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1

Univariate time-series forecasting of monthly peak demand of electricity in northern India  

Science Journals Connector (OSTI)

This study forecasts the monthly peak demand of electricity in the northern region of India using univariate time-series techniques namely Multiplicative Seasonal Autoregressive Integrated Moving Average (MSARIMA) and Holt-Winters Multiplicative Exponential Smoothing (ES) for seasonally unadjusted monthly data spanning from April 2000 to February 2007. In-sample forecasting reveals that the MSARIMA model outperforms the ES model in terms of lower root mean square error, mean absolute error and mean absolute percent error criteria. It has been found that ARIMA (2, 0, 0) (0, 1, 1)12 is the best fitted model to explain the monthly peak demand of electricity, which has been used to forecast the monthly peak demand of electricity in northern India, 15 months ahead from February 2007. This will help Northern Regional Load Dispatch Centre to make necessary arrangements a priori to meet the future peak demand.

Sajal Ghosh

2008-01-01T23:59:59.000Z

2

monthly_peak_2003.xls  

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

O Form EIA-411 for 2005 Released: February 7, 2008 Next Update: October 2007 Table 3a . January Monthly Peak Hour Demand, Actual and Projected by North American Electric...

3

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

4

Monthly Generation System Peak (pbl/generation)  

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

Generation > Generation Hydro Power Wind Power Monthly GSP BPA White Book Dry Year Tools Firstgov Monthly Generation System Peak (GSP) This site is no longer maintained. Page last...

5

Optimization of Demand Response Through Peak Shaving , D. Craigie  

E-Print Network (OSTI)

Optimization of Demand Response Through Peak Shaving G. Zakeri , D. Craigie , A. Philpott , M. Todd for the demand response of such a consumer. We will establish a monotonicity result that indicates fuel supply

Todd, Michael J.

6

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.

7

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

8

Multiobjective demand side management solutions for utilities with peak demand deficit  

Science Journals Connector (OSTI)

Abstract Demand side management (DSM) is a growing concept around the world, particularly in urban India, recently due to presence of time of day (TOD) tariffs for the large commercial and industrial customers. Residential customers are not exposed to TOD tariff structure so far in India. This encourages commercial and industrial customers to schedule their flexible loads as per TOD tariff to extract maximum benefit of it and helps utilities to reduce their peak load demand and reshape the load curve. For efficient DSM implementation, this paper presents a multiobjective DSM solutions based on integer genetic algorithm to benefit both utilities and consumers. The proposed algorithm provides new directions on effective implementation of DSM techniques for Indian utilities. Simulations were carried out on Indian practical distribution system with large commercial and industrial loads. The simulation results of the proposed algorithm shows that the presented DSM technique comprehends reasonable savings to both utility and consumers simultaneously, while reducing the system peak.

Nandkishor Kinhekar; Narayana Prasad Padhy; Hari Om Gupta

2014-01-01T23:59:59.000Z

9

THE ROLE OF BUILDING TECHNOLOGIES IN REDUCING AND CONTROLLING PEAK ELECTRICITY DEMAND  

E-Print Network (OSTI)

LBNL-49947 THE ROLE OF BUILDING TECHNOLOGIES IN REDUCING AND CONTROLLING PEAK ELECTRICITY DEMAND? ..................................... 8 What are the seasonal aspects of electric peak demand?............................ 9 What because of the California electricity crisis (Borenstein 2001). Uncertainties surrounding the reliability

10

Reducing Peak Demand to Defer Power Plant Construction in Oklahoma  

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

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...

11

Scalable Scheduling of Building Control Systems for Peak Demand Reduction  

E-Print Network (OSTI)

Behl, Rahul Mangharam and George J. Pappas Department of Electrical and Systems Engineering University operation of sub- systems such as heating, ventilating, air conditioning and refrigeration (HVAC&R) systems is fundamental for their efficient behavior, especially in elec- trical systems and the electric grid [1]. Peak

Pappas, George J.

12

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

SciTech Connect

The objective of this study was to demonstrate the potential for reducing peak-period electrical demand in moderate-weight commercial buildings by modifying the control of the HVAC system. An 80,000 ft{sup 2} office building with a medium-weight building structure and high window-to-wall ratio was used for a case study in which zone temperature set-points were adjusted prior to and during occupancy. HVAC performance data and zone temperatures were recorded using the building control system. Additional operative temperature sensors for selected zones and power meters for the chillers and the AHU fans were installed for the study. An energy performance baseline was constructed from data collected during normal operation. Two strategies for demand shifting using the building thermal mass were then programmed in the control system and implemented progressively over a period of one month. It was found that a simple demand limiting strategy performed well in this building. This strategy involved maintaining zone temperatures at the lower end of the comfort region during the occupied period up until 2 pm. Starting at 2 pm, the zone temperatures were allowed to float to the high end of the comfort region. With this strategy, the chiller power was reduced by 80-100% (1-2.3 W/ft{sup 2}) during normal peak hours from 2-5 pm, without causing any thermal comfort complaints. The effects on the demand from 2-5 pm of the inclusion of pre-cooling prior to occupancy are unclear.

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

2006-08-01T23:59:59.000Z

13

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

SciTech Connect

The objective of this study was to demonstrate the potential for reducing peak-period electrical demand in moderate-weight commercial buildings by modifying the control of the HVAC system. An 80,000 ft{sup 2} office building with a medium-weight building structure and high window-to-wall ratio was used for a case study in which zone temperature set-points were adjusted prior to and during occupancy. HVAC performance data and zone temperatures were recorded using the building control system. Additional operative temperature sensors for selected zones and power meters for the chillers and the AHU fans were installed for the study. An energy performance baseline was constructed from data collected during normal operation. Two strategies for demand shifting using the building thermal mass were then programmed in the control system and implemented progressively over a period of one month. It was found that a simple demand limiting strategy performed well in this building. This strategy involved maintaining zone temperatures at the lower end of the comfort region during the occupied period up until 2 pm. Starting at 2 pm, the zone temperatures were allowed to float to the high end of the comfort region. With this strategy, the chiller power was reduced by 80-100% (1-2.3 W/ft{sup 2}) during normal peak hours from 2-5 pm, without causing any thermal comfort complaints. The effects on the demand from 2-5 pm of the inclusion of pre-cooling prior to occupancy are unclear.

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

2004-08-01T23:59:59.000Z

14

(2013) 128 Data Center Demand Response: Avoiding the Coincident Peak via  

E-Print Network (OSTI)

(2013) 1­28 Data Center Demand Response: Avoiding the Coincident Peak via Workload Shifting.chen@hp.com Abstract Demand response is a crucial aspect of the future smart grid. It has the potential to provide centers' participation in demand response is becoming increasingly important given their high

Wierman, Adam

15

Demand response: a strategy to address residential air-conditioning peak load in Australia  

Science Journals Connector (OSTI)

Rapid growth in electricity network peak demand is increasing pressure for new investment which may be used for only a few hours a year. Residential air-conditioning is widely believed to be the prime cause of...

Robert Smith; Ke Meng; Zhaoyang Dong

2013-12-01T23:59:59.000Z

16

Using Compressed Air Efficiency Projects to Reduce Peak Industrial Electric Demands: Lessons Learned  

E-Print Network (OSTI)

"To help customers respond to the wildly fluctuating energy markets in California, Pacific Gas & Electric (PG&E) initiated an emergency electric demand reduction program in October 2000 to cut electric use during peak periods. One component...

Skelton, J.

17

Duct Leakage Impacts on Airtightness, Infiltration, and Peak Electrical Demand in Florida Homes  

E-Print Network (OSTI)

return leak from the attic can increase cooling electrical demand by 100%. Duct repairs in a typical. electrically heated Florida home reduce winter peak demand by about 1.6 kW per house at about one-sixth the cost of building new electrical generation...

Cummings, J. B.; Tooley, J. J.; Moyer, N.

1990-01-01T23:59:59.000Z

18

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

SciTech Connect

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 30percent 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.

Yin, Rongxin; Kiliccote, Sila; Piette, Mary Ann; Parrish, Kristen

2010-05-14T23:59:59.000Z

19

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

Office of Environmental Management (EM)

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

20

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.

Note: This page contains sample records for the topic "monthly peak demand" 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

Modeling of GE Appliances in GridLAB-D: Peak Demand Reduction  

SciTech Connect

The widespread adoption of demand response enabled appliances and thermostats can result in significant reduction to peak electrical demand and provide potential grid stabilization benefits. GE has developed a line of appliances that will have the capability of offering several levels of demand reduction actions based on information from the utility grid, often in the form of price. However due to a number of factors, including the number of demand response enabled appliances available at any given time, the reduction of diversity factor due to the synchronizing control signal, and the percentage of consumers who may override the utility signal, it can be difficult to predict the aggregate response of a large number of residences. The effects of these behaviors can be modeled and simulated in open-source software, GridLAB-D, including evaluation of appliance controls, improvement to current algorithms, and development of aggregate control methodologies. This report is the first in a series of three reports describing the potential of GE's demand response enabled appliances to provide benefits to the utility grid. The first report will describe the modeling methodology used to represent the GE appliances in the GridLAB-D simulation environment and the estimated potential for peak demand reduction at various deployment levels. The second and third reports will explore the potential of aggregated group actions to positively impact grid stability, including frequency and voltage regulation and spinning reserves, and the impacts on distribution feeder voltage regulation, including mitigation of fluctuations caused by high penetration of photovoltaic distributed generation and the effects on volt-var control schemes.

Fuller, Jason C.; Vyakaranam, Bharat GNVSR; Prakash Kumar, Nirupama; Leistritz, Sean M.; Parker, Graham B.

2012-04-29T23:59:59.000Z

22

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-

23

High-Performance with Solar Electric Reduced Peak Demand: Premier Homes Rancho Cordoba, CA- Building America Top Innovation  

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

This Building America Innovations profile describes Building America solar home research that has demonstrated the ability to reduce peak demand by 75%. Numerous field studies have monitored power production and system effectiveness.

24

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

E-Print Network (OSTI)

INDUSTRIAL-LOAD-SHAPI1IG: TIlE PRACTICE OF AND PROSPECTS FOR UTILITY/INDUSTRY COOPERATION TO MAUGE PEAK ELECTRICITY DEMAND Donald J. BuIes and David E. Rubin Consultants, Pacific Gas and Electric Company San Francisco, California Michael F.... Maniates Energy and Resources Group, University of California Berkeley, California ABSTRACT Load-management programs designed to reduce demand for electricity during peak periods are becoming increasingly important to electric utilities. For a gf...

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

25

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

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

36E 36E Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California R. Yin, S. Kiliccote, M.A. Piette, K. Parrish Environmental Energy Technologies Division May 2010 Presented at the 2010 ACEEE Summer Study on Energy Efficiency in Buildings, Pacific Grove, CA, August 15-20, 2010, and published in the Proceedings DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information,

26

Green Scheduling of Control Systems for Peak Demand Reduction Truong X. Nghiem, Madhur Behl, Rahul Mangharam and George J. Pappas  

E-Print Network (OSTI)

and refrigeration operate independently of each other and frequently result in temporally correlated energy demand of energy demand by scheduling the control systems within a constrained peak while ensuring custom climate and refrigeration (HVAC&R) systems, chiller sys- tems, and lighting systems operate independently of each other

Pappas, George J.

27

,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected...  

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

Organization (MRO)." ," * The MRO, SERC, and SPP regional boundaries were altered as utilities changed reliability organizations. The historical data series " ,"have not been...

28

,"Table 3a. January Monthly Peak Hour Demand, Actual and Projected...  

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

which oversees electric reliability. * NERC Regional names may be found on the EIA web page for electric reliability. " ," * Regional name and function has changed from...

29

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...

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

1987-01-01T23:59:59.000Z

30

Demand side management of a domestic dishwasher: Wind energy gains, financial savings and peak-time load reduction  

Science Journals Connector (OSTI)

Ireland is currently striving to achieve an ambitious target of supplying 40% of electricity demand with renewable energy by 2020. With the vast majority of this being met by wind energy, an intermittent and non-dispatchable energy source, it is inevitable that frequent substantial curtailment will occur during times of excessive generation. This paper investigates the potential for demand side management to limit the requirement for curtailment and further facilitate the integration of renewable energy by shifting the timing of electrical demand in response to various signals including pricing and wind availability. Using a domestic dishwasher as an example, significant increases in the amount of renewable electricity consumed are demonstrated with simultaneous financial savings for the consumer. Furthermore, secondary benefits such as peak-time demand reductions in excess of 60% are observed. The impact of employing demand side management based on imperfect day-ahead market predictions is also analysed and the resulting deficiencies are quantified.

P. Finn; M. OConnell; C. Fitzpatrick

2013-01-01T23:59:59.000Z

31

Dynamic Control of Electricity Cost with Power Demand Smoothing and Peak Shaving for Distributed Internet Data Centers  

E-Print Network (OSTI)

Dynamic Control of Electricity Cost with Power Demand Smoothing and Peak Shaving for Distributed a major part of their running costs. Modern electric power grid provides a feasible way to dynamically and efficiently manage the electricity cost of distributed IDCs based on the Locational Marginal Pricing (LMP

Rahman, A.K.M. Ashikur

32

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

Massachusetts at Amherst, University of

33

Property:OpenEI/UtilityRate/FlatDemandMonth2 | Open Energy Information  

Open Energy Info (EERE)

FlatDemandMonth2 FlatDemandMonth2 Jump to: navigation, search This is a property of type Number. The allowed values for this property are: 1 2 3 4 5 6 7 8 9 Pages using the property "OpenEI/UtilityRate/FlatDemandMonth2" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 1 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 1 + 00101108-073b-4503-9cd4-01769611c26f + 1 + 001361ca-50d2-49bc-b331-08755a2c7c7d + 1 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 1 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 1 + 001d1952-955c-411b-8ce4-3d146852a75e + 1 + 001ea8be-7a59-4bcb-a923-e8f1015946ee + 1 + 001eaca9-6ce7-4c0f-8578-44fc29654e97 + 1 + 0022e9a5-942c-4e97-94d7-600f5d315ce8 + 1 + 002661b8-2e71-48b8-b657-44ff7372f757 + 1 + 0026b4d3-dd02-4423-95e1-56430d887b28 + 2 +

34

Property:OpenEI/UtilityRate/FlatDemandMonth4 | Open Energy Information  

Open Energy Info (EERE)

FlatDemandMonth4 FlatDemandMonth4 Jump to: navigation, search This is a property of type Number. The allowed values for this property are: 1 2 3 4 5 6 7 8 9 Pages using the property "OpenEI/UtilityRate/FlatDemandMonth4" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 1 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 1 + 00101108-073b-4503-9cd4-01769611c26f + 1 + 001361ca-50d2-49bc-b331-08755a2c7c7d + 1 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 1 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 1 + 001d1952-955c-411b-8ce4-3d146852a75e + 1 + 001ea8be-7a59-4bcb-a923-e8f1015946ee + 1 + 001eaca9-6ce7-4c0f-8578-44fc29654e97 + 1 + 0022e9a5-942c-4e97-94d7-600f5d315ce8 + 1 + 002661b8-2e71-48b8-b657-44ff7372f757 + 1 + 0026b4d3-dd02-4423-95e1-56430d887b28 + 2 +

