater can shift the electrical energy consumption, used to heat water, to off-peak time periods. The electrical energy is shifted without influencing the hot water usage of the customer. The load impact model simulates the effect of controlling the volume of stored hot water on a domestic load. The model mathematics as well as the model verification are discussed. The paper ends with a comparative case study on two residential areas. The case study indicates that the variable volume water heater can reduce the system peak as well as increase the off-peak energy consumption.

Lemmer, E.F.; Delport, G.J.

1999-12-01T23:59:59.000Z

57

Voltage Pulse Profile Characteristics with Space Charge of a Loaded Pulsed Ionization Chamber  

Science Conference Proceedings (OSTI)

An analytical model describing the voltage pulse profile of a pulsed ionization chamber and its relationship to the electron density in a field drift dominated plasma is formulated. The differential equation derived from the equations of motion and conservation of electron density combined with Poisson's equation for the electric space?charge field in the system is solved analytically for the cylindrical?electrode geometry with an external RC circuit. The numerical analysis for the given initial and boundary conditions yields the anode voltage?signal pulse profiles for the period of electron collection as a function of the initial electron density

S.H. Kim; W.H. Ellis

1972-01-01T23:59:59.000Z

58

Recommending energy tariffs and load shifting based on smart household usage profiling  

Science Conference Proceedings (OSTI)

We present a system and study of personalized energy-related recommendation. AgentSwitch utilizes electricity usage data collected from users' households over a period of time to realize a range of smart energy-related recommendations on energy tariffs, ... Keywords: demand response, energy tariffs, load shifting, personalization, recommender systems, smart grid

Joel E. Fischer; Sarvapali D. Ramchurn; Michael Osborne; Oliver Parson; Trung Dong Huynh; Muddasser Alam; Nadia Pantidi; Stuart Moran; Khaled Bachour; Steve Reece; Enrico Costanza; Tom Rodden; Nicholas R. Jennings

2013-03-01T23:59:59.000Z

59

An Evaluation of the HVAC Load Potential for Providing Load Balancing Service  

Science Conference Proceedings (OSTI)

This paper investigates the potential of providing aggregated intra-hour load balancing services using heating, ventilating, and air-conditioning (HVAC) systems. A direct-load control algorithm is presented. A temperature-priority-list method is used to dispatch the HVAC loads optimally to maintain consumer-desired indoor temperatures and load diversity. Realistic intra-hour load balancing signals were used to evaluate the operational characteristics of the HVAC load under different outdoor temperature profiles and different indoor temperature settings. The number of HVAC units needed is also investigated. Modeling results suggest that the number of HVACs needed to provide a {+-}1-MW load balancing service 24 hours a day varies significantly with baseline settings, high and low temperature settings, and the outdoor temperatures. The results demonstrate that the intra-hour load balancing service provided by HVAC loads meet the performance requirements and can become a major source of revenue for load-serving entities where the smart grid infrastructure enables direct load control over the HAVC loads.

Lu, Ning

2012-09-30T23:59:59.000Z

60

Beam loading voltage profile of an accelerating section with a linearly varying group velocity  

E-Print Network (OSTI)

The CLIC Tapered Damped accelerating Structure (TDS) has a 5.4% detuning of the lowest dipole mode. The geometrical variations that produce this detuning range also fix the fundamental mode's group velocity variation - very nearly linear with 0.108c (c is the speed of light) at the structure input to 0.054c at the output. In addition R'/Q also varies approximately linearly, from 22.3 kW/m at the input to 30 kW/m at the output. These variations result in a structure that is neither constant impedance nor constant gradient so the widely used relationships between structure length, input and average accelerating gradient are not applicable. In order to simplify the process of optimizing accelerator parameters an analytic expression for the voltage profile in a structure with a linearly varying group velocity has been derived. A more accurate numerical solution that includes the variation in R'/Q is also presented.

Wuensch, Walter

1999-01-01T23:59:59.000Z

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


61

Electrical and Production Load Factors  

E-Print Network (OSTI)

Load factors are an important simplification of electrical energy use data and depend on the ratio of average demand to peak demand. Based on operating hours of a facility they serve as an important benchmarking tool for the industrial sector. The operating hours of small and medium sized manufacturing facilities are analyzed to identify the most common operating hour or shift work patterns. About 75% of manufacturing facilities fall into expected operating hour patterns with operating hours near 40, 80, 120 and 168 hours/week. Two types of load factors, electrical and production are computed for each shift classification within major industry categories in the U.S. The load factor based on monthly 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, the load factor based on production hours (PLF) shows an inverse trend, varying from about 1.4 for one shift operation to 0.7 for around-the-clock operation. When used as a diagnostic tool, if the PLF exceeds unity, then unnecessary energy consumption may be taking place. For plants operating at 40 hours per week, the ELF value was found to greater than the theoretical maximum, while the PLF value was greater than one, suggesting that these facilities may have significant energy usage outside production hours. The data for the PLF however, is more scattered for plants operating less than 80 hours per week, indicating that grouping PLF data based on operating hours may not be a reasonable approach to benchmarking energy use in industries. This analysis uses annual electricity consumption and demand along with operating hour data of manufacturing plants available in the U.S. Department of Energy’s Industrial Assessment Center (IAC) database. The annual values are used because more desirable monthly data are not available. Monthly data are preferred as they capture the load profile of the facility more accurately. The data there come from Industrial Assessment Centers which employ university engineering students, faculty and staff to perform energy assessments for small to medium-sized manufacturing plants. The nation-wide IAC program is sponsored by the U.S. Department of Energy.

Sen, Tapajyoti

2009-12-01T23:59:59.000Z

62

Methods for Analyzing Electric Load Shape and its Variability  

E-Print Network (OSTI)

15 Figure 12: Load profile by day of week, averaged over thebetween the average load profile and the profile of a givenfrom the average load profile. Figure 12: Load profile by

Price, Philip

2010-01-01T23:59:59.000Z

63

OpenEI - hourly  

Open Energy Info (EERE)

are given by a location defined by the Typical Meteorological Year (TMY) for which the weather data was collected. Commercial load data is sorted by the (TMY) site as a...

64

building load data | OpenEI Community  

Open Energy Info (EERE)

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...

65

electric load data | OpenEI Community  

Open Energy Info (EERE)

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...

66

commercial load | OpenEI Community  

Open Energy Info (EERE)

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...

67

residential load | OpenEI Community  

Open Energy Info (EERE)

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...

68

Comparison of Zone Cooling Load for Radiant and All-Air Conditioning Systems  

E-Print Network (OSTI)

change the cooling load profile for the mechanical systems.and the resulting cooling load profile has been reported inimplications for cooling load profile and peak cooling load

Feng, Jingjuan; Schiavon, Stefano; Bauman, Fred

2012-01-01T23:59:59.000Z

69

NERSC Edison Hours Used Report  

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

Edison Hours Used Edison Hours Used Edison Usage Chart Edison Usage Chart Date Hours Used (in millions) Percent of Maximum Possible (24 hoursday) 10142013 1.852 61.8 10132013...

70

OpenEI Community - load data  

Open Energy Info (EERE)

building load data commercial load data dataset datasets electric load data load data load profile OpenEI residential load TMY3 United States Utility Rate OpenEI Community...

71

OpenEI Community - electric load data  

Open Energy Info (EERE)

building load data commercial load data dataset datasets electric load data load data load profile OpenEI residential load TMY3 United States Utility Rate OpenEI Community...

72

OpenEI Community - building load  

Open Energy Info (EERE)

building load data commercial load data dataset datasets electric load data load data load profile OpenEI residential load TMY3 United States Utility Rate OpenEI Community...

73

OpenEI Community - residential load  

Open Energy Info (EERE)

building load data commercial load data dataset datasets electric load data load data load profile OpenEI residential load TMY3 United States Utility Rate OpenEI Community...

74

OpenEI Community - commercial load  

Open Energy Info (EERE)

building load data commercial load data dataset datasets electric load data load data load profile OpenEI residential load TMY3 United States Utility Rate OpenEI Community...

75

OpenEI Community - building load data  

Open Energy Info (EERE)

building load data commercial load data dataset datasets electric load data load data load profile OpenEI residential load TMY3 United States Utility Rate OpenEI Community...

76

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)

77

OpenEI - hourly data  

Open Energy Info (EERE)

http:en.openei.orgdatasetstaxonomyterm4980 en Solar: hourly solar (direct normal (DNI), global horizontal (GHI), and diffuse) data for selected stations in Sri Lanka from...

78

Transitioning to 12-hour shifts  

Science Conference Proceedings (OSTI)

In 1989, Yankee Rowe nuclear power station successfully implemented a 12-hour shift schedule for all shiftworkers (control room personnel, auxiliary operators, and radiation protection shift technicians) with many positive effects on morale, motivation, and performance. The transition from an 8-hour to a 12-hour shift schedule was initiated, organized, and promoted by the shiftworkers themselves after they had identified numerous inadequacies in the 8-hour shift schedule. Preliminary and final implementation required several steps: (a) a survey of needs, (b) research of potential schedules, (c) cost/benefit analysis, (d) resolution of any union contract conflicts, (e) management approval, and (f) trial shift schedule periods.

Suter, P.S.; Cervassi, S.M.

1993-03-01T23:59:59.000Z

79

NERSC Franklin Hours Used Report  

NLE Websites -- All DOE Office Websites (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

80

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:

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


81

Direct versus Facility Centric Load Control for Automated Demand Response  

E-Print Network (OSTI)

actions to influence load profiles of their customers atISO needs to influence the load profile of a Facility arebe a specific target load profile to be achieved while in

Piette, Mary Ann

2010-01-01T23:59:59.000Z

82

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

E-Print Network (OSTI)

This  baseline  load  profile  (BLP)  is  key  to to  as  the  baseline  load  profile  or  BLP  and  is  key actual  and  estimated  load  profiles  look,  Figure  1 

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

2008-01-01T23:59:59.000Z

83

Transportation Electrification Load Development For A Renewable Future Analysis: Preprint  

DOE Green Energy (OSTI)

The transition to electricity as a transportation fuel will create a new load for electricity generation. A set of regional hourly load profiles for electrified vehicles was developed for the 2010 to 2050 timeframe. The transportation electrical energy was determined using regional population forecast data, historical vehicle per capita data, and market penetration growth functions to determine the number of plug-in electric vehicles (PEVs) in each analysis region. Market saturation scenarios of 30% and 50% of sales of PEVs consuming on average approx. 6 kWh per day were considered. PEV aggregate load profiles from previous work were combined with vehicle population data to generate hourly loads on a regional basis. A transition from consumer-controlled charging toward utility-controlled charging was assumed such that by 2050 approximately 45% of the transportation energy demands could be delivered across four daily time slices under optimal control from the utility?s perspective. This electrified transportation analysis resulted in an estimate for both the flexible load and fixed load shapes on a regional basis that may evolve under two PEV market penetration scenarios.

Markel, T.; Mai, T.; Kintner-Meyer, M.

2010-12-01T23:59:59.000Z

84

NERSC Carver Hours Used Report  

NLE Websites -- All DOE Office Websites (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

85

2001 Exhibition: Event Profile - TMS  

Science Conference Proceedings (OSTI)

2001 Exhibition: Event Profile ... Event Profile ... in transportation and other growing markets require the material to be designed for load bearing applications.

86

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)

87

Predicting hourly building energy usage  

SciTech Connect

This article presents the results of an evaluation to identify the most accurate method for making hourly energy use predictions. The prediction of energy usage by HVAC systems is important for the purposes of HVAC diagnostics, system control, parameter and system identification, optimization and energy management. Many new techniques are now being applied to the analysis problems involved with predicting the future behavior of HVAC systems and deducing properties of these systems. Similar problems arise in most observational disciplines, including physics, biology and economics.

Kreider, J.F. (Univ. of Colorado, Boulder, CO (United States). Dept. of Civil, Environmental and Architectural Engineering); Haberl, J.S. (Texas A and M Univ., College Station, TX (United States). Mechanical Engineering Dept.)

1994-06-01T23:59:59.000Z

88

Estimation of Daily Degree-hours  

Science Conference Proceedings (OSTI)

Degree-hours have many applications in fields such as agriculture, architecture, and power generation. Since daily mean temperatures are more readily available than hourly temperatures, the difference between mean daily degree-hours computed from ...

Nathaniel B. Guttman; Richard L. Lehman

1992-07-01T23:59:59.000Z

89

Transportation Electrification Load Development For a Renewable Future Analysis  

SciTech Connect

Electrification of the transportation sector offers the opportunity to significantly reduce petroleum consumption. The transportation sector accounts for 70% of US petroleum consumption. The transition to electricity as a transportation fuel will create a new load for electricity generation. In support of a recent US Department of Energy funded activity that analyzed a future generation scenario with high renewable energy technology contributions, a set of regional hourly load profiles for electrified vehicles were developed for the 2010 to 2050 timeframe. These load profiles with their underlying assumptions will be presented in this paper. The transportation electrical energy was determined using regional population forecast data, historical vehicle per capita data, and market penetration growth functions to determine the number of plug-in electric vehicles (PEVs) in each analysis region. Two market saturation scenarios of 30% of sales and 50% of sales of PEVs consuming on average {approx}6 kWh per day were considered. Results were generated for 3109 counties and were consolidated to 134 Power Control Areas (PCA) for the use NREL's's regional generation planning analysis tool ReEDS. PEV aggregate load profiles from previous work were combined with vehicle population data to generate hourly loads on a regional basis. A transition from consumer-controlled charging toward utility-controlled charging was assumed such that by 2050 approximately 45% of the transportation energy demands could be delivered across 4 daily time slices under optimal control from the utility perspective. No other literature has addressed the potential flexibility in energy delivery to electric vehicles in connection with a regional power generation study. This electrified transportation analysis resulted in an estimate for both the flexible load and fixed load shapes on a regional basis that may evolve under two PEV market penetration scenarios. EVS25 Copyright.

Markel, Tony; Mai, Trieu; Kintner-Meyer, Michael CW

2010-09-30T23:59:59.000Z

90

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

SciTech Connect

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

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

2005-06-29T23:59:59.000Z

91

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

92

Residential equipment part load curves for use in DOE-2  

SciTech Connect

DOE-2 (DOE2 90) includes several correlation curves that predict the energy use of systems underpart load conditions. DOE-2 simulates systems on an hour-by-hour basis, so the correlations are intended to predict part load energy use (and efficiency) as a function of the part load ratio (PLR) for each hour, where PLR = Hourly Load/Available Capacity. Generally residential and small commercial HVAC equipment meets the load at off-design conditions by cycling on and off. Therefore, the part load correlations must predict the degradation due to this on and off operation over an hourly interval.

Henderson, Hugh; Huang, Y.J.; Parker, D.

1999-02-01T23:59:59.000Z

93

The Autocorrelation of Hourly Wind Speed Observations  

Science Conference Proceedings (OSTI)

The autocorrelation of hourly wind speed observations is estimated for seven stations on the west coast of Canada at selected lags ranging from one hour to two months. The estimated autocorrelation function is fitted by a model that includes a ...

Arthur C. Brett; Stanton E. Tuller

1991-06-01T23:59:59.000Z

94

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

95

Statistical Analysis of Baseline Load Models for Non-Residential Buildings  

E-Print Network (OSTI)

estimation of the baseline load profile. In this paper, weDemand response, Baseline load profile, Impacts estimationto as the baseline load profile (or baseline) and is key to

Coughlin, Katie

2012-01-01T23:59:59.000Z

96

Influence of raised floor on zone design cooling load in commercial buildings.  

E-Print Network (OSTI)

design day zone cooling load profile is evaluated for anThe zone cooling load profiles and the thermal performanceaffects the zone cooling load profile and the peak cooling

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

2010-01-01T23:59:59.000Z

97

Development of a simplified cooling load design tool for underfloor air distribution (UFAD) systems.  

E-Print Network (OSTI)

in design day cooling load profiles for OH and UFAD systems;in design day cooling load profiles for OH and UFAD systems;showed that the cooling load profiles for UFAD and OH are

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

2010-01-01T23:59:59.000Z

98

Simplified calculation method for design cooling loads in underfloor air distribution (UFAD) systems  

E-Print Network (OSTI)

design day cooling load profiles, (2) impact of a thermallyday peak zone cooling load profile for UFAD and a well-mixedaffects the cooling load profiles, therefore it is possible

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

2010-01-01T23:59:59.000Z

99

Virtualizing office hours in CS 50  

Science Conference Proceedings (OSTI)

In Fall 2007, we introduced "virtual office hours" into Harvard College's introductory computer science course, CS 50, so that students could meet with teaching fellows (TFs) online to discuss problem sets at any hour from anywhere. Our goals were to ... Keywords: CSCW, collaboration, distance education, virtual office hours

David J. Malan

2009-07-01T23:59:59.000Z

100

Building Energy Software Tools Directory: Energy Profiler  

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

in several widely used formats. Energy Profiler helps users to better understand their energy usage and associated costs. Keywords load profiles, rate comparisons, data...

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


101

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

SciTech Connect

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

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

2008-01-01T23:59:59.000Z

102

Load cell  

DOE Patents (OSTI)

A load cell combines the outputs of a plurality of strain gauges to measure components of an applied load. Combination of strain gauge outputs allows measurement of any of six load components without requiring complex machining or mechanical linkages to isolate load components. An example six axis load cell produces six independent analog outputs, each directly proportional to one of the six general load components. 16 figs.

Spletzer, B.L.

1998-12-15T23:59:59.000Z

103

Load cell  

DOE Patents (OSTI)

A load cell combines the outputs of a plurality of strain gauges to measure components of an applied load. Combination of strain gauge outputs allows measurement of any of six load components without requiring complex machining or mechanical linkages to isolate load components. An example six axis load cell produces six independent analog outputs which can be combined to determine any one of the six general load components.

Spletzer, Barry L. (Albuquerque, NM)

2001-01-01T23:59:59.000Z

104

Load cell  

DOE Patents (OSTI)

A load cell combines the outputs of a plurality of strain gauges to measure components of an applied load. Combination of strain gauge outputs allows measurement of any of six load components without requiring complex machining or mechanical linkages to isolate load components. An example six axis load cell produces six independent analog outputs, each directly proportional to one of the six general load components.

