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1

Measured Peak Equipment Loads in Laboratories  

SciTech Connect

This technical bulletin documents measured peak equipment load data from 39 laboratory spaces in nine buildings across five institutions. The purpose of these measurements was to obtain data on the actual peak loads in laboratories, which can be used to rightsize the design of HVAC systems in new laboratories. While any given laboratory may have unique loads and other design considerations, these results may be used as a 'sanity check' for design assumptions.

Mathew, Paul A.

2007-09-12T23:59:59.000Z

2

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

3

Peak Load Shifting by Thermal Energy Storage  

Science Conference Proceedings (OSTI)

This technical update from the Electric Power Research Institute (EPRI) reviews the technology of storing energy in hot water and explores the potential for implementing this form of thermal energy storagethrough means of smart electric water heatersas a way to shift peak load on the electric grid. The report presents conceptual background, discusses strategies for peak load shifting and demand response, documents a series of laboratory tests conducted on a representative model of smart water heater, and...

2011-12-14T23:59:59.000Z

4

Definition: Circuit Peak Load Management | Open Energy Information  

Open Energy Info (EERE)

Circuit Peak Load Management Jump to: navigation, search Dictionary.png Circuit Peak Load Management An application utilizing sensors, information processors, communications, and...

5

Conditional model of peak and minimum loads and the load duration curve for electricity  

SciTech Connect

This report presents a model that extends the traditional model of electricity demand to account for intra-period load variation, the kind of variation that is important for evaluating marginal-cost-reflecting price structures. The time-of-day rate is one such price structure. The traditional model of electricity demand explains inter-period demand variation. It says nothing about load variation. The report explains how a model that integrates with previous studies of electricity demand might be formulated. It specifies two concrete models within this framework and estimates them for a number of different utility companies. The model's within-sample-period performance in predicting peak loads is presented for one version of the model extension along with estimations for other variations. In addition a number of plots of actual load distributions, a summation of load variation information, against the actual load distributions, are presented and used to evaluate the performance of specific models.

Trimble, J.L.; Stallings, D.E.; Thomas, B.

1980-05-01T23:59:59.000Z

6

Methods and apparatus for reducing peak wind turbine loads ...  

A method for reducing peak loads of wind turbines in a changing wind environment includes measuring or estimating an instantaneous wind speed and direction at the ...

7

Peak load control energy saving and cycling system  

SciTech Connect

A control system for limiting peak load demand and/or saving electrical energy by cycling the individual loads within an electrical distribution system is described. Electrical power usage in a distribution system is continuously monitored and compared to a pre-set limit. Loads can be added and cycled according to a limit set by the operator. Loads can also be dropped in response to a signal proportional to the electrical power usage in a distribution system within limits defined by the operator.

Burch, J.

1976-10-19T23:59:59.000Z

8

Potential Peak Load Reductions From Residential Energy Efficient Upgrades  

E-Print Network (OSTI)

The demand for electricity is continuing to grow at a substantial rate. Utilities are interested in managing this growth's peak demand for a number of reasons including: costly construction of new generation capacity can be deferred; the reliability of the distribution network can be improved; and added environmental pollution can be minimized. Energy efficiency improvements, especially through residential programs, are increasingly being used to mitigate this rise in peak demand. This paper examines the potential peak load reductions from residential energy efficiency upgrades in hot and humid climates. First, a baseline scenario is established. Then, the demand and consumption impacts of individual upgrade measures are assessed. Several of these upgrades are then combined into a package to assess the synergistic demand and energy impacts. A sensitivity analysis is then performed to assess the impacts of housing characteristics on estimated demand and energy savings. Finally, the demand, energy, and environmental impacts are estimated at the community level.

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

2002-01-01T23:59:59.000Z

9

An Innovative Approach Towards National Peak Load Management  

E-Print Network (OSTI)

An innovative approach was developed and implemented in eight governmental buildings to reduce their load during the peak demand hours in summer of 2007. The innovative approach implemented in these buildings included pre-closing treatment (PCT) between 13:00 and 14:00 h and time-of-day control (TDC) after 14:00 h for air conditioning (A/C) and lighting systems. PCT realized an overall reduction of 3.43 MW, a saving of 11.7% of the buildings peak power demand; while TDC realized a total savings of 8.67 MW at 15:00 h, a saving of 30.7% of the buildings peak power demand at that hour. The temperature build up inside the buildings due to PCT and TDC was within the acceptable range, which validated the technical viability of these measures. The implementation of the innovative approach in the eight governmental buildings with a total measured peak demand of 29.3 MW achieved a reduction of 8.89 MW. This power is now available to other users leading to financial savings of $13.5 million for the nation towards the cost of constructing new power plants and distribution network equipment. More importantly, this reduction in peak power demand of well over 30% involved zero or limited expenditure. A nationwide implementation of this innovative approach in all the governmental and institutional buildings is likely to reduce the national peak power demand by 154 MW which amounts to a capital savings of $232 million towards the cost of new power generation equipment and distribution network.

Al-Mulla, A.; Maheshwari, G. P.; Al-Nakib, D.; ElSherbini, A.; Alghimlas, F.; Al-Taqi, H.; Al-Hadban, Y.

2008-10-01T23:59:59.000Z

10

Investigation of Peak Load Reduction Strategies in Residential Buildings in Cooling Dominated Climates.  

E-Print Network (OSTI)

??This investigation of peak load reduction strategies in residential buildings contributes to the global international efforts in reducing energy consumption and is related directly to… (more)

Atallah, Fady

2013-01-01T23:59:59.000Z

11

Impact of Smart Grid Technologies on Peak Load to 2050 | Open Energy  

Open Energy Info (EERE)

Impact of Smart Grid Technologies on Peak Load to 2050 Impact of Smart Grid Technologies on Peak Load to 2050 Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Impact of Smart Grid Technologies on Peak Load to 2050 Focus Area: Crosscutting Topics: Deployment Data Website: www.iea.org/papers/2011/smart_grid_peak_load.pdf Equivalent URI: cleanenergysolutions.org/content/impact-smart-grid-technologies-peak-l Language: English Policies: "Deployment Programs,Regulations" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Demonstration & Implementation Regulations: Cost Recovery/Allocation This working paper analyses the evolution of peak load demand to 2050 in four key regions: Organisation for Economic Co-operation and Development

12

Testing an Ice Storage System for Peak Load Reduction  

Science Conference Proceedings (OSTI)

Ice storage systems allow for the offset of peak building cooling power by allowing the building operator to choose a convenient window for making ice and then using that ice, rather than a traditional cooling system, to provide space cooling. For the past several years, the Electric Power Research Institute (EPRI) has tested the Ice Bear 30, a 30 ton-hour system designed to operate independently of the unitary system. This report describes the testing and its results, based on work performed at a field ...

2011-04-21T23:59:59.000Z

13

Power consumption scheduling for peak load reduction in smart grid homes  

Science Conference Proceedings (OSTI)

This paper presents a design and evaluates the performance of a power consumption scheduler in smart grid homes, aiming at reducing the peak load in individual homes as well as in the system-wide power transmission network. Following the task model consist ... Keywords: execution time, home controller, peak load reduction, power schedule, smart grid

Junghoon Lee; Gyung-Leen Park; Sang-Wook Kim; Hye-Jin Kim; Chang Oan Sung

2011-03-01T23:59:59.000Z

14

Load controller and method to enhance effective capacity of a photovotaic power supply using a dynamically determined expected peak loading  

DOE Patents (OSTI)

A load controller and method are provided for maximizing effective capacity of a non-controllable, renewable power supply coupled to a variable electrical load also coupled to a conventional power grid. Effective capacity is enhanced by monitoring power output of the renewable supply and loading, and comparing the loading against the power output and a load adjustment threshold determined from an expected peak loading. A value for a load adjustment parameter is calculated by subtracting the renewable supply output and the load adjustment parameter from the current load. This value is then employed to control the variable load in an amount proportional to the value of the load control parameter when the parameter is within a predefined range. By so controlling the load, the effective capacity of the non-controllable, renewable power supply is increased without any attempt at operational feedback control of the renewable supply. The expected peak loading of the variable load can be dynamically determined within a defined time interval with reference to variations in the variable load.

Perez, Richard (Delmar, NY)

2003-04-01T23:59:59.000Z

15

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

16

A computational intelligence scheme for the prediction of the daily peak load  

Science Conference Proceedings (OSTI)

Forecasting of future electricity demand is very important for decision making in power system operation and planning. In recent years, due to privatization and deregulation of the power industry, accurate electricity forecasting has become an important ... Keywords: Computational intelligence, Daily peak load, Mid-term load forecasting, Self-organizing map, Support vector machine

Jawad Nagi; Keem Siah Yap; Farrukh Nagi; Sieh Kiong Tiong; Syed Khaleel Ahmed

2011-12-01T23:59:59.000Z

17

Roof shading and wall glazing techniques for reducing peak building heating and cooling loads. Final report  

SciTech Connect

The roof shading device proved to be effective in reducing peak building cooling loads under both actual testing conditions and in selected computer simulations. The magnitude of cooling load reductions varied from case to case depending on individual circumstances. Key variables that had significant impacts on its thermal performance were the number of months of use annually, the thermal characteristics of the roof construction, hours of building use, and internal gains. Key variables that had significant impacts upon economic performance were the costs of fuel energy for heating and cooling, and heating and cooling equipment efficiency. In general, the more sensitive the building is to climate, the more effective the shading device will be. In the example case, the annual fuel savings ($.05 psf) were 6 to 10% of the estimated installation costs ($.50 to .75 psf). The Trombe wall installation at Roxborough High School proved to be effective in collecting and delivering significant amounts of solar heat energy. It was also effective in conserving heat energy by replacing obsolete windows which leaked large amounts of heat from the building. Cost values were computed for both solar energy contributions and for heat loss reductions by window replacement. Together they amount to an estimated three hundred and ninety dollars ($390.00) per year in equivalent electric fuel costs. When these savings are compared with installation cost figures it is apparent that the Trombe wall installation as designed and installed presents a potentially cost-effective method of saving fuel costs. The study results indicate that improved Trombe wall efficiency can be achieved by making design and construction changes to reduce or eliminate outside air leakage into the system and provide automatic fan control.

Ueland, M.

1981-08-01T23:59:59.000Z

18

Permanent Peak Load Shift Product Deployment for Smart Grid Integration and Operation  

Science Conference Proceedings (OSTI)

This project tested and evaluated an innovative energy storage technology that provides permanent peak load shifting using electro-thermal energy storage in combination with commercial unitary rooftop air conditioning systems. Four Ice Bear 30 units were deployed at a Staples facility to store an estimated 32 kWh each of energy in 10 off-peak hours and reduce an estimated 5 kW of site energy demand for an on-peak six-hour period. The Ice Bear units are monitored and controlled with a smart grid ...

2012-11-14T23:59:59.000Z

19

Peak Load Management of Thermal Loads Using Advanced Thermal Energy Storage Technologies  

Science Conference Proceedings (OSTI)

Almost 50% of electric energy delivered to residences is converted into some sort of thermal energy—hot water, air conditioning, and refrigeration. Storing energy in thermal form is cheaper especially when the medium used to store the energy is an end-use medium for example, hot water. This technical update evaluates two different technologies for storing energy—in cold water and in hot water.GreenPeak technology, a storage condensing unit (SCU) from IE Technologies, uses an ...

2013-12-20T23:59:59.000Z

20

Indoor Air Quality Impacts of a Peak Load Shedding Strategy for a Large  

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

Indoor Air Quality Impacts of a Peak Load Shedding Strategy for a Large Indoor Air Quality Impacts of a Peak Load Shedding Strategy for a Large Retail Building Title Indoor Air Quality Impacts of a Peak Load Shedding Strategy for a Large Retail Building Publication Type Report LBNL Report Number LBNL-59293 Year of Publication 2006 Authors Hotchi, Toshifumi, Alfred T. Hodgson, and William J. Fisk Keywords market sectors, technologies Abstract Mock Critical Peak Pricing (CPP) events were implemented in a Target retail store in the San Francisco Bay Area by shutting down some of the building's packaged rooftop air-handling units (RTUs). Measurements were made to determine how this load shedding strategy would affect the outdoor air ventilation rate and the concentrations of volatile organic compounds (VOCs) in the sales area. Ventilation rates prior to and during load shedding were measured by tracer gas decay on two days. Samples for individual VOCs, including formaldehyde and acetaldehyde, were collected from several RTUs in the morning prior to load shedding and in the late afternoon. Shutting down a portion (three of 11 and five of 12, or 27 and 42%) of the RTUs serving the sales area resulted in about a 30% reduction in ventilation, producing values of 0.50-0.65 air changes per hour. VOCs with the highest concentrations (>10 μg/m3) in the sales area included formaldehyde, 2-butoxyethanol, toluene and decamethylcyclopentasiloxane. Substantial differences in concentrations were observed among RTUs. Concentrations of most VOCs increased during a single mock CPP event, and the median increase was somewhat higher than the fractional decrease in the ventilation rate. There are few guidelines for evaluating indoor VOC concentrations. For formaldehyde, maximum concentrations measured in the store during the event were below guidelines intended to protect the general public from acute health risks.

Note: This page contains sample records for the topic "actual peak load" 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

Indoor Air Quality Impacts of a Peak Load Shedding Strategy for a Large  

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

Indoor Air Quality Impacts of a Peak Load Shedding Strategy for a Large Indoor Air Quality Impacts of a Peak Load Shedding Strategy for a Large Retail Building Title Indoor Air Quality Impacts of a Peak Load Shedding Strategy for a Large Retail Building Publication Type Report Year of Publication 2006 Authors Hotchi, Toshifumi, Alfred T. Hodgson, and William J. Fisk Publisher Lawrence Berkeley National Laboratory Abstract Mock Critical Peak Pricing (CPP) events were implemented in a Target retail store in the San Francisco Bay Area by shutting down some of the building's packaged rooftop air-handling units (RTUs). Measurements were made to determine how this load shedding strategy would affect the outdoor air ventilation rate and the concentrations of volatile organic compounds (VOCs) in the sales area. Ventilation rates prior to and during load shedding were measured by tracer gas decay on two days. Samples for individual VOCs, including formaldehyde and acetaldehyde, were collected from several RTUs in the morning prior to load shedding and in the late afternoon. Shutting down a portion (three of 11 and five of 12, or 27 and 42%) of the RTUs serving the sales area resulted in about a 30% reduction in ventilation, producing values of 0.50-0.65 air changes per hour. VOCs with the highest concentrations (>10 μg/m3) in the sales area included formaldehyde, 2-butoxyethanol, toluene and decamethylcyclopentasiloxane. Substantial differences in concentrations were observed among RTUs. Concentrations of most VOCs increased during a single mock CPP event, and the median increase was somewhat higher than the fractional decrease in the ventilation rate. There are few guidelines for evaluating indoor VOC concentrations. For formaldehyde, maximum concentrations measured in the store during the event were below guidelines intended to protect the general public from acute health risks

22

The Influence of Air-Conditioning Efficiency in the Peak Load Demand for Kuwait  

E-Print Network (OSTI)

A model co-relating the peak load demand of a utility with the allowable power rating (PR) of air-conditioning (AC) systems has been developed in this paper through a well defined methodology. The model is capable to predict the extent of allowable increase in the capital cost of the AC system for an improvement in PR from its base case as well. Furthermore, effectiveness of better PR of AC system for peak load management has been analyzed for Kuwait as a case study. It is found that up to 5,752 MW in reduction in peak load demand and savings of KD 2,301 million in capital expenditures are possible for the years between 2001 and 2025 if the PR of AC systems are improved to 1.2 kW/RT from its present level of 2.0 kW/RT. Also, it is estimated that extent of increase in capital cost of AC system by 106 % is justified for reducing the expenditure for new power plants. The paper will be useful for the energy planner and policy makers in the countries of Arabian Peninsula with huge demand for air-conditioning.

Ali, A. A.; Maheshwari, G. P.

2007-01-01T23:59:59.000Z

23

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

24

A Field Study on Residential Air Conditioning Peak Loads During Summer in College Station, Texas  

E-Print Network (OSTI)

Severe capacity problems are experienced by electric utilities during hot summer afternoons. Several studies have found that, in large part, electric peak loads can be attributed to residential airconditioning use. This air-conditioning peak depends primarily on two factors: (i) the manner in which the homeowner operates his air-conditioner during the hot summer afternoons, and (ii) the amount by which the air-conditioner has been over-designed. Whole-house and air-conditioner electricity use data at 15 minute time intervals have been gathered and analyzed for 8 residences during the summer of 1991, six of which had passed the College Station Good Cents tests. Indoor air temperatures were measured by a mechanical chart recorder, while a weather station located on the main campus of Texas A&M university provided the necessary climatic data, especially ambient temperature, relative humidity and solar radiation. The data were analysed to determine the extent to which air-conditioning over-sizing and homeowner intervention contributes to peak electricity use for newer houses in College Station, Texas.

Reddy, T. A.; Vaidya, S.; Griffith, L.; Bhattacharyya, S.; Claridge, D. E.

1992-01-01T23:59:59.000Z

25

Industrial-Load-Shaping: The Practice of and Prospects for Utility/Industry Cooperation to Manage Peak Electricity Demand  

E-Print Network (OSTI)

Load-management programs designed to reduce demand for electricity during peak periods are becoming increasingly important to electric utilities. For a growing number of utilities, however, such peak-reduction programs don't go far enough in the face of new problems and challenges, and hence are proving ineffective or counterproductive. For example, many of a utility's largest customers--especially industrial customers who may be "locked into" seemingly inflexible process activities--have limited ability to respond to load-management programs that employ price signals as a central peak-reduction tool. Moreover, utilities in general are finding that vigorous efforts to reduce electric load can result in underutilization of base-load generating facilities. In these and other instances, "load-shaping," which emphasizes a shift of electric load or demand from peak to off-peak periods and provides for greater customer flexibility, may be a more effective strategy. This paper explains the need for and presents the components of a load-shaping program, and describes Pacific Gas and Electric Company's (PGandE) recent experience in designing and pursuing an industrial-load-shaping program. The paper also outlines important obstacles and opportunities likely to confront other utilities and industrial customers interested in working together to develop such programs.

Bules, D. J.; Rubin, D. E.; Maniates, M. F.

1986-06-01T23:59:59.000Z

26

Assessment of high temperature nuclear energy storage systems for the production of intermediate and peak-load electric power  

DOE Green Energy (OSTI)

Increased cost of energy, depletion of domestic supplies of oil and natural gas, and dependence on foreign suppliers, have led to an investigation of energy storage as a means to displace the use of oil and gas presently being used to generate intermediate and peak-load electricity. Dedicated nuclear thermal energy storage is investigated as a possible alternative. An evaluation of thermal storage systems is made for several reactor concepts and economic comparisons are presented with conventional storage and peak power producing systems. It is concluded that dedicated nuclear storage has a small but possible useful role in providing intermediate and peak-load electric power.

Fox, E. C.; Fuller, L. C.; Silverman, M. D.

1977-04-18T23:59:59.000Z

27

Indoor Air Quality Impacts of a Peak Load Shedding Strategy for...  

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

Abstract Mock Critical Peak Pricing (CPP) events were implemented in a Target retail store in the San Francisco Bay Area by shutting down some of the building's...

28

Base-Load and Peak Electricity from a Combined Nuclear Heat and Fossil Combined-Cycle Plant  

SciTech Connect

A combined-cycle power plant is proposed that uses heat from a high-temperature reactor and fossil fuel to meet base-load and peak electrical demands. The high temperature gas turbine produces shaft power to turn an electric generator. The hot exhaust is then fed to a heat recovery steam generator (HRSG) that provides steam to a steam turbine for added electrical power production. A simplified computational model of the thermal power conversion system was developed in order to parametrically investigate two different steady-state operation conditions: base load nuclear heat only from an Advanced High Temperature Reactor (AHTR), and combined nuclear heat with fossil heat to increase the turbine inlet temperature. These two cases bracket the expected range of power levels, where any intermediate power level can result during electrical load following. The computed results indicate that combined nuclear-fossil systems have the potential to offer both low-cost base-load electricity and lower-cost peak power relative to the existing combination of base-load nuclear plants and separate fossil-fired peak-electricity production units. In addition, electric grid stability, reduced greenhouse gases, and operational flexibility can also result with using the conventional technology presented here for the thermal power conversion system coupled with the AHTR. (authors)

Conklin, James C.; Forsberg, Charles W. [Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831 (United States)

2007-07-01T23:59:59.000Z

29

Base-Load and Peak Electricity from a Combined Nuclear Heat and Fossil Combined-Cycle Plant  

Science Conference Proceedings (OSTI)

A combined-cycle power plant is proposed that uses heat from a high-temperature reactor and fossil fuel to meet base-load and peak electrical demands. The high-temperature gas turbine produces shaft power to turn an electric generator. The hot exhaust is then fed to a heat recovery steam generator (HRSG) that provides steam to a steam turbine for added electrical power production. A simplified computational model of the thermal power conversion system was developed in order to parametrically investigate two different steady-state operation conditions: base load nuclear heat only from an Advanced High Temperature Reactor (AHTR), and combined nuclear heat with fossil heat to increase the turbine inlet temperature. These two cases bracket the expected range of power levels, where any intermediate power level can result during electrical load following. The computed results indicate that combined nuclear-fossil systems have the potential to offer both low-cost base-load electricity and lower-cost peak power relative to the existing combination of base-load nuclear plants and separate fossil-fired peak-electricity production units. In addition, electric grid stability, reduced greenhouse gases, and operational flexibility can also result with using the conventional technology presented here for the thermal power conversion system coupled with the AHTR.

Conklin, Jim [ORNL; Forsberg, Charles W [ORNL

2007-01-01T23:59:59.000Z

30

Hydrogen-or-Fossil-Combustion Nuclear Combined-Cycle Systems for Base- and Peak-Load Electricity Production  

DOE Green Energy (OSTI)

A combined-cycle power plant is described that uses (1) heat from a high-temperature nuclear reactor to meet base-load electrical demands and (2) heat from the same high-temperature reactor and burning natural gas, jet fuel, or hydrogen to meet peak-load electrical demands. For base-load electricity production, fresh air is compressed; then flows through a heat exchanger, where it is heated to between 700 and 900 C by heat provided by a high-temperature nuclear reactor via an intermediate heat-transport loop; and finally exits through a high-temperature gas turbine to produce electricity. The hot exhaust from the Brayton-cycle gas turbine is then fed to a heat recovery steam generator that provides steam to a steam turbine for added electrical power production. To meet peak electricity demand, the air is first compressed and then heated with the heat from a high-temperature reactor. Natural gas, jet fuel, or hydrogen is then injected into the hot air in a combustion chamber, combusts, and heats the air to 1300 C-the operating conditions for a standard natural-gas-fired combined-cycle plant. The hot gas then flows through a gas turbine and a heat recovery steam generator before being sent to the exhaust stack. The higher temperatures increase the plant efficiency and power output. If hydrogen is used, it can be produced at night using energy from the nuclear reactor and stored until needed. With hydrogen serving as the auxiliary fuel for peak power production, the electricity output to the electric grid can vary from zero (i.e., when hydrogen is being produced) to the maximum peak power while the nuclear reactor operates at constant load. Because nuclear heat raises air temperatures above the auto-ignition temperatures of the various fuels and powers the air compressor, the power output can be varied rapidly (compared with the capabilities of fossil-fired turbines) to meet spinning reserve requirements and stabilize the electric grid. This combined cycle uses the unique characteristics of high-temperature reactors (T>700 C) to produce electricity for premium electric markets whose demands can not be met by other types of nuclear reactors. It may also make the use of nuclear reactors economically feasible in smaller electrical grids, such as those found in many developing countries. The ability to rapidly vary power output can be used to stabilize electric grid performance-a particularly important need in small electrical grids.

Forsberg, Charles W [ORNL; Conklin, Jim [ORNL

2007-09-01T23:59:59.000Z

31

Use of Residential Smart Appliances for Peak-Load Shifting and Spinning Reserves Cost/Benefit Analysis  

Science Conference Proceedings (OSTI)

In this report, we present the results of an analytical cost/benefit study of residential smart appliances from a utility/grid perspective in support of a joint stakeholder petition to the ENERGY STAR program within the Environmental Protection Agency (EPA) and Department of Energy (DOE). The goal of the petition is in part to provide appliance manufacturers incentives to hasten the production of smart appliances. The underlying hypothesis is that smart appliances can play a critical role in addressing some of the societal challenges, such as anthropogenic global warming, associated with increased electricity demand, and facilitate increased penetration of renewable sources of power. The appliances we consider include refrigerator/freezers, clothes washers, clothes dryers, room air-conditioners, and dishwashers. The petition requests the recognition that providing an appliance with smart grid capability, i.e., products that meet the definition of a smart appliance, is at least equivalent to a corresponding five percent in operational machine efficiencies. It is then expected that given sufficient incentives and value propositions, and suitable automation capabilities built into smart appliances, residential consumers will be adopting these smart appliances and will be willing participants in addressing the aforementioned societal challenges by more effectively managing their home electricity consumption. The analytical model we utilize in our cost/benefit analysis consists of a set of user-definable assumptions such as the definition of on-peak (hours of day, days of week, months of year), the expected percentage of normal consumer electricity consumption (also referred to as appliance loads) that can shifted from peak hours to off-peak hours, the average power rating of each appliance, etc. Based on these assumptions, we then formulate what the wholesale grid operating-cost savings, or benefits, would be if the smart capabilities of appliances were invoked, and some percentage of appliance loads were shifted away from peak hours to run during off-peak hours, and appliance loads served power-system balancing needs such as spinning reserves that would otherwise have to be provided by generators. The rationale is that appliance loads can be curtailed for about ten minutes or less in response to a grid contingency without any diminution in the quality of service to the consumer. We then estimate the wholesale grid operating-cost savings based on historical wholesale-market clearing prices (location marginal and spinning reserve) from major wholesale power markets in the United States. The savings derived from the smart grid capabilities of an appliance are then compared to the savings derived from a five percent increase in traditional operational machine efficiencies, referred to as cost in this report, to determine whether the savings in grid operating costs (benefits) are at least as high as or higher than the operational machine efficiency credit (cost).

Sastry, Chellury; Pratt, Robert G.; Srivastava, Viraj; Li, Shun

2010-12-01T23:59:59.000Z

32

Verktyg för lönsamhetsberäkningar vid bränslekonvertering av spetslastpannor från olja till pellets; Tool for estimating the profitability of converting a peak-load oil-fired boiler to pellets.  

E-Print Network (OSTI)

?? This report summarizes the development of a calculation program estimating the profitability of converting a peak-load oil-fired boiler to pellets. To convert an oil-fired… (more)

Sorby, Jonathan

2013-01-01T23:59:59.000Z

33

NREL's Energy-Saving Technology for Air Conditioning Cuts Peak Power Loads Without Using Harmful Refrigerants (Fact Sheet)  

SciTech Connect

This fact sheet describes how the DEVAP air conditioner was invented, explains how the technology works, and why it won an R&D 100 Award. Desiccant-enhanced evaporative (DEVAP) air-conditioning will provide superior comfort for commercial buildings in any climate at a small fraction of the electricity costs of conventional air-conditioning equipment, releasing far less carbon dioxide and cutting costly peak electrical demand by an estimated 80%. Air conditioning currently consumes about 15% of the electricity generated in the United States and is a major contributor to peak electrical demand on hot summer days, which can lead to escalating power costs, brownouts, and rolling blackouts. DEVAP employs an innovative combination of air-cooling technologies to reduce energy use by up to 81%. DEVAP also shifts most of the energy needs to thermal energy sources, reducing annual electricity use by up to 90%. In doing so, DEVAP is estimated to cut peak electrical demand by nearly 80% in all climates. Widespread use of this cooling cycle would dramatically cut peak electrical loads throughout the country, saving billions of dollars in investments and operating costs for our nation's electrical utilities. Water is already used as a refrigerant in evaporative coolers, a common and widely used energy-saving technology for arid regions. The technology cools incoming hot, dry air by evaporating water into it. The energy absorbed by the water as it evaporates, known as the latent heat of vaporization, cools the air while humidifying it. However, evaporative coolers only function when the air is dry, and they deliver humid air that can lower the comfort level for building occupants. And even many dry climates like Phoenix, Arizona, have a humid season when evaporative cooling won't work well. DEVAP extends the applicability of evaporative cooling by first using a liquid desiccant-a water-absorbing material-to dry the air. The dry air is then passed to an indirect evaporative cooling stage, in which the incoming air is in thermal contact with a moistened surface that evaporates the water into a separate air stream. As the evaporation cools the moistened surface, it draws heat from the incoming air without adding humidity to it. A number of cooling cycles have been developed that employ indirect evaporative cooling, but DEVAP achieves a superior efficiency relative to its technological siblings.

Not Available

2012-07-01T23:59:59.000Z

34

NRELs Energy-Saving Technology for Air Conditioning Cuts Peak Power Loads Without Using Harmful Refrigerants (Fact Sheet), NREL (National Renewable Energy Laboratory)  

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

DEVAP Slashes Peak Power Loads DEVAP Slashes Peak Power Loads Desiccant-enhanced evaporative (DEVAP) air-condi- tioning will provide superior comfort for commercial buildings in any climate at a small fraction of the elec- tricity costs of conventional air-conditioning equip- ment, releasing far less carbon dioxide and cutting costly peak electrical demand by an estimated 80%. Air conditioning currently consumes about 15% of the electricity generated in the United States and is a major contributor to peak electrical demand on hot summer days, which can lead to escalating power costs, brownouts, and rolling blackouts. DEVAP employs an innovative combination of air-cooling technologies to reduce energy use by up to 81%. DEVAP also shifts most of the energy needs to thermal energy sources, reducing annual electricity use by up

35

The influence of skill and low back pain on peak and cumulative spine loads during wool harvesting.  

E-Print Network (OSTI)

??Sheep shearing is a physically demanding occupation, with high energy expenditure, spinal loads and risk of back injury. The cost of injury compensation and rehabilitation… (more)

Pal, Poonam

2010-01-01T23:59:59.000Z

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

Persistence of the impact of the Hood River Conservation Project on typical and peak loads three years after weatherization  

SciTech Connect

The Hood River Conservation Project (HRCP) was a major residential retrofit demonstration project, operated by Pacific Power Light Company (Pacific Power) between 1984 and 1988, and funded by the Bonneville Power Administration (Bonneville). The project was designed to install as many cost-effective retrofit measures in as many electrically heated homes as possible in the community of Hood River, Oregon. The Pacific Power HRCP planners statistically selected a special group of 320 Hood River homes that represented a cross-section of the community. The end-use loads (electric space heating, electric water heating, and woodfuel space heating) and the interior temperatures of these homes were monitored for one year before weatherization and three years after weatherization. After more than four years of submetered data collection, 220 single-family, detached homes were available for analysis in the second load study. Weather was normalized for the four heating seasons by matching one day from the pre-program year with one day from each postretrofit year.

White, D.L.; Stovall, T.K.; Tonn, B.E.

1992-02-01T23:59:59.000Z

38

Persistence of the impact of the Hood River Conservation Project on typical and peak loads three years after weatherization  

SciTech Connect

The Hood River Conservation Project (HRCP) was a major residential retrofit demonstration project, operated by Pacific Power & Light Company (Pacific Power) between 1984 and 1988, and funded by the Bonneville Power Administration (Bonneville). The project was designed to install as many cost-effective retrofit measures in as many electrically heated homes as possible in the community of Hood River, Oregon. The Pacific Power HRCP planners statistically selected a special group of 320 Hood River homes that represented a cross-section of the community. The end-use loads (electric space heating, electric water heating, and woodfuel space heating) and the interior temperatures of these homes were monitored for one year before weatherization and three years after weatherization. After more than four years of submetered data collection, 220 single-family, detached homes were available for analysis in the second load study. Weather was normalized for the four heating seasons by matching one day from the pre-program year with one day from each postretrofit year.

White, D.L.; Stovall, T.K.; Tonn, B.E.

1992-02-01T23:59:59.000Z

39

Peak Power at Peak Efficiency  

Peak Power At Peak Efficiency. 21. st. Industry Growth Forum. October 2008. PJ Piper (857) 350?3100. ... At <$10/bbl oil, QM Power’s electric ...

40

The European Electricity Grid System and Winter Peak Load Stress: For how long can the european grid system survive the ever increasing demand during cold winter days?  

E-Print Network (OSTI)

The rich countries of Western Europe and its citizens benefited during at least the last 30 years from an extraordinary stable electricity grid. This stability was achieved by the european grid system and a large flexible and reliable spare power plant capacity. This system allowed a continuous demand growth during the past 10-20 years of up to a few % per year. However, partially due to this overcapacity, no new large power plants have been completed during the past 10-15 years. The obvious consequence is that the reliable spare capacity has been reduced and that a further yearly demand growth of 1-2% for electric energy can only be achieved if new power plants will be constructed soon. Data from various European countries, provided by the UCTE, indicate that the system stress during peak load times and especially during particular cold winter days is much larger than generally assumed. In fact, the latest UCTE data on reliable power capacity indicate that already during the Winter 2007/8 only a few very col...

Dittmar, Michael

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "actual peak load" 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

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

42

Predicted vs. Actual Energy Savings of Retrofitted House  

E-Print Network (OSTI)

This paper reports the results of actual energy savings and the predicted energy savings of retrofitted one-story house located in Dhahran, Saudi Arabia. The process started with modeling the house prior to retrofitting and after retrofitting. The monthly metered energy consumption is acquired from the electric company archives for seven years prior to retrofitting and recording the actual monthly energy consumption of the post retrofitting. The house model is established on DOE 2.1. Actual monthly energy consumption is used to calibrate and fine-tuning the model until the gap between actual and predicted consumption was narrowed. Then the Energy Conservation Measures (ECMs) are entered into the modeled house according to the changes in thermo-physical properties of the envelope and the changes in schedules and number of users. In order to account for those differences, electrical consumption attributed to A/C in summer was isolated and compared. The study followed the International Performance Measurement & Verification Protocol (IPMVP) in assessing the impact of energy conservation measures on actual, metered, building energy consumption. The study aimed to show the predicted savings by the simulated building model and the actual utility bills' analysis in air conditioning consumption and peak at monthly load due to building envelope.

Al-Mofeez, I.

2010-01-01T23:59:59.000Z

43

Residential implementation of critical-peak pricing of electricity  

E-Print Network (OSTI)

L.R. Modeling alternative residential peak-load electricitydemand response to residential critical peak pricing (CPP)analysis of California residential customer response to

Herter, Karen

2006-01-01T23:59:59.000Z

44

Modeling and Forecasting Electric Daily Peak Loads  

E-Print Network (OSTI)

Forecast Update As part of the Mid Term Assessment, staff is preparing a long term wholesale electricity 29, 2012 Preliminary Results of the Electricity Price Forecast Update As part of the Mid Term Assessment, staff is preparing a long term wholesale electricity market price forecast. A summary of the work

Abdel-Aal, Radwan E.