35

Property:OpenEI/UtilityRate/FlatDemandMonth7 | Open Energy Information  

Open Energy Info (EERE)

FlatDemandMonth7 FlatDemandMonth7 Jump to: navigation, search This is a property of type Number. The allowed values for this property are: 1 2 3 4 5 6 7 8 9 Pages using the property "OpenEI/UtilityRate/FlatDemandMonth7" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 1 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 1 + 00101108-073b-4503-9cd4-01769611c26f + 1 + 001361ca-50d2-49bc-b331-08755a2c7c7d + 1 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 1 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 1 + 001d1952-955c-411b-8ce4-3d146852a75e + 1 + 001ea8be-7a59-4bcb-a923-e8f1015946ee + 1 + 001eaca9-6ce7-4c0f-8578-44fc29654e97 + 1 + 0022e9a5-942c-4e97-94d7-600f5d315ce8 + 1 + 002661b8-2e71-48b8-b657-44ff7372f757 + 1 + 0026b4d3-dd02-4423-95e1-56430d887b28 + 1 +

36

Property:OpenEI/UtilityRate/FlatDemandMonth1 | Open Energy Information  

Open Energy Info (EERE)

FlatDemandMonth1 FlatDemandMonth1 Jump to: navigation, search This is a property of type Number. The allowed values for this property are: 1 2 3 4 5 6 7 8 9 Pages using the property "OpenEI/UtilityRate/FlatDemandMonth1" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 1 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 1 + 00101108-073b-4503-9cd4-01769611c26f + 1 + 001361ca-50d2-49bc-b331-08755a2c7c7d + 1 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 1 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 1 + 001d1952-955c-411b-8ce4-3d146852a75e + 1 + 001ea8be-7a59-4bcb-a923-e8f1015946ee + 1 + 001eaca9-6ce7-4c0f-8578-44fc29654e97 + 1 + 0022e9a5-942c-4e97-94d7-600f5d315ce8 + 1 + 002661b8-2e71-48b8-b657-44ff7372f757 + 1 + 0026b4d3-dd02-4423-95e1-56430d887b28 + 2 +

37

Property:OpenEI/UtilityRate/FlatDemandMonth6 | Open Energy Information  

Open Energy Info (EERE)

FlatDemandMonth6 FlatDemandMonth6 Jump to: navigation, search This is a property of type Number. The allowed values for this property are: 1 2 3 4 5 6 7 8 9 Pages using the property "OpenEI/UtilityRate/FlatDemandMonth6" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 1 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 1 + 00101108-073b-4503-9cd4-01769611c26f + 1 + 001361ca-50d2-49bc-b331-08755a2c7c7d + 1 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 1 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 1 + 001d1952-955c-411b-8ce4-3d146852a75e + 1 + 001ea8be-7a59-4bcb-a923-e8f1015946ee + 1 + 001eaca9-6ce7-4c0f-8578-44fc29654e97 + 1 + 0022e9a5-942c-4e97-94d7-600f5d315ce8 + 1 + 002661b8-2e71-48b8-b657-44ff7372f757 + 1 + 0026b4d3-dd02-4423-95e1-56430d887b28 + 1 +

38

Property:OpenEI/UtilityRate/FlatDemandMonth5 | Open Energy Information  

Open Energy Info (EERE)

FlatDemandMonth5 FlatDemandMonth5 Jump to: navigation, search This is a property of type Number. The allowed values for this property are: 1 2 3 4 5 6 7 8 9 Pages using the property "OpenEI/UtilityRate/FlatDemandMonth5" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 1 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 1 + 00101108-073b-4503-9cd4-01769611c26f + 1 + 001361ca-50d2-49bc-b331-08755a2c7c7d + 1 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 1 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 1 + 001d1952-955c-411b-8ce4-3d146852a75e + 1 + 001ea8be-7a59-4bcb-a923-e8f1015946ee + 1 + 001eaca9-6ce7-4c0f-8578-44fc29654e97 + 1 + 0022e9a5-942c-4e97-94d7-600f5d315ce8 + 1 + 002661b8-2e71-48b8-b657-44ff7372f757 + 1 + 0026b4d3-dd02-4423-95e1-56430d887b28 + 1 +

39

Property:OpenEI/UtilityRate/FixedDemandChargeMonth1 | Open Energy  

Open Energy Info (EERE)

Fixed Demand Charge Month 1 Fixed Demand Charge Month 1 Pages using the property "OpenEI/UtilityRate/FixedDemandChargeMonth1" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 7 + 00101108-073b-4503-9cd4-01769611c26f + 1.71 + 0030a241-5084-4404-9fe4-ed558aad8b59 + 8.28 + 0049111b-fba2-46ba-827d-7ce95609a1d9 + 9.51 + 0055db46-f535-4dc9-a192-920d1bdf382b + 3.2 + 0070a37f-0d41-4331-8115-df40c62e00f3 + 13.24 + 007f7b1f-0cba-450c-9023-df962aa387a4 + 5.28 + 008960d4-14ad-4822-b293-140640cf0bcf + 4.924 + 00cdded9-47a1-49b6-a217-10941ffbefc6 + 1.468 + 00e0b930-90c6-43c2-971a-91dade33f76a + 3.35 + 010f37ad-90a9-4aa8-bbdf-c55e72ee1495 + 4.74 + 017a32a0-140a-4e0b-a10c-f6f67905829c + 4.5 + 019941c8-cc3b-452c-b12e-201301099603 + 11.95 +

40

Property:OpenEI/UtilityRate/FlatDemandMonth3 | Open Energy Information  

Open Energy Info (EERE)

FlatDemandMonth3 FlatDemandMonth3 Jump to: navigation, search This is a property of type Number. The allowed values for this property are: 1 2 3 4 5 6 7 8 9 Pages using the property "OpenEI/UtilityRate/FlatDemandMonth3" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 1 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 1 + 00101108-073b-4503-9cd4-01769611c26f + 1 + 001361ca-50d2-49bc-b331-08755a2c7c7d + 1 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 1 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 1 + 001d1952-955c-411b-8ce4-3d146852a75e + 1 + 001ea8be-7a59-4bcb-a923-e8f1015946ee + 1 + 001eaca9-6ce7-4c0f-8578-44fc29654e97 + 1 + 0022e9a5-942c-4e97-94d7-600f5d315ce8 + 1 + 002661b8-2e71-48b8-b657-44ff7372f757 + 1 + 0026b4d3-dd02-4423-95e1-56430d887b28 + 2 +

Note: This page contains sample records for the topic "monthly peak demand" 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

Chapter 10, Peak Demand and Time-Differentiated Energy Savings Cross-Cutting Protocols: The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures  

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

0: Peak Demand and 0: Peak Demand and Time-Differentiated Energy Savings Cross-Cutting Protocols Frank Stern, Navigant Consulting Subcontract Report NREL/SR-7A30-53827 April 2013 The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures 10 - 1 Chapter 10 - Table of Contents 1 Introduction .............................................................................................................................2 2 Purpose of Peak Demand and Time-differentiated Energy Savings .......................................3 3 Key Concepts ..........................................................................................................................5 4 Methods of Determining Peak Demand and Time-Differentiated Energy Impacts ...............7

42

Phase-Change Frame Walls (PCFWs) for Peak Demand Reduction, Load Shifting, Energy Conservation and Comfort  

E-Print Network (OSTI)

) for lowering peak heat transfer rates across walls of residential and small commercial buildings. A PCFW is a typical wall in which phase change materials (PCMs) have been incorporated via macroencapsulation to enhance the energy storage capabilities...

Medina, M.; Stewart, R.

43

Property:OpenEI/UtilityRate/FlatDemandMonth8 | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:OpenEI/UtilityRate/FlatDemandMonth8 Jump to: navigation, search This is a property of type Number. The allowed values for this property are: 1 2 3 4 5 6 7 8 9 Pages using the property "OpenEI/UtilityRate/FlatDemandMonth8" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 1 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 1 + 00101108-073b-4503-9cd4-01769611c26f + 1 + 001361ca-50d2-49bc-b331-08755a2c7c7d + 1 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 1 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 1 + 001d1952-955c-411b-8ce4-3d146852a75e + 1 + 001ea8be-7a59-4bcb-a923-e8f1015946ee + 1 + 001eaca9-6ce7-4c0f-8578-44fc29654e97 + 1 + 0022e9a5-942c-4e97-94d7-600f5d315ce8 + 1 +

44

Property:OpenEI/UtilityRate/FixedDemandChargeMonth11 | Open Energy  

Open Energy Info (EERE)

Name: Fixed Demand Charge Month 11 Pages using the property "OpenEI/UtilityRate/FixedDemandChargeMonth11" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 7 + 00101108-073b-4503-9cd4-01769611c26f + 1.71 + 0030a241-5084-4404-9fe4-ed558aad8b59 + 8.28 + 0049111b-fba2-46ba-827d-7ce95609a1d9 + 9.51 + 0055db46-f535-4dc9-a192-920d1bdf382b + 3.2 + 0070a37f-0d41-4331-8115-df40c62e00f3 + 13.24 + 007f7b1f-0cba-450c-9023-df962aa387a4 + 5.28 + 008960d4-14ad-4822-b293-140640cf0bcf + 4.924 + 00cdded9-47a1-49b6-a217-10941ffbefc6 + 1.468 + 00e0b930-90c6-43c2-971a-91dade33f76a + 3.35 + 010f37ad-90a9-4aa8-bbdf-c55e72ee1495 + 4.74 + 017a32a0-140a-4e0b-a10c-f6f67905829c + 4.5 + 019941c8-cc3b-452c-b12e-201301099603 + 11.95 +

45

Property:OpenEI/UtilityRate/FixedDemandChargeMonth12 | Open Energy  

Open Energy Info (EERE)

Name: Fixed Demand Charge Month 12 Pages using the property "OpenEI/UtilityRate/FixedDemandChargeMonth12" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 7 + 00101108-073b-4503-9cd4-01769611c26f + 1.71 + 0030a241-5084-4404-9fe4-ed558aad8b59 + 8.28 + 0049111b-fba2-46ba-827d-7ce95609a1d9 + 9.51 + 0055db46-f535-4dc9-a192-920d1bdf382b + 3.2 + 0070a37f-0d41-4331-8115-df40c62e00f3 + 13.24 + 007f7b1f-0cba-450c-9023-df962aa387a4 + 5.28 + 008960d4-14ad-4822-b293-140640cf0bcf + 4.924 + 00cdded9-47a1-49b6-a217-10941ffbefc6 + 1.468 + 00e0b930-90c6-43c2-971a-91dade33f76a + 3.35 + 010f37ad-90a9-4aa8-bbdf-c55e72ee1495 + 4.74 + 017a32a0-140a-4e0b-a10c-f6f67905829c + 4.5 + 019941c8-cc3b-452c-b12e-201301099603 + 11.95 +

46

Property:OpenEI/UtilityRate/FixedDemandChargeMonth10 | Open Energy  

Open Energy Info (EERE)

Name: Fixed Demand Charge Month 10 Pages using the property "OpenEI/UtilityRate/FixedDemandChargeMonth10" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 7 + 00101108-073b-4503-9cd4-01769611c26f + 1.71 + 0030a241-5084-4404-9fe4-ed558aad8b59 + 10.59 + 0049111b-fba2-46ba-827d-7ce95609a1d9 + 9.51 + 0055db46-f535-4dc9-a192-920d1bdf382b + 3.2 + 0070a37f-0d41-4331-8115-df40c62e00f3 + 13.24 + 007f7b1f-0cba-450c-9023-df962aa387a4 + 5.28 + 008960d4-14ad-4822-b293-140640cf0bcf + 4.924 + 00cdded9-47a1-49b6-a217-10941ffbefc6 + 1.468 + 00e0b930-90c6-43c2-971a-91dade33f76a + 2.71 + 010f37ad-90a9-4aa8-bbdf-c55e72ee1495 + 4.74 + 017a32a0-140a-4e0b-a10c-f6f67905829c + 4.5 + 019941c8-cc3b-452c-b12e-201301099603 + 11.95 +

47

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

E-Print Network (OSTI)

on Energy Efficiency in Buildings, American Council for an Energy Efficient Economy, Washington D.C., Vol. 9, p. 1, August, 1992. Akbari, H., Bretz, S., Kurn, D.M. and Hanford, J., ?Peak Power and Cooling Energy Savings of High Albedo Roofs,? Energy... positive pressure dehumidified air ventilation in hot humid climates, quiet exhaust fan ventilation in cool climates, solar water heaters, heat pump water heaters, high efficiency right sized heating/cooling equipment, and gas fired combo space...

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

2002-01-01T23:59:59.000Z

48

Monitoring System Used to Identify, Track and Allocate Peak Demand Costs  

E-Print Network (OSTI)

leasing space on the site. The most common way to distribute monthly electric costs within a facility when consumption by area or department is available through submetering or other means, is to apply the average cost per KWH from the utility bill...

Holmes, W. A.

49

Peak Oil Demand: The Role of Fuel Efficiency and Alternative Fuels in a Global Oil Production Decline  

Science Journals Connector (OSTI)

Peak Oil Demand: The Role of Fuel Efficiency and Alternative Fuels in a Global Oil Production Decline ... (11) Another analysis suggests that a transition to hydrogen- and natural-gas-fueled vehiclesand the associated climate benefitswill partly be driven by dwindling oil supplies. ... Within each class, we do not attempt to predict the exact substitute that will dominate (for example, whether electricity, hydrogen fuel cells, or natural gas will prevail in the passenger car market), but rather model the aggregate contribution of alternatives to conventional oil. ...

Adam R. Brandt; Adam Millard-Ball; Matthew Ganser; Steven M. Gorelick

2013-05-22T23:59:59.000Z

50

Development and validation of regression models to predict monthly heating demand for residential buildings  

Science Journals Connector (OSTI)

The present research work concerns development of regression models to predict the monthly heating demand for single-family residential sector in temperate climates, with the aim to be used by architects or design engineers as support tools in the very first stage of their projects in finding efficiently energetic solutions. Another interest to use such simplified models is to make it possible a very quick parametric study in order to optimize the building structure versus environmental or economic criteria. All the energy prediction models were based on an extended database obtained by dynamic simulations for 16 major cities of France. The inputs for the regression models are the building shape factor, the building envelope U-value, the window to floor area ratio, the building time constant and the climate which is defined as function of the sol-air temperature and heating set-point. If the neural network (NN) methods could give precise representations in predicting energy use, with the advantage that they are capable of adjusting themselves to unexpected pattern changes in the incoming data, the multiple regression analysis was also found to be an efficient method, nevertheless with the requirement that an extended database should be used for the regression. The validation is probably the most important level when trying to find prediction models, so 270 different scenarios are analysed in this research work for different inputs of the models. It has been established that the energy equations obtained can do predictions quite well, a maximum deviation between the predicted and the simulated is noticed to be 5.1% for Nice climate, with an average error of 2%. In this paper, we also show that is possible to predict the building heating demand even for more complex scenarios, when the construction is adjacent to non-heated spaces, basements or roof attics.