Spletzer, Barry L. (Albuquerque, NM)

1998-01-01T23:59:59.000Z

105

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

E-Print Network (OSTI)

Abbreviations ADDF ALM AMR CSP DOE DR ELRP ETS EWH FERC HVa Curtailment Service Provider (CSP) at PJM’s request. LBNLof load control tests. The CSP collected hourly load data

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

2004-01-01T23:59:59.000Z

106

OpenEI - hourly emission factors  

Open Energy Info (EERE)

http:en.openei.orgdatasetstaxonomyterm4640 en Hourly Energy Emission Factors for Electricity Generation in the United States http:en.openei.orgdatasetsnode488...

107

Regional Profiles: Pipeline Capacity and Service  

U.S. Energy Information Administration (EIA)

Regional Profiles: Pipeline Capacity ... large petrochemical and electric utility industries drawn there ... accounts for large electricity load ...

108

Load-management decision  

Science Conference Proceedings (OSTI)

Utilities require baseload, intermediate, and peaking plants to meet fluctuating customer demand. These can be supplemented with off-peak generation and storage and load management, which can take the form of direct utility control over interruptible and deferrable customers or customer incentives that require off-peak demand. Utilities should make a careful analysis of their load profile, their generation mix, their ability to shift loads, and customer attitudes before deciding on a load-management program that fits their individual needs. They should also be aware that load management is only a limited resource with a number of uncertainties. Research programs into customer relations, system reliability, communications devices, and special control switches and meters will help to relieve some of the uncertainties. (DCK)

Lihach, N.; Gupta, P.

1982-05-01T23:59:59.000Z

109

Fast Automated Demand Response to Enable the Integration of Renewable Resources  

E-Print Network (OSTI)

the base load data and load profiles. The CAISO and the UCtotal commercial hourly load profile. Second, intra-hourwith estimates for hourly load profiles for data centers,

Watson, David S.

2013-01-01T23:59:59.000Z

110

The application of load models of electric appliances to distribution system analysis  

SciTech Connect

This paper proposes a methodology to apply the load models of key electric appliances in residential area for distribution system analysis. According to the load models, the transformer hourly loading is estimated during simulation iteration by the bus voltage and ambient temperature. A three phase load flow program is then executed to find the feeder daily profile of power consumption and system loss with the transformer hourly loading derived. Besides, the daily power consumption by each type of key appliances can also be solved. To demonstrate the effectiveness of the proposed method, a distribution feeder of Taipower system is selected for computer simulation to find the potential of energy conservation by controlling the feeder service voltage at substation. Moreover, the load model of air conditioners, which are temperature sensitive appliances, is also considered in the program to find the impact of ambient temperature change to the power consumption of residential distribution feeders. It is concluded that the load models of key electric appliances can provide a useful tool for distribution engineers to enhance the accuracy of system analysis to estimate the operation efficiency of distribution system in a more effective manner.

Chen, C.S.; Wu, T.H.; Lee, C.C.; Tzeng, Y.M. [National Sun Yat-Sen Univ., Kaohsiung (Taiwan, Province of China). Dept. of Electrical Engineering

1995-08-01T23:59:59.000Z

111

On-line load relief control  

SciTech Connect

This paper describes the results of an investigation concerning the on-line prediction and enhancement of load relief. The effects of voltage fluctuation, system voltage profile control and generator voltage adjustment on load relief and load shedding operations during under-frequency transients are studied. The technique promoted in the paper may be used to reduce system spinning reserve or prospective load shedding.

Jovanovic, S.; Fox, B.; Thompson, J.G. (Queen' s Univ. of Belfast (United Kingdom))

1994-11-01T23:59:59.000Z

112

Building Energy Software Tools Directory: Load Express  

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

Create project files with Load Express in just 4 easy steps. Select a weather profile, enter simulation parameters, define the zonesrooms in the building and create air handler...

113

Amp-hour counting control for PV hybrid power systems  

SciTech Connect

The performance of an amp-hour (Ah) counting battery charge control algorithm has been defined and tested using the Digital Solar Technologies MPR-9400 microprocessor based PV hybrid charge controller. This work included extensive field testing of the charge algorithm on flooded lead-antimony and valve regulated lead-acid (VRLA) batteries. The test results after one-year have demonstrated that PV charge utilization, battery charge control, and battery state of charge (SOC) has been significantly improved by providing maximum charge to the batteries while limiting battery overcharge to manufacturers specifications during variable solar resource and load periods.

Hund, T.D. [Sandia National Labs., Albuquerque, NM (United States); Thompson, B. [Biri Systems, Ithaca, NY (United States)

1997-06-01T23:59:59.000Z

114

Bradbury Science Museum announces winter opening hours  

NLE Websites -- All DOE Office Websites (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

115

Analyzing occupancy profiles from a lighting controls field study  

SciTech Connect

Despite a number of published studies on the effectiveness of lighting controls in buildings, only one US study examines the occupancy patterns of building occupants. Occupancy profiles allow one to determine, for example, the probability that an office is occupied for each hour of the workday. Occupancy profiles are useful for many purposes including: (1) predicting the effectiveness of occupancy sensors for reducing peak demand, (2) evaluating the impact of human activity on building lighting and other electric loads and (3) providing lighting equipment manufacturers with detailed lighting operation data to help evaluate the impact of advanced lighting controls on equipment life. In this paper, we examine the occupancy profiles for 35 single person offices at a large office building in San Francisco and analyze the data to obtain average occupancy as a function of time of day. In addition, we analyzed the data to identify how the use of occupancy sensors may affect switching cycles and lamp life.

Rubinstein, Francis; Colak, Nesrin; Jennings, Judith; Neils, Danielle

2003-04-30T23:59:59.000Z

116

Estimating Demand Response Load Impacts: Evaluation of Baseline Load Models for Non-  

E-Print Network (OSTI)

, and the Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the ULBNL-63728 Estimating Demand Response Load Impacts: Evaluation of Baseline Load Models for Non .............................................................................................................. 9 4. Baseline Profile (BLP) Models

117

Protecting consumer privacy from electric load monitoring  

Science Conference Proceedings (OSTI)

The smart grid introduces concerns for the loss of consumer privacy; recently deployed smart meters retain and distribute highly accurate profiles of home energy use. These profiles can be mined by Non Intrusive Load Monitors (NILMs) to expose much of ... Keywords: load monitor, privacy, smart meter

Stephen McLaughlin; Patrick McDaniel; William Aiello

2011-10-01T23:59:59.000Z

118

Investigation of residential central air conditioning load shapes in NEMS  

SciTech Connect

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

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

2002-05-01T23:59:59.000Z

119

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

120

Life of a Six-Hour Hurricane  

Science Conference Proceedings (OSTI)

Hurricane Claudette developed from a weak vortex in 6 h as deep convection shifted from downshear into the vortex center, despite ambient vertical wind shear exceeding 10 m s?1. Six hours later it weakened to a tropical storm, and 12 h after the ...

Kay L. Shelton; John Molinari

2009-01-01T23:59:59.000Z

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


121

Forecasting Techniques The Use of Hourly Model-Generated Soundings to Forecast Mesoscale Phenomena. Part I: Initial Assessment in Forecasting Warm-Season Phenomena  

Science Conference Proceedings (OSTI)

Since late 1995, NCEP has made available to forecasters hourly model guidance at selected sites in the form of vertical profiles of various forecast fields. These profiles provide forecasters with increased temporal resolution and greater ...

Robert E. Hart; Gregory S. Forbes; Richard H. Grumm

1998-12-01T23:59:59.000Z

122

NERSC Edison Phase I Hours Used Report  

NLE Websites -- All DOE Office Websites (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

123

Intermediate Species Profiles in Low-Pressure Methane ...  

Science Conference Proceedings (OSTI)

... inhibited by CHF3 at an equal loading of ffuo ... 10 using the experimental temperature profile as input ... HFC mechanism may be down- loaded from http ...

2012-09-09T23:59:59.000Z

124

Day-Ahead/Hour-Ahead Forecasting for Demand Trading: A Guidebook  

Science Conference Proceedings (OSTI)

Demand trading can be an effective hedge against wholesale power price spikes during times of constraint. However, it also can be a high-risk venture. Profitability depends on reliable demand forecasting. Short-term load forecasting (STLF) can minimize the risks of day-ahead purchasing by providing better predictions at the system level. Additionally, STLF can reduce hour-ahead spot market risks and directly support demand trading by providing more accurate assessments of incremental load reductions from...

2001-12-20T23:59:59.000Z

125

Load Control  

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

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

126

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

NLE Websites -- All DOE Office Websites (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

127

LOADING DEVICE  

DOE Patents (OSTI)

A device is presented for loading or charging bodies of fissionable material into a reactor. This device consists of a car, mounted on tracks, into which the fissionable materials may be placed at a remote area, transported to the reactor, and inserted without danger to the operating personnel. The car has mounted on it a heavily shielded magazine for holding a number of the radioactive bodies. The magazine is of a U-shaped configuration and is inclined to the horizontal plane, with a cap covering the elevated open end, and a remotely operated plunger at the lower, closed end. After the fissionable bodies are loaded in the magazine and transported to the reactor, the plunger inserts the body at the lower end of the magazine into the reactor, then is withdrawn, thereby allowing gravity to roll the remaining bodies into position for successive loading in a similar manner.

Ohlinger, L.A.

1958-10-01T23:59:59.000Z

128

DOE Awards Over a Billion Supercomputing Hours to Address Scientific...  

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

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...

129

DOE's Office of Science Awards 95 Million Hours of Supercomputing...  

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

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...

130

Load-shape development aids planning  

SciTech Connect

The concept that provides capable, load-shape development, is being adopted by several utilities and power pools. Public Service Electric and Gas Company has developed a computer simulation model that can predict a utility's load shape for up to a 30-year period. The objective of the PSE and G model, known as EICS (Electric Load-Curve Synthesis) is to provide a demand profile, to examine the impact of load mangement and other activities upon a system's load shape, and to apply appropriate forecast non-load-management and load-management impacts before finally examining the resulting revised load-shape. Other models dealing with load-shape are discussed. Specifically, the Systems Control Inc. model for EPRI (SCI/EPRI), useful in performing accurate simulations of various load-control strategies involving customer appliance control is mentioned.

Gellings, C.W.

1979-12-15T23:59:59.000Z

131

The effect of load parameters on system thermal performance  

SciTech Connect

The effects of load size, load profile and hot water set temperature on system thermal performance are investigated in order to determine the relative importance of these design parameters in sizing a solar water heating system. The WATSUN IV computer program was used to introduce various load sizes, load profiles and set temperatures to a base model. The results indicate that variations in load size have a significant effect on the thermal performance of the system. However, variations in load profile and hot water set temperature seem to have no significant effect on system performance.

Vakili, M.

1984-02-01T23:59:59.000Z

132

Incremental cooling load determination for passive direct gain heating systems  

DOE Green Energy (OSTI)

This paper examines the applicability of the National Association of Home Builders (NAHB) full load compressor hour method for predicting the cooling load increase in a residence, attributable to direct gain passive heating systems. The NAHB method predictions are compared with the results of 200 hour-by-hour simulations using BLAST and the two methods show reasonable agreement. The degree of agreement and the limitations of the NAHB method are discussed.

Sullivan, P.W.; Mahone, D.; Fuller, W.; Gruber, J.; Kammerud, R.; Place, W.; Andersson, B.

1981-05-01T23:59:59.000Z

133

Building Energy Software Tools Directory: Energy Profiler  

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

can view and edit load shapes graphically, manage a database of energy rates, perform rate comparisons and generate estimated bills under a variety of scenarios. Energy Profiler...

134

LOADED WAVEGUIDES  

DOE Patents (OSTI)

>Loaded waveguides are described for the propagation of electromagnetic waves with reduced phase velocities. A rectangular waveguide is dimensioned so as to cut-off the simple H/sub 01/ mode at the operating frequency. The waveguide is capacitance loaded, so as to reduce the phase velocity of the transmitted wave, by connecting an electrical conductor between directly opposite points in the major median plane on the narrower pair of waveguide walls. This conductor may take a corrugated shape or be an aperature member, the important factor being that the electrical length of the conductor is greater than one-half wavelength at the operating frequency. Prepared for the Second U.N. International ConferThe importance of nuclear standards is duscussed. A brief review of the international callaboration in this field is given. The proposal is made to let the International Organization for Standardization (ISO) coordinate the efforts from other groups. (W.D.M.)

Mullett, L.B.; Loach, B.G.; Adams, G.L.

1958-06-24T23:59:59.000Z

135

Load-shape modeling in southeastern utility systems  

SciTech Connect

Load models are tools which have a wide range of application in the electric-utility industry. Some uses include monitoring load-management policies and helping with on-line commitment problems. The output from a load model can be placed in a suitable software environment where daily load curves are computed and displayed. Also, load models can be extended to perform forecasting functions. A weather sensitive load model that takes into account both weekdays and weekends on an hourly basis has been developed and applied to load shape modeling and short term forecasting on three southeastern electric utilities. A software package associated with the load modeling theory was developed and tested. This load-modeling program computes the daily load curve in terms of identifiable components. The program uses historical hourly load data to compute coefficients related to load components including base, growth, seasonal and weather. These coefficients can be used in a mathematical model to compute an estimate of the daily load curve with load values for each hour of the day. The load-modeling procedure described employs a linear least squares method for computing coefficients in the mathematical model.

Lebby, G.L.

1985-01-01T23:59:59.000Z

136

Classification and forecasting of load curves Nolwen Huet  

E-Print Network (OSTI)

on up to stabilisation of the clusters. Finally, the load profiles are predicted by covariance analysis of electricity customer uses. This load curve is only available for customers with automated meter readingClassification and forecasting of load curves Nolwen Huet Abstract The load curve, which gives

Cuesta, Juan Antonio

137

Static identification of delinquent loads  

E-Print Network (OSTI)

The effective use of processor caches is crucial to the performance of applications. It has been shown that cache misses are not evenly distributed throughout a program. In applications running on RISC-style processors, a small number of delinquent load instructions are responsible for most of the cache misses. Identification of delinquent loads is the key to the success of many cache optimization and prefetching techniques. In this paper, we propose a method for identifying delinquent loads that can be implemented at compile time. Our experiments over eighteen benchmarks from the SPEC suite shows that our proposed scheme is stable across benchmarks, inputs, and cache structures, identifying an average of 10 % of the total number of loads in the benchmarks we tested that account for over 90 % of all data cache misses. As far as we know, this is the first time a technique for static delinquent load identification with such a level of precision and coverage has been reported. While comparable techniques can also identify load instructions that cover 90 % of all data cache misses, they do so by selecting over 50 % of all load instructions in the code, resulting in a high number of false positives. If basic block profiling is used in conjunction with our heuristic, then our results show that it is possible to pin down just 1.3 % of the load instructions that account for 82 % of all data cache misses. 1.

Vlad-mihai Panait; Amit Sasturkar Ý

2004-01-01T23:59:59.000Z

138

The Precision and Relative Accuracy of Profiler Wind Measurements  

Science Conference Proceedings (OSTI)

Two independent wind profiles were measured every hour during February 1986 with a five-beam, UHF (405 MHz) wind Profiler at Platteville, Colorado. Our analysis of the horizontal wind components over all heights for the entire month gave a ...

R. G. Strauch; B. L. Weber; A. S. Frisch; C. G. Little; D. A. Merritt; K. P. Moran; D. C. Welsh

1987-12-01T23:59:59.000Z

139

BNL | Center for Functional Nanomaterials Hours of Operation  

NLE Websites -- All DOE Office Websites (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

140

Results of the 1000 Hour Rotary Microfilter Endurance Test  

Stellite on Nitronic 60. 8 SRNL-L3100-2010-00229 Rotary Microfilter 1000 Hour Test Flux Data for 1000 Hour Test 0 1 2 3 4 5 6 0 100 200 300 400 500 ...

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


141

Day-Ahead/Hour-Ahead Forecasting for Demand Trading: A Guidebook  

Science Conference Proceedings (OSTI)

Download report 1006016 for FREE. Demand trading can be an effective hedge against wholesale power price spikes during times of constraint. However, it also can be a high-risk venture. Profitability depends on reliable demand forecasting. Short-term load forecasting (STLF) can minimize the risks of day-ahead purchasing by providing better predictions at the system level. Additionally, STLF can reduce hour-ahead spot market risks and directly support demand trading by providing more accurate assessments o...

2001-12-20T23:59:59.000Z

142

A Technique for Removing the Effect of Migrating Birds in 915-MHz Wind Profiler Data  

Science Conference Proceedings (OSTI)

A method is described and evaluated for decreasing artifacts in radar wind profiler data resulting from overflying, migrating birds. The method processes the prerecorded, averaged spectral data of a wind profiler to derive hourly wind profiles ...

M. S. Pekour; R. L. Coulter

1999-12-01T23:59:59.000Z

143

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

Science Conference Proceedings (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

144

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

145

Regional load curve models: specification and estimation of the DRI Model. Final report. [Forecasts of electric loads in 32 US regions  

SciTech Connect

The DRI Model of hourly load curves is developed in this report. The model is capable of producing long-term forecasts for 32 US regions. These regions were created by aggregating hourly system load data from 146 electric utilities. These utilities supply approximately 95% of all electricity consumed in the continental US. The model forecasts electricity demands for each hour of the year for each of the 32 regions. Model output includes forecasts of peak demands, megawatt hour demands, load factors, and load duration curves. The DRI Model is estimated in two stages. In the first stage, for each region and month, hourly electricity demands are parameterized into load components representing the effects of lifestyles and weather on regional loads through a time-series model. In the second stage, the variation in these parameterized load components across months and regions is modeled econometrically in terms of energy prices, income levels, appliance saturation rates, and other variables. The second-stage models are essentially models of electricity demand which are estimated using estimated first-stage parameters as dependent variables, instead of observed demands. Regional price and income demand elasticities are implied by the second-stage models. Moreover, since the dependent variables refer to particular hours of the day, these estimated elasticities are hour-specific. (Since prices did not vary over the day in years when hourly load data were available, hour-to-hour, cross-price elasticities were not estimated.) Integrated system hourly load forecasts are obtained combining the influences of individual customer classes. Finally, approximate customer class hourly load shapes can be produced for each region, though these series may be useful only in research endeavors since they lack the precision available through survey methods.