45

Improving Industrial Refrigeration System Efficiency - Actual Applications  

E-Print Network (OSTI)

This paper discusses actual design and modifications for increased system efficiency and includes reduced chilled liquid flow during part load operation, reduced condensing and increased evaporator temperatures for reduced system head, thermosiphon cycle cooling during winter operation, compressor intercooling, direct refrigeration vs. brine cooling, insulation of cold piping to reduce heat gain, multiple screw compressors for improved part load operation, evaporative condensers for reduced system head and pumping energy, and using high efficiency motors.

White, T. L.

1980-01-01T23:59:59.000Z

46

Peak Analysis: PAN  

Science Conference Proceedings (OSTI)

... display some information about the currently loaded file ... grouped ascii resolution function Load a grouped ... dialog showing multiple curve entries. ...

2011-12-07T23:59:59.000Z

47

Off peak ice storage generation  

DOE Green Energy (OSTI)

Due to the high costs associated with peak demand charges imposed by most electrical companies today, various means of shifting the peak HVAC load have been identified by the industry. This paper discusses the results of a study based upon a building site located in the high desert of the southwestern United States that evaluated ice storage as a mechanism of operating cost reductions. The discussion addresses both the seasonal and the annual cost and energy impacts of an ice storage system when used in place of an air-to-air heat pump system.

Davis, R.E.; Cerbo, F.J.

1985-01-01T23:59:59.000Z

48

A new approach for modeling the peak utility impacts from a proposed CUAC standard  

E-Print Network (OSTI)

an October-peaking load profile, rather than a more credibleof the space cooling load profiles for the months ofcommercial space cooling load profile for ECAR. This figure

LaCommare, Kristina Hamachi; Gumerman, Etan; Marnay, Chris; Chan, Peter; Coughlin, Katie

2004-01-01T23:59:59.000Z

49

Peak Underground Working Natural Gas Storage Capacity  

Gasoline and Diesel Fuel Update (EIA)

Definitions Definitions Definitions Since 2006, EIA has reported two measures of aggregate capacity, one based on demonstrated peak working gas storage, the other on working gas design capacity. Demonstrated Peak Working Gas Capacity: This measure sums the highest storage inventory level of working gas observed in each facility over the 5-year range from May 2005 to April 2010, as reported by the operator on the Form EIA-191M, "Monthly Underground Gas Storage Report." This data-driven estimate reflects actual operator experience. However, the timing for peaks for different fields need not coincide. Also, actual available maximum capacity for any storage facility may exceed its reported maximum storage level over the last 5 years, and is virtually certain to do so in the case of newly commissioned or expanded facilities. Therefore, this measure provides a conservative indicator of capacity that may understate the amount that can actually be stored.

50

Evaluation of concurrent peak responses  

SciTech Connect

This report deals with the problem of combining two or more concurrent responses which are induced by dynamic loads acting on nuclear power plant structures. Specifically, the acceptability of using the square root of the sum of the squares (SRSS) value of peak values as the combined response is investigated. Emphasis is placed on the establishment of a simplified criterion that is convenient and relatively easy to use by design engineers.

Wang, P.C.; Curreri, J.; Reich, M.

1983-01-01T23:59:59.000Z

51

Oil Peak or Panic?  

SciTech Connect

In this balanced consideration of the peak-oil controversy, Gorelick comes down on the side of the optimists.

Greene, David L [ORNL

2010-01-01T23:59:59.000Z

52

Definition: On-Peak | Open Energy Information  

Open Energy Info (EERE)

Definition Definition Edit with form History Facebook icon Twitter icon » Definition: On-Peak Jump to: navigation, search Dictionary.png On-Peak Those hours or other periods defined by NAESB business practices, contract, agreements, or guides as periods of higher electrical demand.[1] View on Wikipedia Wikipedia Definition Peak demand is used to refer to a historically high point in the sales record of a particular product. In terms of energy use, peak demand describes a period of strong consumer demand. Also Known As peak load Related Terms demand, peak demand References ↑ Glossary of Terms Used in Reliability Standards Temp Like Like You like this.Sign Up to see what your friends like. late:ISGANAttributionsmart grid,smart grid, Retrieved from "http://en.openei.org/w/index.php?title=Definition:On-Peak&oldid=502536"

53

Peaks Over Threshold Plot  

Science Conference Proceedings (OSTI)

... CAPTURE POT.OUT PEAKS OVER THRESHOLD PLOT Y17 R END OF CAPTURE . SKIP 0 READ DPST2F.DAT ITER NPOINTS THRESH R2 XR . ...

2010-12-06T23:59:59.000Z

54

Residential implementation of critical-peak pricing of electricity  

E-Print Network (OSTI)

to time-of-day electricity pricing: first empirical results.S. The trouble with electricity markets: understandingresidential peak-load electricity rate structures. Journal

Herter, Karen

2006-01-01T23:59:59.000Z

55

Residential implementation of critical-peak pricing of electricity  

E-Print Network (OSTI)

residential peak-load electricity rate structures. Journalefficiency efforts. Keywords: electricity rates, residentialmust suffer higher electricity rates to pay for the bill

Herter, Karen

2006-01-01T23:59:59.000Z

56

Residential implementation of critical-peak pricing of electricity  

E-Print Network (OSTI)

Modeling alternative residential peak-load electricity rateKeywords: electricity rates, residential electricity, demandrates be targeted to the largest residential users of electricity,

Herter, Karen

2006-01-01T23:59:59.000Z

57

Mt Peak Utility | Open Energy Information  

Open Energy Info (EERE)

Peak Utility Peak Utility Jump to: navigation, search Name Mt Peak Utility Facility Mt Peak Utility Sector Wind energy Facility Type Small Scale Wind Facility Status In Service Owner Mnt Peak Utility Energy Purchaser Mnt Peak Utility Location Midlothian TX Coordinates 32.42144978°, -97.02427357° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":32.42144978,"lon":-97.02427357,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

58

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

59

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

60

Definition: Peak Demand | Open Energy Information  

Open Energy Info (EERE)

Peak Demand Peak Demand Jump to: navigation, search Dictionary.png Peak Demand The highest hourly integrated Net Energy For Load within a Balancing Authority Area occurring within a given period (e.g., day, month, season, or year)., The highest instantaneous demand within the Balancing Authority Area.[1] View on Wikipedia Wikipedia Definition Peak demand is used to refer to a historically high point in the sales record of a particular product. In terms of energy use, peak demand describes a period of strong consumer demand. Related Terms Balancing Authority Area, energy, demand, balancing authority, smart grid References ↑ Glossary of Terms Used in Reliability Standards An inli LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ne Glossary Definition Retrieved from

Note: This page contains sample records for the topic "actual peak load" 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

PEAK READING VOLTMETER  

DOE Patents (OSTI)

An improvement in peak reading voltmeters is described, which provides for storing an electrical charge representative of the magnitude of a transient voltage pulse and thereafter measuring the stored charge, drawing oniy negligible energy from the storage element. The incoming voltage is rectified and stored in a condenser. The voltage of the capacitor is applied across a piezoelectric crystal between two parallel plates. Amy change in the voltage of the capacitor is reflected in a change in the dielectric constant of the crystal and the capacitance between a second pair of plates affixed to the crystal is altered. The latter capacitor forms part of the frequency determlning circuit of an oscillator and means is provided for indicating the frequency deviation which is a measure of the peak voltage applied to the voltmeter.

Dyer, A.L.

1958-07-29T23:59:59.000Z

62

Peak Demand Reduction from Pre-Cooling with Zone Temperature Reset in an Office Building  

E-Print Network (OSTI)

Use of Building Thermal Mass to Offset Cooling Loads. ASHRAEThe Role of Thermal Mass on the Cooling Load of Buildings.to reduce peak cooling loads with thermal mass control.

Xu, Peng

2010-01-01T23:59:59.000Z

63

Peak demand reduction from pre-cooling with zone temperature reset in an office building  

E-Print Network (OSTI)

Use of Building Thermal Mass to Offset Cooling Loads. ASHRAEThe Role of Thermal Mass on the Cooling Load of Buildings.to reduce peak cooling loads with thermal mass control.

Xu, Peng; Haves, Philip; Piette, Mary Ann; Braun, James

2004-01-01T23:59:59.000Z

64

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

65

The Year of Peak Production  

U.S. Energy Information Administration (EIA)

When world conventional oil production will peak is, of course, the bottom-line question. It has already peaked in the United States, in 1970.

66

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

67

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

68

Pilot Peak Geothermal Project | Open Energy Information  

Open Energy Info (EERE)

Pilot Peak Geothermal Project Pilot Peak Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Pilot Peak Geothermal Project Project Location Information Coordinates 38.342266666667°, -118.10361111111° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":38.342266666667,"lon":-118.10361111111,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

69

Silver Peak Geothermal Area | Open Energy Information  

Open Energy Info (EERE)

Silver Peak Geothermal Area Silver Peak Geothermal Area Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Resource Area: Silver Peak Geothermal Area Contents 1 Area Overview 2 History and Infrastructure 3 Regulatory and Environmental Issues 4 Exploration History 5 Well Field Description 6 Geology of the Area 7 Geofluid Geochemistry 8 NEPA-Related Analyses (5) 9 Exploration Activities (26) 10 References Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"TERRAIN","zoom":6,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"500px","height":"300px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.746167220142,"lon":-117.60267734528,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

70

Desert Peak Geothermal Area | Open Energy Information  

Open Energy Info (EERE)

Desert Peak Geothermal Area Desert Peak Geothermal Area Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Resource Area: Desert Peak Geothermal Area Contents 1 Area Overview 2 History and Infrastructure 3 Regulatory and Environmental Issues 4 Exploration History 5 Well Field Description 6 Geology of the Area 7 Geofluid Geochemistry 8 NEPA-Related Analyses (3) 9 Exploration Activities (8) 10 References Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"TERRAIN","zoom":6,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"500px","height":"300px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.75,"lon":-118.95,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

71

Silver Peak Geothermal Project | Open Energy Information  

Open Energy Info (EERE)

Silver Peak Geothermal Project Silver Peak Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Silver Peak Geothermal Project Project Location Information Coordinates 37.755°, -117.63472222222° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.755,"lon":-117.63472222222,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

72

Green Scheduling: Scheduling of Control Systems for Peak Power Reduction  

E-Print Network (OSTI)

approaches for load shifting and model predictive control have been proposed, we present an alternative approach to reduce the peak power for a set of control systems. The proposed model is intuitive, scalableGreen Scheduling: Scheduling of Control Systems for Peak Power Reduction Truong Nghiem, Madhur Behl

Pappas, George J.

73

How People Actually Use Thermostats  

Science Conference Proceedings (OSTI)

Residential thermostats have been a key element in controlling heating and cooling systems for over sixty years. However, today's modern programmable thermostats (PTs) are complicated and difficult for users to understand, leading to errors in operation and wasted energy. Four separate tests of usability were conducted in preparation for a larger study. These tests included personal interviews, an on-line survey, photographing actual thermostat settings, and measurements of ability to accomplish four tasks related to effective use of a PT. The interviews revealed that many occupants used the PT as an on-off switch and most demonstrated little knowledge of how to operate it. The on-line survey found that 89% of the respondents rarely or never used the PT to set a weekday or weekend program. The photographic survey (in low income homes) found that only 30% of the PTs were actually programmed. In the usability test, we found that we could quantify the difference in usability of two PTs as measured in time to accomplish tasks. Users accomplished the tasks in consistently shorter times with the touchscreen unit than with buttons. None of these studies are representative of the entire population of users but, together, they illustrate the importance of improving user interfaces in PTs.

Meier, Alan; Aragon, Cecilia; Hurwitz, Becky; Mujumdar, Dhawal; Peffer, Therese; Perry, Daniel; Pritoni, Marco

2010-08-15T23:59:59.000Z

74

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

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

Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year ActualWeather Data Title A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year ActualWeather Data Publication Type Journal Year of Publication 2013 Authors Hong, Tianzhen, Wen-Kuei Chang, and Hung-Wen Lin Keywords Actual meteorological year, Building simulation, Energy use, Peak electricity demand, Typical meteorological year, Weather data Abstract Buildings consume more than one third of the world's total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energy management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980 to 2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: 1) annual weather variation has a greater impact on the peak electricity demand than it does on energy use in buildings; 2) the simulated energy use using the TMY3 weather data is not necessarily representative of the average energy use over a long period, and the TMY3 results can be significantly higher or lower than those from the AMY data; 3) the weather impact is greater for buildings in colder climates than warmer climates; 4) the weather impact on the medium-sized office building was the greatest, followed by the large office and then the small office; and 5) simulated energy savings and peak demand reduction by energy conservation measures using the TMY3 weather data can be significantly underestimated or overestimated. It is crucial to run multi-decade simulations with AMY weather data to fully assess the impact of weather on the long-term performance of buildings, and to evaluate the energy savings potential of energy conservation measures for new and existing buildings from a life cycle perspective.

75

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

76

Peak-load pricing and thermal energy storage  

DOE Green Energy (OSTI)

Twenty papers were presented at the meeting. A separate abstract was prepared for each of 19 papers. One paper was processed previously for the Energy Data Base (EDB). Fifteen of the papers were processed for inclusion in Energy Abstracts for Policy Analysis (EAPA). (LCL)

Not Available

1979-01-01T23:59:59.000Z

77

Peak production in an oil depletion model with triangular field profiles  

E-Print Network (OSTI)

Peak production in an oil depletion model with triangular field profiles Dudley Stark School;1 Introduction M. King Hubbert [5] used curve fitting to predict that the peak of oil produc- tion in the U.S.A. would occur between 1965 and 1970. Oil production in the U.S.A. actually peaked in 1970 and has been

Stark, Dudley

78

Peak Oil, Peak Energy Mother Nature Bats Last  

E-Print Network (OSTI)

Peak Oil, Peak Energy Mother Nature Bats Last Martin Sereno 1 Feb 2011 (orig. talk: Nov 2004) #12;Oil is the Lifeblood of Industrial Civilization · 80 million barrels/day, 1000 barrels/sec, 1 cubicPods to the roads themselves) · we're not "addicted to oil" -- that's like saying a person has an "addiction

Sereno, Martin

79

Peak Oil, Peak Energy Mother Nature Bats Last  

E-Print Network (OSTI)

/Predicted (2006) Discovery, Production FSU (former Soviet Union) history Soviet Union collapse 80's oil pricePeak Oil, Peak Energy Mother Nature Bats Last Martin Sereno 1 Feb 2011 (orig. talk: Nov 2004) #12;Oil is the Lifeblood of Industrial Civilization · 80 million barrels/day, 1000 barrels/sec, 1 cubic

Sereno, Martin

80

Texas Nuclear Profile - Comanche Peak  

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

Comanche Peak" "Unit","Summer capacity (mw)","Net generation (thousand mwh)","Summer capacity factor (percent)","Type","Commercial operation date","License expiration date"...

Note: This page contains sample records for the topic "actual peak load" 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

Peak oil: diverging discursive pipelines.  

E-Print Network (OSTI)

??Peak oil is the claimed moment in time when global oil production reaches its maximum rate and henceforth forever declines. It is highly controversial as… (more)

Doctor, Jeff

2012-01-01T23:59:59.000Z

82

Desert Peak Geothermal Area | Open Energy Information  

Open Energy Info (EERE)

Desert Peak Geothermal Area Desert Peak Geothermal Area (Redirected from Desert Peak Area) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Resource Area: Desert Peak Geothermal Area Contents 1 Area Overview 2 History and Infrastructure 3 Regulatory and Environmental Issues 4 Exploration History 5 Well Field Description 6 Geology of the Area 7 Geofluid Geochemistry 8 NEPA-Related Analyses (3) 9 Exploration Activities (8) 10 References Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"TERRAIN","zoom":6,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"500px","height":"300px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.75,"lon":-118.95,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

83

GeoPeak Energy | Open Energy Information  

Open Energy Info (EERE)

GeoPeak Energy GeoPeak Energy Jump to: navigation, search Logo: GeoPeak Energy Name GeoPeak Energy Address 285 Davidson Avenue Place Somerset, New Jersey Zip 08873 Sector Solar Product Residential and Commercial PV Solar Installations Number of employees 11-50 Company Type For Profit Phone number 732-377-3700 Website http://www.geopeakenergy.com Coordinates 40.5326723°, -74.5284554° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":40.5326723,"lon":-74.5284554,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

84

Silver Peak Geothermal Area | Open Energy Information  

Open Energy Info (EERE)

Silver Peak Geothermal Area Silver Peak Geothermal Area (Redirected from Silver Peak Area) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Geothermal Resource Area: Silver Peak Geothermal Area Contents 1 Area Overview 2 History and Infrastructure 3 Regulatory and Environmental Issues 4 Exploration History 5 Well Field Description 6 Geology of the Area 7 Geofluid Geochemistry 8 NEPA-Related Analyses (5) 9 Exploration Activities (26) 10 References Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"TERRAIN","zoom":6,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"500px","height":"300px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.746167220142,"lon":-117.60267734528,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

85

Peak Oil Awareness Network | Open Energy Information  

Open Energy Info (EERE)

Awareness Network Awareness Network Jump to: navigation, search Name Peak Oil Awareness Network Place Crested Butte, Colorado Zip 81224 Website http://www.PeakOilAwarenessNet Coordinates 38.8697146°, -106.9878231° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":38.8697146,"lon":-106.9878231,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

86

Definition: Critical Peak Pricing | Open Energy Information  

Open Energy Info (EERE)

Pricing Pricing Jump to: navigation, search Dictionary.png Critical Peak Pricing When utilities observe or anticipate high wholesale market prices or power system emergency conditions, they may call critical events during a specified time period (e.g., 3 p.m.-6 p.m. on a hot summer weekday), the price for electricity during these time periods is substantially raised. Two variants of this type of rate design exist: one where the time and duration of the price increase are predetermined when events are called and another where the time and duration of the price increase may vary based on the electric grid's need to have loads reduced;[1] Related Terms electricity generation References ↑ https://www.smartgrid.gov/category/technology/critical_peak_pricing Ret LikeLike UnlikeLike

87

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

88

Peaks in Raindrop Size Distributions  

Science Conference Proceedings (OSTI)

The multipeak behavior of raindrop size distributions has been studied. Peaks have been found for distinct drop diameters: 0.7, 1.0, 1.9, and possibly 3.2 mm. The probability is about 65% that at least one of these peaks exists in an observed ...

M. Steiner; A. Waldvogel

1987-10-01T23:59:59.000Z

89

Potential of solar cooling systems for peak demand reduction  

DOE Green Energy (OSTI)

We investigated the technical feasibility of solar cooling for peak demand reduction using a building energy simulation program (DOE2.1D). The system studied was an absorption cooling system with a thermal coefficient of performance of 0.8 driven by a solar collector system with an efficiency of 50% with no thermal storage. The analysis for three different climates showed that, on the day with peak cooling load, about 17% of the peak load could be met satisfactorily with the solar-assisted cooling system without any thermal storage. A performance availability analysis indicated that the solar cooling system should be designed for lower amounts of available solar resources that coincide with the hours during which peak demand reduction is required. The analysis indicated that in dry climates, direct-normal concentrating collectors work well for solar cooling; however, in humid climates, collectors that absorb diffuse radiation work better.

Pesaran, A.A. [National Renewable Energy Lab., Golden, CO (United States); Neymark, J. [Neymark (Joel), Golden, CO (United States)

1994-11-01T23:59:59.000Z

90

Black Peak and Enchantments - CECM  

E-Print Network (OSTI)

Black Peak, North Cascades. A nice two day outing. We hiked on the Maple Pass trail, from Hwy. 20, to Heather Pass, and then on a path to Lewis lake, where ...

91

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...

92

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

93

Emcore/SunPeak Solar Power Plant | Open Energy Information  

Open Energy Info (EERE)

Emcore/SunPeak Solar Power Plant Emcore/SunPeak Solar Power Plant < Emcore Jump to: navigation, search Name Emcore/SunPeak Solar Power Plant Facility Emcore/SunPeak Sector Solar Facility Type Concentrating Photovoltaic Developer SunPeak Solar Location Albuquerque, New Mexico Coordinates 35.0844909°, -106.6511367° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":35.0844909,"lon":-106.6511367,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

94

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

95

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

96

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

97

Before Getting There: Potential and Actual Collaboration  

Science Conference Proceedings (OSTI)

In this paper we introduce the concepts of Actual and Potential Collaboration Spaces. The former applies to the space where collaborative activities are performed, while the second relates to the initial space where opportunities for collaboration are ... Keywords: Doc2U, PIÑAS, casual and informal interactions, potential and actual collaboration spaces, potential collaboration awareness

Alberto L. Morán; Jesús Favela; Ana María Martínez Enríquez; Dominique Decouchant

2002-09-01T23:59:59.000Z

98

IMPROVEMENTS TO THE RADIANT TIME SERIES METHOD COOLING LOAD CALCULATION  

E-Print Network (OSTI)

IMPROVEMENTS TO THE RADIANT TIME SERIES METHOD COOLING LOAD CALCULATION PROCEDURE By BEREKET TO THE RADIANT TIME SERIES METHOD COOLING LOAD CALCULATION PROCEDURE Dissertation Approved: Dr. Jeffrey D- Original RTSM.......................................................153 4.4.1 RTSM Peak Design Cooling Load

99

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

100

Peaks, Plans and (Persnickety) Prices  

Reports and Publications (EIA)

This presentation provides information about EIA's estimates of working gas peak storage capacity, and the development of the natural gas storage industry. Natural gas shale and the need for high deliverability storage are identified as key drivers in natural gas storage capacity development. The presentation also provides estimates of planned storage facilities through 2012.

Information Center

2010-10-28T23:59:59.000Z

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


101

A Sensitivity Study of Building Performance Using 30-Year Actual Weather  

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

Sensitivity Study of Building Performance Using 30-Year Actual Weather Sensitivity Study of Building Performance Using 30-Year Actual Weather Data Title A Sensitivity Study of Building Performance Using 30-Year Actual Weather Data Publication Type Conference Paper Year of Publication 2013 Authors Hong, Tianzhen, Wen-Kuei Chang, and Hung-Wen Lin Date Published 05/2013 Keywords Actual meteorological year, Building simulation, Energy use, Peak electricity demand, Typical meteorological year, Weather data Abstract Traditional energy performance calculated using building simulation with the typical meteorological year (TMY) weather data represents the energy performance in a typical year but not necessarily the average or typical energy performance of a building in long term. Furthermore, the simulated results do not provide the range of variations due to the change of weather, which is important in building energy management and risk assessment of energy efficiency investment. This study analyzes the weather impact on peak electric demand and energy use by building simulation using 30-year actual meteorological year (AMY) weather data for three types of office buildings at two design efficiency levels across all 17 climate zones. The simulated results from the AMY are compared to those from TMY3 to determine and analyze the differences. It was found that yearly weather variation has significant impact on building performance especially peak electric demand. Energy savings of building technologies should be evaluated using simulations with multi-decade actual weather data to fully consider investment risk and the long term performance.

102

Peak Sun Silicon Corp | Open Energy Information  

Open Energy Info (EERE)

Corp Corp Jump to: navigation, search Name Peak Sun Silicon Corp Place Carlsbad, California Zip 92008 Product US-based manufacturer of granular electronic-grade polysilicon for the PV industry. Coordinates 31.60396°, -100.641609° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":31.60396,"lon":-100.641609,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

103

Price Server System for Automated Critical Peak Pricing  

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

Price Server System for Automated Critical Peak Pricing Price Server System for Automated Critical Peak Pricing Speaker(s): David S. Watson Date: June 3, 2005 - 12:00pm Location: 90-3148 Overview of current California Energy Commission (CEC)/Demand Response Research Center (DRRC) Auto-CPP project: This summer, some select commercial CPP customers of PG&E will have the option of joining the Automated Critical Peak Pricing pilot. The pilot will have the same tariffs as standard CPP programs, but will include an added feature: automated shedding of electric loads. Through use of the Price Server System, day-ahead CPP event signals initiated by PG&E will ultimately cause electric loads to be automatically curtailed on commercial customer sites. These optional predetermined shed strategies will occur without

104

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

105

S-Band Loads for SLAC Linac  

SciTech Connect

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

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

2012-08-28T23:59:59.000Z

106

Peak Load Management of Thermal Loads Using Thermal Energy Storage Technologies  

Science Conference Proceedings (OSTI)

This Electric Power Research Institute (EPRI) technical update reviews the technology of storing energy in hot water. The report presents test results from three strategies that can be implemented using a grid connected controller to control the heating elements in a water heater. A separate section analyzes utility Supervisory Control and Data Acquisition (SCADA) data to study the impact of renewable generation on conventional generation. The report also includes a hypothetical case developed for ...

2012-12-21T23:59:59.000Z

107

METHOD OF PEAK CURRENT MEASUREMENT  

DOE Patents (OSTI)

The measurement and recording of peak electrical currents are described, and a method for utilizing the magnetic field of the current to erase a portion of an alternating constant frequency and amplitude signal from a magnetic mediums such as a magnetic tapes is presented. A portion of the flux from the current carrying conductor is concentrated into a magnetic path of defined area on the tape. After the current has been recorded, the tape is played back. The amplitude of the signal from the portion of the tape immediately adjacent the defined flux area and the amplitude of the signal from the portion of the tape within the area are compared with the amplitude of the signal from an unerased portion of the tape to determine the percentage of signal erasure, and thereby obtain the peak value of currents flowing in the conductor.

Baker, G.E.

1959-01-20T23:59:59.000Z

108

Peak shaving through resource buffering  

E-Print Network (OSTI)

Abstract. We introduce and solve a new problem inspired by energy pricing schemes in which a client is billed for peak usage. At each timeslot the system meets an energy demand through a combination of a new request, an unreliable amount of free source energy (e.g. solar or wind power), and previously received energy. The added piece of infrastructure is the battery, which can store surplus energy for future use. More generally, the demands could represent required amounts of energy, water, or any other tenable resource which can be obtained in advance and held until needed. In a feasible solution, each demand must be supplied on time, through a combination of newly requested energy, energy withdrawn from the battery, and free source. The goal is to minimize the maximum request. In the online version of this problem, the algorithm must determine each request without knowledge of future demands or free source availability, with the goal of maximizing the amount by which the peak is reduced. We give efficient optimal algorithms for the offline problem, with and without a bounded battery. We also show how to find the optimal offline battery size, given the requirement that the final battery level equals the initial battery level. Finally, we give efficient Hn-competitive algorithms assuming the peak effective demand is revealed in advance, and provide matching lower bounds. 1

Amotz Bar-noy; Matthew P. Johnson; Ou Liu

2007-01-01T23:59:59.000Z

109

Definition: Variable Peak Pricing | Open Energy Information  

Open Energy Info (EERE)

Variable Peak Pricing Variable Peak Pricing Jump to: navigation, search Dictionary.png Variable Peak Pricing Variable Peak Pricing (VPP) is a hybrid of time-of-use and real-time pricing where the different periods for pricing are defined in advance (e.g., on-peak=6 hours for summer weekday afternoon; off-peak= all other hours in the summer months), but the price established for the on-peak period varies by utility and market conditions.[1] Related Terms real-time pricing References ↑ https://www.smartgrid.gov/category/technology/variable_peak_pricing [[C LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ategory: Smart Grid Definitionssmart grid,off-peak,on-peak,smart grid, |Template:BASEPAGENAME]]smart grid,off-peak,on-peak,smart grid, Retrieved from "http://en.openei.org/w/index.php?title=Definition:Variable_Peak_Pricing&oldid=50262

110

Twin Peaks Motel Space Heating Low Temperature Geothermal Facility | Open  

Open Energy Info (EERE)

Peaks Motel Space Heating Low Temperature Geothermal Facility Peaks Motel Space Heating Low Temperature Geothermal Facility Jump to: navigation, search Name Twin Peaks Motel Space Heating Low Temperature Geothermal Facility Facility Twin Peaks Motel Sector Geothermal energy Type Space Heating Location Ouray, Colorado Coordinates 38.0227716°, -107.6714487° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[]}

111

Silver Peak, Nevada: Energy Resources | Open Energy Information  

Open Energy Info (EERE)

Peak, Nevada: Energy Resources Peak, Nevada: Energy Resources (Redirected from Silver Peak, NV) Jump to: navigation, search Name Silver Peak, Nevada Equivalent URI DBpedia GeoNames ID 5512346 Coordinates 37.7549309°, -117.6348148° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.7549309,"lon":-117.6348148,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

112

Fossil fuel-fired peak heating for geothermal greenhouses  

SciTech Connect

This report examines the capital and operating costs for fossil fuel-fired peak heating systems in geothermally (direct use) heated greenhouses. Issues covered include equipment capital costs, fuel requirements, maintenance and operating costs, system control and integration into conventional hot water greenhouse heating systems. Annual costs per square foot of greenhouse floor area are developed for three climates: Helena, MT; Klamath Falls, OR and San Bernardino, CA, for both boiler and individual unit heater peaking systems. In most applications, peaking systems sized for 60% of the peak load are able to satisfy over 95% of the annual heating requirements and cost less than $0.15 per square foot per year to operate. The propane-fired boiler system has the least cost of operation in all but Helena, MT climate.

Rafferty, K.

1996-12-01T23:59:59.000Z

113

Increased precision in sampling using regression modeling, with an application to electric load research  

SciTech Connect

A model is given for situations in survey sampling in which the characteristic of interest is an expected value of the dependent variable in a regression. For each sample unit, a regression can be used to estimate the expected value of the characteristic of interest for a given set of values of the explanatory variables. The model can be used to calculate the expected value and variance of an estimator of the population total of the expected value of the characteristic of interest, for a given set of values of the explanatory variables. The application involves the estimation of a class-load curve on the system peak day of an electric utility. The conventional method uses, for each customer in the sample, the customer's actual demand on the system peak day to estimate the customer's expected demand under the conditions of the peak day. The proposed method uses, for each customer in the sample, a model to estimate the customer's expected demand under the conditions of the peak day. The conditions are variables such as the time-of-day and weather. The variance of an estimator of a class expected load curve under the conditions of the peak day may be reduced by using the proposed method instead of the conventional method.

Oberg, K.M.

1988-01-01T23:59:59.000Z

114

SnowPeak Energy | Open Energy Information  

Open Energy Info (EERE)

it. SnowPeak Energy is a company located in Reno, Nevada . References "SnowPeak Energy" Retrieved from "http:en.openei.orgwindex.php?titleSnowPeakEnergy&oldid35121...

115

Peak Electricity Impacts of Residential Water Use  

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

Peak Electricity Impacts of Residential Water Use Title Peak Electricity Impacts of Residential Water Use Publication Type Report LBNL Report Number LBNL-5736E Year of Publication...

116

Jiminy Peak Ski Resort Wind Farm | Open Energy Information  

Open Energy Info (EERE)

Jiminy Peak Ski Resort Wind Farm Jiminy Peak Ski Resort Wind Farm Jump to: navigation, search Name Jiminy Peak Ski Resort Wind Farm Facility Jiminy Peak Ski Resort Sector Wind energy Facility Type Community Wind Facility Status In Service Owner Jiminy Peak Mountain Resort Developer Sustainable Energy Developments Energy Purchaser Jiminy Peak Mountain Resort Location Hancock MA Coordinates 42.5554°, -73.2898° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":42.5554,"lon":-73.2898,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

117

Interruptible load control for Taiwan Power Company  

SciTech Connect

Load management is the planning and implementation of those utility activities designed to influence customer use of electricity in ways that will produce desired changes in the utility's load shape. Interruptible load program is an option of load management which provides incentive rate to customers to interrupt or reduce the power demand during the system peak period or emergency condition. Therefore, how to design a proper incentive rate is the most important issue in implementing this program. This paper describes three alternatives designed for the interruptible load program, one of which was activated by Taiwan Power Company (Taipower) and some preliminary results were obtained. The effect of the interruptible load to the system peak demand reduction and the change of daily load curve for large industrial customers were analyzed. This paper estimates the avoided cost and design more appropriate incentive rate structure for interruptible load program.

Chen, C.S.; Leu, J.T. (Dept. of Electrical Engineering, National Sun Yat-Sen Univ., Kaohsiung (TW))

1990-05-01T23:59:59.000Z

118

Desert Peak II Geothermal Facility | Open Energy Information  

Open Energy Info (EERE)

II Geothermal Facility II Geothermal Facility Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Desert Peak II Geothermal Facility General Information Name Desert Peak II Geothermal Facility Facility Desert Peak II Sector Geothermal energy Location Information Location Churchill, Nevada Coordinates 39.753854931241°, -118.95378112793° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.753854931241,"lon":-118.95378112793,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

119

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma  

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

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma Reducing Peak Demand to Defer Power Plant Construction in Oklahoma Located in the heart of "Tornado Alley," Oklahoma Gas & Electric Company's (OG&E) electric grid faces significant challenges from severe weather, hot summers, and about 2% annual load growth. To better control costs and manage electric reliability under these conditions, OG&E is pursuing demand response strategies made possible by implementation of smart grid technologies, tools, and techniques from 2010-2012. The objective is to engage customers in lowering peak demand using smart technologies in homes and businesses and to achieve greater efficiencies on the distribution system. The immediate goal: To defer two 165 MW power plants currently planned for

120

Silver Peak, Nevada: Energy Resources | Open Energy Information  

Open Energy Info (EERE)

Peak, Nevada: Energy Resources Peak, Nevada: Energy Resources Jump to: navigation, search Name Silver Peak, Nevada Equivalent URI DBpedia GeoNames ID 5512346 Coordinates 37.7549309°, -117.6348148° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.7549309,"lon":-117.6348148,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

Note: This page contains sample records for the topic "actual peak load" 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

Table 13. Coal Production, Projected vs. Actual  

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

Coal Production, Projected vs. Actual" Coal Production, Projected vs. Actual" "Projected" " (million short tons)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",999,1021,1041,1051,1056,1066,1073,1081,1087,1098,1107,1122,1121,1128,1143,1173,1201,1223 "AEO 1995",,1006,1010,1011,1016,1017,1021,1027,1033,1040,1051,1066,1076,1083,1090,1108,1122,1137 "AEO 1996",,,1037,1044,1041,1045,1061,1070,1086,1100,1112,1121,1135,1156,1161,1167,1173,1184,1190 "AEO 1997",,,,1028,1052,1072,1088,1105,1110,1115,1123,1133,1146,1171,1182,1190,1193,1201,1209 "AEO 1998",,,,,1088,1122,1127.746338,1144.767212,1175.662598,1176.493652,1182.742065,1191.246948,1206.99585,1229.007202,1238.69043,1248.505981,1260.836914,1265.159424,1284.229736

122

Table 22. Energy Intensity, Projected vs. Actual  

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

Energy Intensity, Projected vs. Actual" Energy Intensity, Projected vs. Actual" "Projected" " (quadrillion Btu / real GDP in billion 2005 chained dollars)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",11.24893441,11.08565002,10.98332766,10.82852279,10.67400621,10.54170176,10.39583203,10.27184573,10.14478673,10.02575883,9.910410202,9.810812106,9.69894802,9.599821783,9.486985399,9.394733753,9.303329725,9.221322623 "AEO 1995",,10.86137373,10.75116461,10.60467959,10.42268977,10.28668187,10.14461664,10.01081222,9.883759026,9.759022105,9.627404949,9.513643295,9.400418762,9.311729546,9.226142899,9.147374752,9.071102491,8.99599906 "AEO 1996",,,10.71047701,10.59846153,10.43655044,10.27812088,10.12746866,9.9694713,9.824165152,9.714832565,9.621874334,9.532324916,9.428169355,9.32931308,9.232716414,9.170931044,9.086870061,9.019963901,8.945602337

123

A Sensitivity Study of Building Performance Using 30-Year Actual...  