Tiberiu Catalina; Joseph Virgone; Eric Blanco

2008-01-01T23:59:59.000Z

51

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

Science Journals Connector (OSTI)

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

Nabeel I.A. Tawalbeh

2012-01-01T23:59:59.000Z

52

Control Strategy for Domestic Water Heaters during Peak Periods and its Impact on the Demand for Electricity  

Science Journals Connector (OSTI)

Because they store hot water, water heaters are easily-shifted loads that can be controlled to reduce peak demands. However, load shifting may have some detrimental consequences on the domestic hot water supply temperature if the heating element is deactivated for a long period of time. Furthermore, a new peak may be caused if a significant number of heaters are reactivated at the same time. This study presents a control strategy for water heaters that minimizes the pick-up demand when the heating elements are reactivated at the end of a load shifting period and that ensures, in all cases, the client's hot water supply. The study is based on a simulation model of a water heater that was experimentally validated and takes into account the diversity of the population's hot water withdrawal profile. More specifically, the data of 8,167 real water withdrawal profiles of several clients were input into the simulation model in order to evaluate the performance of water heaters under different operating conditions.

Alain Moreau

2011-01-01T23:59:59.000Z

53

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

54

Using energy audits to investigate the impacts of common air-conditioning design and installation issues on peak power demand and energy consumption in Austin, Texas  

Science Journals Connector (OSTI)

This study presents an analysis of a unique dataset of 4971 energy audits performed on homes in Austin, Texas in 20092010. We quantify the prevalence of typical air-conditioner design and installation issues such as low efficiency, oversizing, duct leakage, and low measured capacity, and estimate the impacts that resolving these issues would have on peak power demand and cooling energy consumption. We estimate that air-conditioner use in single-family residences currently accounts for 1718% of peak demand in Austin, and we found that improving equipment efficiency alone could save up to 205MW, or 8%, of peak demand. We estimate that 31% of systems in this study were oversized, leading to up to 41MW of excess peak demand. Replacing oversized systems with correctly sized higher efficiency units has the potential for further savings of up to 81MW. We estimate that the mean system could achieve 18% and 20% in cooling energy savings by sealing duct leaks and servicing their air-conditioning units to achieve 100% of nominal capacity, respectively. Although this analysis is limited to the City of Austin, understanding the methods described herein could allow electric utilities in similar climates to make better-informed decisions when considering efficiency improvement programs.

Joshua D. Rhodes; Brent Stephens; Michael E. Webber

2011-01-01T23:59:59.000Z

55

The Costs, Air Quality, and Human Health Effects of Meeting Peak Electricity Demand with Installed Backup Generators  

Science Journals Connector (OSTI)

E.G. thanks John Dawson, Rob Pinder, and Pavan Racherla for assistance with the PMCAMx model, and Janet Joseph, Peter Savio, and Gunnar Walmet from NYSERDA for useful information about backup generators and emergency demand response programs in New York City. ...

Elisabeth A. Gilmore; Lester B. Lave; Peter J. Adams

2006-10-21T23:59:59.000Z

56

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: November 2011 Regional Wholesale Markets: November 2011 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the U.S. The range of daily prices and demand data is shown for the report month and for the year ending with the report month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest

57

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: December 2011 Regional Wholesale Markets: December 2011 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the nation. The range of daily prices and demand data is shown for the report month and for the year ending with the report month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest

58

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: January 2012 Regional Wholesale Markets: January 2012 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the nation. The range of daily prices and demand data is shown for the report month and for the year ending with the report month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest

59

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: October 2011 Regional Wholesale Markets: October 2011 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the U.S. The range of daily prices and demand data is shown for the report month and for the year ending with the report month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest

60

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: March 2012 Regional Wholesale Markets: March 2012 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the Nation. The range of daily prices and demand data is shown for the report month and for the year ending with the report month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest

Note: This page contains sample records for the topic "monthly peak demand" 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

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: February 2012 Regional Wholesale Markets: February 2012 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the Nation. The range of daily prices and demand data is shown for the report month and for the year ending with the report month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest

62

The impact of peak oil on tourism in Spain: An inputoutput analysis of price, demand and economy-wide effects  

Science Journals Connector (OSTI)

This article examines the potential effects of peak oil on Spanish tourism and indirectly on the rest of the economy. We construct several scenarios of price increases in oil, related fossil fuels and their inflationary effects. These scenarios provide the context for an inputoutput (I/O) analysis which uses I/O tables extended with Tourism Satellite Accounts. The analysis comprises three steps: (1) applying an I/O price model to estimate the price change of tourism services in Spain due to an increase in the prices of oil and other fossil fuels; (2) assessing the effects of price changes on demand for tourism services; and (3) estimating the impacts of demand change on the country's economy using an I/O demand model. The results show that a decreased demand for tourism services results in the greatest fall in outputs in the tourism-related shares of air, water, land and railway transport sectors. These are followed by tourism agencies' activities, non-market recreational, cultural and sporting activities, restaurants, and hotels. Depending on the oil price scenario adopted, GDP (Gross domestic product) decreases between?0.08% and?0.38% and the number of jobs lost through direct and indirect effects varies between approximately 20,000 and 100,000.

Ivana Logar; Jeroen C.J.M. van den Bergh

2013-01-01T23:59:59.000Z

63

Statewide Electrical Energy Cost Savings and Peak Demand Reduction from the IECC Code-Compliant, Single-Family Residences in Texas (2002-2009)  

E-Print Network (OSTI)

peaking plant (i.e., capacity savings), the calculated demand savings in MW were then multiplied by the average capital cost of natural gas combined cycle power plant, $1,165 per kW (Kaplan, 2008) using a 15% reserve margin (Faruqui et al. 2007... to the 2001 and 2006 IECC codes. 72?F Heating, 75?F CoolingSpace Temperature Set point (Simulation adjustment3: Heating 72F, Cooling 75F) (b) Heat Pump House: 0.904 360 0.88 kW (Simulation adjustment3: 1.095 kW) HVAC System Type (a) Electric/Gas...

Kim, H; Baltazar, J.C.; Haberl, J.

64

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: September 2011 Regional Wholesale Markets: September 2011 The United States. has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the U.S. The range of daily price and demand data is shown for the month of September 2011 and for the year ending on September 30, 2011. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest (Palo Verde) and

65

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

at work. The recent, more widespread implementation of energy efficiency and demand response programs in many markets has undoubtedly dampened peak demand levels compared to...

66

Peak Oil  

Science Journals Connector (OSTI)

Wissenschaftliche Voraussagen deuten auf Peak Oil, das Maximum globaler Erdlfrderung, in unserer ... der demokratischen Systeme fhren. Psychoanalytische Betrachtung darf Peak Oil fr die Zivilisation als e...

Dr. Manuel Haus; Dr. med. Christoph Biermann

2013-03-01T23:59:59.000Z

67

Electricity Monthly Update  

Annual Energy Outlook 2012 (EIA)

Update November 28, 2012 Map of Electric System Selected for Daily Peak Demand was replaced with the correct map showing Selected Wholesale Electricity and Natural Gas Locations....

68

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

District Small Business Summer Solutions: Energy and DemandSummer Solutions: Energy and Demand Impacts Monthly Energy> B-2 Coordination of Energy Efficiency and Demand Response

Goldman, Charles

2010-01-01T23:59:59.000Z

69

Electricity Monthly Update  

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

Wholesale Markets: October 2014 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale...

70

Electricity Monthly Update  

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

Wholesale Markets: September 2014 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale...

71

Electricity Monthly Update  

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

Wholesale Markets: August 2014 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale...

72

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Wholesale Markets: February 2014 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale...

73

Peak Oil  

Science Journals Connector (OSTI)

At the start of the new millennium, the expression Peak Oil was unknown. Nevertheless, a discussion about when the worlds rate of oil production would reach its maximum had already ... . King Hubbert presented...

Kjell Aleklett

2012-01-01T23:59:59.000Z

74

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"

75

Demand Response | Department of Energy  

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

Demand Response Demand Response Demand Response Demand Response Demand response provides an opportunity for consumers to play a significant role in the operation of the electric grid by reducing or shifting their electricity usage during peak periods in response to time-based rates or other forms of financial incentives. Demand response programs are being used by electric system planners and operators as resource options for balancing supply and demand. Such programs can lower the cost of electricity in wholesale markets, and in turn, lead to lower retail rates. Methods of engaging customers in demand response efforts include offering time-based rates such as time-of-use pricing, critical peak pricing, variable peak pricing, real time pricing, and critical peak rebates. It also includes direct load control programs which provide the

76

Demand Response: Load Management Programs  

E-Print Network (OSTI)

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

Simon, J.

2012-01-01T23:59:59.000Z

77

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

78

Demand Reduction  

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

Grantees may use funds to coordinate with electricity supply companies and utilities to reduce energy demands on their power systems. These demand reduction programs are usually coordinated through...

79

Demand Response Projects: Technical and Market Demonstrations  

E-Print Network (OSTI)

Demand Response Projects: Technical and Market Demonstrations Philip D. Lusk Deputy Director Energy Analyst #12;PLACE CAPTION HERE. #12;#12;#12;#12;City of Port Angeles Demand Response History energy charges · Demand charges during peak period only ­ Reduced demand charges for demand response

80

demand | OpenEI  

Open Energy Info (EERE)

demand demand 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

Note: This page contains sample records for the topic "monthly peak demand" 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

Energy dispatch schedule optimization for demand charge reduction using a photovoltaic-battery storage system with solar forecasting  

Science Journals Connector (OSTI)

Abstract A battery storage dispatch strategy that optimizes demand charge reduction in real-time was developed and the discharge of battery storage devices in a grid-connected, combined photovoltaic-battery storage system (PV+system) was simulated for a summer month, July 2012, and a winter month, November 2012, in an operational environment. The problem is formulated as a linear programming (LP; or linear optimization) routine and daily minimization of peak non-coincident demand is sought to evaluate the robustness, reliability, and consistency of the battery dispatch algorithm. The LP routine leverages solar power and load forecasts to establish a load demand target (i.e., a minimum threshold to which demand can be reduced using a photovoltaic (PV) array and battery array) that is adjusted throughout the day in response to forecast error. The LP routine perfectly minimizes demand charge but forecasts errors necessitate adjustments to the perfect dispatch schedule. The PV+system consistently reduced non-coincident demand on a metered load that has an elevated diurnal (i.e., daytime) peak. The average reduction in peak demand on weekdays (days that contain the elevated load peak) was 25.6% in July and 20.5% in November. By itself, the PV array (excluding the battery array) reduced the peak demand on average 19.6% in July and 11.4% in November. PV alone cannot perfectly mitigate load spikes due to inherent variability; the inclusion of a storage device reduced the peak demand a further 6.0% in July and 9.3% in November. Circumstances affecting algorithm robustness and peak reduction reliability are discussed.

R. Hanna; J. Kleissl; A. Nottrott; M. Ferry

2014-01-01T23:59:59.000Z

82

Monthly Reports  

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

month. Should you have questions about the EM Monthly Reports please contact envmgt@nv.doe.gov or call (702) 295-3521. October 2012 November 2012 December 2012 January 2013...

83

Monthly Reports  

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

month. Should you have questions about the EM Monthly Reports please contact envmgt@nv.doe.gov or call (702) 295-3521. October 2013 November 2013 December 2013 January 2014...

84

Assessment of Demand Response and Advanced Metering  

E-Print Network (OSTI)

#12;#12;2008 Assessment of Demand Response and Advanced Metering Staff Report Federal Energy metering penetration and potential peak load reduction from demand response have increased since 2006. Significant activity to promote demand response or to remove barriers to demand response occurred at the state

Tesfatsion, Leigh

85

Demand Side Management in Rangan Banerjee  

E-Print Network (OSTI)

Demand Side Management in Industry Rangan Banerjee Talk at Baroda in Birla Corporate Seminar August 31,2007 #12;Demand Side Management Indian utilities ­ energy shortage and peak power shortage. Supply for Options ­ Demand Side Management (DSM) & Load Management #12;DSM Concept Demand Side Management (DSM) - co

Banerjee, Rangan

86

Decentralized demand management for water distribution  

E-Print Network (OSTI)

. Actual Daily Demand for Model 2 . . 26 4 Predicted vs. Actual Peak Hourly Demand for Model 1 27 5 Predicted vs. Actual Peak Hourly Demand for Model 2 28 6 Cumulative Hourly Demand Distribution 7 Bryan Distribution Network 8 Typical Summer Diurnal... locating and controlling water that has not been accounted for. The Ford Meter Box Company (1987) advises the testing and recalibration of existing water meters. Because operating costs in a distribution network can be quite substantial, a significant...

Zabolio, Dow Joseph

2012-06-07T23:59:59.000Z

87

Preliminary Assumptions for Natural Gas Peaking  

E-Print Network (OSTI)

Preliminary Assumptions for Natural Gas Peaking Technologies Gillian Charles and Steve Simmons GRAC, Reciprocating Engines Next steps 2 #12;Definitions Baseload Energy: power generated (or conserved) across a period of time to serve system demands for electricity Peaking Capacity: capability of power generating

88

Energy demand  

Science Journals Connector (OSTI)

The basic forces pushing up energy demand are population increase and economic growth. From ... of these it is possible to estimate future energy requirements.

Geoffrey Greenhalgh

1980-01-01T23:59:59.000Z

89

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.

90

Optimal Sizing of Energy Storage and Photovoltaic Power Systems for Demand Charge Mitigation (Poster)  

SciTech Connect

Commercial facility utility bills are often a strong function of demand charges -- a fee proportional to peak power demand rather than total energy consumed. In some instances, demand charges can constitute more than 50% of a commercial customer's monthly electricity cost. While installation of behind-the-meter solar power generation decreases energy costs, its variability makes it likely to leave the peak load -- and thereby demand charges -- unaffected. This then makes demand charges an even larger fraction of remaining electricity costs. Adding controllable behind-the-meter energy storage can more predictably affect building peak demand, thus reducing electricity costs. Due to the high cost of energy storage technology, the size and operation of an energy storage system providing demand charge management (DCM) service must be optimized to yield a positive return on investment (ROI). The peak demand reduction achievable with an energy storage system depends heavily on a facility's load profile, so the optimal configuration will be specific to both the customer and the amount of installed solar power capacity. We explore the sensitivity of DCM value to the power and energy levels of installed solar power and energy storage systems. An optimal peak load reduction control algorithm for energy storage systems will be introduced and applied to historic solar power data and meter load data from multiple facilities for a broad range of energy storage system configurations. For each scenario, the peak load reduction and electricity cost savings will be computed. From this, we will identify a favorable energy storage system configuration that maximizes ROI.