Platt, H.D.; Einhorn, M.A.; Ignelzi, P.C.; Poirier, D.J.

1981-01-01T23:59:59.000Z

146

Matching equipment size to the cooling load  

SciTech Connect

This article presents a heat extraction rate analysis method, using ASHRAE algorithms that enables HVAC system designers to optimally size cooling equipment. The final stage of the cooling load calculation process determines the heat extraction rate required to achieve design conditions. Put another way, this stage determines the equipment capacity required to match the cooling load profile, and it does so in a manner that predicts the resulting space temperature profile, and it does so in a manner that predicts the resulting space temperature profile. It is a stage in the design process that, in practice, may not be given the attention it deserves.

Bloom, B. (Harvey Toub Engineering, Atlanta, GA (United States))

1993-10-01T23:59:59.000Z

147

Demand Management Demonstration Project, Stage 5: development of industrial load simulation model. Executive summary. Final report  

SciTech Connect

The purpose of this project was to design, develop, test and document a computer simulation model of electric utility generating costs required to meet industrial power demands and the effects of utility load management on these generating costs. The results showed that the model developed is a well conceived load management testing, marginal costing tool. What if situations can be readily tested to determine their impact on system profile and short run marginal costs. The terms unshaped and shaped refer to customers or system use patterns before and after some load management technique was tested. The total flexibility of the model is only apparent after the user has studied test runs in detail. Hourly marginal costs reveal many unexpected changes as a result of shaping loads. Other unexpected changes due to varying economic dispatch schedules while shaping, illustrate the unprecedental latitude for the user to explore optimum generation and load management combinations. The general concept of the model is depicted in the flow chart on the next page.

1977-04-01T23:59:59.000Z

148

A Climatological Measure of Extreme Snowdrift Loading on Building Roofs  

Science Conference Proceedings (OSTI)

A physical model of snow transport and deposition is used in combination with historical climatological data to derive a climatological measure of extreme snowdrift loads on building roofs. The snowdrift metric used relies on hourly wind speed, ...

Arthur T. DeGaetano; Michael J. O'Rourke

2004-01-01T23:59:59.000Z

149

Peak load management: Potential options  

SciTech Connect

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

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

1989-10-01T23:59:59.000Z

150

Realizing load reduction functions by aperiodic switching of load groups  

SciTech Connect

This paper investigates the problem of scheduling ON/OFF switching of residential appliances under the control of a Load Management System (LMS). The scheduling process is intended to reduce the controlled appliances` power demand in accordance with a predefined load reduction profile. To solve this problem, a solution approach, based on the methodology of Pulse Width Modulation (PWM), is introduced. This approach provides a flexible mathematical basis for studying different aspects of the scheduling problem. The conventional practices in this area are shown to be special cases of the PWM technique. By applying the PWM-based technique to the scheduling problem, important classes of scheduling errors are identified and analytical expressions describing them are derived. These expressions are shown to provide sufficient information to compensate for the errors. Detailed simulations of load groups` response to switching actions are use to support conclusions of this study.

Navid-Azarbaijani, N. [McGill Univ., Montreal, Quebec (Canada). Dept. of Electrical Engineering; Banakar, M.H. [CAE Electronics Ltd., St. Laurent, Quebec (Canada)

1996-05-01T23:59:59.000Z

151

Low-cost load research for electric utilities  

Science Conference Proceedings (OSTI)

Golden Valley Electric Association (GVEA) developed two pragmatic approaches to meet most load-research objectives at a substantially lower cost than would be incurred with traditional techniques. GVEA serves three customer classes, with most of its load in the Fairbanks area. GVEA's new approaches simulate load curves for individual customer classes to the degree necessary to meet most load-research objectives for the utility, including applications to cost-of-service analysis, rate design, demand-side management, and load forecasting. These approaches make class load-shape information available to utilities that cannot otherwise afford to develop such data. Although the two approaches were developed for a small utility, they are likely to work at least as well for medium and large utilities. The first approach simulates class curves by combining load data from system feeders with information on customer mix and energy usage. GVEA's supervisory control and data acquisition system gives hourly data on feeder loads, and its billing database provides the number of customers and kilowatt-hour usage by customer class on each feeder. The second approach enhances load-research results by redefining target parameters. Data from several like-hours are used to calculate substitutes for the parameters traditionally defined from single-hour data points. The precision of peak responsibility estimates, for example, can be improved if several of the highest hourly demands in a given time period are used rather than the single highest hourly demand. Arguably, use of several highest hourly demands can also improve the reliability of the allocation of responsibility.

Gray, D.A.; Butcher, M.

1994-08-01T23:59:59.000Z

152

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

NLE Websites -- All DOE Office Websites (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...

153

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

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

Twitter Delayed Start or Cancellation of Business Hours Winter Road Closings Winter Weather FAQs Westgate Alternate Routes Reporting IllegalUnethical Activity Working Remotely...

154

Low cutter load raise head  

SciTech Connect

A raise head having a multiplicity of cutters for enlarging a pilot hole into a larger diameter hole by disintegrating the earth formations that surround the pilot hole is provided that will require lower cutter loads to penetrate the formations being bored by directing the rock fracture planes toward the pilot hole forcing the rock to yield with less input energy. The cutters are positioned on the raise head to provide an earth formation contact profile with a major portion of said earth formation contact profile extending outward and upward from said pilot hole. The included angle between the major portion of the earth formation contact profile and the axis of the pilot hole is less than 90/sup 0/.

Saxman, W.C.

1981-03-31T23:59:59.000Z

155

Load management strategies for electric utilities: a production cost simulation  

SciTech Connect

This paper deals with the development and application of a simulation model for analyzing strategies for managing the residential loads of electric utilities. The basic components of the model are (1) a production-cost model, which simulates daily operation of an electric power system; (2) a load model, which disaggregates system loads into appliance loads and other loads; and (3) a comparison model, which compares the production costs and energy consumption needed to meet a particular load profile to the corresponding costs and energy consumption required for another load profile. The profiles in each pair define alternative ways of meeting the same demand. A method for disaggregating load profiles into appliance components is discussed and several alternative strategies for residential load management for a typical northeastern electric utility are formulated. The method is based on an analysis of the composition of electric loads for a number of classes of residential customers in the model utility system. The effect of alternative load management strategies on the entire residential loadcurve is determined by predicting the effects of these strategies on the specific appliance components of the loadcurve. The results of using the model to analyze alternative strategies for residential load management suggest that load management strategies in the residential sector, if adopted by utilities whose operating and load characteristics are similar to those of the system modeled here, must take into account a wide variety of appliances to achieve significant changes in the total load profile. Moreover, the results also suggest that it is not easy to reduce costs significantly through new strategies for managing residential loads only and that, to be worthwhile, cost-reducing strategies will have to encompass many kinds of appliances.

Blair, P.D.

1979-03-01T23:59:59.000Z

156

How and why distribution loads vary  

SciTech Connect

Because the maximum-use rates of gas customers having differing appliance combinations do not coincide, a distribution system's peak-hour flow rate depends on the relative proportions of the load contributed by the appliances of all the different types of residential, commercial, and industrial customers. The maximum load on Central Hudson's distribution system coincides with the maximum hourly gas flow rate for all residential space-heating purposes; however, Central Hudson analyzes the peak-hour load of its commercial and industrial customers individually. The gas-system sendout presented as a sendout-duration curve is a convenient way to show how these various loads determine gas requirements and to compare the economics of alternative supply methods. The sendout-duration curve consists of long-term weather data plotted against time intervals of 1-365 days. If the threshold temperature and the heating load per degree-day are known, the curve allows the calculation of both normal and design annual peakshaving quantities.

Haber, D.P.

1980-01-01T23:59:59.000Z

157

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

Science Conference Proceedings (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

158

Optimizing hourly hydro operations at the Salt Lake City Area integrated projects  

DOE Green Energy (OSTI)

The Salt Lake City Area (SLCA) office of the Western Area Power Administration (Western) is responsible for marketing the capacity and energy generated by the Colorado Storage, Collbran, and Rio Grande hydropower projects. These federal resources are collectively called the Salt Lake City Area Integrated Projects (SLCA/IP). In recent years, stringent operational limitations have been placed on several of these hydropower plants including the Glen Canyon Dam, which accounts for approximately 80% of the SLCA/IP resources. Operational limitations on SLCA/IP hydropower plants continue to evolve as a result of decisions currently being made in the Glen Canyon Dam Environmental Impact Statement (EIS) and the Power Marketing EIS. To analyze a broad range of issues associated with many possible future operational restrictions, Argonne National Laboratory (ANL), with technical assistance from Western has developed the Hydro LP (Linear Program) Model. This model simulates hourly operations at SLCA/IP hydropower plants for weekly periods with the objective of maximizing Western`s net revenues. The model considers hydropower operations for the purpose of serving SLCA firm loads, loads for special projects, Inland Power Pool (IPP) spinning reserve requirements, and Western`s purchasing programs. The model estimates hourly SLCA/IP generation and spot market activities. For this paper, hourly SLCA/IP hydropower plant generation is simulated under three operational scenarios and three hydropower conditions. For each scenario an estimate of Western`s net revenue is computed.

Veselka, T.D.; Hamilton, S. [Argonne National Lab., IL (United States); McCoy, J. [Western Area Power Administration, Salt Lake City, UT (United States)

1995-06-01T23:59:59.000Z

159

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

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

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

160

Periodic load balancing  

Science Conference Proceedings (OSTI)

Multiprocessor load balancing aims to improve performance by moving jobs from highly loaded processors to more lightly loaded processors. Some schemes allow only migration of new jobs upon arrival, while other schemes allow migration of ... Keywords: heavy traffic diffusion approximations, load balancing, periodic load balancing, reflected Brownian motion, resource sharing, transient behavior

Gísli Hjálmtýsson; Ward Whitt

1998-06-01T23:59:59.000Z

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


161

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

SciTech Connect

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

162

Enhancements to ANNSTLF, EPRI's Short Term Load Forecaster  

Science Conference Proceedings (OSTI)

Reliable hourly load forecasts are important to electric utilities, power marketers, energy service providers, and independent system operators. To meet this need, EPRI's Artificial Neural Net Short Term Load Forecaster (ANNSTLF), which is already implemented at more than thirty-five utilities, was recently enhanced for greater accuracy and user friendliness.

1997-12-08T23:59:59.000Z

163

Building Energy Software Tools Directory: Energy Profiler Online  

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

Online service that provides commercial and industrial energy customers with access to energy usage information and analysis tools. Customers can view load profiles, usage...

164

Real Time Pricing as a Default or Optional Service for C&I Customers: A Comparative Analysis of Eight Case Studies  

E-Print Network (OSTI)

use of class average load profiles for setting the commodityof developing an hourly load profile for each individualneed for class-average load profiles for commodity pricing (

Barbose, Galen; Goldman, Charles; Bharvirkar, Ranjit; Hopper, Nicole; Ting, Michael; Neenan, Bernie

2005-01-01T23:59:59.000Z

165

Report of 1,000 Hour Catalyst Longevity Evaluation  

DOE Green Energy (OSTI)

This report presents the results of a 1,000 hour, high-pressure, catalyst longevity test for the decomposition of concentrated sulfuric acid. The reaction is used for both the sulfur-iodine (S-I) cycle and hybrid sulfur cycle. By the time of the delivery date of April 17, 2009, for project milestone no. 2NIN07TC050114, the 1% Pt/TiO2 catalyst had been in the reaction environment for 658 hours. During the first 480 hours of testing, the catalyst activity provided stable, near-equilibrium yields of 46.8% SO2 and 22.8% O2. However, product yields declined at sample exposure times >480 hours. At 658 hours of operation, catalyst activity (based on oxygen yield) declined to 57% relative to the stable period of catalyst activity. Thus, as of April 17, this catalyst did not provide the desired stability level of <10% degradation per 1,000 hours. The experiment was terminated on April 27, after 792 hours, when a fitting failed and the catalyst was displaced from the reactor such that the sample could not be recovered. Oxygen conversion at the end of the experiment was 12.5% and declining, suggesting that at that point, catalyst activity had decreased to 54% of the initial level.

Daniel M. Ginosar

2009-06-01T23:59:59.000Z

166

Development of an Hourly Optimization Tool for Renewable Energy Systems  

SciTech Connect

An hourly optimization tool is developed to select and size renewable energy (RE) systems to meet the energy needs for various federal facilities. The optimization is based on life cost analysis of various RE technologies including wind and PV systems. The developed hourly optimization tool is used to evaluate the cost-effectiveness of RE technologies using complex energy and demand charges such time-of-use (TOU) rates. The paper compares results obtained using hourly analysis instead of annual based calculations to optimize the sizing of RE systems for residential, commercial, and industrial facilities in three representative US climates.

Lee, C.; Walker, A.; Krarti, M.

2010-01-01T23:59:59.000Z

167

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

SciTech Connect

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

Katipamula, Srinivas; Hatley, Darrel D.

2004-12-22T23:59:59.000Z

168

A Quality Assurance System for Canadian Hourly Pressure Data  

Science Conference Proceedings (OSTI)

In this study a comprehensive quality assurance (QA) system, which includes the hydrostatic check combined with a statistical homogeneity test, is designed and applied to hourly pressure records (for 1953–2002) from 761 Canadian stations, to ...

Hui Wan; Xiaolan L. Wang; Val R. Swail

2007-11-01T23:59:59.000Z

169

Complex Quality Assurance of Historical Hourly Surface Airways Meteorological Data  

Science Conference Proceedings (OSTI)

A new complex quality assurance (QA) procedure is developed for historical hourly surface airways meteorological data, recently digitized in a U.S. government–sponsored effort that extends the digital period of record back as early as the late ...

Daniel Y. Graybeal; Arthur T. DeGaetano; Keith L. Eggleston

2004-08-01T23:59:59.000Z

170

Team Surpasses 1 Million Hours Safety Milestone | Department of Energy  

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

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.

171

Team Surpasses 1 Million Hours Safety Milestone | Department of Energy  

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

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.

172

DOE Awards Over a Billion Supercomputing Hours to Address Scientific  

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

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.

173

DOE Awards Over a Billion Supercomputing Hours to Address Scientific  

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

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

174

Global Solar Radiation Estimation from Relative Sunshine Hours in Italy  

Science Conference Proceedings (OSTI)

We examine the existing measurements of global solar radiation and sunshine duration for Italy, and evaluate the errors made in estimating global solar radiation from sunshine hours measurements. We find that the Ångstrom–Black linear relation in ...

A. Andretta; B. Bartoli; B. Coluzzi; V. Cuomo; M. Francesca; C. Serio

1982-10-01T23:59:59.000Z

175

Airport quotas and peak hour pricing : theory and practice  

E-Print Network (OSTI)

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

Odoni, Amedeo R.

1976-01-01T23:59:59.000Z

176

An Hourly Assimilation–Forecast Cycle: The RUC  

Science Conference Proceedings (OSTI)

The Rapid Update Cycle (RUC), an operational regional analysis–forecast system among the suite of models at the National Centers for Environmental Prediction (NCEP), is distinctive in two primary aspects: its hourly assimilation cycle and its use ...

Stanley G. Benjamin; Dezsö Dévényi; Stephen S. Weygandt; Kevin J. Brundage; John M. Brown; Georg A. Grell; Dongsoo Kim; Barry E. Schwartz; Tatiana G. Smirnova; Tracy Lorraine Smith; Geoffrey S. Manikin

2004-02-01T23:59:59.000Z

177

Hourly Energy Emission Factors for Electricity Generation in...  

Open Energy Info (EERE)

Hourly Energy Emission Factors for Electricity Generation in the United States

Emissions from energy use in buildings are usually estimated on an annual...

178

The Temperature Sensitivity of the Residential Load and Commercial Building Load  

SciTech Connect

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

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

2009-07-26T23:59:59.000Z

179

Wind Power Plants and System Operation in the Hourly Time Domain: Preprint  

DOE Green Energy (OSTI)

Because wind is an intermittent power source, the variability may have significant impacts on system operation. Part of the difficulty of analyzing the load following impact of wind is the inadequacy of most modeling frameworks to accurately treat wind plants and the difficulty of untangling causal impacts of wind plants from other dynamic phenomena. This paper presents a simple analysis of an hourly load-following requirement that can be performed without extensive computer modeling. The approach is therefore useful as a first step to quantifying these impacts when extensive modeling and data sets are not available. The variability that wind plants add to the electricity supply must be analyzed in the context of overall system variability. The approach used in this paper does just that. The results show that wind plants do have an impact on load following, but when calculated as a percentage of the installed wind plant capacity, this impact is not large. Another issue is the extent to which wind forecast errors add to imbalance. The relative statistical independence of wind forecast errors and load forecast errors can be used to help quantify the extent to which wind forecast errors impact overall system imbalances.

Milligan, M.

2003-05-01T23:59:59.000Z

180

Building Energy Software Tools Directory: HAP System Design Load  

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

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

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


181

Battery loading device  

SciTech Connect

A battery loading device for loading a power source battery, built in small appliances having a battery loading chamber for selectively loading a number of cylindrical unit batteries or a one body type battery having the same voltage as a number of cylindrical unit batteries, whereby the one body type battery and the battery loading chamber are shaped similarly and asymmetrically in order to prevent the one body type battery from being inserted in the wrong direction.

Phara, T.; Suzuki, M.

1984-08-28T23:59:59.000Z

182

Automatic Electric Load Identification in  

E-Print Network (OSTI)

Abstract — A microgrid is the power system of choice for the electrification of rural areas in developing countries. It should be able to adapt to changing load situations without the need for specialists to change the configuration of the microgrid controller. This paper proposes a self-configuring microgrid management system that is able to adjust both generation and demand of the system, so that also in case of growing electricity demand the grid can still be operable by disconnecting unessential loads. A crucial task for the microgrid controller is to automatically identify the connected loads on the basis of their consumption behaviors. For this, a template-matching algorithm is proposed that is based on Dynamic Time Warping, which is primarily used in speech recognition. It has been found that for load profile analysis, simple signal features such as the number of rising edges or the aggregated energy consumption in a given time window is sufficient to describe the signal. In contrast to speech recognition, frequency domain analysis is not necessary.