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

Contacts Media Contacts A Sensitivity Study of Building Performance Using 30-Year Actual Weather Data Title A Sensitivity Study of Building Performance Using 30-Year Actual...

124

Peak Oil Food Network | Open Energy Information  

Open Energy Info (EERE)

Network Network Jump to: navigation, search Name Peak Oil Food Network Place Crested Butte, Colorado Zip 81224 Website http://www.PeakOilFoodNetwork. References Peak Oil Food Network[1] LinkedIn Connections This article is a stub. You can help OpenEI by expanding it. The Peak Oil Food Network is a networking organization located in Crested Butte, Colorado, and is open to the general public that seeks to promote the creation of solutions to the challenge of food production impacted by the peak phase of global oil production. Private citizens are encouraged to join and contribute by adding comments, writing blog posts or adding to discussions about food and oil related topics. Peak Oil Food Network can be followed on Twitter at: http://www.Twitter.com/PeakOilFoodNtwk Peak Oil Food Network on Twitter

125

STAFF FORECAST OF 2007 PEAK STAFFREPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION STAFF FORECAST OF 2007 PEAK DEMAND STAFFREPORT June 2006 CEC-400.................................................................................. 9 Sources of Forecast Error....................................................................... .................11 Tables Table 1: Revised versus September 2005 Peak Demand Forecast ......................... 2

126

Peak Underground Working Natural Gas Storage Capacity  

U.S. Energy Information Administration (EIA)

Peak Working Natural Gas Capacity. Data and Analysis from the Energy Information Administration (U.S. Dept. of Energy)

127

Determination of Hydrogen Peak Temperatures and Trapping ...  

Science Conference Proceedings (OSTI)

Presentation Title, Determination of Hydrogen Peak Temperatures and Trapping Energies of Various Lattice Defects In Iron Using Thermal Desorption ...

128

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

129

Reducing the Peak Power through Real-Time Scheduling Techniques in Cyber-Physical Energy Systems  

E-Print Network (OSTI)

], large networks of electric cars [4], and automated energy supply and distribution for town and city of electric loads in cyber-physical energy systems. The aim of the proposed approach is to achieve predictability of the activation of electric loads to guarantee an upper bound on the peak electric power

Lipari, Giuseppe

130

Table 14. Coal Production, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Coal Production, Projected vs. Actual Coal Production, Projected vs. Actual (million short tons) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 914 939 963 995 1031 1080 AEO 1983 900 926 947 974 1010 1045 1191 AEO 1984 899 921 948 974 1010 1057 1221 AEO 1985 886 909 930 940 958 985 1015 1041 1072 1094 1116 AEO 1986 890 920 954 962 983 1017 1044 1073 1097 1126 1142 1156 1176 1191 1217 AEO 1987 917 914 932 962 978 996 1020 1043 1068 1149 AEO 1989* 941 946 977 990 1018 1039 1058 1082 1084 1107 1130 1152 1171 AEO 1990 973 987 1085 1178 1379 AEO 1991 1035 1002 1016 1031 1043 1054 1065 1079 1096 1111 1133 1142 1160 1193 1234 1272 1309 1349 1386 1433 AEO 1992 1004 1040 1019 1034 1052 1064 1074 1087 1102 1133 1144 1156 1173 1201 1229 1272 1312 1355 1397 AEO 1993 1039 1043 1054 1065 1076 1086 1094 1102 1125 1136 1148 1161 1178 1204 1237 1269 1302 1327 AEO 1994 999 1021

131

Application of Building Precooling to Reduce Peak Cooling Requirements  

E-Print Network (OSTI)

A building cooling control strategy was developed and tested for a 1.4 million square foot (130,000 square meter) office building located in Hoffman Estates, IL. The goal of the control strategy was to utilize building thermal mass to limit the peak cooling load for continued building operation in the event of the loss of one of the four central chiller units. The algorithm was first developed and evaluated through simulation and then evaluated through tests on two identical buildings. The east building utilized the existing building control strategy while the west building used the precooling strategy developed for this project. Consistent with simulation predictions, the precooling control strategy successfully limited the peak load to 75 % of the cooling capacity for the west building, while the east building operated at 100 % of capacity. Precooling of the building mass provided an economical alternative to the purchase of an additional chiller unit. The estimated cost of installing an additional chiller was approximately $500,000. Computer models developed for this project also showed that precooling based upon cooling cost minimization could result in savings of approximately $25,000 per month during the peak cooling season. The building model was validated with experimental results and could be used in the development of a cost minimization strategy.

Kevin R. Keeney; James E. Braun, Ph.D.

1997-01-01T23:59:59.000Z

132

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

133

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

134

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

135

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

136

Optimization of Demand Response Through Peak Shaving  

E-Print Network (OSTI)

Jul 5, 2013 ... Optimization of Demand Response Through Peak Shaving. G. Zakeri(g.zakeri *** at*** auckland.ac.nz) D. Craigie(David.Craigie ***at*** ...

137

Application of Thermal Storage, Peak Shaving and Cogeneration for Hospitals  

E-Print Network (OSTI)

Energy costs of hospitals can be managed by employing various strategies to control peak electrical demand (KW) while at the same time providing additional security of operation in the event that an equipment failure or a disruption of power from the electric utility occurs. Some electric utilities offer their customers demand (KW) reduction rate incentives. Many hospitals have additional emergency back-up needs for electrical energy. Demand is relatively constant in many hospitals due to high internal loads. These factors coupled with the present competitive alternate fuel market and present opportunities for hospitals to significantly reduce operating costs and provide additional stand-by or back-up electric sources. This paper employs a hospital case study to define and illustrate three energy planning strategies applicable to hospitals. These strategies are peak shaving, thermal storage, cogeneration and/or paralleling with the electric utility.

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

1987-01-01T23:59:59.000Z

138

Table 23. Energy Intensity, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Energy Intensity, Projected vs. Actual Energy Intensity, Projected vs. Actual (quadrillion Btu / $Billion Nominal GDP) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 20.1 18.5 16.9 15.5 14.4 13.2 AEO 1983 19.9 18.7 17.4 16.2 15.1 14.0 9.5 AEO 1984 20.1 19.0 17.7 16.5 15.5 14.5 10.2 AEO 1985 20.0 19.1 18.0 16.9 15.9 14.7 13.7 12.7 11.8 11.0 10.3 AEO 1986 18.3 17.8 16.8 16.1 15.2 14.3 13.4 12.6 11.7 10.9 10.2 9.5 8.9 8.3 7.8 AEO 1987 17.6 17.0 16.3 15.4 14.5 13.7 12.9 12.1 11.4 8.2 AEO 1989* 16.9 16.2 15.2 14.2 13.3 12.5 11.7 10.9 10.2 9.6 9.0 8.5 8.0 AEO 1990 16.1 15.4 11.7 8.6 6.4 AEO 1991 15.5 14.9 14.2 13.6 13.0 12.5 11.9 11.3 10.8 10.3 9.7 9.2 8.7 8.3 7.9 7.4 7.0 6.7 6.3 6.0 AEO 1992 15.0 14.5 13.9 13.3 12.7 12.1 11.6 11.0 10.5 10.0 9.5 9.0 8.6 8.1 7.7 7.3 6.9 6.6 6.2 AEO 1993 14.7 13.9 13.4 12.8 12.3 11.8 11.2 10.7 10.2 9.6 9.2 8.7 8.3 7.8 7.4 7.1 6.7 6.4

139

A distributed approach to taming peak demand  

Science Conference Proceedings (OSTI)

A significant portion of all energy capacity is wasted in over-provisioning to meet peak demand. The current state-of-the-art in reducing peak demand requires central authorities to limit device usage directly, and are generally reactive. We apply techniques ...

Michael Sabolish; Ahmed Amer; Thomas M. Kroeger

2012-06-01T23:59:59.000Z

140

FINAL STAFF FORECAST OF 2008 PEAK DEMAND  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION FINAL STAFF FORECAST OF 2008 PEAK DEMAND STAFFREPORT June 2007 CEC-200 of the information in this paper. #12;Abstract This document describes staff's final forecast of 2008 peak demand demand forecasts for the respective territories of the state's three investor-owned utilities (IOUs

Note: This page contains sample records for the topic "actual peak load" 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

Storm Peak Lab Cloud Property Validation  

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

Storm Peak Lab Cloud Storm Peak Lab Cloud Property Validation Experiment (STORMVEX) Operated by the Atmospheric Radiation Measurement (ARM) Climate Research Facility for the U.S. Department of Energy, the second ARM Mobile Facility (AMF2) begins its inaugural deployment November 2010 in Steamboat Springs, Colorado, for the Storm Peak Lab Cloud Property Validation Experiment, or STORMVEX. For six months, the comprehensive suite of AMF2 instruments will obtain measurements of cloud and aerosol properties at various sites below the heavily instrumented Storm Peak Lab, located on Mount Werner at an elevation of 3220 meters. The correlative data sets that will be created from AMF2 and Storm Peak Lab will equate to between 200 and 300 in situ aircraft flight hours in liquid, mixed phase, and precipitating

142

The Boson peak in supercooled water  

E-Print Network (OSTI)

We perform extensive molecular dynamics simulations of the TIP4P/2005 model of water to investigate the origin of the Boson peak reported in experiments on supercooled water in nanoconfined pores, and in hydration water around proteins. We find that the onset of the Boson peak in supercooled bulk water coincides with the crossover to a predominantly low-density-like liquid below the Widom line $T_W$. The frequency and onset temperature of the Boson peak in our simulations of bulk water agree well with the results from experiments on nanoconfined water. Our results suggest that the Boson peak in water is not an exclusive effect of confinement. We further find that, similar to other glass-forming liquids, the vibrational modes corresponding to the Boson peak are spatially extended and are related to transverse phonons found in the parent crystal, here ice Ih.

Pradeep Kumar; K. Thor Wikfeldt; Daniel Schlesinger; Lars G. M. Pettersson; H. E. Stanley

2013-05-19T23:59:59.000Z

143

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

144

Influence of Air Conditioner Operation on Electricity Use and Peak Demand  

E-Print Network (OSTI)

Electricity demand due to occupant controlled room air conditioners in a large mater-metered apartment building is analyzed. Hourly data on the electric demand of the building and of individual air conditioners are used in analyses of annual and time-of-day peaks. Effects of occupant schedules and behavior are examined. We conclude that room air conditioners cause a sharp annual peak demand because occupants have strongly varying thresholds with respect to toleration of high indoor temperatures. However, time-or-day peaking is smoothed by air conditioning in this building due to significant off-peak operation of air conditioners by some occupants. If occupants were billed directly for electricity, off-peak use would probably diminish making the peaks more pronounced and exacerbating the utility company's load management problems. Future studies of this type in individually metered apartment buildings are recommended.

McGarity, A. E.; Feuermann, D.; Kempton, W.; Norford, L. K.

1987-01-01T23:59:59.000Z

145

Density Forecasting for Long-Term Peak Electricity Demand  

E-Print Network (OSTI)

Long-term electricity demand forecasting plays an important role in planning for future generation facilities and transmission augmentation. In a long-term context, planners must adopt a probabilistic view of potential peak demand levels. Therefore density forecasts (providing estimates of the full probability distributions of the possible future values of the demand) are more helpful than point forecasts, and are necessary for utilities to evaluate and hedge the financial risk accrued by demand variability and forecasting uncertainty. This paper proposes a new methodology to forecast the density of long-term peak electricity demand. Peak electricity demand in a given season is subject to a range of uncertainties, including underlying population growth, changing technology, economic conditions, prevailing weather conditions (and the timing of those conditions), as well as the general randomness inherent in individual usage. It is also subject to some known calendar effects due to the time of day, day of week, time of year, and public holidays. A comprehensive forecasting solution is described in this paper. First, semi-parametric additive models are used to estimate the relationships between demand and the driver variables, including temperatures, calendar effects and some demographic and economic variables. Then the demand distributions are forecasted by using a mixture of temperature simulation, assumed future economic scenarios, and residual bootstrapping. The temperature simulation is implemented through a new seasonal bootstrapping method with variable blocks. The proposed methodology has been used to forecast the probability distribution of annual and weekly peak electricity demand for South Australia since 2007. The performance of the methodology is evaluated by comparing the forecast results with the actual demand of the summer 2007–2008.

Rob J. Hyndman; Shu Fan

2009-01-01T23:59:59.000Z

146

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

147

Automated Demand Response for Critical Peak Pricing  

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

Automated Demand Response for Critical Peak Pricing Speaker(s): Naoya Motegi Date: June 9, 2005 - 12:00pm Location: Bldg. 90 California utilities have been exploring the use of...

148

Peak Underground Working Natural Gas Storage Capacity  

Gasoline and Diesel Fuel Update (EIA)

Note: 1) 'Demonstrated Peak Working Gas Capacity' is the sum of the highest storage inventory level of working gas observed in each facility over the prior 5-year period as...

149

Audit predictions of commercial lighting and plug loads  

SciTech Connect

Energy audits may be conducted at low or no cost to point our cost-effective conservation measures that could be adopted by the building owners. Alternatively, evaluating of the level of conservation measures that should be installed at utility expense. The energy and peak load savings resulting from audit programs are influenced by both the rate of adoption and the installed effectiveness of conservation measures recommended by audits. The accuracy of savings predicted by the audits has long been in question, and affects both the rate of adoption (via ''word-of-mouth'' and media communication of customer satisfaction) as well as the actual benefits to the utility for installed measures. Hence, assessing the accuracy of the audits is an essential element in the implementation and evaluation of effective audit programs designed to utilize the conservation resource. This paper presents an end-use view of audit accuracy for lighting and plug loads. Other analysis of the data from the overall building point of view has been conducted elsewhere. 3 refs., 8 figs., 3 tabs.

Pratt, R.G.

1989-05-01T23:59:59.000Z

150

Wanxiang Silicon Peak Electronics Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Wanxiang Silicon Peak Electronics Co Ltd Wanxiang Silicon Peak Electronics Co Ltd Jump to: navigation, search Name Wanxiang Silicon-Peak Electronics Co Ltd Place Kaihua, Zhejiang Province, China Zip 324300 Sector Solar Product Maker of monocrystalline silicon ingots and wafers and subsidiary of the Wanxiang Group which includes solar cell and module maker Wanxiang Solar. Coordinates 29.140209°, 118.405113° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":29.140209,"lon":118.405113,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

151

K2 Energy Solutions formerly Peak Energy Solutions | Open Energy  

Open Energy Info (EERE)

Energy Solutions formerly Peak Energy Solutions Energy Solutions formerly Peak Energy Solutions Jump to: navigation, search Name K2 Energy Solutions (formerly Peak Energy Solutions) Place Henderson, Nevada Zip 89074 Product Nevada-based designer and fabricator of Lithium Iron Phosphate (LFP) batteries for such applications as EVs, power tools and larger-scale storage. Coordinates 38.83461°, -82.140509° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":38.83461,"lon":-82.140509,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

152

Microgrid Dispatch for Macrogrid Peak-Demand Mitigation  

E-Print Network (OSTI)

Dispatch for Macrogrid Peak- Demand Mitigation NicholasDispatch for Macrogrid Peak-Demand Mitigation Nicholasdetermine whether the peak demand on the substation feeder

DeForest, Nicholas

2013-01-01T23:59:59.000Z

153

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

154

Peak Underground Working Natural Gas Storage Capacity  

Gasoline and Diesel Fuel Update (EIA)

Methodology Methodology Methodology Demonstrated Peak Working Gas Capacity Estimates: Estimates are based on aggregation of the noncoincident peak levels of working gas inventories at individual storage fields as reported monthly over a 60-month period ending in April 2010 on Form EIA-191M, "Monthly Natural Gas Underground Storage Report." The months of measurement for the peak storage volumes by facilities may differ; i.e., the months do not necessarily coincide. As such, the noncoincident peak for any region is at least as big as any monthly volume in the historical record. Data from Form EIA-191M, "Monthly Natural Gas Underground Storage Report," are collected from storage operators on a field-level basis. Operators can report field-level data either on a per reservoir basis or on an aggregated reservoir basis. It is possible that if all operators reported on a per reservoir basis that the demonstrated peak working gas capacity would be larger. Additionally, these data reflect inventory levels as of the last day of the report month, and a facility may have reached a higher inventory on a different day of the report month, which would not be recorded on Form EIA-191M.

155

A new approach for modeling the peak utility impacts from a proposed CUAC standard  

SciTech Connect

This report describes a new Berkeley Lab approach for modeling the likely peak electricity load reductions from proposed energy efficiency programs in the National Energy Modeling System (NEMS). This method is presented in the context of the commercial unitary air conditioning (CUAC) energy efficiency standards. A previous report investigating the residential central air conditioning (RCAC) load shapes in NEMS revealed that the peak reduction results were lower than expected. This effect was believed to be due in part to the presence of the squelch, a program algorithm designed to ensure changes in the system load over time are consistent with the input historic trend. The squelch applies a system load-scaling factor that scales any differences between the end-use bottom-up and system loads to maintain consistency with historic trends. To obtain more accurate peak reduction estimates, a new approach for modeling the impact of peaky end uses in NEMS-BT has been developed. The new approach decrements the system load directly, reducing the impact of the squelch on the final results. This report also discusses a number of additional factors, in particular non-coincidence between end-use loads and system loads as represented within NEMS, and their impacts on the peak reductions calculated by NEMS. Using Berkeley Lab's new double-decrement approach reduces the conservation load factor (CLF) on an input load decrement from 25% down to 19% for a SEER 13 CUAC trial standard level, as seen in NEMS-BT output. About 4 GW more in peak capacity reduction results from this new approach as compared to Berkeley Lab's traditional end-use decrement approach, which relied solely on lowering end use energy consumption. The new method has been fully implemented and tested in the Annual Energy Outlook 2003 (AEO2003) version of NEMS and will routinely be applied to future versions. This capability is now available for use in future end-use efficiency or other policy analysis that requires accurate representation of time varying load reductions.

LaCommare, Kristina Hamachi; Gumerman, Etan; Marnay, Chris; Chan, Peter; Coughlin, Katie

2004-08-01T23:59:59.000Z

156

Table 14a. Average Electricity Prices, Projected vs. Actual  

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

a. Average Electricity Prices, Projected vs. Actual" "Projected Price in Constant Dollars" " (constant dollars, cents per kilowatt-hour in ""dollar year"" specific to each AEO)"...

157

Multiple Attractor in Newton -Leipnik System, Peak to Peak dynamics and Chaos Control  

E-Print Network (OSTI)

The chaotic properties of Newton-Leipnik system are discussed from the view point of strange attractors. Previously, two strange attractors of this system were illustrated which occured from two different initial conditions under the same parameter condition. It is found that above system also exhibits multiple attractors under different parameter values but same initial condition and we have shown the existence of three other strange attractors with varying dimensionality under different parametric conditions. The properties of these attractors are then analyzed on the basis of Lyapunov exponents, power spectra, recurrence analysis and peak-to-peak dynamics. The peak-to-peak dynamics relies on the low dimensionality of the chaotic attractor and allows to approximately model the system. Peak-to-peak plot along with return-time plot are then effectively used to solve the optimal control problem of the system which reverts the system to a periodic situation.

Biswambhar Rakshit; Papri Saha; A. Roy Chowdhury

2005-01-07T23:59:59.000Z

158

Vad är Peak Oil och existerar det?; What is Peak Oil and does it exist?.  

E-Print Network (OSTI)

?? The purpose of this study is the reports of Peak Oil in Swedish newspapers. In otherwords, how do the news portray or describe the… (more)

Wälimaa, Peter

2013-01-01T23:59:59.000Z

159

Wave Modeling—Missing the Peaks  

Science Conference Proceedings (OSTI)

The paper analyzes the capability of the present wave models of properly reproducing the conditions during and at the peak of severe and extreme storms. After providing evidence that this is often not the case, the reasons for it are explored. ...

Luigi Cavaleri

2009-11-01T23:59:59.000Z

160

The Inevitable Peaking of World Oil Production  

E-Print Network (OSTI)

The era of plentiful, low-cost petroleum is approaching an end. ? Without massive mitigation the problem will be pervasive and long lasting. Oil peaking represents a liquid fuels problem, not an “energy crisis”. ? Governments will have to take the initiative on a timely basis. ? In every crisis, there are always opportunities for those that act decisively.

Robert L. Hirsch

2005-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "actual peak load" 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

Shale Gas Production: Potential versus Actual GHG Emissions  

E-Print Network (OSTI)

Shale Gas Production: Potential versus Actual GHG Emissions Francis O'Sullivan and Sergey Paltsev://globalchange.mit.edu/ Printed on recycled paper #12;1 Shale Gas Production: Potential versus Actual GHG Emissions Francis O'Sullivan* and Sergey Paltsev* Abstract Estimates of greenhouse gas (GHG) emissions from shale gas production and use

162

Lighting/HVAC interactions and their effects on annual and peak HVAC requirements in commercial buildings  

SciTech Connect

Lighting measures is one effective strategy for reducing energy use in commercial buildings. Reductions in lighting energy have secondary effects on cooling/heating energy consumption and peak HVAC requirements; in general, they increase the heating and decrease cooling requirements of a building. Net change in a building`s annual and peak energy requirements, however, is difficult to quantify and depends on building characteristics, operating conditions, climate. This paper characterizes impacts of lighting/HVAC interactions on annual and peak heating/cooling requirements of prototypical US commercial buildings through computer simulations using DOE-2.1E building energy analysis program. Ten building types of two vintages and nine climates are chosen to represent the US commercial building stock. For each combination, a prototypical building is simulated with two lighting power densities, and resultant changes in heating and cooling loads are recorded. Simple concepts of Lighting Coincidence Factors are used to describe the observed interactions between lighting and HVAC requirements. (Coincidence Factor (CF) is ratio of changes in HVAC loads to those in lighting loads, where load is either annual or peak load). The paper presents tables of lighting CF for major building types and climates. These parameters can be used for regional or national cost/benefit analyses of lighting- related policies and utility DSM programs. Using Annual CFs and typical efficiencies for heating and cooling systems, net changes in space conditioning energy use from a lighting measure can be calculated. Similarly, Demand CFs can be used to estimate the changes in HVAC sizing, which can then be converted to changes in capital outlay using standard-design curves; or they can be used to estimate coincident peak reductions for the analysis of the utility`s avoided costs. Results from use of these tables are meaningful only when they involve a significantly large number of buildings.

Sezgen, A.O.; Huang, Y.J.

1994-08-01T23:59:59.000Z

163

Definition: Critical Peak Rebates | Open Energy Information  

Open Energy Info (EERE)

Rebates Rebates Jump to: navigation, search Dictionary.png Critical Peak Rebates When utilities observe or anticipate high wholesale market prices or power system emergency conditions, they may call critical events during pre-specified time periods (e.g., 3 p.m.-6 p.m. summer weekday afternoons), the price for electricity during these time periods remains the same but the customer is refunded at a single, predetermined value for any reduction in consumption relative to what the utility deemed the customer was expected to consume.[1] Related Terms electricity generation References ↑ https://www.smartgrid.gov/category/technology/critical_peak_rebates [[C LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ategory: Smart Grid Definitions|Template:BASEPAGENAME]]

164

Residential implementation of critical-peak pricing ofelectricity  

SciTech Connect

This paper investigates how critical-peak pricing (CPP)affects households with different usage and income levels, with the goalof informing policy makers who are considering the implementation of CPPtariffs in the residential sector. Using a subset of data from theCalifornia Statewide Pricing Pilot of 2003-2004, average load changeduring summer events, annual percent bill change, and post-experimentsatisfaction ratings are calculated across six customer segments,categorized by historical usage and income levels. Findings show thathigh-use customers respond significantly more in kW reduction than dolow-use customers, while low-use customers save significantly more inpercentage reduction of annual electricity bills than do high-usecustomers results that challenge the strategy of targeting only high-usecustomers for CPP tariffs. Across income levels, average load and billchanges were statistically indistinguishable, as were satisfaction ratesresults that are compatible with a strategy of full-scale implementationof CPP rates in the residential sector. Finally, the high-use customersearning less than $50,000 annually were the most likely of the groups tosee bill increases about 5 percent saw bill increases of 10 percent ormore suggesting that any residential CPP implementation might considertargeting this customer group for increased energy efficiencyefforts.

Herter, Karen

2006-06-29T23:59:59.000Z

165

August 2010On The Portents of Peak Oil (And Other Indicators of Resource Scarcity)  

E-Print Network (OSTI)

Although economists have studied various indicators of resource scarcity (e.g., unit cost, resource rent, and market price), the phenomenon of “peaking ” has largely been ignored due to its connection to non-economic theories of resource exhaustion (the Hubbert Curve). I take a somewhat different view, one that interprets peaking as a reflection of fundamental economic determinants of an intertemporal equilibrium. From that perspective, it is reasonable to ask whether the occurrence and timing of the peak reveals anything useful regarding the state of resource exhaustion. Accordingly, I examine peaking as an indicator of resource scarcity and compare its performance to the traditional economic indicators. I find the phenomenon of peaking to be an ambiguous indicator, at best. If someone announced that the peak would arrive earlier than expected, and you believed them, you would not know whether the news was good or bad. Unfortunately, the traditional economic indicators fare no better. Their movements are driven partially by long-term trends unrelated to changes in scarcity, and partially but inconsistently driven by actual changes in scarcity. Thus, the traditional indicators provide a signal that is garbled and unreliable.

James L. Smith; Dr. James; L. Smith

2010-01-01T23:59:59.000Z

166

Space cooling demands from office plug loads  

Science Conference Proceedings (OSTI)

Undersizing space cooling systems for office buildings can result in uncomfortable and angry tenants on peak cooling days. However, oversizing wastes money because more capacity is installed than is needed, and oversized systems have a lower energy efficiency which makes operating costs higher than necessary. Oversizing can adversely affect comfort as well, because oversized systems may provide poor humidity control and large temperature variations. Correct system sizing requires estimating building heat loads accurately. This paper discusses the heat load generated by the plug load, which includes any electrical equipment that is plugged into outlets.

Komor, P.

1997-12-01T23:59:59.000Z

167

Table 8.12b Electric Noncoincident Peak Load and Capacity ...  

U.S. Energy Information Administration (EIA)

7 East Central Area Reliability Coordination Agreement (ECAR). 20 United States excluding Alaska and Hawaii. 8 ECAR, MAAC, and MAIN dissolved at the ...

168

Table 8.12a Electric Noncoincident Peak Load and Capacity ...  

U.S. Energy Information Administration (EIA)

7 East Central Area Reliability Coordination Agreement (ECAR). 20 United States excluding Alaska and Hawaii. 8 ECAR, MAAC, and MAIN dissolved at the ...

169

Coolerado Cooler Helps to Save Cooling Energy and Dollars: New Cooling Technology Targets Peak Load Reduction  

SciTech Connect

This document is about a new evaporative cooling technology that can deliver cooler supply air temperatures than either direct or indirect evaporative cooling systems, without increasing humidity. The Coolerado Cooler technology can help Federal agencies reach the energy-use reduction goals of EPAct 2005, particularly in the western United States.

Robichaud, R.

2007-06-01T23:59:59.000Z

170

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

E-Print Network (OSTI)

The energy use of the Texas Youth Commission/Texas Rehabilitation Commission (TYC/TRC) Building at Austin, Texas, was analyzed using the DOE 2.IB building energy simulation program. An analysis was made for the building as specified in the building plans and the specifications provided by the State Purchasing and General Services Commission. Operating schedules for occupancy, lighting, office equipment, and infiltration were assumed. The energy consumption of the TYC/TRC Building can be reduced with certain modifications.

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

1987-01-01T23:59:59.000Z

171

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

172

Incentivizing Advanced Load Scheduling in Smart Homes  

Science Conference Proceedings (OSTI)

In recent years, researchers have proposed numerous advanced load scheduling algorithms for smart homes with the goal of reducing the grid's peak power usage. In parallel, utilities have introduced variable rate pricing plans to incentivize residential ... Keywords: Battery, Electricity, Energy, Grid

Ye Xu, David Irwin, Prashant Shenoy

2013-11-01T23:59:59.000Z

173

Peak power tracking for a solar buck charger  

E-Print Network (OSTI)

This thesis discusses the design, implementation, and testing of a buck converter with peak power tracking. The peak power tracker uses a perturb and observe algorithm to actively track the solar panel's peak power point ...

Cohen, Jeremy Michael, M. Eng. Massachusetts Institute of Technology

2010-01-01T23:59:59.000Z

174

Table 13. Coal Production, Projected vs. Actual Projected  

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

Coal Production, Projected vs. Actual Projected (million short tons) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 999...

175

Table 14b. Average Electricity Prices, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

b. Average Electricity Prices, Projected vs. Actual Projected Price in Nominal Dollars (nominal dollars, cents per kilowatt-hour) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002...

176

Table 14b. Average Electricity Prices, Projected vs. Actual  

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

b. Average Electricity Prices, Projected vs. Actual" "Projected Price in Nominal Dollars" " (nominal dollars, cents per kilowatt-hour)" ,1993,1994,1995,1996,1997,1998,1999,2000,200...

177

Table 8. Total Natural Gas Consumption, Projected vs. Actual  

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

Natural Gas Consumption, Projected vs. Actual" "Projected" " (trillion cubic feet)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011...

178

Peak Power Reduction Strategies for the Lighting Systems in Government Buildings  

E-Print Network (OSTI)

Lighting systems are the second major contributor to the peak power demand and energy consumption in buildings after A/C systems. They account for nearly 20% of the peak power demand and 15% of the annual energy consumption. Thus energy efficient lighting systems and their smart operation can be very effective in reducing the national peak power and energy consumption, particularly for a country like Kuwait where power demand grew from 6750 MW in 2001 to 9075 MW in 2007 (MEW, 2002- 2008). This paper presents an approach developed to reduce the peak power demand in the lighting. The approach included optimum use of daylight, time of day control and delamping. The implementation of this approach for eight government buildings with occupancy of between 7:30 and 2:30 and peak power demand of 29.3 MW achieved a reduction of 2 MW in the peak power demand (around 7%). More importantly this 7% in peak load reduction and 10,628 MWh reduction in the annual energy consumption was achieved without any added cost. Also, the paper includes recommendations for retrofitting cost effective energy efficient lighting systems and implementation of more effective control.

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

2010-01-01T23:59:59.000Z

179

Combi Systems for Low Load homes  

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

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

180

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

Open Energy Info (EERE)

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

Note: This page contains sample records for the topic "actual peak load" 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

The Year of Peak Production - Energy Information Administration  

U.S. Energy Information Administration (EIA)

When world conventional oil production will peak is, of course, the bottom-line question. It has already peaked in the United States, in 1970.

182

Estimates of Peak Underground Working Gas Storage Capacity in the ...  

U.S. Energy Information Administration (EIA)

Estimates of Peak Underground Working Gas Storage Capacity in the United States, 2009 Update The aggregate peak capacity for U.S. underground natural gas storage is ...

183

Magnetotellurics At Silver Peak Area (DOE GTP) | Open Energy...  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak Area Exploration Technique Magnetotellurics Activity Date Usefulness not indicated DOE-funding Unknown...

184

Multispectral Imaging At Silver Peak Area (DOE GTP) | Open Energy...  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Multispectral Imaging At Silver Peak Area (DOE GTP) Exploration...

185

Development Wells At Silver Peak Area (DOE GTP) | Open Energy...  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Development Wells At Silver Peak Area (DOE GTP) Exploration Activity...

186

Ground Magnetics At Silver Peak Area (DOE GTP) | Open Energy...  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Ground Magnetics At Silver Peak Area (DOE GTP) Exploration Activity...

187

Microgrid Dispatch for Macrogrid Peak-Demand Mitigation  

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

Dispatch for Macrogrid Peak-Demand Mitigation Title Microgrid Dispatch for Macrogrid Peak-Demand Mitigation Publication Type Conference Proceedings Refereed Designation Refereed...

188

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

189

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

190

Peak Population: Timing and Influences of Peak Energy on the World and the United States  

E-Print Network (OSTI)

Peak energy is the notion that the world’s total production of usable energy will reach a maximum value and then begin an inexorable decline. Ninety-two percent of the world’s energy is currently derived from the non-renewable sources (oil, coal, natural gas and nuclear). As each of these non-renewable sources individually peaks in production, we can see total energy production peak. The human population is tightly correlated with global energy production, as agriculture and material possessions are energy intensive. It follows that peak energy should have a significant effect on world population. Using a set of mathematical models, including M King Hubbert’s oil peak mathematics, we prepared three models. The first approached the peak energy and population problem from the point of view of a “black-box” homogeneous world. The second model divides the world into ten major regions to study the global heterogeneity of the peak energy and population question. Both of these models include various scenarios for how the world population will develop based on available energy and per capita consumption of that energy. The third model examines energy and climate change within the forty-eight contiguous American states in order to identify some of the “best” and some of the “worst” states in which to live in the year 2050. The black box model indicates that peak energy will occur in 2026 at a maximum production of 104.1 billion barrels of oil equivalent (BBOE). Total energy production in 2011 was 92.78 BBOE. Three scenarios of different energy consumption rates suggest a peak world population occurring between 2026 and 2036, at 7.6-8.3 billion. The regional model indicates that even as each region protects its own energy resources, most of the world will reach peak energy by 2030, and world populations peak between 7.5 and 9 billion. A certain robustness in our conclusion is warranted as similar numbers were obtained via two separate approaches. The third model used several different parameters in order to ascertain that, in general, states that are projected to slow towards flat-line population growth and to become milder due to climate change such as Rhode Island, New York and Ohio are far more suitable with regard to an energy limited world than states that are projected to grow in population as well as become less mild due to climate change such as Texas, Arizona and Nevada. Each of these models in its own way foreshadows necessary changes that the world will experience as the 21st century progresses. The economies of the world have been, and continue to be, built on energy. When energy production is unable to continue growing it must follow that economies will be unable to grow. As the world approaches and passes peak energy, the standard of living in the less developed areas of the world cannot improve without sacrifices being made in the developed world.