Neubauer, J.; Simpson, M.

2013-10-01T23:59:59.000Z

91

A proposed methodology for medium-range maximum demand anticipation and application  

Science Journals Connector (OSTI)

One to three years' anticipation of monthly and weekly peak demand is required to prepare maintenance schedules, develop power pooling agreements, select peaking capacity and provide data required by certain reliability coordinating centers. A total monthly forecast of the maximum demand is deduced and computed for the three years up to April 1981. This is accomplished for an important electrical network in Egypt. The anticipated maximum demand is executed for El-Mehalla El-Kubra city network. This network has an industrial and residential daily load characteristic. Direct monthly maximum demand forecasting is executed by separate treatment of weather-independent and weather-induced demand. The required forecast is derived by two methodologies: the probabilistic extrapolation-correlation, and that suggested by the authors. Daily and monthly data have been collected for more reliable determination of weather load models. Complete analysis, discussion and comments on the results are presented, and the results compared. This comparison reveals that an acceptable and reasonable percentage error is obtained on applying the proposed methodology.

M.S. Kandil; M.Helmy El-Maghraby; H. El-Dosouky

1981-01-01T23:59:59.000Z

92

Desert Peak EGS Project  

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

Desert Peak EGS Project presentation at the April 2013 peer review meeting held in Denver, Colorado.

93

Summary of the 2006 Automated Demand Response Pilot  

E-Print Network (OSTI)

This paper discusses the specific concept for, design of, and results from a pilot program to automate demand response with critical peak pricing. California utilities have been exploring the use of critical peak pricing (CPP) to help reduce peak...

Piette, M.; Kiliccote, S.

2007-01-01T23:59:59.000Z

94

Both Distillate Supply and Demand Reached Extraordinary Levels This Winter  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: This chart shows some critical differences in distillate supply and demand during this winter heating season, in comparison to the past two winters. Typically, distillate demand peaks during the winter months, but "new supply" (refinery production and net imports) cannot increase as much, so the remaining supply needed is drawn from inventories. This pattern is evident in each of the past two winter heating seasons. This winter, however, the pattern was very different, for several reasons: With inventories entering the season at extremely low levels, a "typical" winter stockdraw would have been nearly impossible, particularly in the Northeast, the region most dependent on heating oil. Demand reached near-record levels in December, as colder-than-normal

95

THE STATE OF DEMAND RESPONSE IN CALIFORNIA  

E-Print Network (OSTI)

THE STATE OF DEMAND RESPONSE IN CALIFORNIA Prepared For: California Energy in this report. #12; ABSTRACT By reducing system loads during criticalpeak times, demand response (DR) can.S. and internationally and lay out ideas that could help move California forward. KEY WORDS demand response, peak

96

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

97

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

98

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

99

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

100

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

Note: This page contains sample records for the topic "monthly peak demand" 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

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

102

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

103

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

104

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

105

High-Performance with Solar Electric Reduced Peak Demand: Premier...  

Energy Savers (EERE)

Rancho Cordoba, CA More Documents & Publications High-Performance Home Technologies: Solar Thermal & Photovoltaic Systems; Volume 6 Building America Best Practices Series Zero...

106

Economics of Peak Oil  

Science Journals Connector (OSTI)

Abstract Peak oil refers to the future decline in world production of crude oil and the accompanying potentially calamitous effects. The peak oil literature typically rejects economic analysis. This article argues that economic analysis is indeed appropriate for analyzing oil scarcity because standard economic models can replicate the observed peaks in oil production. Moreover, the emphasis on peak oil is misplaced as peaking is not a good indicator of scarcity, peak oil techniques are overly simplistic, the catastrophes predicted by the peak oil literature are unlikely, and the literature does not contribute to correcting identified market failures. Efficiency of oil markets could be improved by instead focusing on remedying market failures such as excessive private discount rates, environmental externalities, market power, insufficient innovation incentives, incomplete futures markets, and insecure property rights.

S.P. Holland

2013-01-01T23:59:59.000Z

107

Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

page intentionally left blank page intentionally left blank 69 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Transportation Demand Module The NEMS Transportation Demand Module estimates transportation energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), buses, freight and passenger aircraft, freight and passenger rail, freight shipping, and miscellaneous

108

Definition: Demand Side Management | Open Energy Information  

Open Energy Info (EERE)

Side Management Side Management Jump to: navigation, search Dictionary.png Demand Side Management The term for all activities or programs undertaken by Load-Serving Entity or its customers to influence the amount or timing of electricity they use.[1] View on Wikipedia Wikipedia Definition Energy demand management, also known as demand side management (DSM), is the modification of consumer demand for energy through various methods such as financial incentives and education. Usually, the goal of demand side management is to encourage the consumer to use less energy during peak hours, or to move the time of energy use to off-peak times such as nighttime and weekends. Peak demand management does not necessarily decrease total energy consumption, but could be expected to reduce the need

109

Overview of Demand Response  

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

08 PJM 08 PJM www.pjm.com ©2003 PJM Overview of Demand Response PJM ©2008 PJM www.pjm.com ©2003 PJM Growth, Statistics, and Current Footprint AEP, Dayton, ComEd, & DUQ Dominion Generating Units 1,200 + Generation Capacity 165,000 MW Peak Load 144,644 MW Transmission Miles 56,070 Area (Square Miles) 164,250 Members 500 + Population Served 51 Million Area Served 13 States and DC Generating Units 1,200 + Generation Capacity 165,000 MW Peak Load 144,644 MW Transmission Miles 56,070 Area (Square Miles) 164,250 Members 500 + Population Served 51 Million Area Served 13 States and DC Current PJM RTO Statistics Current PJM RTO Statistics PJM Mid-Atlantic Integrations completed as of May 1 st , 2005 ©2008 PJM

110

building demand | OpenEI  

Open Energy Info (EERE)

demand demand 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

111

Best practices and research for handling demand response security issues in the smart grid.  

E-Print Network (OSTI)

??When electricity demand is peak, utilities and other electric Independent Systems Operators (ISOs) keep electric generators on-line in order to meet the high demand. In (more)

Asavachivanthornkul, Prakarn

2010-01-01T23:59:59.000Z

112

Demand Response  

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

Assessment for Eastern Interconnection Youngsun Baek, Stanton W. Hadley, Rocio Martinez, Gbadebo Oladosu, Alexander M. Smith, Fran Li, Paul Leiby and Russell Lee Prepared for FY12 DOE-CERTS Transmission Reliability R&D Internal Program Review September 20, 2012 2 Managed by UT-Battelle for the U.S. Department of Energy DOE National Laboratory Studies Funded to Support FOA 63 * DOE set aside $20 million from transmission funding for national laboratory studies. * DOE identified four areas of interest: 1. Transmission Reliability 2. Demand Side Issues 3. Water and Energy 4. Other Topics * Argonne, NREL, and ORNL support for EIPC/SSC/EISPC and the EISPC Energy Zone is funded through Area 4. * Area 2 covers LBNL and NREL work in WECC and

113

Demand Response and Open Automated Demand Response  

E-Print Network (OSTI)

LBNL-3047E Demand Response and Open Automated Demand Response Opportunities for Data Centers G described in this report was coordinated by the Demand Response Research Center and funded by the California. Demand Response and Open Automated Demand Response Opportunities for Data Centers. California Energy

114

Peak power ratio generator  

DOE Patents (OSTI)

A peak power ratio generator is described for measuring, in combination with a conventional power meter, the peak power level of extremely narrow pulses in the gigahertz radio frequency bands. The present invention in a preferred embodiment utilizes a tunnel diode and a back diode combination in a detector circuit as the only high speed elements. The high speed tunnel diode provides a bistable signal and serves as a memory device of the input pulses for the remaining, slower components. A hybrid digital and analog loop maintains the peak power level of a reference channel at a known amount. Thus, by measuring the average power levels of the reference signal and the source signal, the peak power level of the source signal can be determined.

Moyer, Robert D. (Albuquerque, NM)

1985-01-01T23:59:59.000Z

115

Economic effects of peak oil  

Science Journals Connector (OSTI)

Assuming that global oil production peaked, this paper uses scenario analysis to show the economic effects of a possible supply shortage and corresponding rise in oil prices in the next decade on different sectors in Germany and other major economies such as the US, Japan, China, the OPEC or Russia. Due to the price-inelasticity of oil demand the supply shortage leads to a sharp increase in oil prices in the second scenario, with high effects on GDP comparable to the magnitude of the global financial crises in 2008/09. Oil exporting countries benefit from high oil prices, whereas oil importing countries are negatively affected. Generally, the effects in the third scenario are significantly smaller than in the second, showing that energy efficiency measures and the switch to renewable energy sources decreases the countries' dependence on oil imports and hence reduces their vulnerability to oil price shocks on the world market.

Christian Lutz; Ulrike Lehr; Kirsten S. Wiebe

2012-01-01T23:59:59.000Z

116

Measuring the capacity impacts of demand response  

SciTech Connect

Critical peak pricing and peak time rebate programs offer benefits by increasing system reliability, and therefore, reducing capacity needs of the electric power system. These benefits, however, decrease substantially as the size of the programs grows relative to the system size. More flexible schemes for deployment of demand response can help address the decreasing returns to scale in capacity value, but more flexible demand response has decreasing returns to scale as well. (author)

Earle, Robert; Kahn, Edward P.; Macan, Edo

2009-07-15T23:59:59.000Z

117

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

118

Security and privacy in demand response systems in smart grid.  

E-Print Network (OSTI)

??Demand response programs are used in smart grid to improve stability of the electric grid and to reduce consumption of electricity and costs during peak (more)

Paranjpe, Mithila

2011-01-01T23:59:59.000Z

119

How to Get More Response from Demand Response  

SciTech Connect

Despite all the rhetoric, demand response's contribution to meet peak load will remain elusive in the absence of enabling technology and standardized business protocols. (author)

Neumann, Scott; Sioshansi, Fereidoon; Vojdani, Ali; Yee, Gaymond

2006-10-15T23:59:59.000Z

120

LNG production for peak shaving operations  

SciTech Connect

LNG production facilities are being developed as an alternative or in addition to underground storage throughout the US to provide gas supply during peak gas demand periods. These facilities typically involved a small liquefaction unit with a large LNG storage tank and gas sendout facilities capable of responding to peak loads during the winter. Black and Veatch is active in the development of LNG peak shaving projects for clients using a patented mixed refrigerant technology for efficient production of LNG at a low installed cost. The mixed refrigerant technology has been applied in a range of project sizes both with gas turbine and electric motor driven compression systems. This paper will cover peak shaving concepts as well as specific designs and projects which have been completed to meet this market need.

Price, B.C.

1999-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "monthly peak demand" 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

Demand Response Research in Spain  

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

Demand Response Research in Spain Demand Response Research in Spain Speaker(s): Iñigo Cobelo Date: August 22, 2007 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Mary Ann Piette The Spanish power system is becoming increasingly difficult to operate. The peak load grows every year, and the permission to build new transmission and distribution infrastructures is difficult to obtain. In this scenario Demand Response can play an important role, and become a resource that could help network operators. The present deployment of demand response measures is small, but this situation however may change in the short term. The two main Spanish utilities and the transmission network operator are designing research projects in this field. All customer segments are targeted, and the research will lead to pilot installations and tests.

122

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...

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

1987-01-01T23:59:59.000Z

123

Potential Peak Load Reductions From Residential Energy Efficient Upgrades  

E-Print Network (OSTI)

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...

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

2002-01-01T23:59:59.000Z

124

Commercial & Industrial Demand Response  

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

Resources News & Events Expand News & Events Skip navigation links Smart Grid Demand Response Agricultural Residential Demand Response Commercial & Industrial Demand Response...

125

High Temperatures & Electricity Demand  

E-Print Network (OSTI)

High Temperatures & Electricity Demand An Assessment of Supply Adequacy in California Trends.......................................................................................................1 HIGH TEMPERATURES AND ELECTRICITY DEMAND.....................................................................................................................7 SECTION I: HIGH TEMPERATURES AND ELECTRICITY DEMAND ..........................9 BACKGROUND

126

Desert Peak EGS Project  

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

Geothermal Technologies Program 2010 Peer Review Desert Peak EGS Project, for the Engineered Geothermal Systems Demonstration Projects and Innovative Exploration Technologies. Objective to stimulate permeability in tight well 27-15 and improve connection to rest of the field; improve overall productivity or injectivity. Successful stimulation yields more production and enables more power generation.

127

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Highlights: August 2011 Highlights: August 2011 Extreme heat in Texas, New Mexico, Colorado and Arizona drove significant increases in the retail sales of electricity in the Southwest. Wind generation increased in much of the United States, except the middle of the country where total generation declined. Bituminous coal stocks dropped 14% from August 2010. Key indicators Same Month 2010 Year to date Total Net Generation -1% 11% Residential Retail Price -6% 11% Cooling Degree-Days -3% 2% Natural Gas Price, Henry Hub -6% -9% Bituminous Coal Stocks -14% -14% Subbituminous Coal Stocks -10% -17% Heat wave drives record demand and wholesale prices in Texas A prolonged August heat wave in Texas stressed available generating capacity and produced very high wholesale prices in the Electric

128

Smart (In-home) Power Scheduling for Demand Response on the Smart Grid  

E-Print Network (OSTI)

1 Smart (In-home) Power Scheduling for Demand Response on the Smart Grid Gang Xiong, Chen Chen consumption are part of demand response, which relies on varying price of electricity to reduce peak demand

Yener, Aylin

129

Residential Energy Demand Reduction Analysis and Monitoring Platform - REDRAMP  

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

Dramatic Peak Residential Dramatic Peak Residential Demand Reduction in the Desert Southwest Yahia Baghzouz Center for Energy Research University of Nevada, Las Vegas Golden, CO Overview * Project description * Subdivision energy efficiency features * Home energy monitoring * Demand side management * Feeder loading * Battery Energy Storage System * Future Work Team Members Project Objective and Methodology * The main objective is to reduce peak power demand of a housing subdivision by 65% (compared to housing development that is built to conventional code). * This objective will be achieved by - Energy efficient home construction with roof- integrated PV system - Demand Side Management - Battery Energy Storage System Project schematic Diagram Project Physical Location: Las Vegas, NV Red Rock Hotel/Casino

130

Demand Shifting With Thermal Mass in Large Commercial Buildings: Case  

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

Demand Shifting With Thermal Mass in Large Commercial Buildings: Case Demand Shifting With Thermal Mass in Large Commercial Buildings: Case Studies and Tools Speaker(s): Peng Xu Date: March 9, 2007 - 12:00pm Location: 90-3122 The idea of pre-cooling and demand limiting is to pre-cool buildings at night or in the morning during off-peak hours, storing cooling energy in the building thermal mass and thereby reducing cooling loads during the peak periods. Savings are achieved by reducing on-peak energy and demand charges. The potential for utilizing building thermal mass for load shifting and peak demand reduction has been demonstrated in a number of simulation, laboratory, and field studies. Case studies in a number of office buildings in California has found that a simple demand limiting strategy reduced the chiller power by 20-100% (0.5-2.3W/ft2) during six