Self-configuring Microgrids; Friederich Kupzog; Tehseen Zia; Adeel Abbas Zaidi

2009-01-01T23:59:59.000Z

183

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

184

INCITE Program Doles Out Hours on Supercomputers | Department of Energy  

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

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

185

1991 Pacific Northwest Loads and Resources Study.  

SciTech Connect

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

United States. Bonneville Power Administration.

1991-12-01T23:59:59.000Z

186

Regional load-curve models. Volume 5. Data base. Final report  

SciTech Connect

In preparing to build the models detailed in the first four volumes of the EA-1672 reports, a substantial data gathering, clean-up, and organizing effort was conducted. This volume describes that process and documents the data banks sent to EPRI. Three types of data concepts were needed to explore hourly load forecasting: hourly load, hourly weather and related socioeconomic data concepts. These materials were gathered for the project. EPRI has 32 data tapes that include hourly load and weather data for 32 regions for the period 1962 to 1977. Two other data banks, EPRIDATAA and EPRIDATAM, contain annual and monthly data respectively, gathered for use in this project. Hourly load forecasts out to the year 2000 have also been received by EPRI. DRI's forecasts are contained in the data bank FORECASTBANK. QUERI's forecasts are also available. These data series may prove useful to other researchers exploring related topics.

Platt, H.D.

1984-04-01T23:59:59.000Z

187

Failure Loads and Deformation in 6061-T6 Aluminum Alloy Spot ...  

Science Conference Proceedings (OSTI)

Presentation Title, Failure Loads and Deformation in 6061-T6 Aluminum Alloy ... Application of Neutron Diffraction in Analysis of Residual Stress Profile in the ...

188

EPRI/GRI Load Shape Workshop: Load Data Analysis for Gas and Electric Markets  

Science Conference Proceedings (OSTI)

Load shapes, representing usage patterns in the electric and gas industry, are a key factor in energy company operations and management. In the emerging restructured energy market, retail energy suppliers market energy to final customers and must arrange for electricity generation or gas delivery to meet their customers' needs. EPRI and GRI sponsored a two-day workshop in June, 1999 that addressed a range of issues associated with load shapes, including modeling, profiling for retail market settlement, r...

1999-11-10T23:59:59.000Z

189

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

190

Load Response Fundamentally Matches Power System Reliability Requirements  

Science Conference Proceedings (OSTI)

Responsive load is the most underutilized reliability resource available to the power system. Loads are frequently barred from providing the highest value and most critical reliability services; regulation and spinning reserve. Advances in communications and control technology now make it possible for some loads to provide both of these services. The limited storage incorporated in some loads better matches their response capabilities to the fast reliability-service markets than to the hourly energy markets. Responsive loads are frequently significantly faster and more accurate than generators, increasing power system reliability. Incorporating fast load response into microgrids further extends the reliability response capabilities that can be offered to the interconnected power system. The paper discusses the desired reliability responses, why this matches some loads' capabilities, what the advantages are for the power system, implications for communications and monitoring requirements, and how this resource can be exploited.

Kirby, Brendan J [ORNL

2007-01-01T23:59:59.000Z

191

Discharge circuits and loads  

SciTech Connect

This will be an overview in which some of the general properties of loads are examined: their interface with the energy storage and switching devices; general problems encountered with different types of loads; how load behavior and fault modes can impact on the design of a power conditioning system (PCS).

Sarjeant, W.J.

1980-10-15T23:59:59.000Z

192

Renewable Energies program (6 credit hour) Option A: 11  

E-Print Network (OSTI)

Renewable Energies program (6 credit hour) Option A: 11 Option B: The program is organized by t Spanish Institute and the Asso program on renewable energy will provide students with advanced knowledge. opportunities: option A- two renewable energies; option B include on-site visits to renewable energy generation

Simaan, Nabil

193

A Quality-Control Routine for Hourly Wind Observations  

Science Conference Proceedings (OSTI)

The quality of hourly wind speed and direction observations from 41 northeastern U.S. first-order weather stations is evaluated with regard to the recognition of individual observations that are either obviously in error or of suspect quality. An ...

Arthur T. DeGaetano

1997-04-01T23:59:59.000Z

194

Storing hydroelectricity to meet peak-hour demand  

Science Conference Proceedings (OSTI)

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

Valenti, M.

1992-04-01T23:59:59.000Z

195

Mentee Profile  

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

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

196

Mentor Profile  

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

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

197

IPM Profiling Tool at NERSC  

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

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

198

Market Driven Distributed Energy Storage Requirements for Load Management Applications  

Science Conference Proceedings (OSTI)

Electric energy storage systems are an enabling technology that could help meet the needs of electric utility by managing peak energy demands, helping shift the peak loads to off peak hours and improving the load factor of the electric distribution system. Applications of distributed energy storage systems (DESS) could also provide power quality and reliability benefits to customers and to the electric system. EPRI collaborated with several investor owned utilities to conduct a study to understand the te...

2007-04-18T23:59:59.000Z

199

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

200

Observed Temperature Effects on Hourly Residential Electric Load Reduction in Response to an Experimental Critical Peak Pricing Tariff  

E-Print Network (OSTI)

by building type and climate zone with the intent ofWe roughly describe the climate zones as Coast, Foothills,group A. Stratum B. SPP climate zone - description 1- Coast

Herter, Karen B.; McAuliffe, Patrick K.; Rosenfeld, Arthur H.

2005-01-01T23:59:59.000Z

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


201

Observed Temperature Effects on Hourly Residential Electric Load Reduction in Response to an Experimental Critical Peak Pricing Tariff  

E-Print Network (OSTI)

means of decreasing residential energy consumption. Journalreductions gained through residential CPP rates, with or7. Hypothetical effects of residential CPP rates with and

Herter, Karen B.; McAuliffe, Patrick K.; Rosenfeld, Arthur H.

2005-01-01T23:59:59.000Z

202

After-hours power status of office equipment and energy use of miscellaneous plug-load equipment  

E-Print Network (OSTI)

ovens and computer projectors are categorized as ‘electronics’ although they might alternatively be categorized as ‘heating’

Roberson, Judy A.; Webber, Carrie A.; McWhinney, Marla C.; Brown, Richard E.; Pinckard, Margaret; Busch, John F.

2004-01-01T23:59:59.000Z

203

After-hours power status of office equipment and energy use of miscellaneous plug-load equipment  

E-Print Network (OSTI)

industrial refrigerator, S freezer incandescent tracklight, 50 lamps each phone/PBX centrex system coffee maker, residential model microwave oven

Roberson, Judy A.; Webber, Carrie A.; McWhinney, Marla C.; Brown, Richard E.; Pinckard, Margaret; Busch, John F.

2004-01-01T23:59:59.000Z

204

Bolt profile configuration and load transfer capacity optimisation.  

E-Print Network (OSTI)

??Rapid advances in rock bolting technology over the past four decades have firmly established the usage of rock bolts as the primary rock reinforcement system… (more)

Cao, Chen

2012-01-01T23:59:59.000Z

205

Optimum matching of ohmic loads to the photovoltaic array  

SciTech Connect

Optimum matching of loads to the photovoltaic (PV) generator is most desirable for more accurate sizing, higher system performance and maximum utilization of the costly solar array generator. The quality of load matching depends on the PV array characteristics, the load characteristics, and the insolation profile. A matching factor is defined as the ratio of the load energy to the array maximum energy over a one day period. Optimum matching is achieved by determining the optimal array parameters with respect to the load parameters. Optimization is done using direct-search techniques. Results show that the theoretical optimum matching factor for an ohmic load is 94.34%. For an electrolytic load the matching factor could reach 99.83%. A maximum power tracker can be eliminated if optimum matching is achieved.

Khouzam, K.; Khouzam, L.; Groumpos, P. (Cleveland State Univ., OH (USA))

1991-01-01T23:59:59.000Z

206

Structural load combinations  

SciTech Connect

This paper presents the latest results of the program entitled, ''Probability Based Load Combinations For Design of Category I Structures''. In FY 85, a probability-based reliability analysis method has been developed to evaluate safety of shear wall structures. The shear walls are analyzed using stick models with beam elements and may be subjected to dead load, live load and in-plane eqrthquake. Both shear and flexure limit states are defined analytically. The limit state probabilities can be evaluated on the basis of these limit states. Utilizing the reliability analysis method mentioned above, load combinations for the design of shear wall structures have been established. The proposed design criteria are in the load and resistance factor design (LRFD) format. In this study, the resistance factors for shear and flexure and load factors for dead and live loads are preassigned, while the load factor for SSE is determined for a specified target limit state probability of 1.0 x 10/sup -6/ or 1.0 x 10/sup -5/ during a lifetime of 40 years. 23 refs., 9 tabs.

Hwang, H.; Reich, M.; Ellingwood, B.; Shinozuka, M.

1985-01-01T23:59:59.000Z

207

Watershed Mercury Loading Framework  

Science Conference Proceedings (OSTI)

This report explains and illustrates a simplified stochastic framework, the Watershed Mercury Loading Framework, for organizing and framing site-specific knowledge and information on mercury loading to waterbodies. The framework permits explicit treatment of data uncertainties. This report will be useful to EPRI members, state and federal regulatory agencies, and watershed stakeholders concerned with mercury-related human and ecological health risk.

2003-05-23T23:59:59.000Z

208

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.

209

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.

210

Folding Proteins at 500 ns/hour with Work Queue  

E-Print Network (OSTI)

Abstract—Molecular modeling is a field that traditionally has large computational costs. Until recently, most simulation techniques relied on long trajectories, which inherently have poor scalability. A new class of methods is proposed that requires only a large number of short calculations, and for which minimal communication between computer nodes is required. We considered one of the more accurate variants called Accelerated Weighted Ensemble Dynamics (AWE) and for which distributed computing can be made efficient. We implemented AWE using the Work Queue framework for task management and applied it to an all atom protein model (Fip35 WW domain). We can run with excellent scalability by simultaneously utilizing heterogeneous resources from multiple computing platforms such as clouds (Amazon EC2, Microsoft Azure), dedicated clusters, grids, on multiple architectures (CPU/GPU, 32/64bit), and in a dynamic environment in which processes are regularly added or removed from the pool. This has allowed us to achieve an aggregate sampling rate of over 500 ns/hour. As a comparison, a single process typically achieves 0.1 ns/hour. I.

Badi Abdul-wahid; Li Yu; Dinesh Rajan

2012-01-01T23:59:59.000Z

211

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.

212

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.

213

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.

214

End-Use Load-Shape Estimation: Methods and Validation  

Science Conference Proceedings (OSTI)

In developing effective demand-side management plans and load forecasts, utilities need information on customer hourly load patterns over a range of end-uses. Such information may be obtained using the two methods described in this report for disaggregating whole-building load data. Both methods have been validated using end-use metered data. This report is available only to funders of Program 101A or 101.001. Funders may download this report at http://my.primen.com/Applications/DE/Community/index.asp .

1991-02-01T23:59:59.000Z

215

Climatic indicators for estimating residential heating and cooling loads  

Science Conference Proceedings (OSTI)

An extensive data base of residential energy use generated with the DOE-2.1A simulation code provides an opportunity for correlating building loads predicted by an hourly simulation model to commonly used climatic parameters such as heating and cooling degree-days, and to newer parameters such as insolation-days and latent enthalpy-days. The identification of reliable climatic parameters for estimating cooling loads and the incremental loads for individual building components, such as changing ceiling and wall R-values, infiltration rates or window areas is emphasized.

Huang, Y.J.; Ritschard, R.; Bull, J.; Chang, L.

1986-11-01T23:59:59.000Z

216

Analysis of Loads and Wind Energy Potential for Remote Power Stations in Alaska University of Massachusetts Amherst  

E-Print Network (OSTI)

Analysis of Loads and Wind Energy Potential for Remote Power Stations in Alaska Mia Devine Electric Use (kWh/year) 2,173,400 1,032,800 2,520,500 Average Load 300 kW 140 kW 280 kW Peak Load 600 k load profile. Villages usuall

Massachusetts at Amherst, University of

217

Regional load-curve models: scenario and forecast using the DRI model. Final report. [Forecasts of electric power loads in 32 US regions  

SciTech Connect

Regional load curve models were constructed for 32 regions that have been created by aggregating hourly load data from 146 electric utilities. These utilities supply approximately 95% of the electricity consumed in the continental US. The 32 models forecast electricity demands by hour, 8784 regional load forecasts per year. Because projections are made for each hour in the year, contemporaneous forecasts are available for peak demands, megawatt hour demands, load factors, load duration curves, and typical load shapes. The forecast scenario is described and documented in this volume and the forecast resulting from the use of this scenario is presented. The highlights of this forecast are two observations: (1) peak demands will once again become winter phenomena. By the year 2000, 18 of the 32 regions peak in a winter month as compared with the 8 winter peaking regions in 1977. In the heating season, the model is responsive to the number of heating degree-hours, the penetration rate of electric heating equipment, and the rate at which this space conditioning equipment is utilized, which itself is functionally dependent on the level of real electricity prices and real incomes. Thus, as the penetration rate of electric heating equipment increases, winter season demands grow more rapidly than demands in other seasons and peaks begin to appear in winter months; and (2) load factors begin to increase in the forecast, reversing the trend which began in the early 1960s. Nationally, load factors do not leap upwards, instead they increase gradually from .609 in 1977 to .629 in the year 2000. The improvement is more consequential in some regions, with load factors increasing, at times, by .10 or more. In some regions, load factors continue to decline.

Platt, H.D.

1981-08-01T23:59:59.000Z

218

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

219

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

220

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

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


221

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

222

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

223

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

224

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

225

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

226

What do hourly performance data on a building tell us  

DOE Green Energy (OSTI)

Hourly performance data on a building contain valuable information on the dynamics of the building and of the HVAC systems. Quantities such as the building loss coefficient, solar gains, and the net effect of thermal masses and their couplings are all contained in the data. The building element vector analysis (BEVA) method has been applied to a multizone residential passive solar building monitored under the SERI Class B program. Using short-term data (approximately one week), the building parameters were regressed. With these as inputs, the subsequent performance of the building was well predicted. Using performance data for the period February 3-9, 1982, the building vectors were obtained by regression. The resulting best fit for the zone temperature is given. These parameters were used to predict the temperature for the period February 10-14. The resulting values are also plotted along with the outdoor temperature, solar radiation on a south vertical surface, and auxiliary energy for these periods.

Subbarao, K.

1984-11-01T23:59:59.000Z

227

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

228

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

229

322 IEEE TRANSACTIONS ON POWER SYSTEMS. VOL. 25. NO. I. FEBRUARY 2010 Short-Term Load Forecasting: Similar  

E-Print Network (OSTI)

for Short Term Electrical Load Forecasting," IEEE Trans. PWRS, vol. 11, no. 1, Feb. 1996, pp. 397-402. [4Short-Term Load Forecasting by Feed-Forward Neural Networks Saied S. Sharif1 , James H. Taylor2) is presented for the hourly load forecasting of the coming days. In this approach, 24 independent networks

Luh, Peter

230

HLW Glass Waste Loadings  

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

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

231

OpenEI - load  

Open Energy Info (EERE)

are given by a location defined by the Typical Meteorological Year (TMY) for which the weather data was collected. Commercial load data is sorted by the (TMY) site as a...

232

Composite Load Model Evaluation  

Science Conference Proceedings (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

233

Building Energy Software Tools Directory: TRACE Load 700  

NLE Websites -- All DOE Office Websites (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"

234

The Dynamics of an Upper-Level Trough in the Baroclinic Westerlies: Analysis Based upon Data from a Wind Profiler Network  

Science Conference Proceedings (OSTI)

Hourly wind data from the National Oceanic and Atmospheric Administration's demonstration network of 404-MHz profilers in the central United States and hourly wind data from the standard National Weather Service surface network are used to ...

Howard B. Bluestein; Douglas A. Speheger

1995-08-01T23:59:59.000Z

235

Distribution substation load impacts of residential air conditioner load control  

SciTech Connect

An ongoing experiment to monitor the substation level load impacts of end-use load control is described. An overview of the data acquisition system, experimental procedures and analysis techniques are provided. Results of the 1983 and 1984 experiments demonstrate the value of aggregate load impact monitoring as a means of verifying load research results, calculating the diversity of end-use loads, and predicting the impacts of load management on the transmission and distribution systems.

Heffner, G.C.; Kaufman, D.A.

1985-07-01T23:59:59.000Z

236

Statistical Review of UK Residential Sector Electrical Loads  

E-Print Network (OSTI)

This paper presents a comprehensive statistical review of data obtained from a wide range of literature on the most widely used electrical appliances in the UK residential load sector. It focuses on individual appliances and begins by consideration of the electrical operations performed by the load. This approach allows for the loads to be categorised based on the electrical characteristics, and also provides information on the reactive power characteristics of the load, which is often neglected from standard consumption statistics. This data is particularly important for power system analysis. In addition to this, device ownership statistics and probability distribution functions of power demand are presented for the main residential loads. Although the data presented is primarily intended as a resource for the development of load profiles for power system analysis, it contains a large volume of information which provides a useful database for the wider research community.

Tsagarakis, G; Kiprakis, A E

2013-01-01T23:59:59.000Z

237

Load Monitoring CEC/LMTF Load Research Program  

SciTech Connect

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

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

2007-11-30T23:59:59.000Z

238

Profile and frictional capacity of embedded anchor chains  

SciTech Connect

Previously published methods for solving the force distribution and geometric profile of an embedded anchor chain involve numerical solution by an incremental integration technique. By rationalizing the problem, closed-form expressions for both the load development and chain profile have been derived. These expressions greatly simplify the procedure for estimating the load and inclination of an embedded chain at some connection point in the soil. The analytical work is corroborated with extensive laboratory test results.

Neubecker, S.R.; Randolph, M.F. [Univ. of Western Australia, Nedlands (Australia). Dept. of Civil Engineering

1995-11-01T23:59:59.000Z

239

Mass-Loaded Flows  

E-Print Network (OSTI)

A key process within astronomy is the exchange of mass, momentum, and energy between diffuse plasmas in many types of astronomical sources (including planetary nebulae, wind-blown bubbles, supernova remnants, starburst superwinds, and the intracluster medium) and dense, embedded clouds or clumps. This transfer affects the large scale flows of the diffuse plasmas as well as the evolution of the clumps. I review our current understanding of mass-injection processes, and examine intermediate-scale structure and the global effect of mass-loading on a flow. I then discuss mass-loading in a variety of diffuse sources.