Warner, Kevin 1987-

2012-12-01T23:59:59.000Z

191

Load Management - A Better Way  

E-Print Network (OSTI)

Ohio Edison Company serves about 800,000 customers in Ohio and Pennsylvania, making it one of the 20 largest electric utilities in the nation. The 'cost of service' concept has been basic to rate design throughout the history of the company, and is evident today as the demand related charges have escalated in recent rate cases reflecting the higher costs of installing new generating facilities at today's high construction and financing costs. This paper will describe one of the many applications of load management techniques which has enabled the company to shift well over 100,000 kilowatts of customer load from the on-peak period to the off-peak period in the last four to five years. This is helping delay the need for new plants and allows existing plants to be more fully utilized, resulting in lower costs to customers who use their electric service wisely and possibly lower rate increases in the future than would have been required otherwise.

Easley, J. F.

1982-01-01T23:59:59.000Z

192

Dehumidification and cooling loads from ventilation air  

SciTech Connect

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

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

1997-11-01T23:59:59.000Z

193

Using DER in Transmission-Constrained Urban Load Pockets  

Science Conference Proceedings (OSTI)

Urban load centers are characterized by their dense population, environmental constraints, as well as transmission-constrained electricity delivery. They also have potentially high infrastructure investment costs for distribution system investments to meet peak load growth. This report looks at seven areas in the United States that have been identified as transmission-constrained load pockets, focusing on opportunities for using distributed energy resources (DER).

2007-12-17T23:59:59.000Z

194

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

195

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

196

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

197

New Peak Moisture Design Data in the 1997 ASHRAE Handbook of Fundamentals  

E-Print Network (OSTI)

Chapter 26 of the 1997 edition of the Handbook of Fundamentals published by ASHRAE (American Society of Heating, Refrigerating and Air Conditioning Engineers) contains climatic design data that has been completely revised, recalculated and expanded. Designers of air conditioning systems for hot and humid climates will be pleased to note that, for the first time, the chapter contains values for peak moisture conditions. This is in sharp contrast to older editions, which contained only the average moisture during periods of peak dry bulb temperatures. The new data show that using earlier, temperature-based data for humidity design underestimates the true peak moisture loads by 30 to 50% depending on the humidity control level in the space. This paper explains the new data elements and suggests some of its potential implications for engineers designing air conditioning systems for hot and humid climates.

Harriman, L.

1998-01-01T23:59:59.000Z

198

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 ...

199

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

200

Shale gas production: potential versus actual greenhouse gas emissions*  

E-Print Network (OSTI)

Shale gas production: potential versus actual greenhouse gas emissions* Francis O Environ. Res. Lett. 7 (2012) 044030 (6pp) doi:10.1088/1748-9326/7/4/044030 Shale gas production: potential gas (GHG) emissions from shale gas production and use are controversial. Here we assess the level

Note: This page contains sample records for the topic "actual peak load" 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

LBNL-6280E A Fresh Look at Weather Impact on Peak Electricity Demand and  

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

280E 280E A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30- Year Actual Weather Data Tianzhen Hong 1 , Wen-kuei Chang 2 , Hung-Wen Lin 2 1 Environmental Energy Technologies Division 2 Green Energy and Environment Laboratories, Industrial Technology Research Institute, Taiwan, ROC May 2013 This work was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, the U.S.-China Clean Energy Research Center for Building Energy Efficiency, of the U.S. Department of Energy under Contract No. DE-AC02-

202

The Impact of Residential Air Conditioner Charging and Sizing on Peak Electrical Demand  

E-Print Network (OSTI)

Electric utilities have had a number of air conditioner rebate and maintenance programs for many years. The purpose of these programs was to improve the efficiency of the stock of air conditioning equipment and provide better demand-side management. This paper examines the effect of refrigerant charging (proper servicing of the equipment), system sizing, and efficiency on the steady-state, coincident peak utility demand of a residential central air conditioning system. The study is based on the results of laboratory tests of a three-ton, capillary tube expansion, split-system air conditioner, system capacity and efficiency data available from manufacturer's literature, and assumptions about relative sizing of the equipment to cooling load on a residence. A qualitative discussion is provided concerning the possible impacts of transient operation and total energy use on utility program decisions. The analysis indicates that proper sizing of the unit is the largest factor affecting energy demand of the three factors (sizing, charging, and efficiency) studied in this paper. For typical oversizing of units to cooling loads in houses, both overcharging and undercharging showed significant negative impact on peak demand. The impacts of SEER changes in utility peak demand were found to be virtually independent of oversizing. For properly sized units, there was a small peak benefit to higher efficiency air conditioners.

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

1992-05-01T23:59:59.000Z

203

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

204

Coproduction of peaking fuels in IGCC power plants: a process-screening study. Final report  

SciTech Connect

This study evaluated and compared various options for processing a portion of the medium BTU gas (MBG) produced in a coal gasification combined cycle (GCC) power plant to produce a fuel which might be suitable for peaking or intermediate load use. Two alternate objectives were investigated in separate phases of the study. The first phase examined options for processing and storing a fuel which could be withdrawn and used in absorbing daily load swings in power generation demand. The second phase investigated options for meeting the seasonal peaks in gas demand of a joint gas/electric utility by converting a portion of the MBG to substitute natural gas (SNG) during the months of peak gas demand. For each phase, process designs and cost estimates were completed for several cases, based on both Texaco and BGC-Lurgi Slagging Gasification Technology. For the purposes of this screening study, it was assumed that the peaking fuel production facilities are incremental to the base GCC plant. The costs to produce and store the peaking fuel, excluding the cost of the MBG feed, were calculated by the revenue requirement method. Various sensitivities were evaluated on case assumptions, including a sensitivity to MBG feed value. For daily peaking use, the co-production of methanol and electricity by the ''once-through'' scheme (as studied in EPRI Report AP-2212) proved the most attractive option. Other options which produced gaseous fuels (hydrogen or SNG) for on-site storage were at least 30% more costly. Storage of SNG in an existing natural gas pipeline system was at least 10% higher, excluding pipeline charges. For seasonal SNG production there was little difference between the options studied, within the accuracy of the estimates. 13 refs., 72 tabs.

Shenoy, T.A.; Solomon, J.; O'Brien, V.J.

1986-07-01T23:59:59.000Z

205

SmartCap: Flattening Peak Electricity Demand in Smart Homes Sean Barker, Aditya Mishra, David Irwin, Prashant Shenoy, and Jeannie Albrecht  

E-Print Network (OSTI)

SmartCap: Flattening Peak Electricity Demand in Smart Homes Sean Barker, Aditya Mishra, David Irwin--Flattening household electricity demand reduces generation costs, since costs are disproportionately affected by peak demands. While the vast majority of household electrical loads are interactive and have little scheduling

Shenoy, Prashant

206

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

207

SunPeak Solar LLC | Open Energy Information  

Open Energy Info (EERE)

SunPeak Solar LLC Jump to: navigation, search Name SunPeak Solar LLC Place Palm Desert, California Zip 92260 Product US project developer and asset manager, focussing on PV...

208

Automated Critical Peak Pricing Field Tests: Program Description and Results  

E-Print Network (OSTI)

Usage: The total effective energy charge for usage duringUsage: The total effective energy charge for usage duringtotal effective TOU energy rates through offsetting summer on-peak and part-peak rate credits for usage

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Xu, Peng

2006-01-01T23:59:59.000Z

209

A Multimethod analysis of the Phenomenon of Peak-Oil.  

E-Print Network (OSTI)

??El concepto de Peak-Oil (el cénit del petróleo) es complejo y a menudo malentendido. Después de aclarar que el Peak-Oil es tanto un problema de… (more)

Kerschner, Christian

2012-01-01T23:59:59.000Z

210

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

211

Modeling-Computer Simulations At Desert Peak Area (Wisian & Blackwell...  

Open Energy Info (EERE)

navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Modeling-Computer Simulations At Desert Peak Area (Wisian & Blackwell, 2004) Exploration Activity...

212

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

213

Scaling distributed energy storage for grid peak reduction  

Science Conference Proceedings (OSTI)

Reducing peak demand is an important part of ongoing smart grid research efforts. To reduce peak demand, utilities are introducing variable rate electricity prices. Recent efforts have shown how variable rate pricing can incentivize consumers to use ... Keywords: battery, electricity, energy, grid, peak shaving

Aditya Mishra, David Irwin, Prashant Shenoy, Ting Zhu

2013-01-01T23:59:59.000Z

214

SNAP fuel temperature peaking with cusps in coolant channel  

SciTech Connect

Reactor Fuel Elements--temperature peaking in SNAP due to surrounding rods; systems for nuclear auxiliary power (SNAP)--reactor fuel temperataure peaking due to surrounding fuel rods; temeprature--calculations of peaking of, in SNAP fuel due to sourround fuel rods.

Treuenfels, E. W.

1963-07-19T23:59:59.000Z

215

Distributed Battery Control for Peak Power Shaving in Datacenters  

E-Print Network (OSTI)

Distributed Battery Control for Peak Power Shaving in Datacenters Baris Aksanli and Tajana Rosing to shave peak power demands. Our novel distributed battery control design has no performance impact, reduces the peak power needs, and accurately estimates and maximizes the battery lifetime. We demonstrate

Simunic, Tajana

216

Attachment Implementation Procedures to Report Deferred, Actual, and Required Maintenance  

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

Draft July 9, 2009 Draft July 9, 2009 1 Attachment Implementation Procedures to Report Deferred, Actual, and Required Maintenance On Real Property 1. The following is the FY 2009 implementation procedures for the field offices/sites to determine and report deferred maintenance on real property as required by the Statement of Federal Financial Accounting Standards (SFFAS) No. 6, Accounting for Property, Plant, and Equipment (PP&E) and DOE Order 430.1B, Real Property Asset Management (RPAM). a. This document is intended to assist field offices/sites in consistently and accurately applying the appropriate methods to determine and report deferred maintenance estimates and reporting of annual required and actual maintenance costs. b. This reporting satisfies the Department's obligation to recognize and record deferred

217

Table 12. Total Coal Consumption, Projected vs. Actual  

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

Coal Consumption, Projected vs. Actual" Coal Consumption, Projected vs. Actual" "Projected" " (million short tons)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",920,928,933,938,943,948,953,958,962,967,978,990,987,992,1006,1035,1061,1079 "AEO 1995",,935,940,941,947,948,951,954,958,963,971,984,992,996,1002,1013,1025,1039 "AEO 1996",,,937,942,954,962,983,990,1004,1017,1027,1033,1046,1067,1070,1071,1074,1082,1087 "AEO 1997",,,,948,970,987,1003,1017,1020,1025,1034,1041,1054,1075,1086,1092,1092,1099,1104 "AEO 1998",,,,,1009,1051,1043.875977,1058.292725,1086.598145,1084.446655,1089.787109,1096.931763,1111.523926,1129.833862,1142.338257,1148.019409,1159.695312,1162.210815,1180.029785

218

Table 4. Total Petroleum Consumption, Projected vs. Actual  

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

Petroleum Consumption, Projected vs. Actual Petroleum Consumption, Projected vs. Actual Projected (million barrels) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 6450 6566 6643 6723 6811 6880 6957 7059 7125 7205 7296 7377 7446 7523 7596 7665 7712 7775 AEO 1995 6398 6544 6555 6676 6745 6822 6888 6964 7048 7147 7245 7337 7406 7472 7537 7581 7621 AEO 1996 6490 6526 6607 6709 6782 6855 6942 7008 7085 7176 7260 7329 7384 7450 7501 7545 7581 AEO 1997 6636 6694 6826 6953 7074 7183 7267 7369 7461 7548 7643 7731 7793 7833 7884 7924 AEO 1998 6895 6906 7066 7161 7278 7400 7488 7597 7719 7859 7959 8074 8190 8286 8361 AEO 1999 6884 7007 7269 7383 7472 7539 7620 7725 7841 7949 8069 8174 8283 8351 AEO 2000 7056 7141 7266 7363 7452 7578 7694 7815 7926 8028 8113 8217 8288

219

Table 6. Petroleum Net Imports, Projected vs. Actual Projected  

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

Petroleum Net Imports, Projected vs. Actual Petroleum Net Imports, Projected vs. Actual Projected (million barrels) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 2935 3201 3362 3504 3657 3738 3880 3993 4099 4212 4303 4398 4475 4541 4584 4639 4668 4672 AEO 1995 2953 3157 3281 3489 3610 3741 3818 3920 4000 4103 4208 4303 4362 4420 4442 4460 4460 AEO 1996 3011 3106 3219 3398 3519 3679 3807 3891 3979 4070 4165 4212 4260 4289 4303 4322 4325 AEO 1997 3099 3245 3497 3665 3825 3975 4084 4190 4285 4380 4464 4552 4617 4654 4709 4760 AEO 1998 3303 3391 3654 3713 3876 4053 4137 4298 4415 4556 4639 4750 4910 4992 5087 AEO 1999 3380 3442 3888 4022 4153 4238 4336 4441 4545 4652 4780 4888 4999 5073 AEO 2000 3599 3847 4036 4187 4320 4465 4579 4690 4780 4882 4968 5055 5113

220

Tropical Africa: Calculated Actual Aboveground Live Biomass in Open and  

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

Calculated Actual Aboveground Live Biomass in Open and Calculated Actual Aboveground Live Biomass in Open and Closed Forests (1980) image Brown, S., and G. Gaston. 1996. Tropical Africa: Land Use, Biomass, and Carbon Estimates For 1980. ORNL/CDIAC-92, NDP-055. Carbon Dioxide Information Analysis Center, U.S. Department of Energy, Oak Ridge National Laboratory, Oak Ridge, Tennessee, U.S.A. More Maps Land Use Maximum Potential Biomass Density Area of Closed Forests (By Country) Mean Biomass of Closed Forests (By Country) Area of Open Forests (By Country) Mean Biomass of Open Forests (By County) Percent Forest Cover (By Country) Total Forest Biomass (By Country) Population Density - 1990 (By Administrative Unit) Population Density - 1980 (By Administrative Unit) Population Density - 1970 (By Administrative Unit) Population Density - 1960 (By Administrative Unit)

Note: This page contains sample records for the topic "actual peak load" 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

Table 7b. Natural Gas Wellhead Prices, Projected vs. Actual  

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

b. Natural Gas Wellhead Prices, Projected vs. Actual" b. Natural Gas Wellhead Prices, Projected vs. Actual" "Projected Price in Nominal Dollars" " (nominal dollars per thousand cubic feet)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",1.983258692,2.124739238,2.26534793,2.409252566,2.585728477,2.727400662,2.854942053,2.980927152,3.13861755,3.345819536,3.591100993,3.849544702,4.184279801,4.510016556,4.915074503,5.29147351,5.56022351,5.960471854 "AEO 1995",,1.891706924,1.998384058,1.952818035,2.064227053,2.152302174,2.400016103,2.569033816,2.897681159,3.160088567,3.556344605,3.869033816,4.267391304,4.561932367,4.848599034,5.157246377,5.413405797,5.660917874 "AEO 1996",,,1.630674532,1.740334763,1.862956911,1.9915856,2.10351261,2.194934146,2.287655669,2.378991658,2.476043002,2.589847464,2.717610782,2.836870306,2.967124845,3.117719429,3.294003735,3.485657428,3.728419409

222

Attachment Implementation Procedures to Report Deferred, Actual, and Required Maintenance  

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

Final July 01, 2010 Final July 01, 2010 1 Attachment Implementation Procedures to Report Deferred, Actual, and Required Maintenance On Real Property 1. The following is the FY 2010 implementation procedures for the field offices/sites to determine and report deferred maintenance on real property as required by the Statement of Federal Financial Accounting Standards (SFFAS) No. 6, Accounting for Property, Plant, and Equipment (PP&E) and DOE Order 430.1B, Real Property Asset Management (RPAM). a. This document is intended to assist field offices/sites in consistently and accurately applying the appropriate methods to determine and report deferred maintenance estimates and reporting of annual required and actual maintenance costs. b. This reporting satisfies the Department's obligation to recognize and record deferred

223

Table 5. Domestic Crude Oil Production, Projected vs. Actual  

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

Domestic Crude Oil Production, Projected vs. Actual Domestic Crude Oil Production, Projected vs. Actual Projected (million barrels) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 2508 2373 2256 2161 2088 2022 1953 1891 1851 1825 1799 1781 1767 1759 1778 1789 1807 1862 AEO 1995 2402 2307 2205 2095 2037 1967 1953 1924 1916 1905 1894 1883 1887 1887 1920 1945 1967 AEO 1996 2387 2310 2248 2172 2113 2062 2011 1978 1953 1938 1916 1920 1927 1949 1971 1986 2000 AEO 1997 2362 2307 2245 2197 2143 2091 2055 2033 2015 2004 1997 1989 1982 1975 1967 1949 AEO 1998 2340 2332 2291 2252 2220 2192 2169 2145 2125 2104 2087 2068 2050 2033 2016 AEO 1999 2340 2309 2296 2265 2207 2171 2141 2122 2114 2092 2074 2057 2040 2025 AEO 2000 2193 2181 2122 2063 2016 1980 1957 1939 1920 1904 1894 1889 1889

224

An efficient load model for analyzing demand side management impacts  

SciTech Connect

The main objective of implementing Demand Side Management (DSM) in power systems is to change the utility's load shape--i.e. changes in the time pattern and magnitude of utility's load. Changing the load shape as a result of demand side activities could change the peak load, base load and/or energy demand. Those three variables have to be explicitly modeled into the load curve for properly representing the effects of demand side management. The impact of DSM will be manifested as higher or lower reliability levels. This paper presents an efficient technique to model the system load such that the impact of demand side management on the power system can be easily and accurately evaluated. The proposed technique to model the load duration curve will facilitate the representation of DSM impacts on loss-of-load probability, energy not served and energy consumption. This will provide an analytical method to study the impact of DSM on capacity requirements. So far iterative methods have been applied to study these impacts. The proposed analytical method results in a faster solution with higher accuracy. It takes only 18 seconds on an 80486 PC to solve each case study involving different peak and base loads, and energy use.

Rahman, S.; Rinaldy (Virginia Polytechnic Inst. and State Univ., Blacksburg, VA (United States))

1993-08-01T23:59:59.000Z

225

Climate Change Impacts on Residential and Commercial Loads in the Western U.S. Grid  

SciTech Connect

This report presents a multi-disciplinary 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 cooling load in 10 major cities across the Western United States and Canada. Our results have shown that by the mid-century, building yearly energy consumption and peak load will increase in the Southwest. Moreover, the peak load months will spread out to not only the summer months but also spring and autumn months. The Pacific Northwest will experience more hot days in the summer months. The penetration of the air conditioning (a/c) system in this area is likely to increase significantly over the years. As a result, some locations in the Pacific Northwest may be shifted from winter peaking to summer peaking. Overall, the Western U.S. grid may see more simultaneous peaks across the North and South in summer months. Increased cooling load will result in a significant increase in the motor load, which consumes more reactive power and requires stronger voltage support from the grid. This study suggests an increasing need for the industry to implement new technology to increase the efficiency of temperature-sensitive loads and apply proper protection and control to prevent possible adverse impacts of a/c motor loads.

Lu, Ning; Taylor, Zachary T.; Jiang, Wei; Xie, YuLong; Leung, Lai R.; Correia, James; Wong, Pak C.; Mackey, Patrick S.; Paget, Maria L.

2008-09-30T23:59:59.000Z

226

Transmission and Distribution Benefits of Direct Load Control: Seattle City Light and Snohomish Public Utility District Pilot Project Evaluations  

Science Conference Proceedings (OSTI)

Two residential direct load control programs in the Puget Sound region have reduced peak loads at both the system as well as the local transmission and distribution levels. This report presents program load impact results estimated using metered and disaggregated end-use load data. Included is a detailed description of participants' attitudes toward the programs and their experiences with program implementation.

1994-05-21T23:59:59.000Z

227

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

228

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

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

Promoting Employment Across Kansas (PEAK) (Kansas) Promoting Employment Across Kansas (PEAK) (Kansas) Promoting Employment Across Kansas (PEAK) (Kansas) < Back Eligibility Agricultural Commercial Construction Developer Fuel Distributor Industrial Utility Savings Category Alternative Fuel Vehicles Hydrogen & Fuel Cells Buying & Making Electricity Water Home Weatherization Solar Wind Program Info State Kansas Program Type Corporate Tax Incentive Provider Commerce Promoting Employment Across Kansas (PEAK) allows for the retention of employee payroll withholding taxes for qualified companies or third parties performing services on behalf of such companies. This program offers qualified companies the ability to retain 95 percent of their payroll withholding tax for up to five to seven years. PEAK is available to new

229

www.eia.gov  

U.S. Energy Information Administration (EIA)

Table 8.6.A. Noncoincident Peak Load by North American Electric Reliability Corporation Assessment Area, 2001 - 2011, Actual Summer Peak Load ...

230

Nuclear Hydrogen for Peak Electricity Production and Spinning Reserve  

Science Conference Proceedings (OSTI)

Nuclear energy can be used to produce hydrogen. The key strategic question is this: ''What are the early markets for nuclear hydrogen?'' The answer determines (1) whether there are incentives to implement nuclear hydrogen technology today or whether the development of such a technology could be delayed by decades until a hydrogen economy has evolved, (2) the industrial partners required to develop such a technology, and (3) the technological requirements for the hydrogen production system (rate of production, steady-state or variable production, hydrogen purity, etc.). Understanding ''early'' markets for any new product is difficult because the customer may not even recognize that the product could exist. This study is an initial examination of how nuclear hydrogen could be used in two interconnected early markets: the production of electricity for peak and intermediate electrical loads and spinning reserve for the electrical grid. The study is intended to provide an initial description that can then be used to consult with potential customers (utilities, the Electric Power Research Institute, etc.) to better determine the potential real-world viability of this early market for nuclear hydrogen and provide the starting point for a more definitive assessment of the concept. If this set of applications is economically viable, it offers several unique advantages: (1) the market is approximately equivalent in size to the existing nuclear electric enterprise in the United States, (2) the entire market is within the utility industry and does not require development of an external market for hydrogen or a significant hydrogen infrastructure beyond the utility site, (3) the technology and scale match those of nuclear hydrogen production, (4) the market exists today, and (5) the market is sufficient in size to justify development of nuclear hydrogen production techniques independent of the development of any other market for hydrogen. These characteristics make it an ideal early market for nuclear hydrogen.

Forsberg, C.W.

2005-01-20T23:59:59.000Z

231

ESS 2012 Peer Review - PV Plus Storage for Simultaneous Voltage Smoothing and Peak Shifting - Steve Willard, PNM  

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

Mexico (PNM) - Mexico (PNM) - PV Plus Storage for Simultaneous Voltage PV Plus Storage for Simultaneous Voltage Smoothing and Peak Shifting DOE Peer Review Steve Willard, P.E. September 26, 2012 Project Goals - Develop an even more Beneficial Renewable Resource - Transferable Nationwide Renewable Resource Transferable Nationwide *Created a dispatchable, renewables-based peaking resource *Combined PV and storage at a substation targeting 15% peak-load reduction D t ti bi ti th t i lt l iti t lt l l *Demonstrating a combination that can simultaneously mitigate voltage-level fluctuations as well as enable load shifting *Developed power system models (baseline and projected), and cost/benefit economic models eco o c ode s *Generating, collecting, analyzing and sharing resultant data *Enabling distributed solutions that reduce GHG emissions through the

232

Back-Up/ Peak Shaving Fuel Cell System  

SciTech Connect

This Final Report covers the work executed by Plug Power from 8/11/03 – 10/31/07 statement of work for Topic 2: advancing the state of the art of fuel cell technology with the development of a new generation of commercially viable, stationary, Back-up/Peak-Shaving fuel cell systems, the GenCore II. The Program cost was $7.2 M with the Department of Energy share being $3.6M and Plug Power’s share being $3.6 M. The Program started in August of 2003 and was scheduled to end in January of 2006. The actual program end date was October of 2007. A no cost extension was grated. The Department of Energy barriers addressed as part of this program are: Technical Barriers for Distributed Generation Systems: o Durability o Power Electronics o Start up time Technical Barriers for Fuel Cell Components: o Stack Material and Manufacturing Cost o Durability o Thermal and water management Background The next generation GenCore backup fuel cell system to be designed, developed and tested by Plug Power under the program is the first, mass-manufacturable design implementation of Plug Power’s GenCore architected platform targeted for battery and small generator replacement applications in the telecommunications, broadband and UPS markets. The next generation GenCore will be a standalone, H2 in-DC-out system. In designing the next generation GenCore specifically for the telecommunications market, Plug Power is teaming with BellSouth Telecommunications, Inc., a leading industry end user. The final next generation GenCore system is expected to represent a market-entry, mass-manufacturable and economically viable design. The technology will incorporate: • A cost-reduced, polymer electrolyte membrane (PEM) fuel cell stack tailored to hydrogen fuel use • An advanced electrical energy storage system • A modular, scalable power conditioning system tailored to market requirements • A scaled-down, cost-reduced balance of plant (BOP) • Network Equipment Building Standards (NEBS), UL and CE certifications.

Staudt, Rhonda L.

2008-05-28T23:59:59.000Z

233

Talking Points from ACEEE Report U072: Estimating Peak Demand Impacts of Energy Efficiency Programs: A National Review of Practices and Experience  

E-Print Network (OSTI)

1. Demand-side management is a proven way to affect customer energy use a. Over 2 decades of experience with programs b. Two broad program categories: i. Energy efficiency programs primarily seek to reduce customer energy use (kilowatthours--kWh) on a permanent basis through the installation of energy-efficient technologies. ii. Load management generally focuses on either curtailing or shifting demand (kilowatts--kW) away from high cost, peak demand periods. Demand-response programs are really a type of load management---more “market-based” c. Over 2 decades of program evaluation experience, too. d. Are new drivers for peak demand reduction: reliability; volatile markets and high costs of new generation, transmission and distribution; reducing negative environmental impacts. 2. Peak load management and energy efficiency a. Are clearly overlaps, but peak demand impacts of energy efficiency programs have generally not been program priorities---which, in turn, has affected evaluation approaches and

unknown authors

2007-01-01T23:59:59.000Z

234

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

Science Conference Proceedings (OSTI)

A correlation between the peak luminosity and the peak energy has been found by Yonetoku et al. as L{sub p} {proportional_to}E{sup 2.0}{sub p,i} for 11 pre-Swift long gamma-ray bursts (GRBs). In this study, for a greatly expanded sample of 148 long GRBs in the Swift era, we find that the correlation still exists, but most likely with a slightly different power-law index, i.e., L{sub p} {proportional_to} E{sup 1.7}{sub p,i}. In addition, we have collected 17 short GRBs with necessary data. We find that the correlation of L{sub p} {proportional_to} E{sup 1.7}{sub p,i} also exists for this sample of short events. It is argued that the radiation mechanism of both long and short GRBs should be similar, i.e., of quasi-thermal origin caused by the photosphere, with the dissipation occurring very near the central engine. Some key parameters of the process are constrained. Our results suggest that the radiation processes of both long and short bursts may be dominated by thermal emission, rather than by the single synchrotron radiation. This might put strong physical constraints on the theoretical models.

Zhang, Z. B.; Chen, D. Y. [Department of Physics, College of Sciences, Guizhou University, Guiyang 550025 (China); Huang, Y. F., E-mail: sci.zbzhang@gzu.edu.cn, E-mail: hyf@nju.edu.cn [Department of Astronomy, Nanjing University, Nanjing 210093 (China)

2012-08-10T23:59:59.000Z

235

A control system for improved battery utilization in a PV-powered peak-shaving system  

SciTech Connect

Photovoltaic (PV) power systems offer the prospect of allowing a utility company to meet part of the daily peak system load using a renewable resource. Unfortunately, some utilities have peak system- load periods that do not match the peak production hours of a PV system. Adding a battery energy storage system to a grid-connected PV power system will allow dispatching the stored solar energy to the grid at the desired times. Batteries, however, pose system limitations in terms of energy efficiency, maintenance, and cycle life. A new control system has been developed, based on available PV equipment and a data acquisition system, that seeks to minimize the limitations imposed by the battery system while maximizing the use of PV energy. Maintenance requirements for the flooded batteries are reduced, cycle life is maximized, and the battery is operated over an efficient range of states of charge. This paper presents design details and initial performance results on one of the first installed control systems of this type.

Palomino, E [Salt River Project, Phoenix, AZ (United States); Stevens, J. [Sandia National Labs., Albuquerque, NM (United States); Wiles, J. [New Mexico State Univ., Las Cruces, NM (United States). Southwest Technology Development Inst.

1996-08-01T23:59:59.000Z

236

Analysis of the need for intermediate and peaking technologies in the year 2000. Final report  

SciTech Connect

This analysis was conducted to assess the impact of load management on the future need for intermediate- and peak-generating technologies (IPTs) such as combustion turbines, pumped storage, and cycling coal plants. There would be a reduced need for IPTs if load-management activities such as time-of-use pricing, together with customer-owned energy-storage devices, hot-water-heater controls, and interruptible service can economically remove most of the variation from electric power demands. The objective of this analysis is to assess the need for IPTs in an uncertain future, which will probably include load management and time-differentiated electricity prices. The analysis is exploratory in nature and broad in scope. It does not attempt to predict the future or to model precisely the technical characteristics or economic desirability of load management. Rather, its purpose is to provide research and development planners with some basic insights into the order of magnitude of possible hourly demand shifts on a regional basis and to determine the impact of load management on daily and seasonal variations in electricity demand.

Barrager, S.M.; Campbell, G.L.

1980-04-01T23:59:59.000Z

237

Steam Trap Testing and Evaluation: An Actual Plant Case Study  

E-Print Network (OSTI)

With rising steam costs and a high failure rate on the Joliet Plants standard steam trap, a testing and evaluation program was begun to find a steam trap that would work at Olin-Joliet. The basis was to conduct the test on the actual process equipment and that a minimum life be achieved. This paper deals with the history of the steam system/condensate systems, the setting up of the testing procedure, which traps were and were not tested and the results of the testing program to date.

Feldman, A. L.

1981-01-01T23:59:59.000Z

238

Analysis of the need for intermediate and peaking technologies in the year 2000  

DOE Green Energy (OSTI)

This analysis was conducted to assess the impact of load management on the future need for intermediate- and peak-generating technologies (IPTs) such as combustion turbines, pumped storage, and cycling coal plants. There will be a reduced need for IPTs if load-management activities such as time-of-use pricing, together with customer-owned energy-storage devices, hot-water-heater controls, and interruptible service, can economically remove most of the variation from electric-power demands. Therefore, the analysis assesses the need for IPTs in an uncertain future, which will probably include load management and time-differentiated electricity prices. Section 2 provides a condensed description of the models used in the analysis. (Details and data sets are contained in the appendixes.) Results of sensitivities on growth rates, model parameters, and appliance saturations are discussed in Section 3, which also contains the analysis of the potential impacts of customer energy storage, appliance control, and time-of-use pricing. The future need for intermediate and peaking technologies is analyzed in Section 4.

Barrager, S.M.; Campbell, G.L.