131

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

ScienceCinema (OSTI)

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

Piette, Mary Ann

2011-04-28T23:59:59.000Z

132

Field Demonstration of Automated Demand Response for Both Winter and Summer Events in Large Buildings in the Pacific Northwest  

E-Print Network (OSTI)

Power Administration (BPA), Seattle City Light (SCL),s Bonneville Power Administration (BPA) to meet peak demand.Although BPA has historically been able to meet peak load

Piette, Mary Ann

2014-01-01T23:59:59.000Z

133

Opportunities and Challenges for Data Center Demand Response  

E-Print Network (OSTI)

Opportunities and Challenges for Data Center Demand Response Adam Wierman Zhenhua Liu Iris Liu of renewable energy into the grid as well as electric power peak-load shaving: data center demand response. Data center demand response sits at the intersection of two growing fields: energy efficient data

Wierman, Adam

134

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data in California and for climate zones within those areas. The staff California Energy Demand 2008-2018 forecast

135

MonthlyReport1stQrtr  

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

35 35 0 0 0 35 Number of charging events² 800 0 0 0 800 Electricity consumed (AC MWh) 5.25 0.00 0.00 0.00 5.25 Percent of time with a vehicle connected to charging unit 36% 0% 0% 0% 36% Percent of time with a vehicle drawing power from charging unit 7% 0% 0% 0% 7% Max electricity demand across all days Min electricity demand across all days Electricity demand on single calendar day with highest peak Max percentage of charging units connected across all days Min percentage of charging units connected across all days Percentage of charging units connected on single calendar day with peak electricity demand Region: All Report period: January 2011 through March 2011 Number of EV Project vehicles in region: 35 5/19/2011 5:37:48 PM INL/LTD-11-22097 1 of 2 © 2011 ECOtality

136

MonthlyReport2ndQrtr  

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

955 955 0 11 0 966 Number of charging events² 35,134 0 56 0 35,190 Electricity consumed (AC MWh) 248.96 0.00 0.25 0.00 249.22 Percent of time with a vehicle connected to charging unit 30% 0% 5% 0% 30% Percent of time with a vehicle drawing power from charging unit 6% 0% 1% 0% 6% Max electricity demand across all days Min electricity demand across all days Electricity demand on single calendar day with highest peak Max percentage of charging units connected across all days Min percentage of charging units connected across all days Percentage of charging units connected on single calendar day with peak electricity demand Region: ALL Report period: April 2011 through June 2011 Number of EV Project vehicles in region: 956 8/10/2011 1:13:31 PM INL/LTD-11-22097 © 2011 ECOtality

137

Advanced Demand Responsive Lighting  

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

Demand Demand Responsive Lighting Host: Francis Rubinstein Demand Response Research Center Technical Advisory Group Meeting August 31, 2007 10:30 AM - Noon Meeting Agenda * Introductions (10 minutes) * Main Presentation (~ 1 hour) * Questions, comments from panel (15 minutes) Project History * Lighting Scoping Study (completed January 2007) - Identified potential for energy and demand savings using demand responsive lighting systems - Importance of dimming - New wireless controls technologies * Advanced Demand Responsive Lighting (commenced March 2007) Objectives * Provide up-to-date information on the reliability, predictability of dimmable lighting as a demand resource under realistic operating load conditions * Identify potential negative impacts of DR lighting on lighting quality Potential of Demand Responsive Lighting Control

138

Electricity Demand and Energy Consumption Management System  

E-Print Network (OSTI)

This project describes the electricity demand and energy consumption management system and its application to the Smelter Plant of Southern Peru. It is composted of an hourly demand-forecasting module and of a simulation component for a plant electrical system. The first module was done using dynamic neural networks, with backpropagation training algorithm; it is used to predict the electric power demanded every hour, with an error percentage below of 1%. This information allows management the peak demand before this happen, distributing the raise of electric load to other hours or improving those equipments that increase the demand. The simulation module is based in advanced estimation techniques, such as: parametric estimation, neural network modeling, statistic regression and previously developed models, which simulates the electric behavior of the smelter plant. These modules allow the proper planning because it allows knowing the behavior of the hourly demand and the consumption patterns of the plant, in...

Sarmiento, Juan Ojeda

2008-01-01T23:59:59.000Z

139

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.

140

Coordination of Energy Efficiency and Demand Response  

SciTech Connect

This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025. Improving energy efficiency in our homes, businesses, schools, governments, and industries - which consume more than 70 percent of the nation's natural gas and electricity - is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that 'the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW' by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

Goldman, Charles; Reid, Michael; Levy, Roger; Silverstein, Alison

2010-01-29T23:59:59.000Z

Note: This page contains sample records for the topic "monthly peak demand" 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

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

Addressing Energy Demand through Demand Response:both the avoided energy costs (and demand charges) as wellCoordination of Energy Efficiency and Demand Response,

Shen, Bo

2013-01-01T23:59:59.000Z

142

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

benefits of Demand Side Management (DSM) are insufficient toefficiency, demand side management (DSM) cost effectivenessResearch Center Demand Side Management Demand Side Resources

Heffner, Grayson

2010-01-01T23:59:59.000Z

143

Pacific Northwest Demand Response Project Lee Hall, BPA Smart Grid Program Manager  

E-Print Network (OSTI)

Pacific Northwest Demand Response Project Lee Hall, BPA Smart Grid Program Manager February 14 utilities to invest in DR Regional situational analysis � issues to address #12;Nationally � Demand ResponseSource: FERC Demand Response & Advanced Metering Report, February 2011 Peak DR 65,000 MW 1,062 MW Peak DR

144

Coordination of Energy Efficiency and Demand Response  

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

Coordination of Energy Efficiency and Demand Response Coordination of Energy Efficiency and Demand Response Title Coordination of Energy Efficiency and Demand Response Publication Type Report Refereed Designation Unknown Year of Publication 2010 Authors Goldman, Charles A., Michael Reid, Roger Levy, and Alison Silverstein Pagination 74 Date Published 01/2010 Publisher LBNL City Berkeley Keywords electricity markets and policy group, energy analysis and environmental impacts department Abstract This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025.1 Improving energy efficiency in our homes, businesses, schools, governments, and industries-which consume more than 70 percent of the nation's natural gas and electricity-is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that "the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW" by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

145

Petroleum Marketing Monthly  

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

Crude oil prices U.S. Energy Information Administration | Petroleum Marketing Monthly 3 December 2014...

146

Mass Market Demand Response  

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

Mass Market Demand Response Mass Market Demand Response Speaker(s): Karen Herter Date: July 24, 2002 - 12:00pm Location: Bldg. 90 Demand response programs are often quickly and poorly crafted in reaction to an energy crisis and disappear once the crisis subsides, ensuring that the electricity system will be unprepared when the next crisis hits. In this paper, we propose to eliminate the event-driven nature of demand response programs by considering demand responsiveness a component of the utility obligation to serve. As such, demand response can be required as a condition of service, and the offering of demand response rates becomes a requirement of utilities as an element of customer service. Using this foundation, we explore the costs and benefits of a smart thermostat-based demand response system capable of two types of programs: (1) a mandatory,

147

Demand Response Assessment INTRODUCTION  

E-Print Network (OSTI)

Demand Response Assessment INTRODUCTION This appendix provides more detail on some of the topics raised in Chapter 4, "Demand Response" of the body of the Plan. These topics include 1. The features, advantages and disadvantages of the main options for stimulating demand response (price mechanisms

148

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

149

winter_peak_2005.xls  

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

2b . Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, 2005 and Projected 2006 through 2010 (Megawatts and 2005 Base Year)...

150

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

151

Electric Power Monthly  

Gasoline and Diesel Fuel Update (EIA)

Electric Power Monthly > Electric Power Monthly Back Issues Electric Power Monthly > Electric Power Monthly Back Issues Electric Power Monthly Back Issues Monthly Excel files zipped 2010 January February March April May June July August September October November December 2009 January February March April May June July August September October November December 2008 January February March March Supplement April May June July August September October November December 2007 January February March April May June July August September October November December 2006 January February March April May June July August September October November December 2005 January February March April May June July August September October November December

152

Electricity Monthly Update  

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

Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and...

153

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

the country last July, while temperatures in July 2014 were closer to average. This led to a decrease in demand for electricity generation in July 2014, with total...

154

Providing Regulation Services and Managing Data Center Peak Power Budgets  

E-Print Network (OSTI)

-based peak shaving. However, none of these publications consider the feasibility of using the energy storage AND RELATED WORK Substantial integration of electric vehicles and renewable energy sources into the electric utility companies use to ensure stability. It includes multiple mechanisms, such as demand-response (DR

Simunic, Tajana

155

Green Scheduling: Scheduling of Control Systems for Peak Power Reduction  

E-Print Network (OSTI)

approach to fine-grained coordination of energy demand by scheduling energy consuming control systems of the system variables only, control system execution (i.e. when energy is supplied to the system-Scheduling; Energy Systems; Peak Power Reduction; Load Balancing; I. INTRODUCTION During a major sporting event

Pappas, George J.

156

The use of systematic reviews to analyse demand-side management policy  

Science Journals Connector (OSTI)

Demand-side management (DSM) seeks to reduce overall energy ... change when energy is used to reduce peak demands and smooth the load curve. DSM is ... and carbon emissions reduction. However, the policy side of ...

Peter Warren

2014-06-01T23:59:59.000Z

157

Electricity Monthly Update  

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

by almost 10%, or just over 12 million tons, to 136 million tons. This is the largest month-to-month percentage increase since at least January 2009. In absolute terms,...

158

MSC Monthly Performance Report  

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

Department of Energy Contract DE-AC06-09RL14728 MSC Monthly Performance Report AUG 2013 DOERL-2009-113 Rev 47 ii This page intentionally left blank. CONTENTS MSC Monthly...

159

Monthly Performance Report  

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

Department of Energy Contract DE-AC06-09RL14728 MSC Monthly Performance Report OCT 2013 DOERL-2009-113 Rev 49 ii This page intentionally left blank. CONTENTS MSC Monthly...

160

Monthly Performance Report  

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

Department of Energy Contract DE-AC06-09RL14728 MSC Monthly Performance Report DEC 2013 DOERL-2009-113 Rev 51 ii This page intentionally left blank. CONTENTS MSC Monthly...

Note: This page contains sample records for the topic "monthly peak demand" 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

Monthly Performance Report  

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

Department of Energy Contract DE-AC06-09RL14728 MSC Monthly Performance Report APR 2013 DOERL-2009-113 Rev 43 ii This page intentionally left blank. CONTENTS MSC Monthly...

162

Monthly Performance Report  

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

Department of Energy Contract DE-AC06-09RL14728 MSC Monthly Performance Report JUN 2013 DOERL-2009-113 Rev 45 ii This page intentionally left blank. CONTENTS MSC Monthly...

163

Monthly Performance Report  

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

Department of Energy Contract DE-AC06-09RL14728 MSC Monthly Performance Report JUL 2013 DOERL-2009-113 Rev 46 ii This page intentionally left blank. CONTENTS MSC Monthly...

164

Monthly Performance Report  

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

Department of Energy Contract DE-AC06-09RL14728 MSC Monthly Performance Report MAY 2013 DOERL-2009-113 Rev 44 ii This page intentionally left blank. CONTENTS MSC Monthly...

165

Monthly Performance Report  

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

Department of Energy Contract DE-AC06-09RL14728 MSC Monthly Performance Report SEP 2013 DOERL-2009-113 Rev 48 ii This page intentionally left blank. CONTENTS MSC Monthly...

166

Monthly Performance Report  

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

Department of Energy Contract DE-AC06-09RL14728 MSC Monthly Performance Report FEB 2013 DOERL-2009-113 Rev 41 ii This page intentionally left blank. CONTENTS MSC Monthly...

167

Monthly Performance Report  

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

Department of Energy Contract DE-AC06-09RL14728 MSC Monthly Performance Report NOV 2013 DOERL-2009-113 Rev 50 ii This page intentionally left blank. CONTENTS MSC Monthly...

168

Monthly Newsblast December 2012  

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

In the December 2012 Monthly Newsblast, read about a new funding opportunity, recyling Christmas trees, upcoming events, and more.

169

Monthly Performance Report  

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

4.72 4.59 4.62 4.63 4.44 First Aid Monthly First Aid 12-Month Average FY 3.65 CY 3.33 EXECUTIVE OVERVIEW EXECUTIVE OVERVIEW MSC Monthly Performance Report APR 2014 DOE...

170

Monthly Energy Review The Monthly Energy Review  

Gasoline and Diesel Fuel Update (EIA)

use use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the MER and in other EIA publications. Related Publication: Readers of the MER may also be interested in EIA's Annual Energy Review, where many of the same data series are provided annually beginning with 1949. Contact our National Energy Information Center at 202-586-8800 for more information. Timing of Release: MER data are normally released in the afternoon of the third-from-the-last workday of each month and are usually available electronically late that day. Internet Addresses: E-Mail: infoctr@eia.doe.gov World Wide Web Site: http://www.eia.doe.gov Gopher Site: gopher://gopher.eia.doe.gov FTP Site: ftp://ftp.eia.doe.gov The Monthly Energy Review (ISSN 0095-7356) is published monthly by the Energy Information

171

Evaluation of Conservation Voltage Reduction as a tool for demand side management.  

E-Print Network (OSTI)

??To ensure stability of the power grid, electricity supply and demand must remain in balance in real time. Traditionally utilities, call upon peaking power plants (more)

Dorrody, Ali

2014-01-01T23:59:59.000Z

172

National Action Plan on Demand Response  

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

David Kathan, Ph.D David Kathan, Ph.D Federal Energy Regulatory Commission U.S. DOE Electricity Advisory Committee October 29, 2010 Demand Response as Power System Resources The author's views do not necessarily represent the views of the Federal Energy Regulatory Commission 2 Demand Response * FERC (Order 719) defines demand response as: - A reduction in the consumption of electric energy by customers from their expected consumption in response to an increase in the price of electric energy or to in incentive payments designed to induce lower consumption of electric energy. * The National Action Plan on Demand Response released by FERC staff broadens this definition to include - Consumer actions that can change any part of the load profile of a utility or region, not just the period of peak usage

173

Software demonstration: Demand Response Quick Assessment Tool  

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

Software demonstration: Demand Response Quick Assessment Tool Software demonstration: Demand Response Quick Assessment Tool Speaker(s): Peng Xu Date: February 4, 2008 - 12:00pm Location: 90-3122 The potential for utilizing building thermal mass for load shifting and peak demand reduction has been demonstrated in a number of simulation, laboratory, and field studies. The Demand Response Quick Assessment Tools developed at LBNL will be demonstrated. The tool is built on EnergyPlus simulation and is able to evaluate and compare different DR strategies, such as global temperature reset, chiller cycling, supply air temperature reset, etc. A separate EnergyPlus plotting tool will also be demonstrated during this seminar. Users can use the tool to test EnergyPlus models, conduct parametric analysis, or compare multiple EnergyPlus simulation

174

Demand response enabling technology development  

E-Print Network (OSTI)

Demand Response Enabling Technology Development Phase IEfficiency and Demand Response Programs for 2005/2006,Application to Demand Response Energy Pricing SenSys 2003,

2006-01-01T23:59:59.000Z

175

Demand Response Spinning Reserve Demonstration  

E-Print Network (OSTI)

F) Enhanced ACP Date RAA ACP Demand Response SpinningReserve Demonstration Demand Response Spinning Reservesupply spinning reserve. Demand Response Spinning Reserve

2007-01-01T23:59:59.000Z

176

Cross-sector Demand Response  

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

Resources News & Events Expand News & Events Skip navigation links Smart Grid Demand Response Agricultural Residential Demand Response Commercial & Industrial Demand Response...