J. M. Pittard

2006-07-13T23:59:59.000Z

240

Dynamic model of power system operation incorporating load control  

SciTech Connect

Load management has been proposed as a means whereby an electric utility can reduce its requirements for additional generation, transmission, and distribution investments, shift fuel dependency from limited to more abundant energy resources, and improve the efficiency of the electric energy system. There exist, however, serious technological and economic questions which must be answered to define the cost trade-offs between initiating a load management strategy or adding additional capacity to meet the load. One aspect of this complex problem is to determine how the load profile might be modified by the load management option being considered. Towards this end, a model has been developed to determine how a power system with an active load control system should be operated to make the best use of its available resources. The model is capable of handling all types of conventional generating sources including thermal, hydro, and pumped storage units, and most appliances being considered for direct control including those with inherent or designed storage characteristics. The model uses a dynamic programming technique to determine the optimal operating strategy for a given set of conditions. The use of the model is demonstrated. Case study results indicate that the production cost savings that can be achieved through the use of direct load control are highly dependent on utility characteristics, load characteristics, storage capacity, and penetration. The load characteristics that produce the greatest savings are: large storage capacity; high coincidence with the system peak; large connected load per point; and moderately high diversity fraction.

Kuliasha, M.A.

1980-10-01T23:59:59.000Z

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


241

Cooling load estimation methods  

DOE Green Energy (OSTI)

Ongoing research on quantifying the cooling loads in residential buildings, particularly buildings with passive solar heating systems, is described. Correlations are described that permit auxiliary cooling estimates from monthly average insolation and weather data. The objective of the research is to develop a simple analysis method, useful early in design, to estimate the annual cooling energy required of a given building.

McFarland, R.D.

1984-01-01T23:59:59.000Z

242

LOADING AND UNLOADING DEVICE  

DOE Patents (OSTI)

A device for loading and unloading fuel rods into and from a reactor tank through an access hole includes parallel links carrying a gripper. These links enable the gripper to go through the access hole and then to be moved laterally from the axis of the access hole to the various locations of the fuel rods in the reactor tank.

Treshow, M.

1960-08-16T23:59:59.000Z

243

Multidimensional spectral load balancing  

DOE Patents (OSTI)

A method of and apparatus for graph partitioning involving the use of a plurality of eigenvectors of the Laplacian matrix of the graph of the problem for which load balancing is desired. The invention is particularly useful for optimizing parallel computer processing of a problem and for minimizing total pathway lengths of integrated circuits in the design stage.

Hendrickson, Bruce A. (Albuquerque, NM); Leland, Robert W. (Albuquerque, NM)

1996-12-24T23:59:59.000Z

244

Buildings Stock Load Control  

E-Print Network (OSTI)

Researchers and practitioners have proposed a variety of solutions to reduce electricity consumption and curtail peak demand. This research focuses on electricity demand control by applying some strategies in existing building to reduce it during the extreme climate period. The first part of this paper presents the objectives of the study: ? to restrict the startup polluting manufacturing units (power station), ? to limit the environmental impacts (greenhouse emission), ? to reduce the transport and distribution electricity infrastructures The second part presents the approach used to rise the objectives : ? To aggregat the individual loads and to analyze the impact of different strategies from load shedding to reduce peak power demand by: ? Developing models of tertiary buildings stocks (Schools, offices, Shops, hotels); ? Making simulations for different load shedding strategies to calculate potential peak power saving. The third part is dedicated to the description of the developed models: 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

245

Combined transmission distribution load flow model employing system reduction and voltage variable load representation  

SciTech Connect

In the few decades since its introduction the digital computer has found widespread application within the electric power industry. One of the more fruitful areas for its utilization has been in the determination of the steady-state voltage conditions throughout the system. A power system naturally breaks down into two very distinct parts: transmission and distribution, and traditionally, the voltage problem has been separated the same way. In the transmission system it is referred to as a load flow problem, and in the distribution part it is called a voltage profile. In addition, the loads are often treated differently. Transmission loads are usually considered to be constant power, and the equations that result are therefore nonlinear. In the distribution portion the loads, though specified in terms of power, are sometimes handled as constant impedances, with linear equations. This work produced a new model wherein a mesh transmission system is combined with a radial distribution system and they are solved simultaneously. A system reduction technique is used to eliminate part of the transmission system from consideration, and thereby keep the problem at a manageable size. The solution algorithm incorporates a voltage variable load model which approximates the behavior of real loads more nearly than the common representations.

Enouen, P.W.

1985-01-01T23:59:59.000Z

246

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

SciTech Connect

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

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

2004-06-01T23:59:59.000Z

247

SYSPLAN. Load Leveling Battery System Costs  

SciTech Connect

SYSPLAN evaluates capital investment in customer side of the meter load leveling battery systems. Such systems reduce the customer`s monthly electrical demand charge by reducing the maximum power load supplied by the utility during the customer`s peak demand. System equipment consists of a large array of batteries, a current converter, and balance of plant equipment and facilities required to support the battery and converter system. The system is installed on the customer`s side of the meter and controlled and operated by the customer. Its economic feasibility depends largely on the customer`s load profile. Load shape requirements, utility rate structures, and battery equipment cost and performance data serve as bases for determining whether a load leveling battery system is economically feasible for a particular installation. Life-cycle costs for system hardware include all costs associated with the purchase, installation, and operation of battery, converter, and balance of plant facilities and equipment. The SYSPLAN spreadsheet software is specifically designed to evaluate these costs and the reduced demand charge benefits; it completes a 20 year period life cycle cost analysis based on the battery system description and cost data. A built-in sensitivity analysis routine is also included for key battery cost parameters. The life cycle cost analysis spreadsheet is augmented by a system sizing routine to help users identify load leveling system size requirements for their facilities. The optional XSIZE system sizing spreadsheet which is included can be used to identify a range of battery system sizes that might be economically attractive. XSIZE output consisting of system operating requirements can then be passed by the temporary file SIZE to the main SYSPLAN spreadsheet.

Hostick, C.J. [Pacific Northwest Lab., Richland, WA (United States)

1988-03-22T23:59:59.000Z

248

Estimating Hourly All-Sky Solar Irradiation Components from Meteorological Data  

Science Conference Proceedings (OSTI)

A new method to calculate hourly direct beam and diffuse irradiation on a horizontal surface using 3-h standard meteorological data is described. Comparisons of computed and observed irradiations are made with hourly data obtained in Carpentras ...

F. Kermel

1988-02-01T23:59:59.000Z

249

NOAA Awarded 2.6 Million Processor Hours at NERSC to Run Climate...  

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

NOAA Awarded 2.6 Million Processor Hours at NERSC to Run Climate Change Models NOAA Awarded 2.6 Million Processor Hours at NERSC to Run Climate Change Models September 11, 2008...

250

Seasonal Variations in the Diurnal Characteristics of Heavy Hourly precipitation across the United States  

Science Conference Proceedings (OSTI)

Hourly precipitation data from 1967 to 1983 for the coterminous, United States were harmonically analyzed in order to document the diurnal variability of several categories of heavy hourly precipitation during winter, spring, summer, and autumn. ...

Julie A. Winkler; Brent R. Skeeter; Paul D. Yamamoto

1988-08-01T23:59:59.000Z

251

Calculations of slurry pump jet impingement loads  

SciTech Connect

This paper presents a methodology to calculate the impingement load in the region of a submerged turbulent jet where a potential core exits and the jet is not fully developed. The profile of the jet flow velocities is represented by a piece-wise linear function which satisfies the conservation of momentum flux of the jet flow. The adequacy of the of the predicted jet expansion is further verified by considering the continuity of the jet flow from the region of potential core to the fully developed region. The jet impingement load can be calculated either as a direct impingement force or a drag force using the jet velocity field determined by the methodology presented.

Wu, T.T.

1996-03-04T23:59:59.000Z

252

Investigation of wind induced load on guyline anchors  

SciTech Connect

Most producing oil wells in the United States include guyline anchors to provide structural support for wind loaded service derricks. Recent safety regulations have focused attention on the load transferred to these anchors during high wind, but no definitive data has been available to establish precise requirements for such loading. In order to provide accurate and broadly acceptable data, a full scale field study was conducted on an actual servicing unit subject to severe wind. Load measured on the guyline anchors during the test indicates that there is less load on the guylines than standard criteria would predict. This result seems to be a singular property of oil well servicing units and is probably associated with both the flowfield around the derrick and the vertical velocity profile of the wind.

Hoyt, P.M.

1976-01-01T23:59:59.000Z

253

Monitoring of Electrical End-Use Loads in Commercial Buildings  

E-Print Network (OSTI)

Southern California Edison is currently conducting a program to collect end-use metered data from commercial buildings in its service area. The data will provide actual measurements of end-use loads and will be used in research and in designing energy management programs oriented toward end-use applications. The focus of the program is on five major types of commercial buildings: offices, grocery stores, restaurants, retail stores, and warehouses. End-use metering equipment is installed at about 50 buildings, distributed among these five types. The buildings selected have average demands of 100 to 300 kW. The metered end-uses vary among building types and include HVAC, lighting, refrigeration. plug loads, and cooking. Procedures have been custom-designed to facilitate collection and validation of the end-use load data. For example, the Load Profile Viewer is a PC-based software program for reviewing and validating the end-use load data.

Martinez, M.; Alereza, T.; Mort, D.

1988-01-01T23:59:59.000Z

254

User_TalentProfile  

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

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

255

Load Capacity of Bodies  

E-Print Network (OSTI)

For the stress analysis in a plastic body $\\Omega$, we prove that there exists a maximal positive number $C$, the \\emph{load capacity ratio,} such that the body will not collapse under any external traction field $t$ bounded by $Y_{0}C$, where $Y_0$ is the elastic limit. The load capacity ratio depends only on the geometry of the body and is given by $$ \\frac{1}{C}=\\sup_{w\\in LD(\\Omega)_D} \\frac{\\int_{\\partial\\Omega}|w|dA} {\\int_{\\Omega}|\\epsilon(w)|dV}=\\left\\|\\gamma_D\\right\\|. $$ Here, $LD(\\Omega)_D$ is the space of isochoric vector fields $w$ for which the corresponding stretchings $\\epsilon(w)$ are assumed to be integrable and $\\gamma_D$ is the trace mapping assigning the boundary value $\\gamma_D(w)$ to any $w\\in LD(\\Omega)_D$.

Reuven Segev

2005-11-01T23:59:59.000Z

256

Load responsive hydrodynamic bearing  

Science Conference Proceedings (OSTI)

A load responsive hydrodynamic bearing is provided in the form of a thrust bearing or journal bearing for supporting, guiding and lubricating a relatively rotatable member to minimize wear thereof responsive to relative rotation under severe load. In the space between spaced relatively rotatable members and in the presence of a liquid or grease lubricant, one or more continuous ring shaped integral generally circular bearing bodies each define at least one dynamic surface and a plurality of support regions. Each of the support regions defines a static surface which is oriented in generally opposed relation with the dynamic surface for contact with one of the relatively rotatable members. A plurality of flexing regions are defined by the generally circular body of the bearing and are integral with and located between adjacent support regions. Each of the flexing regions has a first beam-like element being connected by an integral flexible hinge with one of the support regions and a second beam-like element having an integral flexible hinge connection with an adjacent support region. A least one local weakening geometry of the flexing region is located intermediate the first and second beam-like elements. In response to application of load from one of the relatively rotatable elements to the bearing, the beam-like elements and the local weakening geometry become flexed, causing the dynamic surface to deform and establish a hydrodynamic geometry for wedging lubricant into the dynamic interface.

Kalsi, Manmohan S. (Houston, TX); Somogyi, Dezso (Sugar Land, TX); Dietle, Lannie L. (Stafford, TX)

2002-01-01T23:59:59.000Z

257

An improved procedure for developing a calibrated hourly simulation model of an electrically heated and cooled commercial building  

E-Print Network (OSTI)

With the increased use of building energy simulation programs, calibration of simulated data to measured data has been recognized as an important factor in substantiating how well the model fits a real building. Model calibration to measured monthly utility data has been utilized for many years. Recently, efforts have reported calibrated models at the hourly level. Most of the previous methods have relied on very simple comparisons including bar charts, monthly percent difference time-series graphs, and x-y scatter plots. A few advanced methods have been proposed as well which include carpet plots and comparative 3-D time-series plots. Unfortunately, at hourly levels of calibration, many of the traditional graphical calibration techniques become overwhelmed with data and suffer from data overlap. In order to improve upon previously established techniques, 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 hourly temperature-dependent energy use profiles, and 52-week box-whisker-mean plots to display long-term trends. In addition to the graphical calibration techniques, other methods are also used including indoor temperature calibration to improve thermostat schedules and architectural rendering as a means of verifying the building envelope dimensions and shading placement. Several statistical methods are also reviewed for their appropriateness including percent difference, mean bias error (MBE), and the coefficient of variation of the root mean squared error. Results are presented 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 DOE-2. 1D building simulation program to test the new techniques. Use of the new calibration procedures were able to produce a MBE of-0.7% and a CV(RMSE) of 23. 1 % which compare favorably with the most accurate hourly neural network models.

Bou-Saada, Tarek Edmond

1994-01-01T23:59:59.000Z

258

Wind Profiler Observations Preceding Outbreaks of Large Hail over Northeastern Colorado  

Science Conference Proceedings (OSTI)

Wind profiler, rawinsonde, and surface observations of the atmosphere over northeastern Colorado during the morning hours on 44 days were compared to the severity of subsequent thunderstorm activity. On half of thes days, large hail (diameter ?2 ...

David H. Kitzmiller; Wayne E. Mcgovern

1990-03-01T23:59:59.000Z

259

Measured electric hot water standby and demand loads from Pacific Northwest homes. End-Use Load and Consumer Assessment Program  

SciTech Connect

The Bonneville Power Administration began the End-Use Load and Consumer Assessment Program (ELCAP) in 1983 to obtain metered hourly end-use consumption data for a large sample of new and existing residential and commercial buildings in the Pacific Northwest. Loads and load shapes from the first 3 years of data fro each of several ELCAP residential studies representing various segments of the housing population have been summarized by Pratt et al. The analysis reported here uses the ELCAP data to investigate in much greater detail the relationship of key occupant and tank characteristics to the consumption of electricity for water heating. The hourly data collected provides opportunities to understand electricity consumption for heating water and to examine assumptions about water heating that are critical to load forecasting and conservation resource assessments. Specific objectives of this analysis are to: (A) determine the current baseline for standby heat losses by determining the standby heat loss of each hot water tank in the sample, (B) examine key assumptions affecting standby heat losses such as hot water temperatures and tank sizes and locations, (C) estimate, where possible, impacts on standby heat losses by conservation measures such as insulating tank wraps, pipe wraps, anticonvection valves or traps, and insulating bottom boards, (D) estimate the EF-factors used by the federal efficiency standards and the nominal R-values of the tanks in the sample, (E) develop estimates of demand for hot water for each home in the sample by subtracting the standby load from the total hot water load, (F) examine the relationship between the ages and number of occupants and the hot water demand, (G) place the standby and demand components of water heating electricity consumption in perspective with the total hot water load and load shape.

Pratt, R.G.; Ross, B.A.

1991-11-01T23:59:59.000Z

260

Bunch Profiling Using a Rotating Mask  

Science Conference Proceedings (OSTI)

The current method for measuring profiles of proton bunches in accelerators is severely lacking. One must dedicate a great deal of time and expensive equipment to achieve meaningful results. A new method to complete this task uses a rotating mask with slots of three different orientations to collect this data. By scanning over the beam in three different directions, a complete profile for each bunch is built in just seconds, compared to the hours necessary for the previous method. This design was successfully tested using synchrotron radiation emitted by SPEAR3. The profile of the beam was measured in each of the three desired directions. Due to scheduled beam maintenance, only one set of data was completed and more are necessary to solve any remaining issues. The data collected was processed and all of the RMS sizes along the major and minor axes, as well as the tilt of the beam ellipse were measured.

Miller, Mitchell; /SLAC /IIT, Chicago

2012-08-24T23:59:59.000Z

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


261

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

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

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?

262

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

263

Beam profiles from multiple aperture sources  

SciTech Connect

Using a rapidly convergent approximation scheme, formulas are given for beam intensity profiles everywhere. In the first approximation, formulas are found for multiple aperture sources, such as a TFTR design, and integrated power for rectangular plates downstream for Gaussian beamlets. This analysis is duplicated for Lorentzian beamlets which should provide a probable upper bound for off-axis loading as Gaussian beamlets provide a probable lower bound. Formulas for beam intensity profiles are found everywhere. In first approximation, formulas are found for downstream intensity of multiple sources and integrated power for rectangular plates.

Whealton, J.H.

1979-02-01T23:59:59.000Z

264

EIA - State Electricity Profiles  

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

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...

265

Accelerator beam profile analyzer  

DOE Patents (OSTI)

A beam profile analyzer employing sector or quadrant plates each servo controlled to outline the edge of a beam.

Godel, Julius B. (Bayport, NY); Guillaume, Marcel (Grivegnee, BE); Lambrecht, Richard M. (East Quogue, NY); Withnell, Ronald (East Setauket, NY)

1976-01-01T23:59:59.000Z

266

EIA - State Electricity Profiles  

U.S. Energy Information Administration (EIA)

Trade and Reliability; All Reports ‹ See all Electricity Reports State Electricity Profiles. ... Electric Power Industry Emissions Estimates, 1990 Through 2010:

267

Load management and the La Vereda passive solar community  

SciTech Connect

Reviewed are preliminary data available from some of the passive solar homes now operational at the La Vereda subdivision in Santa Fe, New Mexico. The major emphasis is Load Management - an electric utility term pertaining to when and how much energy is used by the customer. A customer's home is considered to be Load Managed when its major demands for electricity occur at times during the day when the utility has surplus generation capacity. For most utilities this surplus occurs during the night and is referred to as the off-peak period. Compared to conventional electric homes, the La Vereda passive solar homes are Naturally Load Managed because most of their backup heating requirements occur during the utility's off-peak period. Naturally Load Managed homes like these allow the backup heating system to operate freely whenever the space needs heat. Load data from six La Vereda homes are compared to similar data from 1) a group of nonsolar super-insulated total electric homes, and 2) the utility's winter system peak day load profile. The comparison verifies the Natural Load Management characteristics of the well-designed passive solar home. The free operation of the backup heating system, especially during cloudy or severe weather, can reduce the Natural Load Management characteristics of the La Verda homes. Is it possible to Force Load Management on a home, regardless of weather conditions and still guarantee that all space heating requirements are satisfied with off-peak energy. One home at La Vereda is discussed that has an experimental Forced Load Management backup heating system designed to use energy only during the utility's off-peak period. Load data from this home is presented and compared to other homes at La Verda.