1980-04-01T23:59:59.000Z

239

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

240

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

Note: This page contains sample records for the topic "actual peak load" 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

Table 16. Total Energy Consumption, Projected vs. Actual  

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

Total Energy Consumption, Projected vs. Actual" Total Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",88.02,89.53,90.72,91.73,92.71,93.61,94.56,95.73,96.69,97.69,98.89,100,100.79,101.7,102.7,103.6,104.3,105.23 "AEO 1995",,89.21,89.98,90.57,91.91,92.98,93.84,94.61,95.3,96.19,97.18,98.38,99.37,100.3,101.2,102.1,102.9,103.88 "AEO 1996",,,90.6,91.26,92.54,93.46,94.27,95.07,95.94,96.92,97.98,99.2,100.38,101.4,102.1,103.1,103.8,104.69,105.5 "AEO 1997",,,,92.64,93.58,95.13,96.59,97.85,98.79,99.9,101.2,102.4,103.4,104.7,105.8,106.6,107.2,107.9,108.6 "AEO 1998",,,,,94.68,96.71,98.61027527,99.81855774,101.254303,102.3907928,103.3935776,104.453476,105.8160553,107.2683716,108.5873566,109.8798981,111.0723877,112.166893,113.0926208

242

Table 7a. Natural Gas Wellhead Prices, Projected vs. Actual  

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

a. Natural Gas Wellhead Prices, Projected vs. Actual" a. Natural Gas Wellhead Prices, Projected vs. Actual" "Projected Price in Constant Dollars" " (constant dollars per thousand cubic feet in ""dollar year"" specific to each AEO)" ,"AEO Dollar Year",1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",1992,1.9399,2.029,2.1099,2.1899,2.29,2.35,2.39,2.42,2.47,2.55,2.65,2.75,2.89,3.01,3.17,3.3,3.35,3.47 "AEO 1995",1993,,1.85,1.899,1.81,1.87,1.8999,2.06,2.14,2.34,2.47,2.69,2.83,3.02,3.12,3.21,3.3,3.35,3.39 "AEO 1996",1994,,,1.597672343,1.665446997,1.74129355,1.815978527,1.866241336,1.892736554,1.913619637,1.928664207,1.943216205,1.964540124,1.988652706,2.003382921,2.024799585,2.056392431,2.099974155,2.14731431,2.218094587

243

Table 14a. Average Electricity Prices, Projected vs. Actual  

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

a. Average Electricity Prices, Projected vs. Actual a. Average Electricity Prices, Projected vs. Actual Projected Price in Constant Dollars (constant dollars, cents per kilowatt-hour in "dollar year" specific to each AEO) AEO Dollar Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1995 1993 6.80 6.80 6.70 6.70 6.70 6.70 6.70 6.80 6.80 6.90 6.90 6.90 7.00 7.00 7.10 7.10 7.20 AEO 1996 1994 7.09 6.99 6.94 6.93 6.96 6.96 6.96 6.97 6.98 6.97 6.98 6.95 6.95 6.94 6.96 6.95 6.91 AEO 1997 1995 6.94 6.89 6.90 6.91 6.86 6.84 6.78 6.73 6.66 6.60 6.58 6.54 6.49 6.48 6.45 6.36

244

Table 4. Total Petroleum Consumption, Projected vs. Actual  

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

Total Petroleum Consumption, Projected vs. Actual" Total Petroleum Consumption, Projected vs. Actual" "Projected" " (million barrels)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",6449.55,6566.35,6643,6723.3,6810.9,6880.25,6956.9,7059.1,7124.8,7205.1,7296.35,7376.65,7446,7522.65,7595.65,7665,7712.45,7774.5 "AEO 1995",,6398.45,6544.45,6555.4,6675.85,6745.2,6821.85,6887.55,6964.2,7048.15,7146.7,7245.25,7336.5,7405.85,7471.55,7537.25,7581.05,7621.2 "AEO 1996",,,6489.7,6526.2,6606.5,6708.7,6781.7,6854.7,6942.3,7008,7084.65,7175.9,7259.85,7329.2,7383.95,7449.65,7500.75,7544.55,7581.05 "AEO 1997",,,,6635.7,6694.1,6825.5,6953.25,7073.7,7183.2,7267.15,7369.35,7460.6,7548.2,7643.1,7730.7,7792.75,7832.9,7884,7924.15

245

Table 9. Natural Gas Production, Projected vs. Actual  

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

Natural Gas Production, Projected vs. Actual" Natural Gas Production, Projected vs. Actual" "Projected" " (trillion cubic feet)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",17.71,17.68,17.84,18.12,18.25,18.43,18.58,18.93,19.28,19.51,19.8,19.92,20.13,20.18,20.38,20.35,20.16,20.19 "AEO 1995",,18.28,17.98,17.92,18.21,18.63,18.92,19.08,19.2,19.36,19.52,19.75,19.94,20.17,20.28,20.6,20.59,20.88 "AEO 1996",,,18.9,19.15,19.52,19.59,19.59,19.65,19.73,19.97,20.36,20.82,21.25,21.37,21.68,22.11,22.47,22.83,23.36 "AEO 1997",,,,19.1,19.7,20.17,20.32,20.54,20.77,21.26,21.9,22.31,22.66,22.93,23.38,23.68,23.99,24.25,24.65 "AEO 1998",,,,,18.85,19.06,20.34936142,20.27427673,20.60257721,20.94442177,21.44076347,21.80969238,22.25416183,22.65365219,23.176651,23.74545097,24.22989273,24.70069313,24.96691322

246

Table 7a. Natural Gas Wellhead Prices, Projected vs. Actual  

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

a. Natural Gas Wellhead Prices, Projected vs. Actual a. Natural Gas Wellhead Prices, Projected vs. Actual Projected Price in Constant Dollars (constant dollars per thousand cubic feet in "dollar year" specific to each AEO) AEO Dollar Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 1992 1.94 2.03 2.11 2.19 2.29 2.35 2.39 2.42 2.47 2.55 2.65 2.75 2.89 3.01 3.17 3.30 3.35 3.47 AEO 1995 1993 1.85 1.90 1.81 1.87 1.90 2.06 2.14 2.34 2.47 2.69 2.83 3.02 3.12 3.21 3.30 3.35 3.39 AEO 1996 1994 1.60 1.67 1.74 1.82 1.87 1.89 1.91 1.93 1.94 1.96 1.99 2.00 2.02 2.06 2.10 2.15 2.22

247

Table 10. Natural Gas Net Imports, Projected vs. Actual  

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

Natural Gas Net Imports, Projected vs. Actual" Natural Gas Net Imports, Projected vs. Actual" "Projected" " (trillion cubic feet)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",2.02,2.4,2.66,2.74,2.81,2.85,2.89,2.93,2.95,2.97,3,3.16,3.31,3.5,3.57,3.63,3.74,3.85 "AEO 1995",,2.46,2.54,2.8,2.87,2.87,2.89,2.9,2.9,2.92,2.95,2.97,3,3.03,3.19,3.35,3.51,3.6 "AEO 1996",,,2.56,2.75,2.85,2.88,2.93,2.98,3.02,3.06,3.07,3.09,3.12,3.17,3.23,3.29,3.37,3.46,3.56 "AEO 1997",,,,2.82,2.96,3.16,3.43,3.46,3.5,3.53,3.58,3.64,3.69,3.74,3.78,3.83,3.87,3.92,3.97 "AEO 1998",,,,,2.95,3.19,3.531808376,3.842532873,3.869043112,3.894513845,3.935930967,3.976293564,4.021911621,4.062207222,4.107616425,4.164502144,4.221304417,4.277039051,4.339964867

248

Table 12. Total Coal Consumption, Projected vs. Actual Projected  

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

Total Coal Consumption, Projected vs. Actual Total Coal Consumption, Projected vs. Actual Projected (million short tons) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 920 928 933 938 943 948 953 958 962 967 978 990 987 992 1006 1035 1061 1079 AEO 1995 935 940 941 947 948 951 954 958 963 971 984 992 996 1002 1013 1025 1039 AEO 1996 937 942 954 962 983 990 1004 1017 1027 1033 1046 1067 1070 1071 1074 1082 1087 AEO 1997 948 970 987 1003 1017 1020 1025 1034 1041 1054 1075 1086 1092 1092 1099 1104 AEO 1998 1009 1051 1044 1058 1087 1084 1090 1097 1112 1130 1142 1148 1160 1162 1180 AEO 1999 1040 1075 1092 1109 1113 1118 1120 1120 1133 1139 1150 1155 1156 1173 AEO 2000 1053 1086 1103 1124 1142 1164 1175 1184 1189 1194 1199 1195 1200 AEO 2001 1078 1112 1135 1153 1165 1183 1191 1220 1228 1228 1235 1240

249

Table 22. Total Carbon Dioxide Emissions, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Total Carbon Dioxide Emissions, Projected vs. Actual Total Carbon Dioxide Emissions, Projected vs. Actual (million metric tons) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 AEO 1983 AEO 1984 AEO 1985 AEO 1986 AEO 1987 AEO 1989* AEO 1990 AEO 1991 AEO 1992 AEO 1993 5009 5053 5130 5207 5269 5335 5401 5449 5504 5562 5621 5672 5724 5771 5819 5867 5918 5969 AEO 1994 5060 5130 5185 5240 5287 5335 5379 5438 5482 5529 5599 5658 5694 5738 5797 5874 5925 AEO 1995 5137 5174 5188 5262 5309 5361 5394 5441.3 5489.0 5551.3 5621.0 5679.7 5727.3 5775.0 5841.0 5888.7 AEO 1996 5182 5224 5295 5355 5417 5464 5525 5589 5660 5735 5812 5879 5925 5981 6030 AEO 1997 5295 5381 5491 5586 5658 5715 5781 5863 5934 6009 6106 6184 6236 6268 AEO 1998 5474 5621 5711 5784 5893 5957 6026 6098 6192 6292 6379 6465 6542 AEO 1999 5522 5689 5810 5913 5976 6036 6084 6152 6244 6325 6418 6493 AEO 2000

250

Table 16. Total Electricity Sales, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Electricity Sales, Projected vs. Actual Electricity Sales, Projected vs. Actual (billion kilowatt-hours) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 2364 2454 2534 2626 2708 2811 AEO 1983 2318 2395 2476 2565 2650 2739 3153 AEO 1984 2321 2376 2461 2551 2637 2738 3182 AEO 1985 2317 2360 2427 2491 2570 2651 2730 2808 2879 2949 3026 AEO 1986 2363 2416 2479 2533 2608 2706 2798 2883 2966 3048 3116 3185 3255 3324 3397 AEO 1987 2460 2494 2555 2622 2683 2748 2823 2902 2977 3363 AEO 1989* 2556 2619 2689 2760 2835 2917 2994 3072 3156 3236 3313 3394 3473 AEO 1990 2612 2689 3083 3488.0 3870.0 AEO 1991 2700 2762 2806 2855 2904 2959 3022 3088 3151 3214 3282 3355 3427 3496 3563 3632 3704 3776 3846 3916 AEO 1992 2746 2845 2858 2913 2975 3030 3087 3146 3209 3276 3345 3415 3483 3552 3625 3699 3774 3847 3921 AEO 1993 2803 2840 2893 2946 2998 3052 3104 3157 3214 3271 3327

251

Table 5. Domestic Crude Oil Production, Projected vs. Actual  

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

Domestic Crude Oil Production, Projected vs. Actual" Domestic Crude Oil Production, Projected vs. Actual" "Projected" " (million barrels)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011 "AEO 1994",2507.55,2372.5,2255.7,2160.8,2087.8,2022.1,1952.75,1890.7,1850.55,1825,1799.45,1781.2,1766.6,1759.3,1777.55,1788.5,1806.75,1861.5 "AEO 1995",,2401.7,2306.8,2204.6,2095.1,2036.7,1967.35,1952.75,1923.55,1916.25,1905.3,1894.35,1883.4,1887.05,1887.05,1919.9,1945.45,1967.35 "AEO 1996",,,2387.1,2310.45,2248.4,2171.75,2113.35,2062.25,2011.15,1978.3,1952.75,1938.15,1916.25,1919.9,1927.2,1949.1,1971,1985.6,2000.2 "AEO 1997",,,,2361.55,2306.8,2244.75,2197.3,2142.55,2091.45,2054.95,2033.05,2014.8,2003.85,1996.55,1989.25,1981.95,1974.65,1967.35,1949.1

252

Direct quantum communication without actual transmission of the message qubits  

E-Print Network (OSTI)

Recently an orthogonal state based protocol of direct quantum communication without actual transmission of particles is proposed by Salih \\emph{et al.}{[}Phys. Rev. Lett. \\textbf{110} (2013) 170502{]} using chained quantum Zeno effect. As the no-transmission of particle claim is criticized by Vaidman {[}arXiv:1304.6689 (2013){]}, the condition (claim) of Salih \\emph{et al.} is weaken here to the extent that transmission of particles is allowed, but transmission of the message qubits (the qubits on which the secret information is encoded) is not allowed. Remaining within this weaker condition it is shown that there exists a large class of quantum states, that can be used to implement an orthogonal state based protocol of secure direct quantum communication using entanglement swapping, where actual transmission of the message qubits is not required. The security of the protocol originates from monogamy of entanglement. As the protocol can be implemented without using conjugate coding its security is independent of non-commutativity.

Chitra Shukla; Anirban Pathak

2013-07-23T23:59:59.000Z

253

Peak power identification on power bumps during test application  

Science Conference Proceedings (OSTI)

Peak power during test can seriously impact circuit performance as well as the power safety for both CUT and tester. In this paper, we propose a method of layout-aware weighted switching activity identification flow that evaluates peak current/power ... Keywords: CMOS device, peak power identification, power bumps, test application, layout-aware weighted switching activity identification flow, dynamic power model, parasitic capacitance, resistance network, power bus, power delivery path, IR-drop, commercial power sign-off analysis tool

Wei Zhao; M. Tehranipoor

2011-07-01T23:59:59.000Z

254

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

SciTech Connect

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

United States. Bonneville Power Administration.

1991-09-01T23:59:59.000Z

255

Sustained Peak Low Cycle Fatigue: The Role of Coatings  

Science Conference Proceedings (OSTI)

The growth process continued by a combined process of oxidation and creep. ... of a model developed for crack growth during sustained peak low cycle fatigue.

256

Peak-shape functions for Neutron Time of Flight  

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

(Draft)-dec. 2003 Introduction A reorganization of the subroutines calculating the peak shape function and derivatives for time of flight neutron powder diffraction has been...

257

Flexible Coal: Evolution from Baseload to Peaking Plant (Brochure...  

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

the transformation of power systems Flexible Coal Evolution from Baseload to Peaking Plant The experience cited in this paper is from a generating station with multiple units...

258

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

Open Energy Info (EERE)

Page Edit History Facebook icon Twitter icon Gas Flux Sampling At Desert Peak Area (Lechler And Coolbaugh, 2007) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home...

259

Flow Shop Scheduling with Peak Power Consumption Constraints  

E-Print Network (OSTI)

enterprises; for example, many energy providers use time-of-use (TOU) tariffs ( e.g. Babu and Ashok. 2008). Peak power consumption has also received some ...

260

Poster: Thermal Energy Storage for Electricity Peak-demand Mitigation...  

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

Poster: Thermal Energy Storage for Electricity Peak-demand Mitigation: A Solution in Developing and Developed World Alike Title Poster: Thermal Energy Storage for Electricity...

Note: This page contains sample records for the topic "actual peak load" 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

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma  

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

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma Located in the heart of "Tornado Alley," Oklahoma Gas & Electric Company's (OG&E) electric grid faces significant...

262

Structural Analysis of the Desert Peak-Brady Geothermal Fields...  

Open Energy Info (EERE)

mapping, delineation of Tertiary strata, analysis of faults and folds, and a new gravity survey have elucidated the structural controls on the Desert Peak and Brady...

263

Evaluation of Peak Heat Release Rates in Electrical Cabinet Fires  

Science Conference Proceedings (OSTI)

The purpose of this report is to reanalyze the peak heat release rates (HRRs) from fires occurring in electrical cabinets of nuclear power plants.

2012-02-23T23:59:59.000Z

264

Flow shop scheduling with peak power consumption constraints  

E-Print Network (OSTI)

Mar 29, 2012 ... In particular, we consider a flow shop scheduling problem with a restriction on peak power consumption, in addition to the traditional ...

265

Peak Oil: Knowledge, Attitudes, and Programming Activities in Public Health.  

E-Print Network (OSTI)

??Peak Oil, or the world reaching the maximum rate of petroleum extraction, poses risks such as depletion of energy resources, amplification of existing threats of… (more)

Tuckerman, Samantha Lynn

2012-01-01T23:59:59.000Z

266

Geothermometry At Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Geothermometry At Silver Peak Area (DOE GTP) Exploration Activity Details Location...

267

Microgrid Dispatch for Macrogrid Peak-Demand Mitigation  

E-Print Network (OSTI)

N ATIONAL L ABORATORY Microgrid Dispatch for Macrogrid Peak-equal opportunity employer. Microgrid Dispatch for Macrogridutility customers, microgrid solutions – the installation of

DeForest, Nicholas

2013-01-01T23:59:59.000Z

268

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

269

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

270

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

271

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

272

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

273

Nonlinear excitations in DNA: Aperiodic models vs actual genome sequences  

E-Print Network (OSTI)

We study the effects of the sequence on the propagation of nonlinear excitations in simple models of DNA in which we incorporate actual DNA sequences obtained from human genome data. We show that kink propagation requires forces over a certain threshold, a phenomenon already found for aperiodic sequences [F. Dom\\'\\i nguez-Adame {\\em et al.}, Phys. Rev. E {\\bf 52}, 2183 (1995)]. For forces below threshold, the final stop positions are highly dependent on the specific sequence. The results of our model are consistent with the stick-slip dynamics of the unzipping process observed in experiments. We also show that the effective potential, a collective coordinate formalism introduced by Salerno and Kivshar [Phys. Lett. A {\\bf 193}, 263 (1994)] is a useful tool to identify key regions in DNA that control the dynamical behavior of large segments. Additionally, our results lead to further insights in the phenomenology observed in aperiodic systems.

Sara Cuenda; Angel Sanchez

2004-07-02T23:59:59.000Z

274

ENSO Impacts on Peak Wind Gusts in the United States  

Science Conference Proceedings (OSTI)

Changes in the peak wind gust magnitude in association with the warm and cold phases of the El Niño–Southern Oscillation (ENSO) are identified over the contiguous United States. All calculations of the peak wind gust are differences in the ...

Jesse Enloe; James J. O'Brien; Shawn R. Smith

2004-04-01T23:59:59.000Z

275

Energy solutions for CO2 emission peak and subsequent decline  

E-Print Network (OSTI)

Energy solutions for CO2 emission peak and subsequent decline Edited by Leif Sønderberg Petersen and Hans Larsen Risø-R-1712(EN) September 2009 Proceedings Risø International Energy Conference 2009 #12;Editors: Leif Sønderberg Petersen and Hans Larsen Title: Energy solutions for CO2 emission peak

276

Diesel Rig Mechanical Peaking System Based on Flywheel Storage Technolgy  

Science Conference Proceedings (OSTI)

Flywheel energy storage technology is an emerging energy storage technology, there is a great development in recent years promising energy storage technology, with a large energy storage, high power, no pollution, use of broad, simple maintenance, enabling ... Keywords: Flywheel energy storage technology, mechanical peaking, diesel rig, peak motor

Shuguang Liu, Jia Wang

2012-07-01T23:59:59.000Z

277

A practical approach for electricity load forecasting  

E-Print Network (OSTI)

Abstract—This paper is a continuation of our daily energy peak load forecasting approach using our modified network which is part of the recurrent networks family and is called feed forward and feed back multi context artificial neural network (FFFB-MCANN). The inputs to the network were exogenous variables such as the previous and current change in the weather components, the previous and current status of the day and endogenous variables such as the past change in the loads. Endogenous variable such as the current change in the loads were used on the network output. Experiment shows that using endogenous and exogenous variables as inputs to the FFFB-MCANN rather than either exogenous or endogenous variables as inputs to the same network produces better results. Experiments show that using the change in variables such as weather components and the change in the past load as inputs to the FFFB-MCANN rather than the absolute values for the weather components and past load as inputs to the same network has a dramatic impact and produce better accuracy.

T. Rashid; T. Kechadi

2005-01-01T23:59:59.000Z

278

Actual Scale MOX Powder Mixing Test for MOX Fuel Fabrication Plant in Japan  

Science Conference Proceedings (OSTI)

Japan Nuclear Fuel Ltd. (hereafter, JNFL) promotes a program of constructing a MOX fuel fabrication plant (hereafter, J-MOX) to fabricate MOX fuels to be loaded in domestic light water reactors. Since Japanese fiscal year (hereafter, JFY) 1999, JNFL, to establish the technology for a smooth start-up and the stable operation of J-MOX, has executed an evaluation test for technology to be adopted at J-MOX. JNFL, based on a consideration that J-MOX fuel fabrication comes commercial scale production, decided an introduction of MIMAS technology into J-MOX main process, from powder mixing through pellet sintering, well recognized as mostly important to achieve good quality product of MOX fuel, since it achieves good results in both fuel production and actual reactor irradiation in Europe, but there is one difference that JNFL is going to use Japanese typical plutonium and uranium mixed oxide powder converted with the micro-wave heating direct de-nitration technology (hereafter, MH-MOX) but normal PuO{sub 2} of European MOX fuel fabricators. Therefore, in order to evaluate the suitability of the MH-MOX powder for the MIMAS process, JNFL manufactured small scale test equipment, and implemented a powder mixing evaluation test up until JFY 2003. As a result, the suitability of the MH-MOX powder for the MIMAS process was positively evaluated and confirmed It was followed by a five-years test named an 'actual test' from JFY 2003 to JFY 2007, which aims at demonstrating good operation and maintenance of process equipment as well as obtaining good quality of MOX fuel pellets. (authors)

Osaka, Shuichi; Kurita, Ichiro; Deguchi, Morimoto [Japan Nuclear Fuel Ltd., 4-108, Aza okitsuke, oaza obuchi rokkasyo-mura, kamikita-gun, Aomori 039-3212 (Japan); Ito, Masanori [Japan Atomic Energy Agency, 4-33 Muramatu, Tokai-mura, Ibaraki 319-1194 (Japan); Goto, Masakazu [Nuclear Fuel Industries, Ltd., 14-10, Mita 3-chome, Minato-ku, Tokyo 108-0073 (Japan)

2007-07-01T23:59:59.000Z

279

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...

280

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...

Note: This page contains sample records for the topic "actual peak load" 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

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...

282

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...

283

Table 17. Total Delivered Residential Energy Consumption, Projected vs. Actual  

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

Total Delivered Residential Energy Consumption, Projected vs. Actual Total Delivered Residential Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 10.3 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.5 10.5 10.5 10.5 10.5 10.6 10.6 AEO 1995 11.0 10.8 10.8 10.8 10.8 10.8 10.8 10.7 10.7 10.7 10.7 10.7 10.7 10.7 10.8 10.8 10.9 AEO 1996 10.4 10.7 10.7 10.7 10.8 10.8 10.9 10.9 11.0 11.2 11.2 11.3 11.4 11.5 11.6 11.7 11.8 AEO 1997 11.1 10.9 11.1 11.1 11.2 11.2 11.2 11.3 11.4 11.5 11.5 11.6 11.7 11.8 11.9 12.0 AEO 1998 10.7 11.1 11.2 11.4 11.5 11.5 11.6 11.7 11.8 11.9 11.9 12.1 12.1 12.2 12.3 AEO 1999 10.5 11.1 11.3 11.3 11.4 11.5 11.5 11.6 11.6 11.7 11.8 11.9 12.0 12.1 AEO 2000 10.7 10.9 11.0 11.1 11.2 11.3 11.4 11.5 11.6 11.7 11.8 11.9 12.0

284

Table 2. Real Gross Domestic Product, Projected vs. Actual  

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

Real Gross Domestic Product, Projected vs. Actual Real Gross Domestic Product, Projected vs. Actual Projected Real GDP Growth Trend (cumulative average percent growth in projected real GDP from first year shown for each AEO) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 3.1% 3.2% 2.9% 2.8% 2.7% 2.7% 2.6% 2.6% 2.6% 2.5% 2.5% 2.5% 2.4% 2.4% 2.4% 2.4% 2.3% 2.3% AEO 1995 3.7% 2.8% 2.5% 2.7% 2.7% 2.6% 2.6% 2.5% 2.5% 2.5% 2.5% 2.4% 2.4% 2.4% 2.3% 2.3% 2.2% AEO 1996 2.6% 2.2% 2.5% 2.5% 2.5% 2.5% 2.4% 2.4% 2.4% 2.4% 2.4% 2.3% 2.3% 2.2% 2.2% 2.2% 1.6% AEO 1997 2.1% 1.9% 2.0% 2.2% 2.3% 2.3% 2.2% 2.2% 2.2% 2.2% 2.2% 2.2% 2.2% 2.1% 2.1% 1.5% AEO 1998 3.4% 2.9% 2.6% 2.5% 2.4% 2.4% 2.3% 2.3% 2.3% 2.3% 2.3% 2.3% 2.3% 2.2% 1.8% AEO 1999 3.4% 2.5% 2.5% 2.4% 2.4% 2.4% 2.3% 2.4% 2.4% 2.4% 2.4% 2.4% 2.4% 1.8% AEO 2000 3.8% 2.9% 2.7% 2.6% 2.6% 2.6% 2.6% 2.6% 2.5% 2.5%

285

Table 7. Petroleum Net Imports, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Net Imports, Projected vs. Actual Petroleum Net Imports, Projected vs. Actual (million barrels per day) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 7.58 7.45 7.12 6.82 6.66 7.09 AEO 1983 5.15 5.44 5.73 5.79 5.72 5.95 6.96 AEO 1984 4.85 5.11 5.53 5.95 6.31 6.59 8.65 AEO 1985 4.17 4.38 4.73 4.93 5.36 5.72 6.23 6.66 7.14 7.39 7.74 AEO 1986 5.15 5.38 5.46 5.92 6.46 7.09 7.50 7.78 7.96 8.20 8.47 8.74 9.04 9.57 9.76 AEO 1987 5.81 6.04 6.81 7.28 7.82 8.34 8.71 8.94 8.98 10.01 AEO 1989* 6.28 6.84 7.49 7.96 8.53 8.83 9.04 9.28 9.60 9.64 9.75 10.02 10.20 AEO 1990 7.20 7.61 9.13 9.95 11.02 AEO 1991 7.28 7.25 7.34 7.48 7.72 8.10 8.57 9.09 9.61 10.07 10.51 11.00 11.44 11.72 11.86 12.11 12.30 12.49 12.71 12.91 AEO 1992 6.86 7.42 7.88 8.16 8.55 8.80 9.06 9.32 9.50 9.80 10.17 10.35 10.56 10.61 10.85 11.00 11.15 11.29 11.50 AEO 1993 7.25 8.01 8.49 9.06

286

Table 7b. Natural Gas Wellhead Prices, Projected vs. Actual  

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

b. Natural Gas Wellhead Prices, Projected vs. Actual b. Natural Gas Wellhead Prices, Projected vs. Actual Projected Price in Nominal Dollars (nominal dollars per thousand cubic feet) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 1.98 2.12 2.27 2.41 2.59 2.73 2.85 2.98 3.14 3.35 3.59 3.85 4.18 4.51 4.92 5.29 5.56 5.96 AEO 1995 1.89 2.00 1.95 2.06 2.15 2.40 2.57 2.90 3.16 3.56 3.87 4.27 4.56 4.85 5.16 5.41 5.66 AEO 1996 1.63 1.74 1.86 1.99 2.10 2.19 2.29 2.38 2.48 2.59 2.72 2.84 2.97 3.12 3.29 3.49 3.73 AEO 1997 2.03 1.82 1.90 1.99 2.06 2.13 2.21 2.32 2.43 2.54 2.65 2.77 2.88 3.00 3.11 3.24 AEO 1998 2.30 2.20 2.26 2.31 2.38 2.44 2.52 2.60 2.69 2.79 2.93 3.06 3.20 3.35 3.48 AEO 1999 1.98 2.15 2.20 2.32 2.43 2.53 2.63 2.76 2.90 3.02 3.12 3.23 3.35 3.47

287

Table 20. Total Delivered Transportation Energy Consumption, Projected vs. Actual  

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

Total Delivered Transportation Energy Consumption, Projected vs. Actual Total Delivered Transportation Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 23.6 24.1 24.5 24.7 25.1 25.4 25.7 26.2 26.5 26.9 27.2 27.6 27.9 28.3 28.6 28.9 29.2 29.5 AEO 1995 23.3 24.0 24.2 24.7 25.1 25.5 25.9 26.2 26.5 26.9 27.3 27.7 28.0 28.3 28.5 28.7 28.9 AEO 1996 23.9 24.1 24.5 24.8 25.3 25.7 26.0 26.4 26.7 27.1 27.5 27.8 28.1 28.4 28.6 28.9 29.1 AEO 1997 24.7 25.3 25.9 26.4 27.0 27.5 28.0 28.5 28.9 29.4 29.8 30.3 30.6 30.9 31.1 31.3 AEO 1998 25.3 25.9 26.7 27.1 27.7 28.3 28.8 29.4 30.0 30.6 31.2 31.7 32.3 32.8 33.1 AEO 1999 25.4 26.0 27.0 27.6 28.2 28.8 29.4 30.0 30.6 31.2 31.7 32.2 32.8 33.1 AEO 2000 26.2 26.8 27.4 28.0 28.5 29.1 29.7 30.3 30.9 31.4 31.9 32.5 32.9

288

Table 22. Energy Intensity, Projected vs. Actual Projected  

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

Energy Intensity, Projected vs. Actual Energy Intensity, Projected vs. Actual Projected (quadrillion Btu / real GDP in billion 2005 chained dollars) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 11.2 11.1 11.0 10.8 10.7 10.5 10.4 10.3 10.1 10.0 9.9 9.8 9.7 9.6 9.5 9.4 9.3 9.2 AEO 1995 10.9 10.8 10.6 10.4 10.3 10.1 10.0 9.9 9.8 9.6 9.5 9.4 9.3 9.2 9.1 9.1 9.0 AEO 1996 10.7 10.6 10.4 10.3 10.1 10.0 9.8 9.7 9.6 9.5 9.4 9.3 9.2 9.2 9.1 9.0 8.9 AEO 1997 10.3 10.3 10.2 10.1 9.9 9.8 9.7 9.6 9.5 9.4 9.3 9.2 9.2 9.1 9.0 8.9 AEO 1998 10.1 10.1 10.1 10.0 9.9 9.8 9.7 9.6 9.5 9.5 9.4 9.3 9.2 9.1 9.0 AEO 1999 9.6 9.7 9.7 9.7 9.6 9.4 9.3 9.1 9.0 8.9 8.8 8.7 8.6 8.5 AEO 2000 9.4 9.4 9.3 9.2 9.1 9.0 8.9 8.8 8.7 8.7 8.6 8.5 8.4 AEO 2001 8.7 8.6 8.5 8.4 8.3 8.1 8.0 7.9 7.8 7.6 7.5 7.4

289

Table 15. Average Electricity Prices, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Average Electricity Prices, Projected vs. Actual Average Electricity Prices, Projected vs. Actual (nominal cents per kilowatt-hour) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 6.38 6.96 7.63 8.23 8.83 9.49 AEO 1983 6.85 7.28 7.74 8.22 8.68 9.18 13.12 AEO 1984 6.67 7.05 7.48 7.89 8.25 8.65 11.53 AEO 1985 6.62 6.94 7.32 7.63 7.89 8.15 8.46 8.85 9.20 9.61 10.04 AEO 1986 6.67 6.88 7.05 7.18 7.35 7.52 7.65 7.87 8.31 8.83 9.41 10.01 10.61 11.33 12.02 AEO 1987 6.63 6.65 6.92 7.12 7.38 7.62 7.94 8.36 8.86 11.99 AEO 1989* 6.50 6.75 7.14 7.48 7.82 8.11 8.50 8.91 9.39 9.91 10.49 11.05 11.61 AEO 1990 6.49 6.72 8.40 10.99 14.5 AEO 1991 6.94 7.31 7.59 7.82 8.18 8.38 8.54 8.73 8.99 9.38 9.83 10.29 10.83 11.36 11.94 12.58 13.21 13.88 14.58 15.21 AEO 1992 6.97 7.16 7.32 7.56 7.78 8.04 8.29 8.57 8.93 9.38 9.82 10.26 10.73 11.25 11.83 12.37 12.96 13.58 14.23 AEO 1993

290

Table 11. Natural Gas Net Imports, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Net Imports, Projected vs. Actual Natural Gas Net Imports, Projected vs. Actual (trillion cubic feet) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 1.19 1.19 1.19 1.19 1.19 1.19 AEO 1983 1.08 1.16 1.23 1.23 1.23 1.23 1.23 AEO 1984 0.99 1.05 1.16 1.27 1.43 1.57 2.11 AEO 1985 0.94 1.00 1.19 1.45 1.58 1.86 1.94 2.06 2.17 2.32 2.44 AEO 1986 0.74 0.88 0.62 1.03 1.05 1.27 1.39 1.47 1.66 1.79 1.96 2.17 2.38 2.42 2.43 AEO 1987 0.84 0.89 1.07 1.16 1.26 1.36 1.46 1.65 1.75 2.50 AEO 1989* 1.15 1.32 1.44 1.52 1.61 1.70 1.79 1.87 1.98 2.06 2.15 2.23 2.31 AEO 1990 1.26 1.43 2.07 2.68 2.95 AEO 1991 1.36 1.53 1.70 1.82 2.11 2.30 2.33 2.36 2.42 2.49 2.56 2.70 2.75 2.83 2.90 2.95 3.02 3.09 3.17 3.19 AEO 1992 1.48 1.62 1.88 2.08 2.25 2.41 2.56 2.68 2.70 2.72 2.76 2.84 2.92 3.05 3.10 3.20 3.25 3.30 3.30 AEO 1993 1.79 2.08 2.35 2.49 2.61 2.74 2.89 2.95 3.00 3.05 3.10

291

Table 8. Total Natural Gas Consumption, Projected vs. Actual  

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

Total Natural Gas Consumption, Projected vs. Actual Total Natural Gas Consumption, Projected vs. Actual Projected (trillion cubic feet) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 19.87 20.21 20.64 20.99 21.20 21.42 21.60 21.99 22.37 22.63 22.95 23.22 23.58 23.82 24.09 24.13 24.02 24.14 AEO 1995 20.82 20.66 20.85 21.21 21.65 21.95 22.12 22.25 22.43 22.62 22.87 23.08 23.36 23.61 24.08 24.23 24.59 AEO 1996 21.32 21.64 22.11 22.21 22.26 22.34 22.46 22.74 23.14 23.63 24.08 24.25 24.63 25.11 25.56 26.00 26.63 AEO 1997 22.15 22.75 23.24 23.64 23.86 24.13 24.65 25.34 25.82 26.22 26.52 27.00 27.35 27.70 28.01 28.47 AEO 1998 21.84 23.03 23.84 24.08 24.44 24.81 25.33 25.72 26.22 26.65 27.22 27.84 28.35 28.84 29.17 AEO 1999 21.35 22.36 22.54 23.18 23.65 24.17 24.57 25.19 25.77 26.41 26.92 27.42 28.02 28.50

292

Table 18. Total Delivered Commercial Energy Consumption, Projected vs. Actual  

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

Total Delivered Commercial Energy Consumption, Projected vs. Actual Total Delivered Commercial Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 6.8 6.9 6.9 7.0 7.1 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.4 7.5 7.5 7.5 7.5 7.6 AEO 1995 6.9 6.9 7.0 7.0 7.0 7.1 7.1 7.1 7.1 7.1 7.2 7.2 7.2 7.2 7.3 7.3 7.3 AEO 1996 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.5 7.6 7.6 7.7 7.7 7.8 7.9 8.0 8.0 8.1 AEO 1997 7.4 7.4 7.4 7.5 7.5 7.6 7.7 7.7 7.8 7.8 7.9 7.9 8.0 8.1 8.1 8.2 AEO 1998 7.5 7.6 7.7 7.8 7.9 8.0 8.0 8.1 8.2 8.3 8.4 8.4 8.5 8.6 8.7 AEO 1999 7.4 7.8 7.9 8.0 8.1 8.2 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 AEO 2000 7.7 7.8 7.9 8.0 8.1 8.2 8.3 8.4 8.5 8.5 8.7 8.7 8.8 AEO 2001 7.8 8.1 8.3 8.6 8.7 8.9 9.0 9.2 9.3 9.5 9.6 9.7 AEO 2002 8.2 8.4 8.7 8.9 9.0 9.2 9.4 9.6 9.7 9.9 10.1

293

Table 21. Total Transportation Energy Consumption, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Transportation Energy Consumption, Projected vs. Actual Transportation Energy Consumption, Projected vs. Actual (quadrillion Btu) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 18.6 18.2 17.7 17.3 17.0 16.9 AEO 1983 19.8 20.1 20.4 20.4 20.5 20.5 20.7 AEO 1984 19.2 19.0 19.0 19.0 19.1 19.2 20.1 AEO 1985 20.0 19.8 20.0 20.0 20.0 20.1 20.3 AEO 1986 20.5 20.8 20.8 20.6 20.7 20.3 21.0 AEO 1987 21.3 21.5 21.6 21.7 21.8 22.0 22.0 22.0 21.9 22.3 AEO 1989* 21.8 22.2 22.4 22.4 22.5 22.5 22.5 22.5 22.6 22.7 22.8 23.0 23.2 AEO 1990 22.0 22.4 23.2 24.3 25.5 AEO 1991 22.1 21.6 21.9 22.1 22.3 22.5 22.8 23.1 23.4 23.8 24.1 24.5 24.8 25.1 25.4 25.7 26.0 26.3 26.6 26.9 AEO 1992 21.7 22.0 22.5 22.9 23.2 23.4 23.6 23.9 24.1 24.4 24.8 25.1 25.4 25.7 26.0 26.3 26.6 26.9 27.1 AEO 1993 22.5 22.8 23.4 23.9 24.3 24.7 25.1 25.4 25.7 26.1 26.5 26.8 27.2 27.6 27.9 28.1 28.4 28.7 AEO 1994 23.6

294

Table 10. Natural Gas Production, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Production, Projected vs. Actual Production, Projected vs. Actual (trillion cubic feet) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 14.74 14.26 14.33 14.89 15.39 15.88 AEO 1983 16.48 16.27 16.20 16.31 16.27 16.29 14.89 AEO 1984 17.48 17.10 17.44 17.58 17.52 17.32 16.39 AEO 1985 16.95 17.08 17.11 17.29 17.40 17.33 17.32 17.27 17.05 16.80 16.50 AEO 1986 16.30 16.27 17.15 16.68 16.90 16.97 16.87 16.93 16.86 16.62 16.40 16.33 16.57 16.23 16.12 AEO 1987 16.21 16.09 16.38 16.32 16.30 16.30 16.44 16.62 16.81 17.39 AEO 1989* 16.71 16.71 16.94 17.01 16.83 17.09 17.35 17.54 17.67 17.98 18.20 18.25 18.49 AEO 1990 16.91 17.25 18.84 20.58 20.24 AEO 1991 17.40 17.48 18.11 18.22 18.15 18.22 18.39 18.82 19.03 19.28 19.62 19.89 20.13 20.07 19.95 19.82 19.64 19.50 19.30 19.08 AEO 1992 17.43 17.69 17.95 18.00 18.29 18.27 18.51 18.75 18.97