177

Demand Response Programs for Oregon  

E-Print Network (OSTI)

Demand Response Programs for Oregon Utilities Public Utility Commission May 2003 Public Utility ....................................................................................................................... 1 Types of Demand Response Programs............................................................................ 3 Demand Response Programs in Oregon

178

Demand response enabling technology development  

E-Print Network (OSTI)

behavior in developing a demand response future. Phase_II_Demand Response Enabling Technology Development Phase IIYi Yuan The goal of the Demand Response Enabling Technology

Arens, Edward; Auslander, David; Huizenga, Charlie

2008-01-01T23:59:59.000Z

179

Automated Demand Response and Commissioning  

E-Print Network (OSTI)

Fully-Automated Demand Response Test in Large Facilities14in DR systems. Demand Response using HVAC in Commercialof Fully Automated Demand Response in Large Facilities

Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

2005-01-01T23:59:59.000Z

180

Open Automated Demand Response for Small Commerical Buildings  

SciTech Connect

This report characterizes small commercial buildings by market segments, systems and end-uses; develops a framework for identifying demand response (DR) enabling technologies and communication means; and reports on the design and development of a low-cost OpenADR enabling technology that delivers demand reductions as a percentage of the total predicted building peak electric demand. The results show that small offices, restaurants and retail buildings are the major contributors making up over one third of the small commercial peak demand. The majority of the small commercial buildings in California are located in southern inland areas and the central valley. Single-zone packaged units with manual and programmable thermostat controls make up the majority of heating ventilation and air conditioning (HVAC) systems for small commercial buildings with less than 200 kW peak electric demand. Fluorescent tubes with magnetic ballast and manual controls dominate this customer group's lighting systems. There are various ways, each with its pros and cons for a particular application, to communicate with these systems and three methods to enable automated DR in small commercial buildings using the Open Automated Demand Response (or OpenADR) communications infrastructure. Development of DR strategies must consider building characteristics, such as weather sensitivity and load variability, as well as system design (i.e. under-sizing, under-lighting, over-sizing, etc). Finally, field tests show that requesting demand reductions as a percentage of the total building predicted peak electric demand is feasible using the OpenADR infrastructure.

Dudley, June Han; Piette, Mary Ann; Koch, Ed; Hennage, Dan

2009-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "monthly peak demand" 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

Demand Response In California  

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

Presentation covers the demand response in California and is given at the FUPWG 2006 Fall meeting, held on November 1-2, 2006 in San Francisco, California.

182

Energy Demand Forecasting  

Science Journals Connector (OSTI)

This chapter presents alternative approaches used in forecasting energy demand and discusses their pros and cons. It... Chaps. 3 and 4 ...

S. C. Bhattacharyya

2011-01-01T23:59:59.000Z

183

summer_peak_2004.xls  

Annual Energy Outlook 2012 (EIA)

(Megawatts and 2004 Base Year) Summer Noncoincident Peak Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year ECAR FRCC MAAC MAIN...

184

winter_peak_2003.xls  

Gasoline and Diesel Fuel Update (EIA)

and 2003 Base Year) Winter Noncoincident Peak Load Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year ECAR FRCC MAAC MAIN...

185

summer_peak_2003.xls  

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

(Megawatts and 2003 Base Year) Summer Noncoincident Peak Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year ECAR FRCC MAAC MAIN...

186

winter_peak_2004.xls  

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

and 2004 Base Year) Winter Noncoincident Peak Load Contiguous U.S. Eastern Power Grid Texas Power Grid Western Power Grid Projected Year Base Year ECAR FRCC MAAC MAIN...

187

Demand side management in smart grid: A review and proposals for future direction  

Science Journals Connector (OSTI)

Abstract This paper mainly focuses on demand side management and demand response, including drivers and benefits, shiftable load scheduling methods and peak shaving techniques. Demand side management techniques found in literature are overviewed and a novel electricity demand control technique using real-time pricing is proposed. Currently users have no means to change their power consumption to benefit the whole system. The proposed method consists of modern system identification and control that would enable user side load control. This would potentially balance demand side with supply side more effectively and would also reduce peak demand and make the whole system more efficient.

Linas Gelazanskas; Kelum A.A. Gamage

2014-01-01T23:59:59.000Z

188

National Cybersecurity Awareness Month  

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

National Cybersecurity Awareness Month (NCSAM) October 2013 Every October, the Department of Energy joins the Department of Homeland Security (DHS) and others across the country...

189

Monthly News Blast  

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

Multimedia Corner Monthly News Blast July 2013 Secretaries Moniz and Vilsack Speaking at Biomass 2013 Secretary of Energy Ernest Moniz and Secretary of Agriculture Tom Vilsack...

190

Petroleum Marketing Monthly  

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

U.S. Refi ner wholesale petroleum product volumes U.S. Energy Information Administration | Petroleum Marketing Monthly 13 December 2014...

191

Petroleum Marketing Monthly  

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

U.S. Refi ner retail petroleum product volumes U.S. Energy Information Administration | Petroleum Marketing Monthly 9 December 2014...

192

Petroleum Marketing Monthly  

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

U.S. Refi ner retail petroleum product prices U.S. Energy Information Administration | Petroleum Marketing Monthly 7 December 2014...

193

Electricity Monthly Update  

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

See all Electricity Reports Electricity Monthly Update With Data for September 2014 | Release Date: Nov. 25, 2014 | Next Release Date: Dec. 23, 2014 Previous Issues Issue:...

194

Electricity Monthly Update  

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

See all Electricity Reports Electricity Monthly Update With Data for October 2014 | Release Date: Dec. 23, 2014 | Next Release Date: Jan. 26, 2015 Previous Issues Issue:...

195

MSC Monthly Performance Report  

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

month of January, ISMS Phase I activities continued, as scheduled. The Senior Management Review Board completed its evaluation on January 15, 2010, and notified MSA management...

196

Electricity Monthly Update  

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

See all Electricity Reports Electricity Monthly Update With Data for August 2014 | Release Date: Oct. 24, 2014 | Next Release Date: Nov. 24, 2014 Previous Issues Issue: October...

197

Peak Power Reduction Strategies for the Lighting Systems in Government Buildings  

E-Print Network (OSTI)

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...

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

2010-01-01T23:59:59.000Z

198

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2035. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA

199

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are further subdivided into the energy- intensive manufacturing industries and non-energy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process-flow or end-use accounting procedure, whereas the non- manufacturing industries are modeled with substantially less detail. The petroleum refining industry is not included in the Industrial Demand Module, as it is simulated separately in the Petroleum Market Module of NEMS. The Industrial Demand Module calculates energy consumption for the four Census Regions (see Figure 5) and disaggregates the energy consumption

200

RTP Customer Demand Response  

Science Journals Connector (OSTI)

This paper provides new evidence on customer demand response to hourly pricing from the largest and...real-time pricing...(RTP) program in the United States. RTP creates value by inducing load reductions at times...

Steven Braithwait; Michael OSheasy

2002-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "monthly peak demand" 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

World Energy Demand  

Science Journals Connector (OSTI)

A reliable forecast of energy resources, energy consumption, and population in the future is a ... So, instead of absolute figures about future energy demand and sources worldwide, which would become...3.1 correl...

Giovanni Petrecca

2014-01-01T23:59:59.000Z

202

Transportation Demand This  

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

Transportation Demand Transportation Demand This page inTenTionally lefT blank 75 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Transportation Demand Module The NEMS Transportation Demand Module estimates transportation energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific and associated technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), buses, freight and passenger aircraft, freight

203

Optimal Demand Bidding for Time-Shiftable Loads Hamed Mohsenian-Rad, Senior Member, IEEE  

E-Print Network (OSTI)

and enhancing demand response and peak-load shaving programs. In this paper, we seek to answer the following], [6], intelligent pools [7], irrigation pumps [8], water heaters [9], batch processes in data centers loads have recently received a great deal of attention due to their role in demand response and peak

Mohsenian-Rad, Hamed

204

Monthly Biodiesel Production Report  

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

Monthly Biodiesel Production Monthly Biodiesel Production Report November 2013 With Data for September 2013 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Monthly Biodiesel Production Report This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or

205

Economic vulnerability to Peak Oil  

Science Journals Connector (OSTI)

Abstract Peak Oil, which refers to the maximum possible global oil production rate, is increasingly gaining attention in both science and policy discourses. However, little is known about how this phenomenon will impact economies, despite its apparent imminence and potential dangers. In this paper, we construct a vulnerability map of the U.S. economy, combining two approaches for analyzing economic systems, i.e. inputoutput analysis and social network analysis (applied to economic data). Our approach reveals the relative importance of individual economic sectors, and how vulnerable they are to oil price shocks. As such, our dual-analysis helps identify which sectors, due to their strategic position, could put the entire U.S. economy at risk from Peak Oil. For the U.S., such sectors would include Iron Mills, Fertilizer Production and Transport by Air. Our findings thus provide early warnings to downstream companies about potential trouble in their supply chain, and inform policy action for Peak Oil. Although our analysis is embedded in a Peak Oil narrative, it is just as valid and useful in the context of developing a climate roadmap toward a low carbon economy.

Christian Kerschner; Christina Prell; Kuishuang Feng; Klaus Hubacek

2013-01-01T23:59:59.000Z

206

Petroleum Supply Monthly Archives  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Supply Monthly Petroleum Supply Monthly Petroleum Supply Monthly Archives With Data for December 2011 | Release Date: February 29, 2012 Changes to Table 26. "Production of Crude Oil by PAD District and State": Current State-level data are now included in Table 26, in addition to current U.S. and PAD District sums. State offshore production for Louisiana, Texas, Alaska, and California, which are included in the State totals, are no longer reported separately in a "State Offshore Production" category. Previously, State-level values lagged 2 months behind the U.S. and PAD District values. Beginning with this publication, they will be on the same cycle. Also included in this publication are two additional pages for Table 26 that provide October and November data. With the release of

207

Historical Monthly Energy Review  

Gasoline and Diesel Fuel Update (EIA)

73-92) 73-92) Distribution Category UC-950 Historical Monthly Energy Review 1973-1992 Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. The information contained herein should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. Historical Monthly Energy Review The Historical Monthly Energy Review (HMER) presents monthly and annual data from 1973 through 1992 on production, consumption, stocks, imports, exports, and prices of the principal energy commodities in the United States. Also included are data on international

208

Petroleum Marketing Monthly  

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

Information Administration, Form EIA-782A, "Refi ners'Gas Plant Operators' Monthly Petroleum Product Sales Report." Source: U. U. U. U S. S S S S E E E Ene ne erg r r y y y In n...

209

Petroleum Marketing Monthly  

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

U.S. Refi ner wholesale petroleum product prices Source: U.S. Energy Information Administration, Form EIA-782A, "Refi ners'Gas Plant Operators' Monthly Petroleum Product Sales...

210

Petroleum Marketing Monthly  

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

acquisition cost for crude oil declined 3.34 (3.5 percent), to 92.27 per barrel. Petroleum products Motor gasoline * September monthly average prices for refi ner sales of...

211

ORSSAB monthly board meeting  

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

The ORSSAB monthly board meeting is open to the public. The board will hear a presentation and discuss the development of a comprehensive mercury strategy for the Oak Ridge Reservation.

212

Natural Gas Monthly  

Reports and Publications (EIA)

Highlights activities, events, and analyses associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer related activities and underground storage data are also reported.

2014-01-01T23:59:59.000Z

213

Disability Employment Awareness Month  

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

Utilizing the talents of all Americans is essential for our Nation to out-innovate, out-educate, and out-build the rest of the world. During National Disability Employment Awareness Month, we...

214

Petroleum Marketing Monthly  

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

See footnotes at end of table. U.S. Energy Information Administration | Petroleum Marketing Monthly 14 December 2014 Table 6. U.S. refi ner motor gasoline prices by grade and...

215

MSC Monthly Performance Report  

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

be completed by the end of Calendar Year 2009. EXECUTIVE OVERVIEW MSC Monthly Performance Report November 2009 DOERL-2009-113 REV 2 4 2.0 ANALYSIS OF FUNDS Table 2-1. Mission...

216

Geographic Area Month  

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

Fuels by PAD District and State (Cents per Gallon Excluding Taxes) - Continued Geographic Area Month No. 1 Distillate No. 2 Distillate a No. 4 Fuel b Sales to End Users Sales for...

217

Black History Month  

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

During National African American History Month, we pay tribute to the contributions of past generations and reaffirm our commitment to keeping the American dream alive for the next generation. In...

218

Residential Demand Response  

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

that can store underutilized renewable or off peak electric energy for space and water heating. ETS systems store electric energy as heat in a well insulated brick core. Built-in...

219

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

shift in the short-run price elasticity of gasoline demand.A meta-analysis of the price elasticity of gasoline demand.2007. Consumer demand un- der price uncertainty: Empirical

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

220

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

analysis of the demand for oil in the Middle East. EnergyEstimates elasticity of demand for crude oil, not gasoline.World crude oil and natural gas: a demand and supply model.

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "monthly peak demand" 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

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

analysis of the demand for oil in the Middle East. EnergyEstimates elasticity of demand for crude oil, not gasoline.World crude oil and natural gas: a demand and supply model.

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

222

BLACK HISTORY MONTH  

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

Black History Month is an annual celebration of achievements by black Americans and a time for recognizing the central role of African Americans in U.S. history. The event grew out of Negro History Week, created by historian Carter G. Woodson and other prominent African Americans. Other countries around the world, including Canada and the United Kingdom, also devote a month to celebrating black history.