Pyde, S.E.

1981-01-01T23:59:59.000Z

268

Look-ahead voltage and load margin contingency selection functions for large-scale power systems  

SciTech Connect

Given the current operating condition (obtained from the real-time data), the near-term load demand at each bus (obtained from short-term load forecast), and the generation dispatch (say, based on economic dispatch), the authors present in this paper a load margin measure (MW and/or MVAR) to assess the system`s ability to withstand the forecasted load and generation variations. The authors also present a method to predict near-term system voltage profiles. The proposed look-ahead measure and the proposed voltage prediction are then applied to contingency selections for the near-term power system in terms of load margins to collapse and of the bus voltage magnitudes. They evaluate the proposed load-ahead measure and the voltage profile prediction on several power systems including a 1169-bus power system with 53 contingencies with promising results.

Chiang, H.D.; Wang, C.S.; Flueck, A.J. [Cornell Univ., Ithaca, NY (United States). School of Electrical Engineering

1997-02-01T23:59:59.000Z

269

Regression Models for Demand Reduction based on Cluster Analysis of Load  

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

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

270

Voltage control of emerging distribution systems with induction motor loads using robust LQG approach  

E-Print Network (OSTI)

mode" in emerging distribution systems. The small-signal stability analysis indicates that load voltageVoltage control of emerging distribution systems with induction motor loads using robust LQG has significant performance to improve the voltage profile of the distributed generation system

Pota, Himanshu Roy

271

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

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

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

272

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

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

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

273

MTS Table Top Load frame  

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

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

274

Industrial Load Shaping: A Utility Strategy to Deal with Competition  

E-Print Network (OSTI)

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 manufacturing facilities. Both the customer and the utility should realize benefits from these changes. There are five generic load shaping categories: rescheduling operations, capacity additions, product storage, automation and flexible manufacturing and electrotechnologies. The customized nature of the program requires that the utility work with industry experts to help customers identify specific load shape opportunities. The remainder of this paper provides guidelines for utility planners interested in developing such a program. It begins with an overview of general objectives, technology alternatives, market evaluation and selection criteria, and program implementation and monitoring procedures. The paper concludes with two utility case studies.

Bules, D.

1987-09-01T23:59:59.000Z

275

Field Test Protocol: Standard Internal Load Generation in Unoccupied Test Homes  

Science Conference Proceedings (OSTI)

This document describes a simple and general way to generate House Simulation Protocol (HSP)-consistent internal sensible and latent loads in unoccupied homes. It is newly updated based on recent experience, and provides instructions on how to calculate and set up the operational profiles in unoccupied homes. The document is split into two sections: how to calculate the internal load magnitude and schedule, and then what tools and methods should be used to generate those internal loads to achieve research goals.

Fang, X.; Christensen, D.; Barker, G.; Hancock, E.

2011-06-01T23:59:59.000Z

276

Status of Jefferson Lab's Load Locked Polarized Electron Beam  

DOE Green Energy (OSTI)

A new 100 kV load locked polarized electron gun has been built at Jefferson Lab. The gun is installed in a test stand on a beam line that resembles the first few meters of the CEBAF nuclear physics photoinjector. With this gun, a GaAs photocathode can be loaded from atmosphere, hydrogen cleaned, activated and taken to high voltage in less than 8 hours. The gun is a three chamber design, with all of the moving parts remaining at ground potential during gun operation. Studies of gun performance, photocathode life times, transverse emittance at high bunch charge, helicity correlated effects and beam polarizations from new photocathode samples will all be greatly facilitated by the use of this load locked gun.

M.L. Stutzman; P. Adderley; M. Baylac; J. Clark; A. Day; J. Grames; J. Hansknecht; M. Poelker

2002-09-01T23:59:59.000Z

277

Forecasting electricity load demand: analysis of the 2001 rationing period  

E-Print Network (OSTI)

CEPEL e UENF. Abstract. This paper studies the electricity load demand behavior during the 2001 rationing period, which was implemented because of the Brazilian energetic crisis. The hourly data refers to a utility situated in the southeast of the country. We use the model proposed by Soares and Souza (2003), making use of generalized long memory to model the seasonal behavior of the load. The rationing period is shown to have imposed a structural break in the series, decreasing the load at about 20%. Even so, the forecast accuracy is decreased only marginally, and the forecasts rapidly readapt to the new situation. The forecast errors from this model also permit verifying the public response to pieces of information released regarding the crisis.

Leonardo Rocha Souza; Lacir Jorge Soares; Leonardo Rocha Souza; Epge Fundação; Getúlio Vargas; Lacir Jorge Soares

2003-01-01T23:59:59.000Z

278

Customer Strategies for Responding to Day-Ahead Market Hourly Electricity Pricing  

E-Print Network (OSTI)

facilities that receive electricity service from Niagaraperiods is your facility’s electricity use highest? ( CHECKthe next day’s hourly electricity prices? ( CHECK ONLY ONE )

2005-01-01T23:59:59.000Z

279

Customer Strategies for Responding to Day-Ahead Market Hourly Electricity Pricing  

E-Print Network (OSTI)

next day’s hourly electricity prices? ( CHECK ONLY ONE ) 1.to Real Time Electricity Prices, Unpublished Manuscript atahead Wholesale Market Electricity Prices: Case Study of RTP

2005-01-01T23:59:59.000Z

280

Analysis of Sub-Hourly Ramping Impacts of Wind Energy and Balancing Area Size: Preprint  

DOE Green Energy (OSTI)

In this paper, we analyze sub-hourly ramping requirements and the benefit of combining Balancing Authority operations with significant wind penetrations.

Milligan, M.; Kirby, B.

2008-06-01T23:59:59.000Z

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


281

Customer Strategies for Responding to Day-Ahead Market Hourly Electricity Pricing  

E-Print Network (OSTI)

nature of electric service and usage, defining the hoursElectric. 12 The resulting evaluation report estimated elasticities and found measurable reductions in energy usage

2005-01-01T23:59:59.000Z

282

Intra-hour Direct Normal Irradiance solar forecasting using genetic programming  

E-Print Network (OSTI)

UNIVERSITY OF CALIFORNIA, SAN DIEGO Intra-hour Direct NormalChair University of California, San Diego iii TABLE OFRPS,” Technical report, California Independent System

Queener, Benjamin Daniel

2012-01-01T23:59:59.000Z

283

Analysis of sweeping heat loads on divertor plate materials  

SciTech Connect

The heat flux on the divertor plate of a fusion reactor is probably one of the most limiting constraints on its lifetime. The current heat flux profile on the outer divertor plate of a device like ITER is highly peaked with narrow profile. The peak heat flux can be as high as 30--40 MW/m{sup 2} with full width at half maximum (FWHM) is in the order of a few centimeters. Sweeping the separatrix along the divertor plate is one of the options proposed to reduce the thermomechanical effects of this highly peaked narrow profile distribution. The effectiveness of the sweeping process is investigated parametrically for various design values. The optimum sweeping parameters of a particular heat load will depend on the design of the divertor plate as well as on the profile of such a heat load. In general, moving a highly peaked heat load results in substantial reduction of the thermomechanical effects on the divertor plate. 3 refs., 8 figs.

Hassanein, A.

1991-12-31T23:59:59.000Z

284

Analysis of sweeping heat loads on divertor plate materials  

SciTech Connect

The heat flux on the divertor plate of a fusion reactor is probably one of the most limiting constraints on its lifetime. The current heat flux profile on the outer divertor plate of a device like ITER is highly peaked with narrow profile. The peak heat flux can be as high as 30--40 MW/m{sup 2} with full width at half maximum (FWHM) is in the order of a few centimeters. Sweeping the separatrix along the divertor plate is one of the options proposed to reduce the thermomechanical effects of this highly peaked narrow profile distribution. The effectiveness of the sweeping process is investigated parametrically for various design values. The optimum sweeping parameters of a particular heat load will depend on the design of the divertor plate as well as on the profile of such a heat load. In general, moving a highly peaked heat load results in substantial reduction of the thermomechanical effects on the divertor plate. 3 refs., 8 figs.

Hassanein, A.

1991-01-01T23:59:59.000Z

285

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

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

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

286

Preconditioning Outside Air: Cooling Loads from Building Ventilation  

E-Print Network (OSTI)

HVAC equipment manufacturers, specifiers and end users interacting in the marketplace today are only beginning to address the series of issues promulgated by the increased outside air requirements in ASHRAE Standard 62- 1989, "Ventilation for Acceptable Indoor Air Quality", that has cascaded into building codes over the early to mid 1990's. There has been a twofold to fourfold increase in outside air requirements for many commercial building applications, compared to the 1981 version of the standard. To mitigate or nullify these additional weather loads, outdoor air preconditioning technologies are being promoted in combination with conventional HVAC operations downstream as a means to deliver the required fresh air and control humidity indoors. Preconditioning is the term applied for taking outside air to the indoor air setpoint (dry bulb temperature and relative humidity). The large humidity loads from outside air can now be readily recognized and quantified at cooling design point conditions using the extreme humidity ratios/dew points presented in the ASHRAE Handbook of Fundamentals Chapter 26 "Climatic Design Information". This paper presents an annual index called the Ventilation Load Index (VLI), recently developed by the Gas Research Institute (GRI) that measures the magnitude of latent (and sensible) loads for preconditioning outside air to indoor space conditions over the come of an entire year. The VLI has units of ton-hrs/scfm of outside air. The loads are generated using new weather data binning software called ~BinMaker, also from GRI, that organizes the 239 city, 8760 hour by hour, TMY2 weather data into user selected bidtables. The VLI provides a simple methodology for accessing the cooling load impact of increased ventilation air volumes and a potential basis for defining a "humid" climate location.

Kosar, D.

1998-01-01T23:59:59.000Z

287

Commercial equipment loads: End-Use Load and Consumer Assessment Program (ELCAP)  

SciTech Connect

The Office of Energy Resources of the Bonneville Power Administration is generally responsible for the agency's power and conservation resource planning. As associated responsibility which supports a variety of office functions is the analysis of historical trends in and determinants of energy consumption. The Office of Energy Resources' End-Use Research Section operates a comprehensive data collection program to provide pertinent information to support demand-side planning, load forecasting, and demand-side program development and delivery. Part of this on-going program is known as the End-Use Load and Consumer Assessment Program (ELCAP), an effort designed to collect electricity usage data through direct monitoring of end-use loads in buildings. This program is conducted for Bonneville by the Pacific Northwest Laboratory. This report provides detailed information on electricity consumption of miscellaneous equipment from the commercial portion of ELCAP. Miscellaneous equipment includes all commercial end-uses except heating, ventilating, air conditioning, and central lighting systems. Some examples of end-uses covered in this report are office equipment, computers, task lighting, refrigeration, and food preparation. Electricity consumption estimates, in kilowatt-hours per square food per year, are provided for each end-use by building type. The following types of buildings are covered: office, retail, restaurant, grocery, warehouse, school, university, and hotel/motel. 6 refs., 35 figs., 12 tabs.

Pratt, R.G.; Williamson, M.A.; Richman, E.E.; Miller, N.E.

1990-07-01T23:59:59.000Z

288

Geographical extrapolation of typical hourly weather data for energy calculation in buildings  

E-Print Network (OSTI)

FOR REAL 1951 YEARS PASSIVE HOUSES DAILY LOADS FOR REAL 1951Requirements for Real Year Passive Houses DAILY LOADS FORranch house of 112 m^ (1,200 ft^), a more massive passive

Arens, Edward A; Flynn, Larry E; Nall, Daniel N; Ruberg, Kalev

1980-01-01T23:59:59.000Z

289

Load Management: Opportunity or Calamity?  

E-Print Network (OSTI)

After the change in the economics of generating electricity which took place in 1973, many utilities are examining options to hold down their costs. One fact which is clear is that the difference between peak and off peak generating costs is much 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 during peak periods are both examples of load control which lower the costs borne by the utility. The other option is the use of seasonal surcharges or time-of-day rates to induce customers to alter their usage patterns. Both these load management options focus on reducing utility costs overall without regard to the cost to the consumers affected by the load management options. The issue, then, is whether industrial customers can find opportunities to lower their costs under load management.

Males, R.; Hassig, N.

1981-01-01T23:59:59.000Z

290

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

291

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 is disclosed. 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. 13 figs.

Wheat, S.R.

1997-05-13T23:59:59.000Z

292

Quantification of Variability and Uncertainty in Hourly NOx Emissions from Coal-Fired Power Plants  

E-Print Network (OSTI)

1 Quantification of Variability and Uncertainty in Hourly NOx Emissions from Coal-Fired Power to quantify variability and uncertainty for NOx emissions from coal-fired power plants. Data for hourly NOx Uncertainty, Variability, Emission Factors, Coal-Fired Power Plants, NOx emissions, Regression Models

Frey, H. Christopher

293

Multi-hour network planning based on domination between sets of traffic matrices  

Science Conference Proceedings (OSTI)

In multi-hour network design, periodic traffic variations along time are considered in the dimensioning process. Then, the non coincidence of traffic peaks along the day or the week can be exploited. This paper investigates the application of the traffic ... Keywords: Multi-hour traffic, Network planning, Traffic domination

P. Pavon-Marino; B. Garcia-Manrubia; R. Aparicio-Pardo

2011-02-01T23:59:59.000Z

294

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.

295

Cloudy Sky Version of Bird's Broadband Hourly Clear Sky Model (Presentation)  

DOE Green Energy (OSTI)

Presentation on Bird's Broadband Hourly Clear Sky Model given by NREL's Daryl Myers at SOLAR 2006. The objective of this report is to produce ''all sky'' modeled hourly solar radiation. This is based on observed cloud cover data using a SIMPLE model.

Myers, D.

2006-08-01T23:59:59.000Z

296

Influence Of Lateral Load Distributions On Pushover Analysis Effectiveness  

SciTech Connect

The effectiveness of two simple load distributions for pushover analysis recently proposed by the authors is investigated through a comparative study, involving static and dynamic analyses of seismic response of eccentrically braced frames. It is shown that in the upper floors only multimodal pushover procedures provide results close to the dynamic profile, while the proposed load patterns are always conservative in the lower floors. They over-estimate the seismic response less than the uniform distribution, representing a reliable alternative to the uniform or more sophisticated adaptive procedures proposed by seismic codes.

Colajanni, P.; Potenzone, B. [Dipartimento di Ingegneria Civile, Universita di Messina, Contrada Di Dio, S. Agata, 98166 Messina (Italy)

2008-07-08T23:59:59.000Z

297

Customization of the EPRI Artificial Neural Network Short-Term Load Forecaster (ANNSTLF) and User Support for the California Independent System Operator (CA-ISO)  

Science Conference Proceedings (OSTI)

Load forecasting is an important part of power system planning and operation. In the past, forecasting was achieved by extrapolating existing load data combined with other influencing factors. This method is no longer accurate enough. The Artificial Neural Network Short-Term Load Forecaster (ANNSTLF) is a tool for the quick and accurate prediction of hourly loads that provides the level of accuracy required by today's complex and competitive power markets. This report describes all the deliverables for t...

2002-11-19T23:59:59.000Z

298

Alaska Village Electric Load Calculator  

DOE Green Energy (OSTI)

As part of designing a village electric power system, the present and future electric loads must be defined, including both seasonal and daily usage patterns. However, in many cases, detailed electric load information is not readily available. NREL developed the Alaska Village Electric Load Calculator to help estimate the electricity requirements in a village given basic information about the types of facilities located within the community. The purpose of this report is to explain how the load calculator was developed and to provide instructions on its use so that organizations can then use this model to calculate expected electrical energy usage.

Devine, M.; Baring-Gould, E. I.

2004-10-01T23:59:59.000Z

299

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

300

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

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

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

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


301

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

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

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"

302

PWR AXIAL BURNUP PROFILE ANALYSIS  

Science Conference Proceedings (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

303

Texas Crop Profile: Onions  

E-Print Network (OSTI)

This profile of onion production in Texas gives an overview of basic commodity information; discusses insect, disease and weed pests; and covers cultural and chemical control methods.

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

2000-04-12T23:59:59.000Z

304

Thermal Energy Storage for Cooling of Commercial Buildings  

E-Print Network (OSTI)

According to the Load Profile. $1 is the daily coolingload,c) illus- trates a design load profile for a partial storageDay Design Day Hourly Load Profile for a Building with a

Akbari, H.

2010-01-01T23:59:59.000Z

305

Matching collector's azimuthal orientation and energy demand profile for thermosyphonic systems  

SciTech Connect

When a load profile is given, a thermosyphonic solar water heater's collector's azimuthal orientation should be considered as a parameter for maximizing the system's performance. This is demonstrated by simulating such a system with various azimuthal collectors orientation subjected to a single fixed or a daily routine load during the day. The results indicate that the system performance, which is measured here by the average (or mixed-cup) temperature of the withdrawn load, could be improved appreciably by a proper match between the collector's azimuthal orientation and the specifics of the load profiles.

Sokolov, M.; Vaxman, M. (Tel Aviv Univ. (Israel). School of Engineering)

1989-08-01T23:59:59.000Z

306

LOAD FORECASTING Eugene A. Feinberg  

E-Print Network (OSTI)

's electricity price forecasting model, produces forecast of gas demand consistent with electric load. #12Gas demand Council's Market Price of Electricity Forecast Natural GasDemand Electric Load Aggregating Natural between the natural gas and electricity and new uses of natural gas emerge. T natural gas forecasts

Feinberg, Eugene A.