295

Table 17. Total Energy Consumption, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Energy Consumption, Projected vs. Actual Energy Consumption, Projected vs. Actual (quadrillion Btu) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 79.1 79.6 79.9 80.8 82.1 83.3 AEO 1983 78.0 79.5 81.0 82.4 83.9 84.6 89.0 AEO 1984 78.5 79.4 81.2 83.1 85.1 86.4 93.0 AEO 1985 77.6 78.5 79.8 81.2 82.7 83.3 84.2 85.0 85.7 86.3 87.2 AEO 1986 77.0 78.8 79.8 80.7 81.5 82.9 83.8 84.6 85.3 86.0 86.6 87.4 88.3 89.4 90.2 AEO 1987 78.9 80.0 82.0 82.8 83.9 85.1 86.2 87.1 87.9 92.5 AEO 1989* 82.2 83.8 84.5 85.4 86.2 87.1 87.8 88.7 89.5 90.4 91.4 92.4 93.5 AEO 1990 84.2 85.4 91.9 97.4 102.8 AEO 1991 84.4 85.0 86.0 87.0 87.9 89.1 90.4 91.8 93.1 94.3 95.6 97.1 98.4 99.4 100.3 101.4 102.5 103.6 104.7 105.8 AEO 1992 84.7 87.0 88.0 89.2 90.5 91.4 92.4 93.4 94.5 95.6 96.9 98.0 99.0 100.0 101.2 102.2 103.2 104.3 105.2 AEO 1993 87.0 88.3 89.8 91.4 92.7 94.0 95.3 96.3 97.5 98.6

296

Table 3. Gross Domestic Product, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Gross Domestic Product, Projected vs. Actual Gross Domestic Product, Projected vs. Actual (cumulative average percent growth in projected real GDP from first year shown for each AEO) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 4.3% 3.8% 3.6% 3.3% 3.2% 3.2% AEO 1983 3.3% 3.3% 3.4% 3.3% 3.2% 3.1% 2.7% AEO 1984 2.7% 2.4% 2.9% 3.1% 3.1% 3.1% 2.7% AEO 1985 2.3% 2.2% 2.7% 2.8% 2.9% 3.0% 3.0% 3.0% 2.9% 2.8% 2.8% AEO 1986 2.6% 2.5% 2.7% 2.5% 2.5% 2.6% 2.6% 2.6% 2.5% 2.5% 2.5% 2.5% 2.5% 2.5% 2.5% AEO 1987 2.7% 2.3% 2.4% 2.5% 2.5% 2.6% 2.6% 2.5% 2.4% 2.3% AEO 1989* 4.0% 3.4% 3.1% 3.0% 2.9% 2.8% 2.7% 2.7% 2.7% 2.6% 2.6% 2.6% 2.6% AEO 1990 2.9% 2.3% 2.5% 2.5% 2.4% AEO 1991 0.8% 1.0% 1.7% 1.8% 1.8% 1.9% 2.0% 2.1% 2.1% 2.1% 2.2% 2.2% 2.2% 2.2% 2.2% 2.2% 2.2% 2.2% 2.2% 2.2% AEO 1992 -0.1% 1.6% 2.0% 2.2% 2.3% 2.2% 2.2% 2.2% 2.2% 2.3% 2.3% 2.3% 2.3% 2.2%

297

Table 20. Total Industrial Energy Consumption, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Industrial Energy Consumption, Projected vs. Actual Industrial Energy Consumption, Projected vs. Actual (quadrillion Btu) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 24.0 24.1 24.4 24.9 25.5 26.1 AEO 1983 23.2 23.6 23.9 24.4 24.9 25.0 25.4 AEO 1984 24.1 24.5 25.4 25.5 27.1 27.4 28.7 AEO 1985 23.2 23.6 23.9 24.4 24.8 24.8 24.4 AEO 1986 22.2 22.8 23.1 23.4 23.4 23.6 22.8 AEO 1987 22.4 22.8 23.7 24.0 24.3 24.6 24.6 24.7 24.9 22.6 AEO 1989* 23.6 24.0 24.1 24.3 24.5 24.3 24.3 24.5 24.6 24.8 24.9 24.4 24.1 AEO 1990 25.0 25.4 27.1 27.3 28.6 AEO 1991 24.6 24.5 24.8 24.8 25.0 25.3 25.7 26.2 26.5 26.1 25.9 26.2 26.4 26.6 26.7 27.0 27.2 27.4 27.7 28.0 AEO 1992 24.6 25.3 25.4 25.6 26.1 26.3 26.5 26.5 26.0 25.6 25.8 26.0 26.1 26.2 26.4 26.7 26.9 27.2 27.3 AEO 1993 25.5 25.9 26.2 26.8 27.1 27.5 27.8 27.4 27.1 27.4 27.6 27.8 28.0 28.2 28.4 28.7 28.9 29.1 AEO 1994 25.4 25.9

298

Table 8. Natural Gas Wellhead Prices, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Wellhead Prices, Projected vs. Actual Natural Gas Wellhead Prices, Projected vs. Actual (current dollars per thousand cubic feet) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 4.32 5.47 6.67 7.51 8.04 8.57 AEO 1983 2.93 3.11 3.46 3.93 4.56 5.26 12.74 AEO 1984 2.77 2.90 3.21 3.63 4.13 4.79 9.33 AEO 1985 2.60 2.61 2.66 2.71 2.94 3.35 3.85 4.46 5.10 5.83 6.67 AEO 1986 1.73 1.96 2.29 2.54 2.81 3.15 3.73 4.34 5.06 5.90 6.79 7.70 8.62 9.68 10.80 AEO 1987 1.83 1.95 2.11 2.28 2.49 2.72 3.08 3.51 4.07 7.54 AEO 1989* 1.62 1.70 1.91 2.13 2.58 3.04 3.48 3.93 4.76 5.23 5.80 6.43 6.98 AEO 1990 1.78 1.88 2.93 5.36 9.2 AEO 1991 1.77 1.90 2.11 2.30 2.42 2.51 2.60 2.74 2.91 3.29 3.75 4.31 5.07 5.77 6.45 7.29 8.09 8.94 9.62 10.27 AEO 1992 1.69 1.85 2.03 2.15 2.35 2.51 2.74 3.01 3.40 3.81 4.24 4.74 5.25 5.78 6.37 6.89 7.50 8.15 9.05 AEO 1993 1.85 1.94 2.09 2.30

299

Table 16. Total Energy Consumption, Projected vs. Actual Projected  

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

Total Energy Consumption, Projected vs. Actual Total Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 88.0 89.5 90.7 91.7 92.7 93.6 94.6 95.7 96.7 97.7 98.9 100.0 100.8 101.7 102.7 103.6 104.3 105.2 AEO 1995 89.2 90.0 90.6 91.9 93.0 93.8 94.6 95.3 96.2 97.2 98.4 99.4 100.3 101.2 102.1 102.9 103.9 AEO 1996 90.6 91.3 92.5 93.5 94.3 95.1 95.9 96.9 98.0 99.2 100.4 101.4 102.1 103.1 103.8 104.7 105.5 AEO 1997 92.6 93.6 95.1 96.6 97.9 98.8 99.9 101.2 102.4 103.4 104.7 105.8 106.6 107.2 107.9 108.6 AEO 1998 94.7 96.7 98.6 99.8 101.3 102.4 103.4 104.5 105.8 107.3 108.6 109.9 111.1 112.2 113.1 AEO 1999 94.6 97.0 99.2 100.9 102.0 102.8 103.6 104.7 106.0 107.2 108.5 109.7 110.8 111.8

300

Table 9. Natural Gas Production, Projected vs. Actual Projected  

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

Natural Gas Production, Projected vs. Actual Natural Gas Production, Projected vs. Actual Projected (trillion cubic feet) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 17.71 17.68 17.84 18.12 18.25 18.43 18.58 18.93 19.28 19.51 19.80 19.92 20.13 20.18 20.38 20.35 20.16 20.19 AEO 1995 18.28 17.98 17.92 18.21 18.63 18.92 19.08 19.20 19.36 19.52 19.75 19.94 20.17 20.28 20.60 20.59 20.88 AEO 1996 18.90 19.15 19.52 19.59 19.59 19.65 19.73 19.97 20.36 20.82 21.25 21.37 21.68 22.11 22.47 22.83 23.36 AEO 1997 19.10 19.70 20.17 20.32 20.54 20.77 21.26 21.90 22.31 22.66 22.93 23.38 23.68 23.99 24.25 24.65 AEO 1998 18.85 19.06 20.35 20.27 20.60 20.94 21.44 21.81 22.25 22.65 23.18 23.75 24.23 24.70 24.97 AEO 1999 18.80 19.13 19.28 19.82 20.23 20.77 21.05 21.57 21.98 22.47 22.85 23.26 23.77 24.15

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301

Table 19. Total Delivered Industrial Energy Consumption, Projected vs. Actual  

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

Total Delivered Industrial Energy Consumption, Projected vs. Actual Total Delivered Industrial Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 AEO 1994 25.4 25.9 26.3 26.7 27.0 27.1 26.8 26.6 26.9 27.2 27.7 28.1 28.3 28.7 29.1 29.4 29.7 30.0 AEO 1995 26.2 26.3 26.5 27.0 27.3 26.9 26.6 26.8 27.1 27.5 27.9 28.2 28.4 28.7 29.0 29.3 29.6 AEO 1996 26.5 26.6 27.3 27.5 26.9 26.5 26.7 26.9 27.2 27.6 27.9 28.2 28.3 28.5 28.7 28.9 29.2 AEO 1997 26.2 26.5 26.9 26.7 26.6 26.8 27.1 27.4 27.8 28.0 28.4 28.7 28.9 29.0 29.2 29.4 AEO 1998 27.2 27.5 27.2 26.9 27.1 27.5 27.7 27.9 28.3 28.7 29.0 29.3 29.7 29.9 30.1 AEO 1999 26.7 26.4 26.4 26.8 27.1 27.3 27.5 27.9 28.3 28.6 28.9 29.2 29.5 29.7 AEO 2000 25.8 25.5 25.7 26.0 26.5 26.9 27.4 27.8 28.1 28.3 28.5 28.8 29.0

302

Table 18. Total Residential Energy Consumption, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Residential Energy Consumption, Projected vs. Actual Residential Energy Consumption, Projected vs. Actual (quadrillion Btu) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 10.1 10.1 10.1 10.1 10.2 10.2 AEO 1983 9.8 9.9 10.0 10.1 10.2 10.1 10.0 AEO 1984 9.9 9.9 10.0 10.2 10.3 10.3 10.5 AEO 1985 9.8 10.0 10.1 10.3 10.6 10.6 10.9 AEO 1986 9.6 9.8 10.0 10.3 10.4 10.8 10.9 AEO 1987 9.9 10.2 10.3 10.3 10.4 10.5 10.5 10.5 10.5 10.6 AEO 1989* 10.3 10.5 10.4 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 10.5 AEO 1990 10.4 10.7 10.8 11.0 11.3 AEO 1991 10.2 10.7 10.7 10.8 10.8 10.8 10.9 10.9 10.9 11.0 11.0 11.0 11.1 11.2 11.2 11.3 11.4 11.4 11.5 11.6 AEO 1992 10.6 11.1 11.1 11.1 11.1 11.1 11.2 11.2 11.3 11.3 11.4 11.5 11.5 11.6 11.7 11.8 11.8 11.9 12.0 AEO 1993 10.7 10.9 11.0 11.0 11.0 11.1 11.1 11.1 11.1 11.2 11.2 11.2 11.2 11.3 11.3 11.4 11.4 11.5 AEO 1994 10.3 10.4 10.4 10.4

303

Table 6. Domestic Crude Oil Production, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Domestic Crude Oil Production, Projected vs. Actual Domestic Crude Oil Production, Projected vs. Actual (million barrels per day) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 8.79 8.85 8.84 8.80 8.66 8.21 AEO 1983 8.67 8.71 8.66 8.72 8.80 8.63 8.11 AEO 1984 8.86 8.70 8.59 8.45 8.28 8.25 7.19 AEO 1985 8.92 8.96 9.01 8.78 8.38 8.05 7.64 7.27 6.89 6.68 6.53 AEO 1986 8.80 8.63 8.30 7.90 7.43 6.95 6.60 6.36 6.20 5.99 5.80 5.66 5.54 5.45 5.43 AEO 1987 8.31 8.18 8.00 7.63 7.34 7.09 6.86 6.64 6.54 6.03 AEO 1989* 8.18 7.97 7.64 7.25 6.87 6.59 6.37 6.17 6.05 6.00 5.94 5.90 5.89 AEO 1990 7.67 7.37 6.40 5.86 5.35 AEO 1991 7.23 6.98 7.10 7.11 7.01 6.79 6.48 6.22 5.92 5.64 5.36 5.11 4.90 4.73 4.62 4.59 4.58 4.53 4.46 4.42 AEO 1992 7.37 7.17 6.99 6.89 6.68 6.45 6.28 6.16 6.06 5.91 5.79 5.71 5.66 5.64 5.62 5.63 5.62 5.55 5.52 AEO 1993 7.20 6.94 6.79 6.52 6.22 6.00 5.84 5.72

304

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

305

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...

306

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

307

Peaking World Oil Production: Impacts, Mitigation and Risk Management  

E-Print Network (OSTI)

The peaking of world oil production presents the U.S. and the world with an unprecedented risk management problem. As peaking is approached, liquid fuel prices and price volatility will increase dramatically, and, without timely mitigation, the economic, social, and political costs will be unprecedented. Viable mitigation options exist on both the supply and demand sides, but to have substantial impact, they must be initiated more than a decade in advance of peaking. In 2003, the world consumed nearly 80 million barrels per day (MM bpd) of oil. U.S. consumption was almost 20 MM bpd,

Robert L. Hirsch; Roger H. Bezdek; Robert M. Wendling

2005-01-01T23:59:59.000Z

308

Cooling commercial buildings with off-peak power  

Science Conference Proceedings (OSTI)

Large commercial buildings use more electricity for cooling than for heating, and can account for 40% of summer peak demand. A cool storage technique in which compressors chill or freeze water during off-peak periods and the water is circulated during peak hours is in use in 100 commercial buildings. Reports indicate that these systems are economical, although little information is available, but engineers are hesitant to incorporate them because of possible damage from leaks or rust and other uncertainties. The Electric Power Research Institute is evaluating the performance of several systems to answer some of the operating and maintenance questions raised by engineers. 3 references, 3 figures. (DCK)

Lihach, N.; Rabl, V.

1983-10-01T23:59:59.000Z

309

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

310

Load-curve responsiveness to weather and the cost-effectiveness of conservation  

SciTech Connect

A cost-benefit analysis of home-weatherization projects using average incremental power costs instead of peak or off-peak costs shows that some programs are no longer cost-effective. Weatherization improves the energy efficiency of houses and reduces demand on the utility, but a study of how monthly load curves at a Pacific Northwest utility responded to weather over a 12-month period indicates that abnormal weather shifts the entire load curve. 1 figure. (DCK)

Hellman, M.M.

1982-09-30T23:59:59.000Z

311

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

312

Multi-State Load Models for Distribution System Analysis  

Science Conference Proceedings (OSTI)

Recent work in the field of distribution system analysis has shown that the traditional method of peak load analysis is not adequate for the analysis of emerging distribution system technologies. Voltage optimization, demand response, electric vehicle charging, and energy storage are examples of technologies with characteristics having daily, seasonal, and/or annual variations. In addition to the seasonal variations, emerging technologies such as demand response and plug in electric vehicle charging have the potential to send control signals to the end use loads which will affect how they consume energy. In order to support time-series analysis over different time frames and to incorporate potential control signal inputs it is necessary to develop detailed end use load models which accurately represent the load under various conditions, and not just during the peak load period. This paper will build on previous work on detail end use load modeling in order to outline the method of general multi-state load models for distribution system analysis.

Schneider, Kevin P.; Fuller, Jason C.; Chassin, David P.

2011-11-01T23:59:59.000Z

313

EA-1921: Silver Peak Area Geothermal Exploration Project Environmental  

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

921: Silver Peak Area Geothermal Exploration Project 921: Silver Peak Area Geothermal Exploration Project Environmental Assessment, Esmeralda County, Nevada EA-1921: Silver Peak Area Geothermal Exploration Project Environmental Assessment, Esmeralda County, Nevada SUMMARY The Bureau of Land Management (BLM)(lead agency) and DOE are jointly preparing this EA, which evaluates the potential environmental impacts of a project proposed by Rockwood Lithium Inc (Rockwood), formerly doing business as Chemetall Foote Corporation. Rockwood has submitted to the BLM, Tonopah Field Office, an Operations Plan for the construction, operation, and maintenance of the Silver Peak Area Geothermal Exploration Project within Esmeralda County, Nevada. The purpose of the project is to determine subsurface temperatures, confirm the existence of geothermal resources, and

314

Resistivity Tomography At Silver Peak Area (DOE GTP) | Open Energy  

Open Energy Info (EERE)

source source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Page Edit History Facebook icon Twitter icon » Resistivity Tomography At Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Single-Well and Cross-Well Resistivity At Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak Area Exploration Technique Single-Well and Cross-Well Resistivity Activity Date Usefulness not indicated DOE-funding Unknown References (1 January 2011) GTP ARRA Spreadsheet Retrieved from "http://en.openei.org/w/index.php?title=Resistivity_Tomography_At_Silver_Peak_Area_(DOE_GTP)&oldid=689883" Categories:

315

Structural Analysis of the Desert Peak-Brady Geothermal Fields,  

Open Energy Info (EERE)

Structural Analysis of the Desert Peak-Brady Geothermal Fields, Structural Analysis of the Desert Peak-Brady Geothermal Fields, Northwestern Nevada: Implications for Understanding Linkages Between Northeast-Trending Structures and Geothermal Reservoirs in the Humboldt Structural Zone Jump to: navigation, search OpenEI Reference LibraryAdd to library Conference Paper: Structural Analysis of the Desert Peak-Brady Geothermal Fields, Northwestern Nevada: Implications for Understanding Linkages Between Northeast-Trending Structures and Geothermal Reservoirs in the Humboldt Structural Zone Abstract Detailed geologic mapping, delineation of Tertiary strata, analysis of faults and folds, and a new gravity survey have elucidated the structural controls on the Desert Peak and Brady geothermal fields in the Hot Springs Mountains of northwestern Nevada. The fields lie within the Humboldt

316

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

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

Track B - Critical Guidance for Peak Performance Homes Track B - Critical Guidance for Peak Performance Homes Track B - Critical Guidance for Peak Performance Homes Presentations from Track B, Critical Guidance for Peak Performance Homes of the U.S. Department of Energy Building America program's 2012 Residential Energy Efficiency Stakeholder Meeting are provided below as Adobe Acrobat PDFs. These presentations for this track covered the following topics: Ventilation Strategies in High Performance Homes; Combustion Safety in Tight Houses; Implementation Program Case Studies; Field Testing from Start to Finish; and Humidity Control and Analysis. why_we_ventilate.pdf formaldehyde_new_homes.pdf whole_bldg_ventilation.pdf combustion_safety_codes.pdf combustion_diagnostics.pdf test_protocols_results.pdf utility_incentive_programs.pdf

317

EA-1921: Silver Peak Area Geothermal Exploration Project Environmental  

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

921: Silver Peak Area Geothermal Exploration Project 921: Silver Peak Area Geothermal Exploration Project Environmental Assessment, Esmeralda County, Nevada EA-1921: Silver Peak Area Geothermal Exploration Project Environmental Assessment, Esmeralda County, Nevada SUMMARY The Bureau of Land Management (BLM)(lead agency) and DOE are jointly preparing this EA, which evaluates the potential environmental impacts of a project proposed by Rockwood Lithium Inc (Rockwood), formerly doing business as Chemetall Foote Corporation. Rockwood has submitted to the BLM, Tonopah Field Office, an Operations Plan for the construction, operation, and maintenance of the Silver Peak Area Geothermal Exploration Project within Esmeralda County, Nevada. The purpose of the project is to determine subsurface temperatures, confirm the existence of geothermal resources, and

318

Multispectral Imaging At Silver Peak Area (Laney, 2005) | Open Energy  

Open Energy Info (EERE)

Laney, 2005) Laney, 2005) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Multispectral Imaging At Silver Peak Area (Laney, 2005) Exploration Activity Details Location Silver Peak Area Exploration Technique Multispectral Imaging Activity Date Usefulness not indicated DOE-funding Unknown Notes Geology and Geophysics of Geothermal Systems, Gregory Nash, 2005. A third objective was testing ASTER multispectral data for small-scale mapping of the geology of the northern Silver Peak Range, Nevada near the Fish Lake Valley geothermal field. References Patrick Laney (2005) Federal Geothermal Research Program Update - Fiscal Year 2004 Retrieved from "http://en.openei.org/w/index.php?title=Multispectral_Imaging_At_Silver_Peak_Area_(Laney,_2005)&oldid=511017"

319

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

320

Residential Response to Critical Peak Pricing of Electricity  

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

Residential Response to Critical Peak Pricing of Electricity Speaker(s): Karen Herter Date: June 30, 2005 - 12:00pm Location: Bldg. 90 A recent California study collected detailed...

Note: This page contains sample records for the topic "actual peak load" 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

Automated Critical Peak Pricing Field Tests: Program Description and Results  

E-Print Network (OSTI)

E-2: Baseline Peak and Maximum Demand Savings at Each Auto-45 Table 4-8: Maximum Demand saving by Site and Non-and the non-coincident maximum demand savings. If all twelve

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Xu, Peng

2006-01-01T23:59:59.000Z

322

Transient Peak Currents in Permanent Magnet Synchronous Motors  

E-Print Network (OSTI)

Transient Peak Currents in Permanent Magnet Synchronous Motors for Symmetrical Short Circuits Terms-- Permanent magnet synchronous motor, short circuit, protection measure, transient behavior I 33095 Paderborn, Germany Abstract--To enable constant-power areas with permanent magnet synchronous

Noé, Reinhold

323

Off peak cooling using an ice storage system  

E-Print Network (OSTI)

The electric utilities in the United States have entered a period of slow growth due to a combination of increased capital costs and a staggering rise in the costs for fuel. In addition to this, the rise in peak power ...

Quinlan, Edward Michael

1980-01-01T23:59:59.000Z

324

The Annual Peak in the SST Anomaly Spectrum  

Science Conference Proceedings (OSTI)

The manner in which monthly mean sea surface temperature anomalies (SSTAs) show enhanced variance at the annual period in the extratropics (an annual peak in the variance spectrum) is illustrated by observations and model simulations. A mechanism,...

Jens Möller; Dietmar Dommenget; Vladimir A. Semenov

2008-06-01T23:59:59.000Z

325

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

326

Development of a dispatchable PV peak shaving system. Final report on PV:BONUS Phase 2 activities  

DOE Green Energy (OSTI)

In July 1993, the Delmarva Power and Light Company (now Conectiv, Inc.) was awarded a contract for the development of a Dispatchable Photovoltaic Peak Shaving System under the US Department of Energy PV:BONUS Program. The rationale for the dispatchable PV peak shaving system is based on the coincidence between the solar resource and the electrical load in question. Where poor coincidence exists, a PV array by itself does little to offset peak demands. However, with the addition of a relatively small amount of energy storage, the energy from the PV array can be managed and the value of the PV system increases substantially. In Phase 2, Delmarva Power continued the refinement of the system deployed in Phase 1. Four additional dispatchable PV peak shaving systems were installed for extended testing and evaluation at sites in Delaware, Maryland, Wisconsin and North Carolina. A second type of system that can be used to provide back-up power as well as peak shaving was also developed in Phase 2. This PV-UPS system used a packaging approach nearly identical to the PV peak shaving system, although there were significant differences in the design of the power electronics and control systems. Conceptually, the PV-UPS system builds upon the idea of adding value to PV systems by increasing functionality. A prototype of the PV-UPS system was installed in Delaware for evaluation near the end of the contract period.

Ferguson, W.D. [Conectiv, Inc., Wilmington, DE (United States); Nigro, R.M. [Applied Energy Group, Inc., Hauppauge, NY (United States)

1999-01-20T23:59:59.000Z

327

Distribution load study aids system planning  

SciTech Connect

The Walnut Metering Project is an experimental substation and distribution system metering installation designed to provide quantitative data for distribution system planning. The design and operation of the metering equipment are discussed. After 3 years of operation it was concluded that the primary economic benefits anticipated from the determination of substation area diversity characteristics did not materialize because the peaking characteristics of the substations in the area were typically coincident with each other. However, the data obtained had a significant positive impact, both economically and operationally, in the field of equipment loadability, and is beneficial to activities related to load projections and distribution system planning. (LCL)

Scofield J.M.

1976-07-01T23:59:59.000Z

328

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

329

Observation of low magnetic field density peaks in helicon plasma  

SciTech Connect

Single density peak has been commonly observed in low magnetic field (<100 G) helicon discharges. In this paper, we report the observations of multiple density peaks in low magnetic field (<100 G) helicon discharges produced in the linear helicon plasma device [Barada et al., Rev. Sci. Instrum. 83, 063501 (2012)]. Experiments are carried out using argon gas with m = +1 right helical antenna operating at 13.56 MHz by varying the magnetic field from 0 G to 100 G. The plasma density varies with varying the magnetic field at constant input power and gas pressure and reaches to its peak value at a magnetic field value of {approx}25 G. Another peak of smaller magnitude in density has been observed near 50 G. Measurement of amplitude and phase of the axial component of the wave using magnetic probes for two magnetic field values corresponding to the observed density peaks indicated the existence of radial modes. Measured parallel wave number together with the estimated perpendicular wave number suggests oblique mode propagation of helicon waves along the resonance cone boundary for these magnetic field values. Further, the observations of larger floating potential fluctuations measured with Langmuir probes at those magnetic field values indicate that near resonance cone boundary; these electrostatic fluctuations take energy from helicon wave and dump power to the plasma causing density peaks.

Barada, Kshitish K.; Chattopadhyay, P. K.; Ghosh, J.; Kumar, Sunil; Saxena, Y. C. [Institute for Plasma Research, Bhat, Gandhinagar 382428 (India)

2013-04-15T23:59:59.000Z

330

Peaking of world oil production: Impacts, mitigation, & risk management  

SciTech Connect

The peaking of world oil production presents the U.S. and the world with an unprecedented risk management problem. As peaking is approached, liquid fuel prices and price volatility will increase dramatically, and, without timely mitigation, the economic, social, and political costs will be unprecedented. Viable mitigation options exist on both the supply and demand sides, but to have substantial impact, they must be initiated more than a decade in advance of peaking.... The purpose of this analysis was to identify the critical issues surrounding the occurrence and mitigation of world oil production peaking. We simplified many of the complexities in an effort to provide a transparent analysis. Nevertheless, our study is neither simple nor brief. We recognize that when oil prices escalate dramatically, there will be demand and economic impacts that will alter our simplified assumptions. Consideration of those feedbacks will be a daunting task but one that should be undertaken. Our aim in this study is to-- • Summarize the difficulties of oil production forecasting; • Identify the fundamentals that show why world oil production peaking is such a unique challenge; • Show why mitigation will take a decade or more of intense effort; • Examine the potential economic effects of oil peaking; • Describe what might be accomplished under three example mitigation scenarios. • Stimulate serious discussion of the problem, suggest more definitive studies, and engender interest in timely action to mitigate its impacts.

Hirsch, R.L. (SAIC); Bezdek, Roger (MISI); Wendling, Robert (MISI)

2005-02-01T23:59:59.000Z

331

A peak power tracker for small wind turbines in battery charging applications  

Science Conference Proceedings (OSTI)

This paper describes the design, implementation and testing of a prototype version of a peak power tracking system for small wind turbines in battery charging applications. The causes for the poor performance of small wind turbines in battery charging applications are explained and previously proposed configurations to increase the power output of the wind turbines are discussed. Through computer modeling of the steady-state operation the potential performance gain of the proposed system in comparison with existing systems is calculated. It is shown that one configuration consisting of reactive compensation by capacitors and a DC/DC converter is able to optimally load the wind turbine and thus obtain maximum energy capture over the whole range of wind speeds. A proof of concept of the peak power tracking system is provided by building and testing a prototype version. The peak power tracking system is tested in combination with a typical small wind turbine generator on a dynamometer. Steady-state operating curves confirming the performance improvement predicted by calculations are presented.

De Broe, A.M.; Drouilhet, S.; Gevorgian, V.

1999-12-01T23:59:59.000Z

332

Smart Operations of Air-Conditioning and Lighting Systems in Government Buildings for Peak Power Reduction  

E-Print Network (OSTI)

During the summer 2007 smart operation strategies for air-conditioning (A/C) and lighting systems were developed and tested in a number of governmental buildings in Kuwait as one of the solutions to reduce the national peak demand for electrical power that commonly occur around 15:00 h. The working hours for these building are generally between 07:00 and 14:00 h and their peak demand exceeds 600 MW. The smart operation strategies implemented in these buildings included pre-closing treatment (PCT) between 13:00 and 14:00 h and time-of-day control (TDC) after 14:00 h. Also de-lamping was carried out in some of the buildings to readjust the higher than recommended illumination levels. This paper presents the achievements of implementing these smart operations strategies in Justice Palace Complex (JPC) as a case study. The peak load of this building was 3700 kW. The achievements are summarized as an all time saving of 22 kW by de-lamping, an additional saving of 27 kW through TDC of lighting, direct savings between 13:00 and 22:00 h by closing supply and return air fans of 52 air-handling units with a connected load 400 kW, and an additional saving of 550 kW during the same period by optimizing the cooling production and distribution. In conclusion project achieved an overall reduction in power demand of around 20% between 13:00 to 17:00 h and reduction ranging from 7% to 15% between 17:00 to 20:00 h.

Al-Hadban, Y.; Maheshwari, G. P.; Al-Nakib, D.; Al-Mulla, A.; Alasseri, R.

2008-10-01T23:59:59.000Z

333

Table 19. Total Commercial Energy Consumption, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

Commercial Energy Consumption, Projected vs. Actual Commercial Energy Consumption, Projected vs. Actual (quadrillion Btu) 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 AEO 1982 6.6 6.7 6.8 6.8 6.8 6.9 AEO 1983 6.4 6.6 6.8 6.9 7.0 7.1 7.2 AEO 1984 6.2 6.4 6.5 6.7 6.8 6.9 7.3 AEO 1985 5.9 6.1 6.2 6.3 6.4 6.5 6.7 AEO 1986 6.2 6.3 6.4 6.4 6.5 7.1 7.4 AEO 1987 6.1 6.1 6.3 6.4 6.6 6.7 6.8 6.9 6.9 7.3 AEO 1989* 6.6 6.7 6.9 7.0 7.0 7.1 7.2 7.3 7.3 7.4 7.5 7.6 7.7 AEO 1990 6.6 6.8 7.1 7.4 7.8 AEO 1991 6.7 6.9 7.0 7.1 7.1 7.2 7.3 7.4 7.5 7.6 7.7 7.8 7.9 8.0 8.1 8.2 8.3 8.4 8.6 8.7 AEO 1992 6.8 7.1 7.2 7.3 7.3 7.4 7.5 7.6 7.7 7.8 7.9 8.0 8.1 8.2 8.3 8.4 8.5 8.6 8.7 AEO 1993 7.2 7.3 7.4 7.4 7.5 7.6 7.7 7.7 7.8 7.9 7.9 8.0 8.0 8.1 8.1 8.1 8.2 8.2 AEO 1994 6.8 6.9 6.9 7.0 7.1 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.4 7.5 7.5 7.5 7.5 AEO 1995 6.94 6.9 7.0 7.0 7.0 7.1 7.1 7.1 7.1 7.1 7.2 7.2 7.2 7.2 7.3 7.3 AEO 1996 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.5 7.6 7.6 7.7 7.7 7.8 7.9 8.0

334

Actual versus design performance of solar systems in the National Solar Data Network  

Science Conference Proceedings (OSTI)

This report relates field measured performance to the designer predicted performance. The field measured data was collected by the National Solar Data Network (NSDN) over a period of six years. Data from 25 solar systems was selected from a data pool of some 170 solar systems. The scope of the project extends beyond merely presenting comparisons of data. There is an attempt to provide answers which will move the solar industry forward. As a result of some industry and research workshops, several concerns arose which can be partially allayed by careful study of the NSDN data. These are: What types of failures occurred and why. How good was the design versus actual performance. Why was predicted performance not achieved in the field. Which components should be integrated with a system type for good performance. Since the designs span several years and since design philosophies are quite variable, the measured results were also compared to f-Chart 5.1 results. This comparison is a type of normalization in that all systems are modeled with the same process. An added benefit of this normalization is a further validation of the f-Chart model on a fairly large scale. The systems were modeled using equipment design parameters, measured loads, and f-Chart weather data from nearby cities.

Logee, T.L.; Kendall, P.W.

1984-09-01T23:59:59.000Z

335

Automated Critical Peak Pricing Field Tests: 2006 Pilot Program Description and Results  

E-Print Network (OSTI)

together  during  this  peak  demand period to use power 21 Peak Demand Baseline study.  Their average peak demand reduction was 14% of the 

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila

2007-01-01T23:59:59.000Z

336

Wind loading on solar collectors  

DOE Green Energy (OSTI)

The present design methodology for the determination of wind loading on the various solar collectors has been reviewed and assessed. The total force coefficients of flat plates of aspect ratios 1.0 and 3.0, respectively, at various angles of attack obtained by using the guidelines of the ANSI A58.1-1982, have been compared with those obtained by using the methodology of the ASCE Task Committee, 1961, and the experimental results of the full-scale test of heliostats by Peglow. The turbulent energy spectra, currently employed in the building code, are compared with those of Kaimal et al., Lumley, and Ponofsky for wind velocities of 20.0 m/s and 40.24 m/s at an elevation of 9.15 m. The longitudinal spectra of the building code overestimates the Kaimal spectra in the frequency range of 0.007 Hz to 0.08 Hz and underestimates beyond the frequency of 0.08 Hz. The peak angles of attack, on the heliostat, stowed in horizontal position, due to turbulent vertical and lateral components of wind velocity, have been estimated by using Daniel's methodology for three wind velocities and compared with the value suggested by the code. The experimental results of a simple test in the laboratory indicate the feasibility of decreasing the drag forces of the flat plate by reducing the solidity ratio.

Bhaduri, S.; Murphy, L.M.

1985-06-01T23:59:59.000Z

337

The University of Texas at Austin Jan-03 PART I CRIMES Reported Unfounded Actual Cleared % Clrd.  