223

Petroleum supply monthly, February 1988. [Contains glossary  

SciTech Connect

Total US demand for petroleum products during February 1988 averaged about 17.6 million barrels per day, 0.9 million barrels per day above the average of a year earlier. This marks the third consecutive month in which total product supplied has exceeded 17.0 million barrels per day. For the most part, the disposition of the major products continued to follow seasonal patterns. Total products stocks dropped by 26.0 million barrels to 683.1 million barrels. Refinery utilization fell from January's 82.8 percent rate to 81.1 percent. Crude oil imports from Saudi Arabia rose to 1.2 million barrels per day, 0.4 million barrels per day above the average for January. Unusually mild weather, especially in the Mid-Atlantic states and New England, kept deliveries of both distillate and residual fuel oil virtually unchanged from January's high seasonal levels, although both were still well above the levels for these products the same time last year. Distillate demand averaged 3.5 million barrels per day in February, five percent above the February 1987 average. Residual fuel oil demand was 1.6 million barrels per day this month, nine percent greater than a year ago. Part of this increase in demand from the previous year reflects the improved competitive position of residual fuel oil in some utility and industrial markets, mostly due to increases in natural gas prices starting in the fourth quarter of 1987. 12 figs.

Not Available

1988-04-25T23:59:59.000Z

224

Demand Activated Manufacturing Architecture  

SciTech Connect

Honeywell Federal Manufacturing & Technologies (FM&T) engineers John Zimmerman and Tom Bender directed separate projects within this CRADA. This Project Accomplishments Summary contains their reports independently. Zimmerman: In 1998 Honeywell FM&T partnered with the Demand Activated Manufacturing Architecture (DAMA) Cooperative Business Management Program to pilot the Supply Chain Integration Planning Prototype (SCIP). At the time, FM&T was developing an enterprise-wide supply chain management prototype called the Integrated Programmatic Scheduling System (IPSS) to improve the DOE's Nuclear Weapons Complex (NWC) supply chain. In the CRADA partnership, FM&T provided the IPSS technical and business infrastructure as a test bed for SCIP technology, and this would provide FM&T the opportunity to evaluate SCIP as the central schedule engine and decision support tool for IPSS. FM&T agreed to do the bulk of the work for piloting SCIP. In support of that aim, DAMA needed specific DOE Defense Programs opportunities to prove the value of its supply chain architecture and tools. In this partnership, FM&T teamed with Sandia National Labs (SNL), Division 6534, the other DAMA partner and developer of SCIP. FM&T tested SCIP in 1998 and 1999. Testing ended in 1999 when DAMA CRADA funding for FM&T ceased. Before entering the partnership, FM&T discovered that the DAMA SCIP technology had an array of applications in strategic, tactical, and operational planning and scheduling. At the time, FM&T planned to improve its supply chain performance by modernizing the NWC-wide planning and scheduling business processes and tools. The modernization took the form of a distributed client-server planning and scheduling system (IPSS) for planners and schedulers to use throughout the NWC on desktops through an off-the-shelf WEB browser. The planning and scheduling process within the NWC then, and today, is a labor-intensive paper-based method that plans and schedules more than 8,000 shipped parts per month based on more than 50 manually-created document types. The fact that DAMA and FM&T desired to move from paper-based manual architectures to digitally based computer architectures gave further incentive for the partnership to grow. FM&T's greatest strength was its knowledge of NWC-wide scheduling and planning with its role as the NWC leader in manufacturing logistics. DAMA's asset was its new knowledge gained in the research and development of advanced architectures and tools for supply chain management in the textiles industry. These complimentary strengths allowed the two parties to provide both the context and the tools for the pilot. Bender: Honeywell FM&T participated in a four-site supply chain project, also referred to as an Inter-Enterprise Pipeline Evaluation. The MSAD project was selected because it involves four NWC sites: FM&T, Pantex, Los Alamos National Laboratory (LANL), and Lawrence Livermore National Laboratory (LLNL). FM&T had previously participated with Los Alamos National Laboratory in FY98 to model a two-site supply chain project, between FM&T and LANL. Evaluation of a Supply Chain Methodology is a subset of the DAMA project for the AMTEX consortium. LANL organization TSA-7, Enterprise Modeling and Simulation, has been involved in AMTEX and DAMA through development of process models and simulations for LANL, the NWC, and others. The FY 1998 and this FY 1999 projects directly involved collaboration between Honeywell and the Enterprise Modeling and Simulation (TSA-7) and Detonation Science and Technology (DX1) organizations at LANL.

Bender, T.R.; Zimmerman, J.J.

2001-02-07T23:59:59.000Z

225

Changing Energy Demand Behavior: Potential of Demand-Side Management  

Science Journals Connector (OSTI)

There is a great theoretical potential to save resources by managing our demand for energy. However, demand-side management (DSM) programs targeting behavioral patterns of...

Dr. Sylvia Breukers; Dr. Ruth Mourik

2013-01-01T23:59:59.000Z

226

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

No. ER06-615-000 CAISO Demand Response Resource User Guide -8 2.1. Demand Response Provides a Range of Benefits to8 2.2. Demand Response Benefits can be Quantified in Several

Heffner, Grayson

2010-01-01T23:59:59.000Z

227

Silver Peak Innovative Exploration Project  

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

DOE Geothermal Peer Review 2010 - Presentation. Project objectives: Reduce the high level of risk during the early stages of geothermal project development by conducting a multi-faceted and innovative exploration and drilling program at Silver Peak. Determine the combination of techniques that are most useful and cost-effective in identifying the geothermal resource through a detailed, post-project evaluation of the exploration and drilling program.

228

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 39 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2035. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial.

229

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 12 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS 27 data.

230

Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Residential Demand Module The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" (UEC) by appliance (in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type

231

Automated Demand Response Opportunities in Wastewater Treatment Facilities  

SciTech Connect

Wastewater treatment is an energy intensive process which, together with water treatment, comprises about three percent of U.S. annual energy use. Yet, since wastewater treatment facilities are often peripheral to major electricity-using industries, they are frequently an overlooked area for automated demand response opportunities. Demand response is a set of actions taken to reduce electric loads when contingencies, such as emergencies or congestion, occur that threaten supply-demand balance, and/or market conditions occur that raise electric supply costs. Demand response programs are designed to improve the reliability of the electric grid and to lower the use of electricity during peak times to reduce the total system costs. Open automated demand response is a set of continuous, open communication signals and systems provided over the Internet to allow facilities to automate their demand response activities without the need for manual actions. Automated demand response strategies can be implemented as an enhanced use of upgraded equipment and facility control strategies installed as energy efficiency measures. Conversely, installation of controls to support automated demand response may result in improved energy efficiency through real-time access to operational data. This paper argues that the implementation of energy efficiency opportunities in wastewater treatment facilities creates a base for achieving successful demand reductions. This paper characterizes energy use and the state of demand response readiness in wastewater treatment facilities and outlines automated demand response opportunities.

Thompson, Lisa; Song, Katherine; Lekov, Alex; McKane, Aimee

2008-11-19T23:59:59.000Z

232

Demand Response In California  

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

Energy Efficiency & Energy Efficiency & Demand Response Programs Dian M. Grueneich, Commissioner Dian M. Grueneich, Commissioner California Public Utilities Commission California Public Utilities Commission FUPWG 2006 Fall Meeting November 2, 2006 Commissioner Dian M. Grueneich November 2, 2006 1 Highest Priority Resource Energy Efficiency is California's highest priority resource to: Meet energy needs in a low cost manner Aggressively reduce GHG emissions November 2, 2006 2 Commissioner Dian M. Grueneich November 2, 2006 3 http://www.cpuc.ca.gov/PUBLISHED/REPORT/51604.htm Commissioner Dian M. Grueneich November 2, 2006 4 Energy Action Plan II Loading order continued "Pursue all cost-effective energy efficiency, first." Strong demand response and advanced metering

233

On Demand Guarantees in Iran.  

E-Print Network (OSTI)

??On Demand Guarantees in Iran This thesis examines on demand guarantees in Iran concentrating on bid bonds and performance guarantees. The main guarantee types and (more)

Ahvenainen, Laura

2009-01-01T23:59:59.000Z

234

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

235

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electric Power Sector Coal Stocks: March 2012 Electric Power Sector Coal Stocks: March 2012 Stocks The seasonal winter drawdown of coal stocks was totally negated during the winter months this year due to low natural gas prices and unseasonably warm temperatures throughout the continental United States. In fact, March 2012 was the seventh straight month that coal stockpiles at power plants increased from the previous month. The largest driver of increasing stockpiles has been declining consumption of coal due to unseasonably warm weather and declining natural gas prices. Because much of the coal supplied to electric generators is purchased through long-term contracts, increasing coal stockpiles have proven difficult for electric power plant operators to handle. Some operators have inventories so high that they are refusing

236

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electric Power Sector Coal Stocks: October 2013 Electric Power Sector Coal Stocks: October 2013 Stocks In October 2013, total coal stocks increased 0.8 percent from the previous month. This follows the normal seasonal pattern for this time of year as the country begins to build up coal stocks to be consumed during the winter months. Compared to last October, coal stocks decreased 17.7 percent. This occurred because coal stocks in October 2012 were at an extremely high level. Days of Burn Days of burn Coal capacity The average number of days of burn held at electric power plants is a forward looking estimate of coal supply given a power plant's current stockpile and past consumption patterns. The total bituminous supply decreased from 85 days the previous month to 78 days in October 2013, while the total subbituminous supply decreased from 63 days in September 2013 to

237

monthly | OpenEI  

Open Energy Info (EERE)

714 714 Varnish cache server Browse Upload data GDR 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2142280714 Varnish cache server monthly Dataset Summary Description The Florida Geological Survey is where data related to oil, gas, and geothermal resources for the state of Florida are made public. This dataset contains monthly oil and gas production data for January and February of 2011. The dataset is in .xls format, and displays well status, well production, and cumulative data. Source Florida Geological Survey Date Released February 28th, 2011 (3 years ago) Date Updated Unknown Keywords data Florida gas monthly oil production Data application/vnd.ms-excel icon February 2011 oil and gas production data (xls, 33.8 KiB)

238

Monthly Energy Review  

Gasoline and Diesel Fuel Update (EIA)

May May 26, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/05) Distribution Category UC-950 Monthly Energy Review

239

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electric Power Sector Coal Stocks: November 2011 Electric Power Sector Coal Stocks: November 2011 Stocks As discussed in this month's feature story, electric power sector coal stocks continued to replenish after the summer burn in November, though stockpile levels remain below 2010 and 2009 levels. All coal stockpile levels declined from November 2010, with bituminous coal stockpile levels 9 percent lower than the same month of 2010. Days of Burn Days of burn Coal capacity The average number of days of burn held at electric power plants is a forward looking estimate of coal supply given a power plantâ€(tm)s current stockpile and past consumption patterns. The average number of days of burn held on hand at electric power plants dropped slightly from last month and remained below levels seen in November of 2010 or 2009. While

240

Monthly Energy Statistics  

Gasoline and Diesel Fuel Update (EIA)

July July 2003 E n e r g y P l u g : R e s i d e n t i a l E n e r g y C o n s u m p t i o n Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: July 28, 2003 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the

Note: This page contains sample records for the topic "monthly peak demand" 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

Energy Demand Staff Scientist  

E-Print Network (OSTI)

Energy Demand in China Lynn Price Staff Scientist February 2, 2010 #12;Founded in 1988 Focused on End-Use Energy Efficiency ~ 40 Current Projects in China Collaborations with ~50 Institutions in China Researcher #12;Talk OutlineTalk Outline · Overview · China's energy use and CO2 emission trends · Energy

Eisen, Michael

242

Energy Demand Modeling  

Science Journals Connector (OSTI)

From the end of World War II until the early 1970s there was a strong and steady increase in the demand for energy. The abundant supplies of fossil and other ... an actual fall in the real price of energy of abou...

S. L. Schwartz

1980-01-01T23:59:59.000Z

243

November 2010 monthly report  

SciTech Connect

These viewgraphs are to be provided to NNSA to update the status of the B61 Life Extension Project work and activities. The viewgraphs cover such issues as budget, schedule, scope, and the like. They are part of the monthly reporting process.

Neff, Warren E [Los Alamos National Laboratory

2010-12-07T23:59:59.000Z

244

Monthly Energy Review  

SciTech Connect

This publication presents an overview of the Energy information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. Two brief ``energy plugs`` (reviews of EIA publications) are included, as well.

NONE

1996-05-28T23:59:59.000Z

245

Late January Cold Impacted Both Supply & Demand  

Gasoline and Diesel Fuel Update (EIA)

A brief cold spell occurred in the second half of January on top of A brief cold spell occurred in the second half of January on top of the low stocks. Cold weather increases demand, but it also can interfere with supply, as happened this past January. During the week ending January 22, temperatures in the New England and the Mid-Atlantic areas shifted from being15 percent and 17 percent warmer than normal, respectively, to 24 percent and 22 percent colder than normal. The weather change increased weekly heating requirements by about 40 percent. Temperature declines during the winter affect heating oil demand in a number of ways: Space heating demand increases; Electricity peaking demand increases and power generators must turn to distillate to meet the new peak needs; Fuel switching from natural gas to distillate occurs among large

246

title Automated Price and Demand Response Demonstration for Large Customers  

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

Automated Price and Demand Response Demonstration for Large Customers Automated Price and Demand Response Demonstration for Large Customers in New York City using OpenADR booktitle International Conference for Enhanced Building Operations ICEBO year month address Montreal Quebec abstract p class p1 Open Automated Demand Response OpenADR an XML based information exchange model is used to facilitate continuous price responsive operation and demand response participation for large commercial buildings in New York who are subject to the default day ahead hourly pricing We summarize the existing demand response programs in New York and discuss OpenADR communication prioritization of demand response signals and control methods Building energy simulation models are developed and field tests are conducted to evaluate continuous energy management

247

Three Case Studues of the Application of Energy Systems Optimization Best Prectices for Automatic Demand Response  

E-Print Network (OSTI)

Three Case Studies of the Application of Energy Systems Optimization Best Practices for Automatic Demand Response Yifu Shi Kelly Guiberteau Carlos Yagua, P.E. James Watt, P.E. Energy Systems Laboratory, Texas A&M University College.... INTRODUCTION The overall goal of the demand response program is to reduce facilities peak energy demand to reduce the cost of electricity for both Austin Energy and their customer. Reducing the demand mitigates the need to construct additional...

Shi, Y.; Guiberteau, K.; Yagua, C.; Watt, J.