307

Wind load reduction for heliostats  

DOE Green Energy (OSTI)

This report presents the results of wind-tunnel tests supported through the Solar Energy Research Institute (SERI) by the Office of Solar Thermal Technology of the US Department of Energy as part of the SERI research effort on innovative concentrators. As gravity loads on drive mechanisms are reduced through stretched-membrane technology, the wind-load contribution of the required drive capacity increases in percentage. Reduction of wind loads can provide economy in support structure and heliostat drive. Wind-tunnel tests have been directed at finding methods to reduce wind loads on heliostats. The tests investigated primarily the mean forces, moments, and the possibility of measuring fluctuating forces in anticipation of reducing those forces. A significant increase in ability to predict heliostat wind loads and their reduction within a heliostat field was achieved.

Peterka, J.A.; Hosoya, N.; Bienkiewicz, B.; Cermak, J.E.

1986-05-01T23:59:59.000Z

308

A Moored Profiling Instrument*  

Science Conference Proceedings (OSTI)

The specifications and performance of a moored vertical profiling instrument, designed to acquire near-full-ocean-depth profile time series data at high vertical resolution, are described. The 0.8-m-diameter by 0.4-m-wide device utilizes a ...

K. W. Doherty; D. E. Frye; S. P. Liberatore; J. M. Toole

1999-11-01T23:59:59.000Z

309

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

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

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)","(%)"

310

ON THE LOAD CAPACITY OF THE HYDRO-MAGNETICALLY LUBRICATED SLIDER BEARING  

SciTech Connect

The load capacity of liquid metal lubricated slider bearings subject to an applied magnetic field transverse to the film is investigated. The optimum profile is determined and found to be the Rayleigh step form with the riser location and step height ratio dependent on the strength of the magnetic field. Load capacity is favored by large magnetic fields, small film thicknesses, and electrically insulating bearing surfaces. Only modest load increases can be obtained from conventional magnets of reasonable size. Substantial load increases could be accomplished by the recently developed superconducting electromagnets. (auth)

Osterle, J.F.; Young, F.J.

1962-05-01T23:59:59.000Z

311

A model of the domestic hot water load  

SciTech Connect

The electrical load required to supply domestic hot water is an important load for two reasons: (1) It represents a large portion (30 to 50%) of the domestic load; (2) It is a load which can easily be controlled by the consumer or the supplier, because the use of the hot water need not coincide with the heating of hot water. A model representing the electrical system load due to hot water consumption from storage water heaters is provided. Variable parameters include the average amount of water used, the mean and deviation of distributions of usage times, thermostat settings, inlet water temperature and electrical heating element ratings. These parameters are used to estimate the after diversity electricity demand profile, and were verified for accuracy by comparison with measurements. The model enables this prediction of the effects of load control, examples of which are given in this paper. The model is also useful for evaluation of the response which could be expected from demand-side management options. These include changing the size of heating elements, reduction in water consumption and reduction in thermostat settings.

Lane, I.E. [Energy Efficiency Enterprises, Lynnwood Manor (South Africa); Beute, N. [Cape Technikon, Cape Town (South Africa)

1996-11-01T23:59:59.000Z

312

Integrating load management with supply-side operations - A case study  

SciTech Connect

The main topic of this paper analyses and discusses the operational integration of Load Management operations with co-generation, power-pool purchases/sells and other supply-side options, where the common denominator is the hourly short-run marginal cost. The second topic concerns the operational coordination problem between a generating utility and its retail distributors when both parties use load management. The thirds is the interactive impacts of interruptible sales and other demand-side programs on the distribution load curve. The discussion is based on the operational experiences at Skydkraft, the largest investor-owned utility in Sweden.

Edvinsson, M.J.; Nilsson, M.O.

1987-08-01T23:59:59.000Z

313

ELECTRICAL LOAD ANTICIPATOR AND RECORDER  

DOE Patents (OSTI)

A system is described in which an indication of the prevailing energy consumption in an electrical power metering system and a projected power demand for one demand in terval is provided at selected increments of time within the demand interval. Each watt-hour meter in the system is provided with an impulse generator that generates two impulses for each revolution of the meter disc. In each demand interval, for example, one half-hour, of the metering system, the total impulses received from all of the meters are continuously totaled for each 5-minute interval and multiplied by a number from 6 to 1 depending upon which 5- minute interval the impulses were received. This value is added to the total pulses received in the intervals preceding the current 5-minute interval within the half-hour demand interval tc thereby provide an indication of the projected power demand every 5 minutes in the demand interval.

Werme, J.E.

1961-09-01T23:59:59.000Z

314

Electrical load management for the California water system  

DOE Green Energy (OSTI)

To meet its water needs California has developed an extensive system for transporting water from areas with high water runoff to areas with high water demand. This system annually consumes more than 6 billion kilowatt hours (kWh) of electricity for pumping water and produces more than 12 billion kWh/year of hydroelectric power. From the point of view of energy conservation, the optimum operation of the California water supply system would require that pumping be done at night and generation be done during the day. Night pumping would reduce electric power peak load demand and permit the pumps to be supplied with electricity from ''base load'' generating plants. Daytime hydro power generation would augment peak load power generation by fossil-fuel power plants and save fuel. The technical and institutional aspects of this type of electric power load management for water projects are examined for the purpose of explaining some of the actions which might be pursued and to develop recommendations for the California Energy Resources Conservation and Development Commission (ERCDC). The California water supply system is described. A brief description is given of various energy conservation methods, other than load management, that can be used in the management of water resources. An analysis of load management is presented. Three actions for the ERCDC are recommended: the Commission should monitor upcoming power contract negotiations between the utilities and the water projects; it should determine the applicability of the power-pooling provisions of the proposed National Energy Act to water systems; and it should encourage and support detailed studies of load management methods for specific water projects.

Krieg, B.; Lasater, I.; Blumstein, C.

1977-07-01T23:59:59.000Z

315

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

NLE Websites -- All DOE Office Websites (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

316

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

317

DOE Awards 265 Million Hours of Supercomputing Time to Advance Leading  

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

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

318

Spatial and Temporal Characteristics of Heavy Hourly Rainfall in the United States  

Science Conference Proceedings (OSTI)

The climatology of heavy rain events from hourly precipitation observations by Brooks and Stensrud is revisited in this study using two high-resolution precipitation datasets that incorporate both gauge observations and radar estimates. Analyses ...

Nathan M. Hitchens; Harold E. Brooks; Russ S. Schumacher

2013-12-01T23:59:59.000Z

319

DOE Awards 265 Million Hours of Supercomputing Time to Advance Leading  

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

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

320

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

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

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

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


321

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

322

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

NLE Websites -- All DOE Office Websites (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

323

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

324

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

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

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

325

A simple method to downscale daily wind statistics to hourly wind data  

E-Print Network (OSTI)

Wind is the principal driver in the wind erosion models. The hourly wind speed data were generally required for precisely wind erosion modeling. In this study, a simple method to generate hourly wind speed data from daily wind statistics (daily average and maximum wind speeds together or daily average wind speed only) was established. A typical windy location with 3285 days (9 years) measured hourly wind speed data were used to validate the downscaling method. The results showed that the overall agreement between observed and simulated cumulative wind speed probability distributions appears excellent, especially for the wind speeds greater than 5 m s-1 range (erosive wind speed). The results further revealed that the values of daily average erosive wind power density (AWPD) calculated from generated wind speeds fit the counterparts computed from measured wind speeds well with high models' efficiency (Nash-Sutcliffe coefficient). So that the hourly wind speed data can be predicted from daily average and maximu...

Guo, Zhongling

2013-01-01T23:59:59.000Z

326

The Relationships between Network Lightning Surface and Hourly Observations of Thunderstorms  

Science Conference Proceedings (OSTI)

Relationships were established between lightning location data and surface hourly observations of thunderstorms for 132 stations in the northeastern United States. The relationships are based on statistics derived from 2 × 2 contingency tables ...

Ronald M. Reap; Richard E. Orville

1990-01-01T23:59:59.000Z

327

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

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

328

Building Technologies Program: Tax Deduction Qualified Software- Hourly Analysis Program (HAP) version 4.31  

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

Provides required documentation that Hourly Analysis Program (HAP) version 4.31 meets Internal Revenue Code §179D, Notice 2006-52, dated June 2, 2006, for calculating commercial building energy and power cost savings.

329

Cluster Analysis of Hourly Wind Measurements to Reveal Synoptic Regimes Affecting Air Quality  

Science Conference Proceedings (OSTI)

A clustering algorithm is developed to study hourly, ground-level wind measurements obtained from a network of monitoring stations positioned throughout the San Francisco Bay Area of California. A statistical model based on principal components ...

Scott Beaver; Ahmet Palazoglu

2006-12-01T23:59:59.000Z

330

Building Technologies Program: Tax Deduction Qualified Software- Hourly Analysis Program (HAP) version 4.40  

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

Provides required documentation that Hourly Analysis Program (HAP) version 4.40 meets Internal Revenue Code §179D, Notice 2006-52, dated April 10, 2009, for calculating commercial building energy and power cost savings.

331

Building Technologies Program: Tax Deduction Qualified Software- Hourly Analysis Program (HAP) version 4.34  

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

Provides required documentation that Hourly Analysis Program (HAP) version 4.34 meets Internal Revenue Code §179D, Notice 2006-52, dated June 2, 2006, for calculating commercial building energy and power cost savings.

332

Building Technologies Program: Tax Deduction Qualified Software- Hourly Analysis Program (HAP) version 4.50  

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

Provides required documentation that Hourly Analysis Program (HAP) version 4.50 meets Internal Revenue Code §179D, Notice 2006-52, dated June 2, 2006, for calculating commercial building energy and power cost savings.

333

Improved Quality Assurance for Historical Hourly Temperature and Humidity: Development and Application to Environmental Analysis  

Science Conference Proceedings (OSTI)

Historical hourly surface synoptic (airways) meteorological reports from around the United States have been digitized as part of the NOAA Climate Database Modernization Program. An important component is improvement of quality assurance ...

Daniel Y. Graybeal; Arthur T. DeGaetano; Keith L. Eggleston

2004-11-01T23:59:59.000Z

334

How much carbon dioxide (CO 2 ) is produced per kilowatt-hour ...  

U.S. Energy Information Administration (EIA)

How much carbon dioxide (CO 2) is produced per kilowatt-hour when generating electricity with fossil fuels? You can calculate the amount of CO2 produced per kWh for ...

335

NREL Develops Sub-Hour Solar Power Data Set (Fact Sheet), NREL...  

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

Sub-Hour Solar Power Data Set NREL data will help utilities incorporate solar energy into their electric power systems. Large-scale deployment of solar energy requires a favorable...

336

A novel 2-D model approach for the prediction of hourly solar radiation  

Science Conference Proceedings (OSTI)

In this work, a two-dimensional (2-D) representation of the hourly solar radiation data is proposed. The model enables accurate forecasting using image prediction methods. One year solar radiation data that is acquired and collected between August 1, ...

F. Onur Hocaoglu; Ö Nezih Gerek; Mehmet Kurban

2007-06-01T23:59:59.000Z

337

Analysis of Sub-Hourly Ramping Impacts of Wind Energy and Balancing Area Size (Poster)  

DOE Green Energy (OSTI)

WindPower 2008 conference sponsored by AWEA held in Houston, TX on June 1-4 2008. This poster illustrates the data collected for an analysis of sub-hourly ramping impacts of wind energy and balancing area size.

Milligan, M.; Kirby, B.

2008-06-01T23:59:59.000Z

338

Hourly Rainfall Changes in Response to Surface Air Temperature over Eastern Contiguous China  

Science Conference Proceedings (OSTI)

In this study, late-summer rainfall over eastern contiguous China is classified according to hourly intensity and the changes of moderate, intense, and extreme precipitation in response to variation of surface air temperature are analyzed. The e-...

Rucong Yu; Jian Li

2012-10-01T23:59:59.000Z

339

6-Hour to 1-Year Variance of Five Global Precipitation Sets  

Science Conference Proceedings (OSTI)

Three-hourly time series of precipitation from three high-resolution precipitation products [Tropical Rainfall Measuring Mission (TRMM) algorithm 3B-42, the Climate Prediction Center’s morphing method (CMORPH), and the Precipitation Estimation ...

Alex C. Ruane; John O. Roads

2007-08-01T23:59:59.000Z

340

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

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

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

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


341

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

342

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

343

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

344

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

NLE Websites -- All DOE Office Websites (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

345

Determination of Semivariogram Models to Krige Hourly and Daily Solar Irradiance in Western Nebraska  

Science Conference Proceedings (OSTI)

In this paper, linear and spherical semivariogram models were determined for use in kriging hourly and daily solar irradiation for every season of the year. The data used to generate the models were from 18 weather stations in western Nebraska. ...

G. G. Merino; D. Jones; D. E. Stooksbury; K. G. Hubbard

2001-06-01T23:59:59.000Z

346

Model for Aggregated Water Heater Load Using Dynamic Bayesian Networks  

Science Conference Proceedings (OSTI)

The transition to the new generation power grid, or “smart grid”, requires novel ways of using and analyzing data collected from the grid infrastructure. Fundamental functionalities like demand response (DR), that the smart grid needs, rely heavily on the ability of the energy providers and distributors to forecast the load behavior of appliances under different DR strategies. This paper presents a new model of aggregated water heater load, based on dynamic Bayesian networks (DBNs). The model has been validated against simulated data from an open source distribution simulation software (GridLAB-D). The results presented in this paper demonstrate that the DBN model accurately tracks the load profile curves of aggregated water heaters under different testing scenarios.

Vlachopoulou, Maria; Chin, George; Fuller, Jason C.; Lu, Shuai; Kalsi, Karanjit

2012-07-19T23:59:59.000Z

347

Spinning Reserve from Responsive Load  

SciTech Connect

As power system costs rise and capacity is strained demand response can provide a significant system reliability benefit at a potentially attractive cost. The 162 room Music Road Hotel in Pigeon Forge Tennessee agreed to host a spinning reserve test. The Tennessee Valley Authority (TVA) supplied real-time metering and monitoring expertise to record total hotel load during both normal operations and testing. Preliminary testing showed that hotel load can be curtailed by 22% to 37% depending on the outdoor temperature and the time of day. The load drop was very rapid, essentially as fast as the 2 second metering could detect.

Kueck, John D [ORNL; Kirby, Brendan J [ORNL; Laughner, T [Tennessee Valley Authority (TVA); Morris, K [Tennessee Valley Authority (TVA)

2009-01-01T23:59:59.000Z

348

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

NLE Websites -- All DOE Office Websites (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

349

EXPERIMENTAL VERIFICATION OF THE LOAD-FOLLOWING POTENTIAL OF A HOT DRY ROCK GEOTHERMAL RESERVOIR  

E-Print Network (OSTI)

Figure 1. Transient Shut-in Pressure Profiles for the Injection and Production Wells. Conversely, when. During this entire period of cyclic production, the pressure at the injection well was maintained experience. The control system on the injection well worked adequately until the 4-hour pulsed flow period

350

Advanced nonintrusive load monitoring system  

E-Print Network (OSTI)

There is a need for flexible, inexpensive metering technologies that can be deployed in many different monitoring scenarios. Individual loads may be expected to compute information about their power consumption. Utility ...

Wichakool, Warit, 1977-

2011-01-01T23:59:59.000Z

351

OpenEI - building load  

Open Energy Info (EERE)

are given by a location defined by the Typical Meteorological Year (TMY) for which the weather data was collected. Commercial load data is sorted by the (TMY) site as a...

352

Permanent Load Shift Control Strategies  

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

of Permanent Load Shifting for HVAC and other storage assets as it relates to summer on-peak demand, how it can be dynamically and autonomously controlled, and its relationship...

353

Building load control and optimization  

E-Print Network (OSTI)

Researchers and practitioners have proposed a variety of solutions to reduce electricity consumption and curtail peak demand. This research focuses on load control by improving the operations in existing building HVAC ...

Xing, Hai-Yun Helen, 1976-

2004-01-01T23:59:59.000Z

354

Identify Employee Commuting Clusters for Greenhouse Gas Profile |  

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

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

355

Thirty Stage Annular Centrifugal Contactor Thermal Profile Measurements  

Science Conference Proceedings (OSTI)

A thirty stage 5 cm annular centrifugal contactor cascade has been assembled and tested to obtain thermal profiles during both ambient and heated input conditions of operation. Thermocouples were installed on every stage as well as feed inputs and Real-time data was taken during experiments lasting from two to eight hours at total flow rates of 0.5 to 1.4 liters per minute. Ambient temperature profile results show that only a small amount of heat is generated by the mechanical energy of the contactors. Steady state temperature profiles mimic the ambient temperature of the lab but are higher toward the middle of the cascade. Heated inlet solutions gave temperature profiles with smaller temperature gradients, more driven by the temperature of the inlet solutions than ambient lab temperature. Temperature effects of solution mixing, even at rotor speeds of 4000 rpm, were not measurable.

David H. Meikrantz; Troy G. Garn; Jack D. Law

2010-02-01T23:59:59.000Z

356

Removal of bird contamination in wind profiler signal spectra.  

DOE Green Energy (OSTI)

The problem of bird interference with radar performance is as old as radar itself; however, the problem specific to wind profiler operation has not drawn the attention of researchers until the last 5 or 6 years. Since then, the problem has been addressed in many publications and several ways to solve it have been indicated. Recent advances in radar hardware and software made the last generation of profilers much more immune to bird contamination. However, many older profilers are still in use; errors in averaged (hourly) winds due to bird interference may be as high as 15 m/s. The objective of the present study is to develop a practical method to derive mean winds from averaged spectral data of a 915-MHz wind profiler under the condition of bird contamination.

Pekour, M. S.

1998-06-05T23:59:59.000Z

357

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

358

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

359

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

360

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

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


361

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

362

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

363

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

364

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

365

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

366

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

367

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

368

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

369

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

370

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

371

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

372

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

373

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

374

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

375

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

376

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

377

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

378

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

379

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

380

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

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


381

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

382

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

383

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

384

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

385

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

386

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

387

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

388

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

389

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

390

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

391

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

392

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

393

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

394

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

395

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

396

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

397

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

398

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

399

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

400

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

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


401

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

402

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

403

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

404

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

405

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

406

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

407

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

408

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

409

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

410

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

411

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

412

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

413

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

414

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

415

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

416

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

417

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

418

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

419

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

420

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

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421

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

422

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

423

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

424

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

425

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

426

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

427

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

428

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

429

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

430

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

431

Adaptive web usage profiling  

Science Conference Proceedings (OSTI)

Web usage models and profiles capture significant interests and trends from past accesses. They are used to improve user experience, say through recommendation of pages, pre-fetching of pages, etc. While browsing behavior changes dynamically over time, ...