E-Print Network (OSTI)

The University of Texas at Austin Jan-03 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1/93) #12;The University of Texas at Austin Feb-03 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1/93) #12;The University of Texas at Austin Mar-03 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1

Johns, Russell Taylor

338

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

339

Monitoring of electrical end-use loads in commercial buildings  

Science Conference Proceedings (OSTI)

A California utility 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 selected have average demands of 100kW 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. PC-based software programs have been developed for reviewing and validating the end-sue load data and for generating reports.

Martinez, M. (Southern California Edison, CA (US)); Alereza, T.; Mort, D. (ADM Associates, Sacramento, CA (US))

1989-01-01T23:59:59.000Z

340

Performance improvement of a solar heating system utilizing off-peak electric auxiliary  

DOE Green Energy (OSTI)

The design and construction of a heat pump system suitable for incorporating in a space solar heating system utilizing off-peak storage from the electric utility are described. The performance of the system is evaluated. The refrigerating capacity, heating capacity and compressor horsepower for a heat pump system using a piston type compressor are first determined. The heat pump design is also matched with the existing University of Toledo solar house heating system. The refrigerant is Freon-12 working between a condensing temperature of up to 172/sup 0/F and evaporator temperature between 0/sup 0/F and 75/sup 0/F. The heat pump is then installed. Performance indices for the heat pump and the heating system in general are defined and generated by the on-line computer monitoring system for the 1979/80 heating season operation. Monthly and seasonal indices such as heat pump coefficient of performance, collector efficiency, percent of heating load supplied by solar energy and individual components efficiencies in general are recorded. The data collected is then analyzed and compared with previously collected data. The improvement in the performance resulting from the addition of a piston type compressor with an external motor belt drive is then evaluated. Data collected points to the potentially improved operating performance of a solar heating system utilizing off-peak storage from the electric utility. Data shows that the seasonal percent of space heating load supplied by solar is 60% and the seasonal percent cost of space heating load supplied by solar is 82% with a solar collection coefficient of performance of 4.6. Data also indicates that such a system would pay for itself in 14 years when used in Northwest Ohio.

Eltimsahy, A.H.

1980-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "actual peak load" 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

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

342

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

343

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

344

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...

345

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...

346

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...

347

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...

348

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...

349

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...

350

Test experience with multiterminal HVDC load flow and stability programs  

Science Conference Proceedings (OSTI)

A powerful new set of load flow and stability programs for the study of HVdc systems has recently been completed. During the development of the programs novel applications of multiterminal HVdc systems were investigated, firstly on a large test system and later on actual utility models. This paper describes the test systems used, the HVdc systems studied and some of the interesting system related aspects of the HVdc system performance.

Chapman, D.G.; Davies, J.B. (Manitoba HVDC Research Centre, Winnipeg, Manitoba (CA)); McNichol, J.R. (Manitoba Hydro, Winnipeg, Manitoba (CA)); Gulachenski, E.M.; Doe, S. (New England Power Service Co., Westboro, MA (US)); Balu, N.J. (EPRI, Palo Alto, CA (US))

1988-07-01T23:59:59.000Z

351

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

352

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

353

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

354

Cuttings Analysis At Desert Peak Area (Laney, 2005) | Open Energy  

Open Energy Info (EERE)

Desert Peak Area (Laney, 2005) Desert Peak Area (Laney, 2005) Exploration Activity Details Location Desert Peak Area Exploration Technique Cuttings Analysis Activity Date Usefulness not indicated DOE-funding Unknown Notes Remote Sensing for Exploration and Mapping of Geothermal Resources, Wendy Calvin, 2005. Task 1: Detailed analysis of hyperspectral imagery obtained in summer of 2003 over Brady's Hot Springs region was completed and validated (Figure 1). This analysis provided a local map of both sinter and tufa deposits surrounding the Ormat plant, identified fault extensions not previously recognized from field mapping and has helped constrain where to put additional wells that were drilled at the site. Task 2: Initial analysis of Landsat and ASTER data for Buffalo Valley and Pyramid Lake was

355

Peak polarity overturn for charged particles in laser ablation process  

Science Conference Proceedings (OSTI)

The charged particles emitted during laser ablation off a brass target are detected using a metal probe in air. A special phenomenon is found in the recorded signals: following a giant electromagnetic peak observed immediately after the emission of the pulsed laser, a minor peak occurs whose polarity merely depends on the distance between the probe and the laser focal spot on the target. Under the condition of our experiment, the overturn point is 1.47 mm, i.e., the minor peak remains negative when the probe distance is less than 1.47 mm; it becomes positive while the probe is set at a distance beyond 1.47 mm. A hypothesis is proposed to explain the overturn that takes the flight behavior of the charged particles both in plasma and propagating shock wave into consideration.

Zhang, P.; Ji, Y. J.; Lai, X. M.; Bian, B. M.; Li, Z. H. [Department of Information Physics and Engineering, Nanjing University of Science and Technology, Nanjing 210094 (China)

2006-07-01T23:59:59.000Z

356

Scenario Analysis of Peak Demand Savings for Commercial Buildings with  

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

Scenario Analysis of Peak Demand Savings for Commercial Buildings with Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California Title Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California Publication Type Conference Paper LBNL Report Number LBNL-3636e Year of Publication 2010 Authors Yin, Rongxin, Sila Kiliccote, Mary Ann Piette, and Kristen Parrish Conference Name 2010 ACEEE Summer Study on Energy Efficiency in Buildings Conference Location Pacific Grove, CA Keywords demand response and distributed energy resources center, demand response research center, demand shifting (pre-cooling), DRQAT Abstract This paper reports on the potential impact of demand response (DR) strategies in commercial buildings in California based on the Demand Response Quick Assessment Tool (DRQAT), which uses EnergyPlus simulation prototypes for office and retail buildings. The study describes the potential impact of building size, thermal mass, climate, and DR strategies on demand savings in commercial buildings. Sensitivity analyses are performed to evaluate how these factors influence the demand shift and shed during the peak period. The whole-building peak demand of a commercial building with high thermal mass in a hot climate zone can be reduced by 30% using an optimized demand response strategy. Results are summarized for various simulation scenarios designed to help owners and managers understand the potential savings for demand response deployment. Simulated demand savings under various scenarios were compared to field-measured data in numerous climate zones, allowing calibration of the prototype models. The simulation results are compared to the peak demand data from the Commercial End-Use Survey for commercial buildings in California. On the economic side, a set of electricity rates are used to evaluate the impact of the DR strategies on economic savings for different thermal mass and climate conditions. Our comparison of recent simulation to field test results provides an understanding of the DR potential in commercial buildings.

357

Integration and operation of post-combustion capture system on coal-fired power generation: load following and peak power  

E-Print Network (OSTI)

Coal-fired power plants with post combustion capture and sequestration (CCS) systems have a variety of challenges to integrate the steam generation, air quality control, cooling water systems and steam turbine with the ...

Brasington, Robert David, S.M. Massachusetts Institute of Technology

2012-01-01T23:59:59.000Z

358

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

359

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

360

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

Note: This page contains sample records for the topic "actual peak load" 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

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

362

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

363

Electric Power Annual - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Table 8.6.A. Noncoincident Peak Load by North American Electric Reliability Corporation Assessment Area, 2001 - 2011, Actual

364

SCHOOL OF HISTORY & PHILOSOPHY Peak Carbon. Climate change and energy  

E-Print Network (OSTI)

SCHOOL OF HISTORY & PHILOSOPHY Peak Carbon. Climate change and energy policy ARTS2241 S2, 2010 #12 to be overcome before Australia can make deep cuts in greenhouse emissions, particularly from energy generation AIMS · Create awareness of the `bigger picture' that connects concerns over climate change and energy

Green, Donna

365

Scalable Scheduling of Building Control Systems for Peak Demand Reduction  

E-Print Network (OSTI)

is model predictive control (MPC) ([6], [7]). In [6] the authors inves- tigated MPC for thermal energyScalable Scheduling of Building Control Systems for Peak Demand Reduction Truong X. Nghiem, Madhur operation of sub- systems such as heating, ventilating, air conditioning and refrigeration (HVAC&R) systems

Pappas, George J.

366

Performance of a voltage peak detection-based flickermeter  

Science Conference Proceedings (OSTI)

Voltage fluctuations and rapid voltage changes lead to lamps flickering and disturbance of visual perception may occur consequently. For evaluation of the flicker severity level by means of voltage measurement there was developed an instrument called ... Keywords: Matlab Simulink, flickermeter, interharmonics, performance analysis, voltage fluctuation, voltage peak detection

Jiri Drapela

2009-12-01T23:59:59.000Z

367

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

368

Peak Dose Assessment for Proposed DOE-PPPO Authorized Limits  

Science Conference Proceedings (OSTI)

The Oak Ridge Institute for Science and Education (ORISE), a U.S. Department of Energy (DOE) prime contractor, was contracted by the DOE Portsmouth/Paducah Project Office (DOE-PPPO) to conduct a peak dose assessment in support of the Authorized Limits Request for Solid Waste Disposal at Landfill C-746-U at the Paducah Gaseous Diffusion Plant (DOE-PPPO 2011a). The peak doses were calculated based on the DOE-PPPO Proposed Single Radionuclides Soil Guidelines and the DOE-PPPO Proposed Authorized Limits (AL) Volumetric Concentrations available in DOE-PPPO 2011a. This work is provided as an appendix to the Dose Modeling Evaluations and Technical Support Document for the Authorized Limits Request for the C-746-U Landfill at the Paducah Gaseous Diffusion Plant, Paducah, Kentucky (ORISE 2012). The receptors evaluated in ORISE 2012 were selected by the DOE-PPPO for the additional peak dose evaluations. These receptors included a Landfill Worker, Trespasser, Resident Farmer (onsite), Resident Gardener, Recreational User, Outdoor Worker and an Offsite Resident Farmer. The RESRAD (Version 6.5) and RESRAD-OFFSITE (Version 2.5) computer codes were used for the peak dose assessments. Deterministic peak dose assessments were performed for all the receptors and a probabilistic dose assessment was performed only for the Offsite Resident Farmer at the request of the DOE-PPPO. In a deterministic analysis, a single input value results in a single output value. In other words, a deterministic analysis uses single parameter values for every variable in the code. By contrast, a probabilistic approach assigns parameter ranges to certain variables, and the code randomly selects the values for each variable from the parameter range each time it calculates the dose (NRC 2006). The receptor scenarios, computer codes and parameter input files were previously used in ORISE 2012. A few modifications were made to the parameter input files as appropriate for this effort. Some of these changes included increasing the time horizon beyond 1,050 years (yr), and using the radionuclide concentrations provided by the DOE-PPPO as inputs into the codes. The deterministic peak doses were evaluated within time horizons of 70 yr (for the Landfill Worker and Trespasser), 1,050 yr, 10,000 yr and 100,000 yr (for the Resident Farmer [onsite], Resident Gardener, Recreational User, Outdoor Worker and Offsite Resident Farmer) at the request of the DOE-PPPO. The time horizons of 10,000 yr and 100,000 yr were used at the request of the DOE-PPPO for informational purposes only. The probabilistic peak of the mean dose assessment was performed for the Offsite Resident Farmer using Technetium-99 (Tc-99) and a time horizon of 1,050 yr. The results of the deterministic analyses indicate that among all receptors and time horizons evaluated, the highest projected dose, 2,700 mrem/yr, occurred for the Resident Farmer (onsite) at 12,773 yr. The exposure pathways contributing to the peak dose are ingestion of plants, external gamma, and ingestion of milk, meat and soil. However, this receptor is considered an implausible receptor. The only receptors considered plausible are the Landfill Worker, Recreational User, Outdoor Worker and the Offsite Resident Farmer. The maximum projected dose among the plausible receptors is 220 mrem/yr for the Outdoor Worker and it occurs at 19,045 yr. The exposure pathways contributing to the dose for this receptor are external gamma and soil ingestion. The results of the probabilistic peak of the mean dose analysis for the Offsite Resident Farmer indicate that the average (arithmetic mean) of the peak of the mean doses for this receptor is 0.98 mrem/yr and it occurs at 1,050 yr. This dose corresponds to Tc-99 within the time horizon of 1,050 yr.

DELIS MALDONADO

2012-06-01T23:59:59.000Z

369

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

370

Stress Actually Makes You Stronger ... At Least Some of the Time  

Office of Science (SC) Website

Stress Actually Makes You Stronger ... At Least Some of the Time News Featured Articles 2013 2012 2011 2010 2009 2008 2007 2006 2005 Science Headlines Presentations & Testimony...

371

The Multiple Peril Crop Insurance Actual Production History (APH) Insurance Plan  

E-Print Network (OSTI)

The Actual Production History insurance plan protects against crop losses from a number of causes. All aspects of this insurance are described, including reporting requirements for the producer.

Stokes, Kenneth; Barnaby, G. A. Art; Waller, Mark L.; Outlaw, Joe

2008-10-07T23:59:59.000Z

372

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

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

govCampaignsColorado: The Storm Peak Lab Cloud Property Validation govCampaignsColorado: The Storm Peak Lab Cloud Property Validation Experiment (STORMVEX) Campaign Links STORMVEX Website Related Campaigns Colorado: CFH/CMH Deployment to StormVEx 2011.02.01, Mace, AMF Colorado: SP2 Deployment at StormVEx 2010.11.15, Sedlacek, AMF Colorado : Cavity Attenuated Phase Shift 2010.11.15, Massoli, AMF Colorado: Infrared Thermometer (IRT) 2010.11.15, Mace, AMF Colorado: StormVEX Aerosol Size Distribution 2010.11.15, Hallar, AMF Colorado: Direct Measurements of Snowfall 2010.11.15, McCubbin, AMF Colorado: Thunderhead Radiative Flux Analysis Campaign 2010.11.15, Long, AMF Colorado: Ice Nuclei and Cloud Condensation Nuclei Characterization 2010.11.15, Cziczo, AMF Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA.

373

The SECIS instrument on the Lomnicky Peak Observatory  

E-Print Network (OSTI)

Heating mechanisms of the solar corona will be investigated at the high-altitude solar observatory Lomnicky Peak of the Astronomical Institute of SAS (Slovakia) using its mid-size Lyot coronagraph and post-focal instrument SECIS provided by Astronomical Institute of the University of Wroclaw (Poland). The data will be studied with respect to the energy transport and release responsible for heating the solar corona to temperatures of mega-Kelvins. In particular investigations will be focused on detection of possible high-frequency MHD waves in the solar corona. The scientific background of the project, technical details of the SECIS system modified specially for the Lomnicky Peak coronagraph, and inspection of the test data are described in the paper.

Ambroz, J; Rudawy, P; Rybak, J; Phillips, K J H

2010-01-01T23:59:59.000Z

374

Categorical Exclusion for Pinnacle Peak Substation PCB contaminated Electrical  

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

Categorical Exclusion for Pinnacle Peak Substation PCB contaminated Electrical Equipment Removal Project located north of Phoenix, Maricopa County, Arizona RECORD OF CATEGORICAL EXCLUSION DETERMINATION A. Proposed Action: Western proposes drain and dispose of PCB contaminated oil from two bushings, and decontaminate one· bushing and rack, break apart PCB contaminated concrete and excavate PCB contaminated soil at Pinnacle Peak Substation. Western will be use existing access roads and vehicles such as cranes, backhoes, dozers, bucket trucks, crew trucks and pickup trucks to bring personnel and equipment to the work area. This work is necessary to maintain the safety and reliability of the bulk electrical system. The project is located in Maricopa County, Arizona. The attached map shows the

375

Firing Excess Refinery Butane in Peaking Gas Turbines  

E-Print Network (OSTI)

New environmentally-driven regulations for motor gasoline volatility will significantly alter refinery light ends supply/demand balancing. This, in turn, will impact refinery economics. This paper presumes that one outcome will be excess refinery normal butane production, which will reduce refinery normal butane value and price. Explored is an opportunity for a new use for excess refinery normal butane- as a fuel for utility peaking gas turbines which currently fire kerosene and #2 oil. Our paper identifies the fundamental driving forces which are changing refinery butane economics, examines how these forces influence refinery production, and evaluates the potential for using normal butanes as peaking utility gas turbine fuel, especially on the US East Coast.

Pavone, A.; Schreiber, H.; Zwillenberg, M.

1989-09-01T23:59:59.000Z

376

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

377

Analyses of Magnetic-Field Peak-Exposure Summary Measures  

Science Conference Proceedings (OSTI)

Past emphasis on exposure characterization and analyses for magnetic fields has been on measures of central tendency, such as long-term time-weighted average (TWA) exposure. Past emphasis on exposure characterization and analyses for magnetic fields has been on measures of central tendency such as long-term time-weighted average (TWA) exposure. This report examines peak exposure measures such as the maximum and 99th percentile of measurements during a day. EPRI sponsored this study to enhance industry kn...

2003-11-19T23:59:59.000Z

378

Deconvolution of mixed gamma emitters using peak parameters  

SciTech Connect

When evaluating samples containing mixtures of nuclides using gamma spectroscopy the situation sometimes arises where the nuclides present have photon emissions that cannot be resolved by the detector. An example of this is mixtures of {sup 241}Am and plutonium that have L x-ray emissions with slightly different energies which cannot be resolved using a high-purity germanium detector. It is possible to deconvolute the americium L x-rays from those plutonium based on the {sup 241}Am 59.54 keV photon. However, this requires accurate knowledge of the relative emission yields. Also, it often results in high uncertainties in the plutonium activity estimate due to the americium yields being approximately an order of magnitude greater than those for plutonium. In this work, an alternative method of determining the relative fraction of plutonium in mixtures of {sup 241}Am and {sup 239}Pu based on L x-ray peak location and shape parameters is investigated. The sensitivity and accuracy of the peak parameter method is compared to that for conventional peak decovolution.

Gadd, Milan S [Los Alamos National Laboratory; Garcia, Francisco [Los Alamos National Laboratory; Magadalena, Vigil M [Los Alamos National Laboratory

2011-01-14T23:59:59.000Z

379

Engineering to Control Noise, Loading, and Optimal Operating Points  

Science Conference Proceedings (OSTI)

Successful engineering of low-energy nuclear systems requires control of noise, loading, and optimum operating point (OOP) manifolds. The latter result from the biphasic system response of low-energy nuclear reaction (LENR)/cold fusion systems, and their ash production rate, to input electrical power. Knowledge of the optimal operating point manifold can improve the reproducibility and efficacy of these systems in several ways. Improved control of noise, loading, and peak production rates is available through the study, and use, of OOP manifolds. Engineering of systems toward the OOP-manifold drive-point peak may, with inclusion of geometric factors, permit more accurate uniform determinations of the calibrated activity of these materials/systems.

Mitchell R. Swartz

2000-11-12T23:59:59.000Z

380

Comparison of strength and load-based methods for testing wind turbine blades  

DOE Green Energy (OSTI)

The purpose of this paper is to compare two methods of blade test loading and show how they are applied in an actual blade test. Strength and load-based methods were examined to determine the test load for an Atlantic Orient Corporation (AOC) 15/50 wind turbine blade for fatigue and static testing. Fatigue load-based analysis was performed using measured field test loads extrapolated for extreme rare events and scaled to thirty-year spectra. An accelerated constant amplitude fatigue test that gives equivalent damage at critical locations was developed using Miner`s Rule and the material S-N curves. Test load factors were applied to adjust the test loads for uncertainties, and differences between the test and operating environment. Similar analyses were carried, out for the strength-based fatigue test using the strength of the blade and the material properties to determine the load level and number of constant amplitude cycles to failure. Static tests were also developed using load and strength criteria. The resulting test loads were compared and contrasted. The analysis shows that, for the AOC 15/50 blade, the strength-based test loads are higher than any of the static load-based cases considered but were exceeded in the fatigue analysis for a severe hot/wet environment.

Musial, W.D.; Clark, M.E.; Egging, N. [and others

1996-11-01T23:59:59.000Z

Note: This page contains sample records for the topic "actual peak load" 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

SAPHIRE 8 Volume 7 - Data Loading  

Science Conference Proceedings (OSTI)

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

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

2011-03-01T23:59:59.000Z

382

Impact of Reflective Roofing on Cooling Electrical Use and Peak Demand in a Florida Retail Mall  

E-Print Network (OSTI)

Architects in hot climates have long recognized that reflective roof colors can reduce building cooling load. Experimentation spanning nearly three decades has shown that white roofing surfaces can significantly reduce surface temperatures and cooling loads (Givoni and Hoffmann, 1968; Reagan and Acklam, 1979; Griggs and Shipp, 1988; Anderson, 1989; Anderson et al., 1991 and Bansal et al., 1992). More importantly, measured cooling energy savings of white surfaces have been significant in California's climate (Akbari et al., 1991, 1992, 1997). In Florida, field research by the Florida Solar Energy Center (FSEC) since 1993 has quantified the impact of reflective roof coatings on sub-metered air conditioning (AC) consumption in tests in a dozen occupied homes (Parker et al., 1993; 1994; 1995; 1997). The coatings were applied to the roofs of each home in mid-summer after a month-long period of monitoring during which meteorological conditions, building temperatures and AC energy use were recorded. Using weather periods with similar temperatures and solar insolation, air conditioning energy use was reduced by 10% - 43% in the homes. The average drop in space cooling energy use was about 7.4 kWh/day or 19% of the pre-application air conditioning consumption. Unfortunately, until this project there has been little objective testing of the impact of roof whitening on the AC load of commercial buildings in Florida. Two demonstration sites have been monitored. The first was an elementary school in Cocoa Beach, Florida, which was monitored for a year before and after a white roof coating was applied. A final report on this project was published in the CADDET Newsletter (Parker et al., 1996a, b). The project demonstrated a 10% annual savings in chiller energy with a 30% reduction in peak cooling electrical demand. This paper summarizes the findings from the second demonstration at a commercial strip mall.

Parker, D. S.; Sonne, J. K.; Sherwin, J. R.

2002-01-01T23:59:59.000Z

383

Critical analysis of European load management practices. Final report for period January--July 1976  

SciTech Connect

Load management has been practiced in Europe for approximately a quarter century. A critical evaluation of the initial objectives and economic justifications for load management given in Europe may help energy policymakers in the U.S. assess the relevance of load management to meeting their current energy goals. Load management was adopted in Europe primarily to promote a growth in energy sales at a rate greater than the increase in capacity requirements. Utilities were able to improve daily load factors during the winter peak period; however, they may not have been successful in maintaining or improving their financial strength through load management. Increased capital and operating expenditures in the generation and distribution systems became necessary as the power system evolved in response to changing load characteristics. Rates charged to customers did not always produce adequate revenues from managed loads to cover the capital and operating costs to supply those loads. Comprehensive studies of the long-term costs and benefits might have prevented some of the load management problems experienced in Europe. Load management was not introduced in Europe to reduce utility production costs, conserve energy or scarce fuels, improve the environment, or influence summer loads. Accordingly, the European experience with load management may not be relevant to energy policymakers in the U.S. who desire to achieve these objectives.

1977-01-01T23:59:59.000Z

384

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

385

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

386

Validation Methodology to Allow Simulated Peak Reduction and Energy Performance Analysis of Residential Building Envelope with Phase Change Materials: Preprint  

SciTech Connect

Phase change materials (PCM) represent a potential technology to reduce peak loads and HVAC energy consumption in residential buildings. This paper summarizes NREL efforts to obtain accurate energy simulations when PCMs are modeled in residential buildings: the overall methodology to verify and validate Conduction Finite Difference (CondFD) and PCM algorithms in EnergyPlus is presented in this study. It also shows preliminary results of three residential building enclosure technologies containing PCM: PCM-enhanced insulation, PCM impregnated drywall and thin PCM layers. The results are compared based on predicted peak reduction and energy savings using two algorithms in EnergyPlus: the PCM and Conduction Finite Difference (CondFD) algorithms.

Tabares-Velasco, P. C.; Christensen, C.; Bianchi, M.

2012-08-01T23:59:59.000Z

387

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

388

Peak Demand Reduction from Pre-Cooling with Zone Temperature Reset in an Office Building  

E-Print Network (OSTI)

Peak Demand Reduction from Pre-Cooling with Zone TemperatureUniversity of California. Peak Demand Reduction from Pre-shifted in time and the peak demand is reduced. The building

Xu, Peng

2010-01-01T23:59:59.000Z

389

Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California  

E-Print Network (OSTI)

Scenario Analysis of Peak Demand Savings for CommercialScenario Analysis of Peak Demand Savings for CommercialThe whole-building peak demand of a commercial building with

Yin, Rongxin

2010-01-01T23:59:59.000Z

390

Peak demand reduction from pre-cooling with zone temperature reset in an office building  

E-Print Network (OSTI)

an Energy-Efficient Economy. Peak Demand Reduction from Pre-No. DE-AC03-76SF00098. Peak Demand Reduction from Pre-shifted in time and the peak demand is reduced. The building

Xu, Peng; Haves, Philip; Piette, Mary Ann; Braun, James

2004-01-01T23:59:59.000Z

391

Home cogeneration system can augment peak power requirements  

SciTech Connect

The use of internal combustion engines to supplement peak power generation to homeowners is suggested. As in a car heater, internal combustion engines would recover heat from the radiators to heat the house. The IC, inlet and outlet lines, thermostat, muffler (''critical''), induction generator, and reverse power delay are schematicized. Synchronous generators are not recommended. Disadvantages include the potential pollution, high capital cost, and the resistance of homeowners ''acquainted with the problems of owning a car.'' A simple method to determine the economics of home cogeneration is given. Special consideration is paid to the induction generator, and the engine starter.

Krishnan, K.R.

1983-06-01T23:59:59.000Z

392

Mercury Vapor At Silver Peak Area (Henkle, Et Al., 2005) | Open...  

Open Energy Info (EERE)

Mercury Vapor At Silver Peak Area (Henkle, Et Al., 2005) Exploration Activity Details Location Silver Peak Area Exploration Technique Mercury Vapor Activity Date Usefulness useful...

393

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

Open Energy Info (EERE)

Water Sampling At Silver Peak Area (Henkle, Et Al., 2005) Exploration Activity Details Location Silver Peak Area Exploration Technique Water Sampling Activity Date Usefulness...

394

Flow Test At Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Flow Test At Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak Area...

395

Density Log at Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Density Log at Silver Peak Area (DOE GTP) Exploration Activity Details...

396

Rock Density At Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Density At Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Rock Density At Silver Peak Area (DOE GTP) Exploration...

397

2-M Probe At Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Exploration Activity Details Location Silver Peak Area Exploration Technique 2-M Probe Activity Date Usefulness not indicated DOE-funding Unknown...

398

Gamma Log At Silver Peak Area (DOE GTP) | Open Energy Information  

Open Energy Info (EERE)

Silver Peak Area (DOE GTP) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Gamma Log At Silver Peak Area (DOE GTP) Exploration Activity Details...

399

Electric Power Annual  

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

1. Demand-Side Management Program Annual Effects by Program Category, 2002 through 2011 Energy Efficiency Load Management Total Year Energy Savings (Thousand MWh) Actual Peak Load...

400

Estimation of Lightning Stroke Peak Current as a Function of Peak Electric Field and the Normalized Amplitude of Signal Strength: Corrections and Improvements  

Science Conference Proceedings (OSTI)

The authors have made connections and improvements to published equations relating the peak current and the peak electric field intensity for return strokes of cloud-to-ground lightning. The original published equations were derived from ...

Y. P. Liaw; D. R. Cook; D. L. Sisterson

1996-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "actual peak load" 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

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

402

Anisotropic Sliding Dynamics, Peak Effect, and Metastability in Stripe Systems  

E-Print Network (OSTI)

A variety of soft and hard condensed matter systems are known to form stripe patterns. Here we use numerical simulations to analyze how such stripe states depin and slide when interacting with a random substrate and with driving in different directions with respect to the orientation of the stripes. Depending on the strength and density of the substrate disorder, we find that there can be pronounced anisotropy in the transport produced by different dynamical flow phases. We also find a disorder-induced "peak effect" similar to that observed for superconducting vortex systems, which is marked by a transition from elastic depinning to a state where the stripe structure fragments or partially disorders at depinning. Under the sudden application of a driving force, we observe pronounced metastability effects similar to those found near the order-disorder transition associated with the peak effect regime for three-dimensional superconducting vortices. The characteristic transient time required for the system to reach a steady state diverges in the region where the flow changes from elastic to disordered. We also find that anisotropy of the flow persists in the presence of thermal disorder when thermally-induced particle hopping along the stripes dominates. The thermal effects can wash out the effects of the quenched disorder, leading to a thermally-induced stripe state. We map out the dynamical phase diagram for this system, and discuss how our results could be explored in electron liquid crystal systems, type-1.5 superconductors, and pattern-forming colloidal assemblies.

C. J. Olson Reichhardt; C. Reichhardt; A. R. Bishop

2010-11-03T23:59:59.000Z

403

Load Reduction, Demand Response and Energy Efficient Technologies and Strategies  

SciTech Connect

The Department of Energy’s (DOE’s) Pacific Northwest National Laboratory (PNNL) was tasked by the DOE Office of Electricity (OE) to recommend load reduction and grid integration strategies, and identify additional demand response (energy efficiency/conservation opportunities) and strategies at the Forest City Housing (FCH) redevelopment at Pearl Harbor and the Marine Corps Base Hawaii (MCBH) at Kaneohe Bay. The goal was to provide FCH staff a path forward to manage their electricity load and thus reduce costs at these FCH family housing developments. The initial focus of the work was at the MCBH given the MCBH has a demand-ratchet tariff, relatively high demand (~18 MW) and a commensurate high blended electricity rate (26 cents/kWh). The peak demand for MCBH occurs in July-August. And, on average, family housing at MCBH contributes ~36% to the MCBH total energy consumption. Thus, a significant load reduction in family housing can have a considerable impact on the overall site load. Based on a site visit to the MCBH and meetings with MCBH installation, FCH, and Hawaiian Electric Company (HECO) staff, recommended actions (including a "smart grid" recommendation) that can be undertaken by FCH to manage and reduce peak-demand in family housing are made. Recommendations are also made to reduce overall energy consumption, and thus reduce demand in FCH family housing.

Boyd, Paul A.; Parker, Graham B.; Hatley, Darrel D.

2008-11-19T23:59:59.000Z

404

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

405

Load controller and method to enhance effective capacity of a photovoltaic power supply  

DOE Patents (OSTI)

A load controller and method are provided for maximizing effective capacity of a non-controllable, renewable power supply coupled to a variable electrical load also coupled to a conventional power grid. Effective capacity is enhanced by monitoring power output of the renewable supply and loading, and comparing the loading against the power output and a load adjustment threshold determined from an expected peak loading. A value for a load adjustment parameter is calculated by subtracting the renewable supply output and the load adjustment parameter from the current load. This value is then employed to control the variable load in an amount proportional to the value of the load control parameter when the parameter is within a predefined range. By so controlling the load, the effective capacity of the non-controllable, renewable power supply is increased without any attempt at operational feedback control of the renewable supply. The renewable supply may comprise, for example, a photovoltaic power supply or a wind-based power supply.

Perez, Richard (Delmar, NY)

2000-01-01T23:59:59.000Z

406

Benefits of Industrial Boiler Control and Economic Load Allocation at AMOCO Chemicals, Decatur, Alabama  

E-Print Network (OSTI)

The objective of this paper is to provide an overview of the economic benefits realized by Amoco's Decatur plant from the utilization of Honeywell's Industrial Boiler Control solution and Turbo Economic Load Allocation packages on an integrated four boiler system. The boiler control scheme, integrated header pressure control scheme, boiler efficiency measurement, the concepts involved in the economic load allocation problem and the solution to this problem, as applied to the Amoco Decatur site will be discussed. In addition, actual fuel savings achieved from the use of a DCS boiler control solution coupled with the application of economic load allocation will be presented, based on several months of plant data.

Winter, J.

1998-04-01T23:59:59.000Z

407

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

408

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

409

Cost analysis of an ammonia dry cooling system with a Chicago Bridge and Iron peak shaving system  

SciTech Connect

A study was performed to determine the potential for reducing the cost associated with dry cooling by using an ammonia dry cooling system augmented with the Chicago Bridge and Iron (CP and I) peak shaving system. The cost analysis of an all-dry ammonia cooling system operating in conjunction with a peak shaving system is documented. The peak shaving system utilizes the excess cooling capability available at night to cool water to be used for supplemental cooling during the following day. The analysis consisted of determining the incremental cost of cooling for the CB and I system and comparing this cost to the incremental cost of cooling for both dry and wet/dry systems for a consistent set of design conditions and assumptions. The wet/dry systems were analyzed over a range of water usages. The basis of the comparisons was a cooling system designed for installations with a 650 mWe (gross) coal-fired power plant. From results of the study it was concluded that: the CB and I system shows a substantial economic advantage when compared with an all-dry cooling system; the CB and I system appears to be competitive with wet/dry cooling systems using about 2 to 3% water; and the CB and I system demonstrates a clear economic advantage when compared to both dry and wet/dry concepts for a winter peaking utility where the excess generation is assumed to displace both base-loaded coal-fired power generation and oil-fired gas turbine peaking units.

Drost, M.K.; Johnson, B.M.

1980-12-01T23:59:59.000Z

410

Actinide destruction and power peaking analysis in a 1000 MWt advanced burner reactor using moderated heterogeneous target assemblies  

SciTech Connect

The purpose of this research was to determine the effect of moderated heterogeneous subassemblies located in the core of a sodium-cooled fast reactor on minor actinide (MA) destruction rates over the lifecycle of the core. Additionally, particular emphasis was placed on the power peaking of the pins and the assemblies with the moderated targets as compared to standard unmoderated heterogeneous targets and a core without MA targets present. Power peaking analysis was performed on the target assemblies and on the fuel assemblies adjacent to the targets. The moderated subassemblies had a marked improvement in the overall destruction of heavy metals in the targets. The design with acceptable power peaking results had a 12.25% greater destruction of heavy metals than a similar ex-core unmoderated assembly. The increase in minor actinide destruction was most evident with americium where the moderated assemblies reduced the initial amount to less than 3% of the initial loading over a period of five years core residency. In order to take advantage of the high minor actinide destruction and minimize the power peaking effects, a hybrid scenario was devised where the targets resided ex-core in a moderated assembly for the first 506.9 effective full power days (EFPDs) and were moved to an in-core arrangement with the moderated targets removed for the remainder of the lifecycle. The hybrid model had an assembly and pin power peaking of less than 2.0 and a higher heavy metal and minor actinide destruction rate than the standard unmoderated heterogeneous targets either in-core or ex-core. The hybrid model has a 54.5% greater Am reduction over the standard ex-core model. It also had a 27.8% greater production of Cm and a 41.5% greater production of Pu than the standard ex-core model. The radiotoxicity of the targets in the hybrid design was 20% less than the discharged standard ex-core targets.