Bhushan Shankar Suryavanshi; Nematollaah Shiri; Sudhir P. Mudur

2005-08-01T23:59:59.000Z

432

Vertically Rising Microstructure Profiler  

Science Conference Proceedings (OSTI)

The vertically rising microstructure profiler was designed to measure temperature gradient and conductivity gradient microstructure in lakes, reservoirs and coastal seas. The instrument is totally independent of surface craft while collecting ...

G. D. Carter; J. Imberger

1986-09-01T23:59:59.000Z

433

Performance profiles style sheet  

U.S. Energy Information Administration (EIA)

investment throughout most of this period compared with the 1990s. Title: Performance profiles style sheet Author: Greg Filas Created Date: 12/23/2010 7:12:57 PM ...

434

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

435

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

436

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

437

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

438

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

439

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

440

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

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


441

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

442

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

443

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

444

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

445

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

446

Fermilab | Women's History Month - Profiles  

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

Profiles The profiles on this page present a cross section of women from the Fermilab community. Fermilab hopes that profiles of these women will inspire young women everywhere to...

447

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

SciTech Connect

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

448

Long-term residential load forecasting. Final report  

SciTech Connect

The main objective of this study was to isolate and evaluate the importance of various factors, many of which are household characteristics and weather conditions, that determine the demand for electricity at different times of day. A second purpose was to investigate one of the factors in detail, namely, prices, which was feasible because half of the households in the sample were subjected to time-of-day pricing. Substantial differences between the load curves of the experimental and control groups were found. Households in the experimental group significantly decreased electricity usage when its price was high, the consumption being shifted partly into the early morning hours but more heavily into the evening. The importance of certain appliances in shifting the load curve is also clearly brought out. For example, households with a dishwasher or electric heating appeared to change the timing of use of these appliances under peak-load pricing. Other appliances were also important in determining the load curve for both groups. Swimming pool pumps and air conditioning, for instance, were important determinants in the summer, whereas in the winter, electric heating and dishwashers substantially increased consumption levels.

Granger, C.W.J.; Engle, R.F.; Ramanathan, R.; Andersen, A.

1978-02-01T23:59:59.000Z

449

Load transfer coupling regression curve fitting for distribution load forecasting  

SciTech Connect

The planning of distribution facilities requires forecasts of future substation and feeder loads. Extrapolation based on a curve fit to past annual peak loads is currently the most popular manner of accomplishing this forecast. Curve fitting suffers badly from data shifts caused by switching as loads are routinely moved from one substation to another during the course of utility operations. This switching contaminates the data, reducing forecast accuracy. A new regression application reduces error due to these transfers by over an order of magnitude. A key to the usefulness of this method is that the amount of the transfer, and its direction (whether it was to or from a substation), is not a required input. The new technique, aspects of computer implementation of it, and a series of tests showing its advantage over normal multiple regression methods are given.

Willis, H.L.; Powell, R.W.

1984-05-01T23:59:59.000Z

450

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

451

Adaptive Fluid Electrical Conductivity Logging to Determine the Salinity Profiles in Groundwater  

E-Print Network (OSTI)

Adaptive Fluid Electrical Conductivity Logging to Determine the Salinity Profiles in Groundwater(t) Analysis Method · Integrate C(z,t), or FEC profile, over z of logged interval to get salinity mass per unit salinity TMDL requires wetland management of salt loads to the San Joaquin River · Dearth of groundwater

Quinn, Nigel

452

FINAL PROJECT REPORT LOAD MODELING TRANSMISSION RESEARCH  

E-Print Network (OSTI)

PSLF that incorporates motor  A?C, ZIP, and electronic load the fractions motors A?C, ZIP, and electronic loads.    Usethat incorporates motor  A?C, ZIP, and  electronic load 

Lesieutre, Bernard

2013-01-01T23:59:59.000Z

453

Monthly Crustal Loading Corrections for Satellite Altimetry  

Science Conference Proceedings (OSTI)

Satellite altimeter measurements of sea surface height include a small contribution from vertical motion of the seafloor caused by crustal loading. Loading by ocean tides is routinely allowed for in altimeter data processing. Here, loading by ...

R. D. Ray; S. B. Luthcke; T. van Dam

2013-05-01T23:59:59.000Z

454

Direct Measurements of Vertical-Velocity Power Spectra with the Sousy-VHF-Radar Wind Profiler System  

Science Conference Proceedings (OSTI)

We present power spectra of vertical velocities measured with the SOUSY-VHF-Radax wind profiler.over a 5-day period in October and November 1981. Most of the data consist of hourly vertical velocity profiles based on 12-rain averages, but, for ...

M. F. Larsen; J. Rutger; D. N. Holden

1987-12-01T23:59:59.000Z

455

NOAA Awarded 2.6 Million Processor Hours at NERSC to Run Climate Change  

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

NOAA Awarded 2.6 NOAA Awarded 2.6 Million Processor Hours at NERSC to Run Climate Change Models NOAA Awarded 2.6 Million Processor Hours at NERSC to Run Climate Change Models September 11, 2008 WASHINGTON, DC - The U.S. Department of Energy's (DOE) Office of Science will make available more than 10 million hours of computing time for the U.S. Commerce Department's National Oceanic and Atmospheric Administration (NOAA) to explore advanced climate change models at three of DOE's national laboratories as part of a three-year memorandum of understanding on collaborative climate research signed today by the two agencies. NOAA will work with climate change models as well as perform near real-time high-impact (non-production) weather prediction research using computing time on DOE Office of Science resources including two of the world's top

456

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

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

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

457

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

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

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

458

Developing hourly weather data for locations having only daily weather data  

Science Conference Proceedings (OSTI)

A methodology was developed to modify an hourly TMY weather tape to be representative of a location for which only average daily weather parameters were avilable. Typical hourly and daily variations in solar flux, and other parameters, were needed to properly exercise a computer model to predict the transient performance of a solar controlled greenhouse being designed for Riyadh, Saudi Arabia. The starting point was a TMY tape for Yuma, Arizona, since the design temperatures for summer and winter are nearly identical for Yuma and Riyadh. After comparing six of the most important weather variables, the hourly values on the Yuma tape were individually adjusted to give the same overall daily average conditions as existed in the long-term Riyadh data. Finally, a statistical analysis was used to confirm quantitatively that the daily variations between the long term average values for Riyadh and the modified TMY weather tape for Yuma matched satisfactorily.

Talbert, S.G.; Herold, K.E.; Jakob, F.E.; Lundstrom, D.K.

1983-06-01T23:59:59.000Z

459

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

Open Energy Info (EERE)

China sites from DLR China 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 China. 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 China DLR DNI GEF GHI solar SWERA UNEP Data application/zip icon Download Data (zip, 953.6 KiB) Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage

460

Sub-Hour Solar Data for Power System Modeling From Static Spatial Variability Analysis: Preprint  

Science Conference Proceedings (OSTI)

High penetration renewable integration studies need high quality solar power data with spatial-temporal correlations that are representative of a real system. This paper will summarize the research relating sequential point-source sub-hour global horizontal irradiance (GHI) values to static, spatially distributed GHI values. This research led to the development of an algorithm for generating coherent sub-hour datasets that span distances ranging from 10 km to 4,000 km. The algorithm, in brief, generates synthetic GHI values at an interval of one-minute, for a specific location, using SUNY/Clean Power Research, satellite-derived, hourly irradiance values for the nearest grid cell to that location and grid cells within 40 km.

Hummon, M.; Ibanez, E.; Brinkman, G.; Lew, D.

2012-12-01T23:59:59.000Z

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


461

Building Energy Software Tools Directory: Load Express  

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

graphical interface makes Load Express a powerful engineering tool with a very short learning curve. The "rookie" or experienced user can quickly and accurately perform load...

462

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

463

Decentralized customerlevel under frequency load shedding in...  

Open Energy Info (EERE)

enables the management of large groups of distributed loads under a single innovative control schemes to use the flexibility of electrical loads for power system purposes....

464

Amp-hour counting charge control for photovoltaic hybrid power systems  

SciTech Connect

An amp-hour counting battery charge control algorithm has been defined and tested using the Digital Solar Technologies MPR-9400 microprocessor based photovoltaic hybrid charge controller. This work included extensive laboratory and field testing of the charge algorithm on vented lead-antimony and valve regulated lead-acid batteries. The test results have shown that with proper setup amp-hour counting charge control is more effective than conventional voltage regulated sub-array shedding in returning the lead-acid battery to a high state of charge.

Hund, T.D. [Sandia National Labs., Albuquerque, NM (United States); Thompson, B. [Biri Systems, Ithaca, NY (United States)

1997-10-01T23:59:59.000Z

465

The Base Load Fallacy and other Fallacies disseminated by Renewable Energy Deniers  

E-Print Network (OSTI)

Abstract: The Base-Load Fallacy is the incorrect notion that renewable energy cannot supply base-load (24-hour) electric power. Alternatives to base-load coal power can be provided by efficient energy use, solar hot water, bioenergy, large-scale wind power, solar thermal electricity with thermal storage, and geothermal, with gas power playing a transitional role. In particular, large-scale wind power from geographically distributed sites is partially reliable and can be made more so by installing a little additional low-cost peak-load back-up from gas turbines. Other fallacies are refuted concisely in the appendix. 1 Opponents of renewable energy, from the coal and nuclear industries and from NIMBY (Not In My Backyard) groups, are disseminating the Base-Load Fallacy, that is, the fallacy that renewable energy cannot provide base-load (24-hour) power to substitute for coal-fired electricity. In Australia, even Government Ministers and some journalists are propagating this conventional ‘wisdom’, although it is false. This fallacy is the principal weapon of renewable energy deniers. Other fallacies are discussed briefly in the appendix. The political implications are that, if these fallacies become widely believed, renewable energy would always have to remain a niche market, rather than achieve its true potential of becoming a

Dr Mark Diesendorf

2010-01-01T23:59:59.000Z

466

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.

467

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,

468

Method for loading resin beds  

DOE Patents (OSTI)

An improved method of preparing nuclear reactor fuel by carbonizing a uranium loaded cation exchange resin provided by contacting a H.sup.+ loaded resin with a uranyl nitrate solution deficient in nitrate, comprises providing the nitrate deficient solution by a method comprising the steps of reacting in a reaction zone maintained between about 145.degree.-200.degree. C, a first aqueous component comprising a uranyl nitrate solution having a boiling point of at least 145.degree. C with a second aqueous component to provide a gaseous phase containing HNO.sub.3 and a reaction product comprising an aqueous uranyl nitrate solution deficient in nitrate.

Notz, Karl J. (Oak Ridge, TN); Rainey, Robert H. (Knoxville, TN); Greene, Charles W. (Knoxville, TN); Shockley, William E. (Oak Ridge, TN)

1978-01-01T23:59:59.000Z

469

An hourly-based performance comparison of an integrated micro-structural perforated shading screen with standard shading systems  

E-Print Network (OSTI)

during summer and solar heating gains during the winter. Theconsider heating by increasing solar gains, cooling byand cooling loads. Heating loads excluded solar gains and

Appelfeld, David

2013-01-01T23:59:59.000Z

470

Six- and three-hourly meteorological observations from 223 USSR stations  

SciTech Connect

This document describes a database containing 6- and 3-hourly meteorological observations from a 223-station network of the former Soviet Union. These data have been made available through cooperation between the two principal climate data centers of the United States and Russia: the National Climatic Data Center (NCDC), in Asheville, North Carolina, and the All-Russian Research Institute of Hydrometeorological Information -- World Data Centre (RIHMI-WDC) in Obninsk. Station records consist of 6- and 3-hourly observations of some 24 meteorological variables including temperature, weather type, precipitation amount, cloud amount and type, sea level pressure, relative humidity, and wind direction and speed. The 6-hourly observations extend from 1936 to 1965; the 3-hourly observations extend from 1966 through the mid-1980s (1983, 1984, 1985, or 1986; depending on the station). These data have undergone extensive quality assurance checks by RIHMI-WDC, NCDC, and the Carbon Dioxide Information Analysis Center (CDIAC). The database represents a wealth of meteorological information for a large and climatologically important portion of the earth`s land area, and should prove extremely useful for a wide variety of regional climate change studies. These data are available free of charge as a numeric data package (NDP) from CDIAC. The NDP consists of this document and 40 data files that are available via the Internet or on 8mm tape. The total size of the database is {approximately}2.6 gigabytes.

Razuvaev, V.N.; Apasova, E.B.; Martuganov, R.A. [All-Russian Research Inst. of Hydrometeorologicl Information, Obninsk (Russia). World Data Centre; Kaiser, D.P. [Oak Ridge National Lab., TN (United States)

1995-04-01T23:59:59.000Z

471

NETL: News Release - DOE Awards Local Researcher with 3 Million Hours on  

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

8, 2008 8, 2008 DOE Awards Local Researcher with 3 Million Hours on Premier Supercomputer Morgantown, W.Va.-The U.S. Department of Energy's (DOE) Office of Science announced today that a scientist at DOE's National Energy Technology Laboratory (NETL) has been awarded 3 million hours of processor time to conduct advanced research on fossil fuel power plants on one of the world's most powerful supercomputers. http://energy.gov/news/5849.htm The Office of Science awarded the supercomputer hours to Madhava Syamlal, a scientist at NETL, as one of 55 nationwide recipients who received a total of 265 million processor hours. Syamlal, along with his team of co-investigators, will use the powerful Cray XT4 supercomputer at ORNL to vastly increase the speed of coal gasifier simulations to aid in the design and optimization of the power plants. His team is composed of Thomas O'Brien (NETL), Chris Guenther (NETL), Sreekanth Pannala (ORNL), Ramanan Sankaran (ORNL), and Aytekin Gel (Aeolus Research Inc.).

472

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

E-Print Network (OSTI)

than 30 countries signed a deal on Tuesday to build the world's most advanced nuclear fusion reactor nuclear reactors, but critics argue it could be at least 50 years before a commercially viable reactorThirty states sign ITER nuclear fusion plant deal 1 hour, 28 minutes ago Representatives of more

473

NREL RSF Weather Data 2011 A csv containing hourly weather data...  

Open Energy Info (EERE)

NREL RSF Weather Data 2011 A csv containing hourly weather data at NREL's Research and Support Facility (RSF) for 2011. 2013-02-12T18:36:26Z 2013-02-12T18:36:26Z I am submitting...

474

Predicting Future Hourly Residential Electrical Consumption: A Machine Learning Case Study  

E-Print Network (OSTI)

(e.g., HVAC) for a specific building, optimizing control systems and strategies for a buildingPredicting Future Hourly Residential Electrical Consumption: A Machine Learning Case Study Richard building energy modeling suffers from several factors, in- cluding the large number of inputs required

Tennessee, University of

475

Sams Teach Yourself Paint Shop Pro 6 in 24 Hours, 1st edition  

Science Conference Proceedings (OSTI)

From the Publisher:This easily accessible tutorial uses a friendly, conversational approach to teach you the basics of Paint Shop Pro 6. With its careful, step-by-step approach, Sams Teach Yourself Paint Shop Pro 6 in 24 Hours makes it easy even for ...

T. Michael Clark; Michael Clark / Kris Tufto

1999-11-01T23:59:59.000Z

476

REDCap 102 Training Session This two-hour session presented by Heather Kim  

E-Print Network (OSTI)

at Vanderbilt. This version of REDCap is main- tained by the UIC Design and Analysis Core, and is offeredREDCap 102 Training Session This two-hour session presented by Heather Kim will explore some Capture) is a secure, web- based application for building and managing online databases for the collection

Illinois at Chicago, University of

477

REDCap 102 Training Session This two-hour session presented by John O'Keefe  

E-Print Network (OSTI)

REDCap team at Vanderbilt. This version of REDCap is main- tained by the UIC Design and Analysis CoreREDCap 102 Training Session This two-hour session presented by John O'Keefe will explore some Data Capture) is a secure, web- based application for building and managing online databases

Illinois at Chicago, University of

478

Climatology of Heavy Rain Events in the United States from Hourly Precipitation Observations  

Science Conference Proceedings (OSTI)

Flash flooding is frequently associated with heavy precipitation (defined here as ?1 in. h?1) occurring over a short period of time. To begin a study of flash flood–producing rain events, the Hourly Precipitation Dataset (HPD) is used to develop ...

Harold E. Brooks; David J. Stensrud

2000-04-01T23:59:59.000Z

479

From the Big Bang to the Higgs Boson in Less Than an Hour  

E-Print Network (OSTI)

From the Big Bang to the Higgs Boson in Less Than an Hour Jeffrey D H Higgs boson Gauge bosons (force field quanta) Higgs boson and vacuum expectation value Strong) photon Z boson W bosons H Higgs boson Gauge bosons (force field quanta) Higgs boson and vacuum

Fygenson, Deborah Kuchnir

480

From the Big Bang to the Higgs Boson in Less Than an Hour  

E-Print Network (OSTI)

From the Big Bang to the Higgs Boson in Less Than an Hour Jeffrey D neutrino Z0 W + W -g gluon (8) photon Z boson W bosons Quarks Leptons H Higgs boson Gauge bosons (force field quanta) Higgs boson and vacuum expectation value Strong force EM force Weak force #12;Par7cles

Fygenson, Deborah Kuchnir

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


481

Fuel Cell Stacks Still Going Strong After 5,000 Hours  

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

Two fuel cell stacks developed by FuelCell Energy in partnership with Versa Power Systems achieved 5,000 hours of service in February, meeting a goal of the U.S. Department of Energy's Solid State Energy Conversion Alliance.

482

EMERGENCY CONTACTS for DOWNER LAB Contact Phone After Hours Purpose/Additional Info  

E-Print Network (OSTI)

EMERGENCY CONTACTS for DOWNER LAB Contact Phone After Hours Purpose/Additional Info UT Police.utexas.edu/facilities/services for further information and non-emergency service request forms) Environmental Health & Safety 471-3511 911 emergencies, call 911 or go to a local hospital emergency room. (see healthyhorns.utexas.edu/emergencies

Shvets, Gennady