Kenneth Allen; Travis Knight; Samuel Bays

2011-05-01T23:59:59.000Z

411

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

412

10-MW GTO converter for battery peaking service  

SciTech Connect

A bidirectional 18-pulse voltage source converter utilizing gate turn-off thyristors (GTO's) is described. The converter, which is rated 10 MVA, was placed in service in early 1988 to connect an energy storage battery to a utility grid. The converter is rated and controlled to operate in all four quadrants (discharge, charge, leading vars, or lagging vars) at the full 10-MVA rating. It is capable of independent rapid control of real and reactive power with a transient response of 16 ms to changes in commanded value of real or reactive power. Thus it is usable as a reactive power controller (static var control), voltage control, frequency control, power system stabilizer, or as a real power peaking station. For use as a reactive power controller only, no battery would be needed. The design, construction, control, and application of the converter are described, and performance data taken at factory power test and at the installation are given.

Walker, L.H. (Drive Development Engineering, Drive Systems, General Electric Co., Salem, VA (US))

1990-01-01T23:59:59.000Z

413

Implications of "peak oil" for atmospheric CO2 and climate  

E-Print Network (OSTI)

Peaking of global oil production may have a large effect on future atmospheric CO2 amount and climate change, depending upon choices made for subsequent energy sources. We suggest that, if estimates of oil and gas reserves by the Energy Information Administration are realistic, it is feasible to keep atmospheric CO2 from exceeding approximately 450 ppm, provided that future exploitation of the huge reservoirs of coal and unconventional fossil fuels incorporates carbon capture and sequestration. Existing coal-fired power plants, without sequestration, must be phased out before mid-century to achieve this limit on atmospheric CO2. We also suggest that it is important to "stretch" oil reserves via energy efficiency, thus avoiding the need to extract liquid fuels from coal or unconventional fossil fuels. We argue that a rising price on carbon emissions is probably needed to keep CO2 beneath the 450 ppm ceiling.

Kharecha, P A

2007-01-01T23:59:59.000Z

414

Assessing Climate Information Use in Agribusiness. Part I: Actual and Potential Use and Impediments to Usage  

Science Conference Proceedings (OSTI)

A project for the development of methodology to enable agribusiness decision makers to utilize more effectively climate information involved investigation of three agribusiness firms, as well as measurement of their actual and potential use. The ...

Stanley A. Changnon; Steven T. Sonka; Steven Hofing

1988-08-01T23:59:59.000Z

415

Trends of Calculated and Simulated Actual Evaporation in the Yangtze River Basin  

Science Conference Proceedings (OSTI)

Actual evaporation in the Yangtze River basin is calculated by the complementary relationship approach—that is, the advection–aridity (AA) model with parameter validation from 1961 to 2007—and simulated by the general circulation model (GCM) ...

Yanjun Wang; Bo Liu; Buda Su; Jianqing Zhai; Marco Gemmer

2011-08-01T23:59:59.000Z

416

Use of Remotely Sensed Actual Evapotranspiration to Improve Rainfall–Runoff Modeling in Southeast Australia  

Science Conference Proceedings (OSTI)

This paper explores the use of the Moderate Resolution Imaging Spectroradiometer (MODIS), mounted on the polar-orbiting Terra satellite, to determine leaf area index (LAI), and use actual evapotranspiration estimated using MODIS LAI data combined ...

Yongqiang Zhang; Francis H. S. Chiew; Lu Zhang; Hongxia Li

2009-08-01T23:59:59.000Z

417

Estimating Actual Evapotranspiration from Satellite and Meteorological Data in Central Bolivia  

Science Conference Proceedings (OSTI)

Spatial estimates of actual evapotranspiration are useful for calculating the water balance of river basins, quantifying hydrological services provided by ecosystems, and assessing the hydrological impacts of land-use practices. To provide this ...

Christian Seiler; Arnold F. Moene

2011-05-01T23:59:59.000Z

418

Spinning Reserve From Hotel Load Response: Initial Progress  

SciTech Connect

This project was motivated by the fundamental match between hotel space conditioning load response capability and power system contingency response needs. As power system costs rise and capacity is strained demand response can provide a significant system reliability benefit at a potentially attractive cost. At ORNL s suggestion, Digital Solutions Inc. adapted its hotel air conditioning control technology to supply power system spinning reserve. This energy saving technology is primarily designed to provide the hotel operator with the ability to control individual room temperature set-points based upon occupancy (25% to 50% energy savings based on an earlier study [Kirby and Ally, 2002]). DSI added instantaneous local load shedding capability in response to power system frequency and centrally dispatched load shedding capability in response to power system operator command. The 162 room Music Road Hotel in Pigeon Forge Tennessee agreed to host the spinning reserve test. The Tennessee Valley Authority supplied real-time metering equipment in the form of an internet connected Dranetz-BMI power quality meter and monitoring expertise to record total hotel load during both normal operations and test results. The Sevier County Electric System installed the metering. Preliminary testing showed that hotel load can be curtailed by 22% to 37% depending on the outdoor temperature and the time of day. These results are prior to implementing control over the common area air conditioning loads. Testing was also not at times of highest system or hotel loading. Full response occurred in 12 to 60 seconds from when the system operator s command to shed load was issued. The load drop was very rapid, essentially as fast as the 2 second metering could detect, with all units responding essentially simultaneously. Load restoration was ramped back in over several minutes. The restoration ramp can be adjusted to the power system needs. Frequency response testing was not completed. Initial testing showed that the units respond very quickly. Problems with local power quality generated false low frequency signals which required testing to be stopped. This should not be a problem in actual operation since the frequency trip points will be staggered to generate a droop curve which mimics generator governor response. The actual trip frequencies will also be low enough to avoid power quality problems. The actual trip frequencies are too low to generate test events with sufficient regularity to complete testing in a reasonable amount of time. Frequency response testing will resume once the local power quality problem is fully understood and reasonable test frequency settings can be determined. Overall the preliminary testing was extremely successful. The hotel response capability matches the power system reliability need, being faster than generation response and inherently available when the power system is under the most stress (times of high system and hotel load). Periodic testing is scheduled throughout the winter and spring to characterize hotel response capability under a full range of conditions. More extensive testing will resume when summer outdoor temperatures are again high enough to fully test hotel response.

Kueck, John D [ORNL; Kirby, Brendan J [ORNL

2008-11-01T23:59:59.000Z

419

Wind load design methods for ground-based heliostats and parabolic dish collectors  

DOE Green Energy (OSTI)

The purpose of this design method is to define wind loads on flat heliostat and parabolic dish collectors in a simplified form. Wind loads are defined for both mean and peak loads accounting for the protective influence of upwind collectors, wind protective fences, or other wind-blockage elements. The method used to define wind loads was to generalize wind load data obtained during tests on model collectors, heliostats or parabolic dishes, placed in a modeled atmospheric wind in a boundary-layer wind-tunnel at Colorado State University. For both heliostats and parabolic dishes, loads are reported for solitary collectors and for collectors as elements of a field. All collectors were solid with negligible porosity; thus the effects of porosity in the collectors is not addressed.

Peterka, J.A.; Derickson, R.G. (Colorado State Univ., Fort Collins, CO (United States). Fluid Dynamics and Diffusion Lab.)

1992-09-01T23:59:59.000Z

420

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

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


421

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.

422

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

423

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

424

Silver Peak Innovative Exploration Project Geothermal Project | Open Energy  

Open Energy Info (EERE)

Innovative Exploration Project Geothermal Project Innovative Exploration Project Geothermal Project Jump to: navigation, search Last modified on July 22, 2011. Project Title Silver Peak Innovative Exploration Project Project Type / Topic 1 Recovery Act: Geothermal Technologies Program Project Type / Topic 2 Validation of Innovative Exploration Technologies Project Description The scope of this three phase project includes tasks to validate a variety of innovative exploration and drilling technologies which aim to accurately characterize the geothermal site and thereby reduce project risk. Phase 1 exploration will consist of two parts: 1) surface and near surface investigations and 2) subsurface geophysical surveys and modeling. The first part of Phase 1 includes: a hyperspectral imaging survey (to map thermal anomalies and geothermal indicator minerals), shallow temperature probe measurements, and drilling of temperature gradient wells to depths of 1000 feet. In the second part of Phase 1, 2D & 3D geophysical modeling and inversion of gravity, magnetic, and magnetotelluric datasets will be used to image the subsurface. This effort will result in the creation of a 3D model composed of structural, geological, and resistivity components. The 3D model will then be combined with the temperature data to create an integrated model that will be used to prioritize drill target locations.

425

Dick Cheney, Peak Oil and the Final Count Down  

E-Print Network (OSTI)

In the April 2004 issue of the magazine the Middle East I found a statement that Vice-President Dick Cheney had made in a speech at the London Institute of Petroleum Autumn lunch in 1999 when he was Chairman of Halliburton. A key passage from his speech was: “That means by 2010 we will need on the order of an additional fifty million barrels a day.” It suggested that he was fully aware of the issue of peak oil. A full text of the talk had been available on the website of the Institute of Petroleum, but has now been removed (wwww.petroleum.co.uk/speeches.htm). Nevertheless, further research did bring to light a printed version, dated 24.08.00, as follows: Dick Cheney: “From the standpoint of the oil industry obviously- and I'll talk a little later on about gas- for over a hundred years we as an industry have had to deal with the pesky problem that once you find oil and pump it out of the ground you've got to turn around and find more or go out of business. Producing oil is obviously a self-depleting activity. Every year you've got to find and develop reserves equal to your output just to stand still, just to stay even. This is as true for companies as well in the broader

Kjell Aleklett

2004-01-01T23:59:59.000Z

426

Fracture Permeability Evolution in Desert Peak Quartz Monzonite  

SciTech Connect

Fracture flow experiments are being conducted on quartz monzonite core from the Desert Peak East EGS site, Churchill County, Nevada. The flow experiments are conducted at temperatures of 167-169 C and 5.5 MPa confining pressure through artificial fractures. Two injection fluids, a saline solution and a silica-bearing solution, have been used to date. Flow rates are typically 0.02 mL/min, but other rates have been used. The fracture surfaces are characterized with a contact profilometer. The profilometry data demonstrate that it is possible to fabricate statistically similar fracture surfaces and enable us to map aperture variations, which we use in numerical simulations. Effluent samples are collected for chemical analysis. The fluid pressure gradient is measured across the specimen and effective hydraulic apertures are calculated. The experiments show a reduction in permeability over time for both injection fluids, but a more rapid loss of permeability was observed for the silica-bearing solution. The calculated hydraulic aperture is observed to decrease by 17% for the saline solution and 75% for the silica-bearing fluid, respectively. Electrical resistivity measurements, which are sensitive to the ionic content of the pore fluid, provide additional evidence of fluid-rock interactions.

Carlson, S R; Roberts, J J; Detwiler, R L; Viani, B E; Roberts, S K

2005-05-10T23:59:59.000Z

427

A three phase load flow algorithm for Shipboard Power Systems  

E-Print Network (OSTI)

Load Flow (Power Flow) is the determination of the steady state operating conditions for the system. This is a very important tool utilized by many real time applications in power systems. Traditional load flow methods, which incorporate Gauss-Seidel and/or Newton Raphson techniques, were primarily developed for transmission system analysis. Distribution load flow analysis must incorporate its unique characteristics such as unbalanced loads, distributed loads, radial network structure, and one, two, or three phase lines. Also, there are a variety of components included in distribution systems such as switches, transformers, voltage regulators, and distributed generators. Therefore, the traditional methods cannot be directly applied to distribution systems since the assumptions made for transmission systems are not valid for the unique characteristics of distribution systems. A Shipboard Power System (SPS) is a finite inertia electric power system. The generation, transmission, and distribution systems in SPSs are tightly coupled. In reality, the transmission system consists of the lines that interconnect the generator buses in a ring configuration. The distribution system consists of lines, transformers, and loads connected in a radial configuration. When analyzing a SPS, its distinct characteristics must be taken into consideration. Therefore, just as transmission and distribution systems have unique methods of analysis, SPSs also need a unique method of analysis. A load flow algorithm for a SPS must consider its distribution system characteristics as well as the unique characteristics of SPSs. The work presented in this thesis discussed a load flow algorithm developed for Shipboard Power Systems and terrestrial wye and delta connected radial distribution systems. The issues in developing a load flow algorithm for a SPS are addressed and the solution is presented. This solution combines three methods that addressed the issues of multiple sources, ring configuration, and radial load flow. This algorithm was tested on the IEEE 37 Bus Radial Distribution Test Feeder and a simplified Shipboard Power Test System developed by researchers in the Power System Automation Laboratory. The results produced minimal percent error when compared to the actual output results.

Medina-Calder?on, M?onica M

2003-01-01T23:59:59.000Z

428

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

SciTech Connect

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

Goldman, Charles A.

2002-03-01T23:59:59.000Z

429

Building America Top Innovations Hall of Fame Profile … High-Performance with Solar Electric Reduced Peak Demand: Premier Homes Rancho Cordoba, CA  

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

95 homes in Premier Gardens are 95 homes in Premier Gardens are equipped with photovoltaic panels that take advantage of solar energy to offset peak power loads during the hottest part of the day. As the housing market continues to evolve toward zero net-energy ready homes, Building America research has provided essential guidance for integrating renewable energy systems with high-performance homes and showing how they align with utility peak-demand reduction interests. Solar photovoltaic technology is an attractive option for utilities because they can reduce reliance on fossil-fuel energy. More significantly, it reduces peak demand because systems produce the most power on sunny summer afternoons coincident with the highest demand for air conditioning. Photovoltaic systems have been a part of several research projects conducted by

430

Program Design Analysis using BEopt Building Energy Optimization Software: Defining a Technology Pathway Leading to New Homes with Zero Peak Cooling Demand; Preprint  

SciTech Connect

An optimization method based on the evaluation of a broad range of different combinations of specific energy efficiency and renewable-energy options is used to determine the least-cost pathway to the development of new homes with zero peak cooling demand. The optimization approach conducts a sequential search of a large number of possible option combinations and uses the most cost-effective alternatives to generate a least-cost curve to achieve home-performance levels ranging from a Title 24-compliant home to a home that uses zero net source energy on an annual basis. By evaluating peak cooling load reductions on the least-cost curve, it is then possible to determine the most cost-effective combination of energy efficiency and renewable-energy options that both maximize annual energy savings and minimize peak-cooling demand.

Anderson, R.; Christensen, C.; Horowitz, S.

2006-08-01T23:59:59.000Z

431

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

432

Comparison of actual and predicted energy savings in Minnesota gas-heated single-family homes  

Science Conference Proceedings (OSTI)

Data available from a recent evaluation of a home energy audit program in Minnesota are sufficient to allow analysis of the actual energy savings achieved in audited homes and of the relationship between actual and predicted savings. The program, operated by Northern States Power in much of the southern half of the state, is part of Minnesota's version of the federal Residential Conservation Service. NSP conducted almost 12 thousand RCS audits between April 1981 (when the progam began) and the end of 1982. The data analyzed here, available for 346 homes that obtained an NSP energy audit, include monthly natural gas bills from October 1980 through April 1983; heating degree day data matched to the gas bills; energy audit reports; and information on household demographics, structure characteristics, and recent conservation actions from mail and telephone surveys. The actual reduction in weather-adjusted natural gas use between years 1 and 3 averaged 19 MBtu across these homes (11% of preprogram consumption); the median value of the saving was 16 MBtu/year. The variation in actual saving is quite large: gas consumption increased in almost 20% of the homes, while gas consumption decreased by more than 50 MBtu/year in more than 10% of the homes. These households reported an average expenditure of almost $1600 for the retrofit measures installed in their homes; the variation in retrofit cost, while large, was not as great as the variation in actual natural gas savings.

Hirst, E.; Goeltz, R.

1984-03-01T23:59:59.000Z

433

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

434

Fatigue damage estimate comparisons for northern European and U.S. wind farm loading environments  

DOE Green Energy (OSTI)

Typical loading histories associated with wind turbine service environments in northern Europe and within a large wind farm in the continental US were recently compared by Kelley (1995) using the WISPER [Ten Have, 1992] loading standard and its development protocol. In this study, an equivalent load spectrum for a US wind farm was developed by applying the WISPER development protocol to representative service load histories collected from two adjacent turbines operating within a large wind farm in San Gorgonio Pass, California. The results of this study showed that turbines operating in the California wind farm experience many more loading cycles with larger peak-to-peak values for the same mean wind speed classification than their European counterparts. In this paper, the impact of the two WISPER-protocol fatigue-load spectra on service lifetime predictions are used to compare and contrast the impact of the two loading environments with one another. The service lifetime predictions are made using the LIFE2 Fatigue Analysis Code [Sutherland and Schluter, 1989] with the fatigue properties of typical fiber glass composite blade materials. Additional analyses, based on rainflow counted time histories from the San Gorgonio turbines, are also used in the comparisons. In general, these results indicate that the WISPER load spectrum from northern European sites significantly underestimates the WISPER protocol load spectrum from a US wind farm site; i.e., the WISPER load spectrum significantly underestimates the number and magnitude of the loads observed at a US wind farm site. The authors conclude that there are fundamental differences in the two service environments.

Sutherland, H.J. [Sandia National Labs., Albuquerque, NM (United States). Wind Energy Technology Dept.; Kelley, N.D. [National Renewable Energy Lab., Golden, CO (United States). Wind Technology Div.

1995-05-01T23:59:59.000Z

435

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

436

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...

437

A Historical Perspective and Business Model for Load Response Aggregation Based on Priority Service  

E-Print Network (OSTI)

A Historical Perspective and Business Model for Load Response Aggregation Based on Priority Service] limits consumption during peak demand periods and is set by the customer according to a rate agreements of a colored light indicator which tariff is active. In its June 17, 1985 issue Electric Utility Week published

Oren, Shmuel S.

438

Method and system for regulating peak residential power demand  

SciTech Connect

A temperature monitoring system that monitors temperature outside the residence and a supply system responsive to the monitoring system that controls the supply of electrical power to major home appliances such as air conditioning devices, food preparation devices, clothes drying devices, and water heating devices is described. The major home appliances are arranged in pairs and connected to a main power distribution system in these pair arrangements through a load dispatcher including continuity sensitive switches. The appliances are continuously connected to the electrical power distribution system when the outdoor temperature is below a predetermined value. However, when the outdoor temperature exceeds the predetermined value, the continuity switches then control the supply of power to the appliances by supplying power to one of the appliances to the exclusion of the other in each pair arrangement. Whenever electrical power is not being supplied to one of the appliances in the pair arrangement requiring power, the other of the appliances is supplied with electrical power. In accordance with another aspect of the invention, the outdoor temperature is monitored and controls the operation of an air conditioning unit. When the outdoor temperature exceeds a predetermined value, the air conditioner is cycled between on and off conditions on a timed, periodic basis without regard to the temperature inside the residence at least until the temperature outside the residence drops below the predetermined value. The air conditioner may be cycled between on and off conditions on the periodic basis until the outdoor temperature drops a predetermined amount below the predetermined value, for example, drops at least 5/sup 0/ or 6/sup 0/ below the predetermined value. 12 Claims, 5 Drawing Figures.

Dixon, W.A.

1975-12-09T23:59:59.000Z

439

Peak Tracking by Simultaneous Inversion: Toward a One-Step Acoustic Tomography Analysis  

Science Conference Proceedings (OSTI)

A number of geophysical observing techniques, including ocean acoustic tomography, obtain sequences of records of which the observed relative maxima (“peaks”) are used to infer properties of the system via inversions. Traditionally, these peaks ...

Uwe Send

1996-10-01T23:59:59.000Z

440

Production of Hydrogen at the Forecourt Using Off-Peak Electricity: June 2005 (Milestone Report)  

DOE Green Energy (OSTI)

This milestone report provides information about the production of hydrogen at the forecourt using off-peak electricity as well as the Hydrogen Off-Peak Electricity (HOPE) model.

Levene, J. I.

2007-02-01T23:59:59.000Z

Note: This page contains sample records for the topic "actual peak load" 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

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

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

The VPP rates during the five-hour peak period vary daily depending on the cost of electricity. The VPP also includes a critical peak price (CPP) component that is...

442

Design and evaluation of seasonal storage hydrogen peak electricity supply system  

E-Print Network (OSTI)

The seasonal storage hydrogen peak electricity supply system (SSHPESS) is a gigawatt-year hydrogen storage system which stores excess electricity produced as hydrogen during off-peak periods and consumes the stored hydrogen ...

Oloyede, Isaiah Olanrewaju

2011-01-01T23:59:59.000Z

443

Microsoft Word - BUGS_The Next Smart Grid Peak Resource Final...  

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

April 15, 2010 DOENETL-20101406 Backup Generators (BUGS): The Next Smart Grid Peak Resource Backup Generators (BUGS): The Next Smart Grid Peak Resource v1.0 ii DISCLAIMER This...

444

Peak CO2? China's Emissions Trajectories to 2050  

SciTech Connect

As a result of soaring energy demand from a staggering pace of economic growth and the related growth of energy-intensive industry, China overtook the United States to become the world's largest contributor to CO{sub 2} emissions in 2007. At the same time, China has taken serious actions to reduce its energy and carbon intensity by setting both short-term energy intensity reduction goal for 2006 to 2010 as well as long-term carbon intensity reduction goal for 2020. This study focuses on a China Energy Outlook through 2050 that assesses the role of energy efficiency policies in transitioning China to a lower emission trajectory and meeting its intensity reduction goals. In the past years, LBNL has established and significantly enhanced the China End-Use Energy Model based on the diffusion of end-use technologies and other physical drivers of energy demand. This model presents an important new approach for helping understand China's complex and dynamic drivers of energy consumption and implications of energy efficiency policies through scenario analysis. A baseline ('Continued Improvement Scenario') and an alternative energy efficiency scenario ('Accelerated Improvement Scenario') have been developed to assess the impact of actions already taken by the Chinese government as well as planned and potential actions, and to evaluate the potential for China to control energy demand growth and mitigate emissions. It is a common belief that China's CO{sub 2} emissions will continue to grow throughout this century and will dominate global emissions. The findings from this research suggest that this will not likely be the case because of saturation effects in appliances, residential and commercial floor area, roadways, railways, fertilizer use, and urbanization will peak around 2030 with slowing population growth. The baseline and alternative scenarios also demonstrate that the 2020 goals can be met and underscore the significant role that policy-driven energy efficiency improvements will play in carbon mitigation along with a decarbonized power supply through greater renewable and non-fossil fuel generation.

Zhou, Nan; Fridley, David G.; McNeil, Michael; Zheng, Nina; Ke, Jing; Levine, Mark

2011-05-01T23:59:59.000Z

445

Preparing for the Peak: Energy Security and Atlantic Canada 1 Larry Hughes  

E-Print Network (OSTI)

region that will be particularly vulnerable to peak oil, since almost all of the region's oil is imported is destined for markets outside the region. This paper examines some of the potential impacts of peak oil the reliance on refined petroleum products for space heating and transportation. When peak oil production

Hughes, Larry

446

Available online at www.sciencedirect.com Future world oil production: growth, plateau, or peak?  

E-Print Network (OSTI)

Available online at www.sciencedirect.com Future world oil production: growth, plateau, or peak considers how long world oil production can continue to grow or if it will eventually plateau or peak and then decline. The paper concludes with the observation that whether peak oil has already occurred

Ito, Garrett

447

Result Demonstration Report Pigweed Control in Grain Sorghum Using Peak. 1996 to 1999  

E-Print Network (OSTI)

74 78 Peak + Methylated Oil 0.75 oz + 1 pt 78 88 93 1) WAT = Weeks after treatment application. #12Result Demonstration Report Pigweed Control in Grain Sorghum Using Peak. 1996 to 1999 Brent Bean Summary Studies were conducted from 1996 to 1999 to evaluate pigweed control in grain sorghum using Peak

Mukhtar, Saqib

448

Implications of ``peak oil'' for atmospheric CO2 and climate Pushker A. Kharecha1  

E-Print Network (OSTI)

Implications of ``peak oil'' for atmospheric CO2 and climate Pushker A. Kharecha1 and James E environments. If conventional oil production peaks within the next few decades, it may have a large effect., and J. E. Hansen (2008), Implications of ``peak oil'' for atmospheric CO2 and climate, Global Biogeochem

449

Impacts of time-of-day on average electricity prices and utility load factors  

SciTech Connect

A degree of rationalism is brought to the rate debate between marginalist time of day advocates and embedded cost traditionalists by an empirical analysis. Studies show that neither side can claim victory. The results show that blanket statements cannot be made concerning the impacts of TOD in demand and load factor, and that rates reduce only slightly. This paper summarizes the impacts of marginal cost TOD rates on peak demand, generation, load factor, and the average price of electricity. The methodology includes calculation of marginal cost, prediction of effect of TOD on load shapes by means of a Load Curve Forecasting model, and a production costing model. A matrix shows that impacts of TOD rates on individual utilities will depend on the specific utility customer mix, load shape, and generation mix.

Chamberlin, J.H.; Dickson, C.T.; Spann, R.M.

1982-06-01T23:59:59.000Z

450

Do 'enabling technologies' affect customer performance in price-responsive load programs?  

SciTech Connect

Price-responsive load (PRL) programs vary significantly in overall design, the complexity of relationships between program administrators, load aggregators, and customers, and the availability of ''enabling technologies''. Enabling technologies include such features as web-based power system and price monitoring, control and dispatch of curtailable loads, communications and information systems links to program participants, availability of interval metering data to customers in near real time, and building/facility/end-use automation and management capabilities. Two state agencies - NYSERDA in New York and the CEC in California - have been conspicuous leaders in the demonstration of demand response (DR) programs utilizing enabling technologies. In partnership with key stakeholders in these two states (e.g., grid operator, state energy agencies, and program administrators), Lawrence Berkeley National Laboratory (LBNL) and Pacific Northwest National Laboratory (PNNL) surveyed 56 customers who worked with five contractors participating in CEC or NYSERDA-sponsored DR programs. We combined market research and actual load curtailment data when available (i.e., New York) or customer load reduction targets in order to explore the relative importance of contractor's program design features, sophistication of control strategies, and reliance on enabling technologies in predicting customer's ability to deliver load reductions in DR programs targeted to large commercial/industrial customers. We found preliminary evidence that DR enabling technology has a positive effect on load curtailment potential. Many customers indicated that web-based energy information tools were useful for facilitating demand response (e.g., assessing actual performance compared to load reduction contract commitments), that multiple notification channels facilitated timely response, and that support for and use of backup generation allowed customers to achieve significant and ! predictable load curtailment s. We also found that 60-70 percent of the customers relied on manual approaches to implementing load reductions/curtailments, rather than automated load control response. The long-term sustainability of customer load curtailments would be significantly enhanced by automated load response capabilities, such as optimizing EMCS systems to respond to day-ahead energy market prices or load curtailments in response to system emergencies.

Goldman, Charles A.; Kintner-Meyer, Michael; Heffner, Grayson

2002-05-15T23:59:59.000Z

451

Do 'enabling technologies' affect customer performance in price-responsive load programs?  

SciTech Connect

Price-responsive load (PRL) programs vary significantly in overall design, the complexity of relationships between program administrators, load aggregators, and customers, and the availability of ''enabling technologies''. Enabling technologies include such features as web-based power system and price monitoring, control and dispatch of curtailable loads, communications and information systems links to program participants, availability of interval metering data to customers in near real time, and building/facility/end-use automation and management capabilities. Two state agencies - NYSERDA in New York and the CEC in California - have been conspicuous leaders in the demonstration of demand response (DR) programs utilizing enabling technologies. In partnership with key stakeholders in these two states (e.g., grid operator, state energy agencies, and program administrators), Lawrence Berkeley National Laboratory (LBNL) and Pacific Northwest National Laboratory (PNNL) surveyed 56 customers who worked with five contractors participating in CEC or NYSERDA-sponsored DR programs. We combined market research and actual load curtailment data when available (i.e., New York) or customer load reduction targets in order to explore the relative importance of contractor's program design features, sophistication of control strategies, and reliance on enabling technologies in predicting customer's ability to deliver load reductions in DR programs targeted to large commercial/industrial customers. We found preliminary evidence that DR enabling technology has a positive effect on load curtailment potential. Many customers indicated that web-based energy information tools were useful for facilitating demand response (e.g., assessing actual performance compared to load reduction contract commitments), that multiple notification channels facilitated timely response, and that support for and use of backup generation allowed customers to achieve significant and ! predictable load curtailment s. We also found that 60-70 percent of the customers relied on manual approaches to implementing load reductions/curtailments, rather than automated load control response. The long-term sustainability of customer load curtailments would be significantly enhanced by automated load response capabilities, such as optimizing EMCS systems to respond to day-ahead energy market prices or load curtailments in response to system emergencies.

Goldman, Charles A.; Kintner-Meyer, Michael; Heffner, Grayson

2002-05-15T23:59:59.000Z

452

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

453

The University of Texas at Austin Jan-11 PART I CRIMES Reported Unfounded Actual Cleared % Clrd.  

E-Print Network (OSTI)

The University of Texas at Austin Jan-11 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1.7% DP Form #31 - Page 1(Rev. 1/93) #12;The University of Texas at Austin Jan-11 PART I CRIMES BURGLARY/93) #12;The University of Texas at Austin Jan-11 PART I CRIMES BURGLARY & THEFT TARGET SECTION (List Other

Johns, Russell Taylor

454

The University of Texas at Austin Jan-00 PART I CRIMES Reported Unfounded Actual Cleared % Clrd.  

E-Print Network (OSTI)

The University of Texas at Austin Jan-00 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1.3% DP Form #31 - Page 1(Rev. 1/93) #12;The University of Texas at Austin Jan-00 PART I CRIMES BURGLARY of Texas at Austin Jan-00 PART I CRIMES BURGLARY & THEFT TARGET SECTION (List Other Target Areas) #/Month

Johns, Russell Taylor

455

The University of Texas at Austin Jan-06 PART I CRIMES Reported Unfounded Actual Cleared % Clrd.  

E-Print Network (OSTI)

The University of Texas at Austin Jan-06 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1 Total % Rcvd. 1.0% DP Form #31 - Page 1(Rev. 1/93) #12;The University of Texas at Austin Jan-06 PART I/93) #12;The University of Texas at Austin Jan-06 PART I CRIMES BURGLARY & THEFT TARGET SECTION (List Other

Johns, Russell Taylor

456

The University of Texas at Austin Jan-09 PART I CRIMES Reported Unfounded Actual Cleared % Clrd.  

E-Print Network (OSTI)

The University of Texas at Austin Jan-09 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1. 8.0% DP Form #31 - Page 1(Rev. 1/93) #12;The University of Texas at Austin Jan-09 PART I CRIMES/93) #12;The University of Texas at Austin Jan-09 PART I CRIMES BURGLARY & THEFT TARGET SECTION (List Other

Johns, Russell Taylor

457

The University of Texas at Austin Jan-08 PART I CRIMES Reported Unfounded Actual Cleared % Clrd.  

E-Print Network (OSTI)

The University of Texas at Austin Jan-08 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1 Total % Rcvd. 2.2% DP Form #31 - Page 1(Rev. 1/93) #12;The University of Texas at Austin Jan-08 PART I(Rev. 1/93) #12;The University of Texas at Austin Jan-08 PART I CRIMES BURGLARY & THEFT TARGET SECTION

Johns, Russell Taylor

458

The University of Texas at Austin Jan-04 PART I CRIMES Reported Unfounded Actual Cleared % Clrd.  

E-Print Network (OSTI)

The University of Texas at Austin Jan-04 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1.1% DP Form #31 - Page 1(Rev. 1/93) #12;The University of Texas at Austin Jan-04 PART I CRIMES BURGLARY University of Texas at Austin Jan-04 PART I CRIMES BURGLARY & THEFT TARGET SECTION (List Other Target Areas

Johns, Russell Taylor

459

The University of Texas at Austin Jan-01 PART I CRIMES Reported Unfounded Actual Cleared % Clrd.  

E-Print Network (OSTI)

The University of Texas at Austin Jan-01 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1/93) #12;The University of Texas at Austin Jan-01 PART I CRIMES BURGLARY & THEFT TARGET SECTION Maintenance. 1/93)Co #12;The University of Texas at Austin Jan-01 PART I CRIMES BURGLARY & THEFT TARGET SECTION

Johns, Russell Taylor

460

The University of Texas at Austin Jan-05 PART I CRIMES Reported Unfounded Actual Cleared % Clrd.  

E-Print Network (OSTI)

The University of Texas at Austin Jan-05 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1/93) #12;The University of Texas at Austin Jan-05 PART I CRIMES BURGLARY & THEFT TARGET SECTION Maintenance - Page 2(Rev. 1/93) #12;The University of Texas at Austin Jan-05 PART I CRIMES BURGLARY & THEFT TARGET

Johns, Russell Taylor

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461

The University of Texas at Austin Jan-10 PART I CRIMES Reported Unfounded Actual Cleared % Clrd.  

E-Print Network (OSTI)

The University of Texas at Austin Jan-10 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1 of Texas at Austin Jan-10 PART I CRIMES BURGLARY & THEFT TARGET SECTION Maintenance Shops Offices 6 OF REPORT DP Form #31 - Page 2(Rev. 1/93) #12;The University of Texas at Austin Jan-10 PART I CRIMES

Johns, Russell Taylor

462

The University of Texas at Austin Jan-02 PART I CRIMES Reported Unfounded Actual Cleared % Clrd.  

E-Print Network (OSTI)

The University of Texas at Austin Jan-02 PART I CRIMES Reported Unfounded Actual Cleared % Clrd. 1 Theft Total $280 $280 Total % Rcvd 0.4% DP Form #31 - Page 1(Rev. 1/93) #12;The University of Texas/93)Co #12;The University of Texas at Austin Jan-02 PART I CRIMES BURGLARY & THEFT TARGET SECTION (List

Johns, Russell Taylor

463

The University of Texas at Austin Jan07 PART I CRIMES Reported Unfounded Actual Cleared % Clrd.  

E-Print Network (OSTI)

The University of Texas at Austin Jan07 PART I CRIMES Reported Unfounded Actual Cleared.1% DP Form #31 Page 1(Rev. 1/93) #12;The University of Texas at Austin Jan07 PART I CRIMES BURGLARY Form #31 Page 2(Rev. 1/93) #12;The University of Texas at Austin Jan07 PART I CRIMES BURGLARY

Johns, Russell Taylor

464

Modeling of Optimal Oil Production and Comparing with Actual and Contractual Oil Production: Iran Case  

E-Print Network (OSTI)

Modeling of Optimal Oil Production and Comparing with Actual and Contractual Oil Production: Iran, Davis Introduction · The Iran Oil Project, initiated in 2007, aims to find the inefficiencies and their possible sources in Iranian oil and gas policies. Background Information Assumptions · Perfect Competition

California at Davis, University of

465

Satellite-Based Actual Evapotranspiration over Drying Semiarid Terrain in West Africa  

Science Conference Proceedings (OSTI)

A simple satellite-based algorithm for estimating actual evaporation based on Makkink’s equation is applied to a seasonal cycle in 2002 at three test sites in Ghana, West Africa: at a location in the humid tropical southern region and two in the ...

D. Schüttemeyer; Ch Schillings; A. F. Moene; H. A. R. de Bruin

2007-01-01T23:59:59.000Z

466

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

467

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...