2013-01-01T23:59:59.000Z

248

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

4 4 The commercial module forecasts consumption by fuel 15 at the Census division level using prices from the NEMS energy supply modules, and macroeconomic variables from the NEMS Macroeconomic Activity Module (MAM), as well as external data sources (technology characterizations, for example). Energy demands are forecast for ten end-use services 16 for eleven building categories 17 in each of the nine Census divisions (see Figure 5). The model begins by developing forecasts of floorspace for the 99 building category and Census division combinations. Next, the ten end-use service demands required for the projected floorspace are developed. The electricity generation and water and space heating supplied by distributed generation and combined heat and power technologies are projected. Technologies are then

249

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 51 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are further subdivided into the energy- intensive manufacturing industries and nonenergy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process-flow or end-use accounting procedure, whereas the non- manufacturing industries are modeled with substantially less detail. The petroleum refining industry is not included in the Industrial Module, as it is simulated separately in the Petroleum Market Module of NEMS. The Industrial Module calculates

250

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

251

Project of the Month  

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

project-of-the-month Office of Environmental project-of-the-month Office of Environmental Management 1000 Independence Ave., SW Washington, DC 20585 202-586-7709 en One-of-a-Kind Facility Now in Safe Shutdown http://energy.gov/em/articles/one-kind-facility-now-safe-shutdown One-of-a-Kind Facility Now in Safe Shutdown

252

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

253

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

254

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Highlights: March 2012 Highlights: March 2012 Average natural gas prices at the Henry Hub declined for the eighth straight month leading to a nearly 40% increase in consumption for electricity during March 2012. The warmest March on record for much of the central U.S. drove a 5% decrease in residential retail sales when compared to March 2011. U.S. coal supplies as measured by days of burn were above 80 days for the third straight month in March as declining coal consumption drove coal stockpile increases. Key Indicators Mar 2012 % Change from Mar 2011 Total Net Generation (Thousand MWh) 309,709 -2.9% Residential Retail Price (cents/kWh) 11.76 1.5% Retail Sales (Thousand MWh) 282,453 -2.6% Heating Degree-Days 377 -36.4% Natural Gas Price, Henry Hub ($/MMBtu) 2.22 -45.7% Coal Stocks

255

End of Month Working  

Gasoline and Diesel Fuel Update (EIA)

The level of gas in storage at the end of the last heating season (March The level of gas in storage at the end of the last heating season (March 31, 2000) was 1,150 billion cubic feet (Bcf), just above the 1995-1999 average of 1,139 Bcf. Underground working gas storage levels are currently about 8-9 percent below year-ago levels. In large part, this is because injection rates since April 1 have been below average. Storage injections picked up recently due to warm weather in the last half of October. The month of November is generally the last month available in the year for injections into storage. A cold November would curtail net injections into storage. If net injections continue at average levels this winter, we project that storage levels will be low all winter, reaching a level of 818 Bcf at the end of March, the lowest level since 1996

256

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

March 2012 | Release Date: May 29, 2012 | Next March 2012 | Release Date: May 29, 2012 | Next Release Date: June 26, 2012 | Re-Release Date: November 28, 2012 (correction) Previous Issues Issue: November 2013 October 2013 September 2013 August 2013 July 2013 June 2013 May 2013 April 2013 March 2013 February 2013 January 2013 December 2012 November 2012 Previous issues Format: html xls Go Highlights: March 2012 Average natural gas prices at the Henry Hub declined for the eighth straight month leading to a nearly 40% increase in consumption for electricity during March 2012. The warmest March on record for much of the central U.S. drove a 5% decrease in residential retail sales when compared to March 2011. U.S. coal supplies as measured by days of burn were above 80 days for the third straight month in March as declining coal consumption drove

257

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

258

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electric Power Sector Coal Stocks: February 2012 Electric Power Sector Coal Stocks: February 2012 Stocks The unseasonably warm temperatures that the continental United States experienced throughout the winter, coupled with low natural gas prices, caused coal stocks at power plants to increase throughout the winter of 2011 - 2012. During this period, coal stocks usually see a seasonal decline due to the added need for electricity generation from coal plants for spacing heating load. However, it was the sixth straight month that coal stocks increased from the previous month, with this trend likely to continue as the country enters into spring. Days of Burn Days of burn Coal capacity The average number of days of burn held at electric power plants is a forward looking estimate of coal supply given a power plant's current

259

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

260

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

Note: This page contains sample records for the topic "monthly peak demand" 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

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

262

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

263

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

264

Monthly Energy Review  

Gasoline and Diesel Fuel Update (EIA)

December December 23, 1997 Electronic Access Monthly Energy Review (MER) data are also available through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/contents.html * A portable document format (pdf) file of the complete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.overview/monthly .energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-from-the-last

265

Petroleum Marketing Monthly Archives  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Marketing Monthly Archives Petroleum Marketing Monthly Archives Choose the year of the Petroleum Marketing Monthly you wish to view. + EXPAND ALL 2014-2015 2014 2015 Data ending January 10/2013 2012-2013 2012 2013 Data ending January 10/2011 January 10/2012 February 11/2011 February 11/2012 March 12/2011 March 12/2012 April 1/2012 April 1/2013 May 2/2012 May 2/2013 June 3/2012 June 3/2013 July 4/2012 July 4/2013 August 5/2012 August 5/2013 September 6/2012 September 6/2013 October 7/2012 October 7/2013 November 8/2012 November 8/2013 December 9/2012 December 9/2013 2010 - 2011 2010 2011 Data ending Data ending January 10/2009 January 10/2010 February 11/2009 February 11/2010 March 12/2009 March 12/2010 April 1/2010 April 1/2011 May 2/2010 May 2/2011

266

Seasonality in Community Water Demand Ronald C. Griffin and Chan Chang  

E-Print Network (OSTI)

are more price responsive than winter demands implies that price can be a more effective al- locative tool price, (b) demand price elasticity appears to vary seasonally, and (c) the demand price specification functional forms are contrasted for their abilities to identify monthly price elasticities. Results

Griffin, Ronald

267

On making energy demand and network constraints compatible in the last mile of the power grid  

Science Journals Connector (OSTI)

Abstract In the classical electricity grid power demand is nearly instantaneously matched by power supply. In this paradigm, the changes in power demand in a low voltage distribution grid are essentially nothing but a disturbance that is compensated for by control at the generators. The disadvantage of this methodology is that it necessarily leads to a transmission and distribution network that must cater for peak demand. So-called smart meters and smart grid technologies provide an opportunity to change this paradigm by using demand side energy storage to moderate instantaneous power demand so as to facilitate the supply-demand match within network limitations. A receding horizon model predictive control method can be used to implement this idea. In this paradigm demand is matched with supply, such that the required customer energy needs are met but power demand is moderated, while ensuring that power flow in the grid is maintained within the safe operating region, and in particular peak demand is limited. This enables a much higher utilisation of the available grid infrastructure, as it reduces the peak-to-base demand ratio as compared to the classical control methodology of power supply following power demand. This paper investigates this approach for matching energy demand to generation in the last mile of the power grid while maintaining all network constraints through a number of case studies involving the charging of electric vehicles in a typical suburban low voltage distribution network in Melbourne, Australia.

Iven Mareels; Julian de Hoog; Doreen Thomas; Marcus Brazil; Tansu Alpcan; Derek Jayasuriya; Valentin Menzel; Lu Xia; Ramachandra Rao Kolluri

2014-01-01T23:59:59.000Z

268

Peak oil supply or oil not for sale?  

Science Journals Connector (OSTI)

Abstract The restrictions imposed by climate change are inevitable and will be exerted either via precautionary mitigation of (mainly energy-related) CO2 emissions or via irreversible impacts on ecosystems and on human habitats. Either way, oil markets are bound to incur drastic shrinking. Concern over peak oil supply will crumble when the irrevocable peak oil demand is created. Replacing oil in the world's energy economies requires redirected market forces, notably in the form of steadily increasing oil end-use prices. Yet, thus far, crude oil prices have obeyed the market fundamentals of expanding-contracting demand and oligopolistic supply. A hockey stick supply curve supports high sales prices, providing large rents to submarginal sources. Cutting oil demand and maintaining high prices implies reducing the supply hockey stick's length by curtailing some oil producers. In such a scenario, the alliances, goals, and tactics of oil geopolitics are set to change. We identify a distribution over friendly and hostile oil suppliers, with others drifting in between the two sides. Conflicts and warfare are less aimed at conquering oil fields for exploitation than at paralyzing production capabilities of opponents or of unreliable transient sources. Covert warfare and instigation of internal conflicts are likely tactics to exhaust hostile opponents.

Aviel Verbruggen; Thijs Van de Graaf

2013-01-01T23:59:59.000Z

269

Monthly News Blast: February 2013  

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

In the February 2013 Monthly News Blast, read about recent blog posts, the monthly staff spotlight video, upcoming events, and more.

270

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Highlights: February 2012 Highlights: February 2012 Warm temperatures across much of the U.S. led to lower retail sales of electricity during February 2012. Natural gas-fired generation increased in every region of the United States when compared to February 2011. Wholesale electricity prices remained in the low end of the annual range for most wholesale markets due to low demand and depressed natural gas prices Key Indicators Feb 2012 % Change from Feb. 2011 Total Net Generation (Thousand MWh) 310,298 -1.0% Residential Retail Price (cents/kWh) 11.55 3.9% Retail Sales (Thousand MWh) 285,684 -3.5% Heating Degree-Days 654 -12.0% Natural Gas Price, Henry Hub ($/MMBtu) 2.60 -38.1% Coal Stocks (Thousand Tons) 186,958 -13.6% Coal Consumption (Thousand Tons) 62,802 -14.6% Natural Gas Consumption

271

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

February 2012 | Release Date: Apr. 30, February 2012 | Release Date: Apr. 30, 2012 | Next Release Date: May 25, 2012 | Re-Release Date: November 28, 2012 (correction) Previous Issues Issue: November 2013 October 2013 September 2013 August 2013 July 2013 June 2013 May 2013 April 2013 March 2013 February 2013 January 2013 December 2012 November 2012 Previous issues Format: html xls Go Highlights: February 2012 Warm temperatures across much of the U.S. led to lower retail sales of electricity during February 2012. Natural gas-fired generation increased in every region of the United States when compared to February 2011. Wholesale electricity prices remained in the low end of the annual range for most wholesale markets due to low demand and depressed natural gas prices Key Indicators Feb 2012 % Change from Feb. 2011

272

Modeling, Analysis, and Control of Demand Response Resources  

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

Modeling, Analysis, and Control of Demand Response Resources Modeling, Analysis, and Control of Demand Response Resources Speaker(s): Johanna Mathieu Date: April 27, 2012 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Sila Kiliccote While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can play an active role in power systems via Demand Response (DR). Recent DR programs have focused on peak load reduction in commercial buildings and industrial facilities (C&I facilities). We present a regression-based baseline model, which allows us to quantify DR performance. We use this baseline model to understand the performance of C&I facilities participating in an automated dynamic pricing DR program in California. In this program, facilities are

273

Monthly Energy Review - June 2008  

Gasoline and Diesel Fuel Update (EIA)

Monthly Publications: Other monthly EIA reports are Petroleum Supply Monthly Publications: Other monthly EIA reports are Petroleum Supply Monthly, Petroleum Marketing Monthly, Natural Gas Monthly, Electric Power Monthly, and Inter- national Petroleum Monthly. For more information, contact the National Energy Information Center at 202-586-8800 or InfoCtr@eia.doe.gov. Electronic Access The MER is available on EIA's Web site in a variety of formats at: http://www.eia.doe.gov/mer. Complete MER, and individual MER sections: Portable Document Format (PDF) files. Individual table and graph pages: PDF files. Data files for individual tables: Excel (XLS) files and ASCII comma-delimited (CSV) files. Note: PDF files display selected annual and monthly data. Excel and CSV files display all avail- able annual and monthly data, often at a greater level of precision than the PDF files.

274

Petroleum Supply Monthly  

Gasoline and Diesel Fuel Update (EIA)

December 2011 December 2011 February 2012 Energy Information Administration/Petroleum Supply Monthly, ii December 2011 EIA DATA ARE AVAILABLE IN ELECTRONIC FORM All current EIA publications are available on the EIA web site. Users can view and download selected pages or entire reports, search for information, download EIA data and analysis applications, and find out about new EIA information products and services: World Wide Web: http://www.eia.doe.gov FTP: ftp://ftp.eia.doe.gov Customers who do not have access to the Internet may call the National Energy Information Center (NEIC) to request a single print-

275

Petroleum Supply Monthly  

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

With Data for September 2013 With Data for September 2013 November 2013 Energy Information Administration/Petroleum Supply Monthly, ii September 2013 EIA DATA ARE AVAILABLE IN ELECTRONIC FORM All current EIA publications are available on the EIA web site. Users can view and download selected pages or entire reports, search for information, download EIA data and analysis applications, and find out about new EIA information products and services: World Wide Web: http://www.eia.doe.gov FTP: ftp://ftp.eia.doe.gov Customers who do not have access to the Internet may call the National Energy Information Center (NEIC) to request a single print-

276

Petroleum marketing monthly  

SciTech Connect

The Petroleum Marketing Monthly (PMM) is designed to give information and statistical data about a variety of crude oils and refined petroleum products. The publication provides statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Sales data for motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane are presented.

Not Available

1992-03-01T23:59:59.000Z

277

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

E-Print Network (OSTI)

by utilizing thermal energy storage such as ice storage orThermal Storage Utilization. Journal of Solar Energy

Yin, Rongxin

2010-01-01T23:59:59.000Z

278

Electrical Energy Conservation and Peak Demand Reduction Potential for Buildings in Texas: Preliminary Results  

E-Print Network (OSTI)

diversity factors, building thermal integrity, climate zone, and appliance saturations. Building stock growth rates were estimated from regional population and employment census data. Also, energy audit data from the Bonneville Power Authority (9) were... diversity factors, building thermal integrity, climate zone, and appliance saturations. Building stock growth rates were estimated from regional population and employment census data. Also, energy audit data from the Bonneville Power Authority (9) were...

Hunn, B. D.; Baughman, M. L.; Silver, S. C.; Rosenfeld, A. H.; Akbari, H.

1985-01-01T23:59:59.000Z

279

Peak Demand Reduction with Dual-Source Heat Pumps Using Municipal Water  

E-Print Network (OSTI)

The objective of this project was to examine a dual-source (air and/or water-coupled) heat pump concept which would reduce or eliminate the need for supplemental electrical resistance heating (strip heaters). The project examined two system options...

Morehouse, J. H.; Khan, J. A.; Connor, L. N.; Pal, D.

280

Demand Side Management using VOLTAGE / DISTRIBUTION OPTIMIZATION Quality improvement & Peak reduction  

Science Journals Connector (OSTI)

In order to improve the quality of the electrical energy delivered at consumer households a Voltage Optimization Device (VOD) is introduced in each household. This device controls the output voltage accurately at...

N. H. M. Hofmeester; C. J. van de Water

1994-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "monthly peak demand" 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

Factors Influencing Water Heating Energy Use and Peak Demand in a Large Scale Residential Monitoring Study  

E-Print Network (OSTI)

A load research project by the Florida Power Corporation (FPC) is monitoring 200 residences in Central Florida, collecting detailed end-use load data. The monitoring is being performed to better estimate the impact of FPC's load control program...

Bouchelle, M. P.; Parker, D. S.; Anello, M. T.

2000-01-01T23:59:59.000Z

282

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

E-Print Network (OSTI)

Figure 9 Chiller Power in Pre-Cooling Tests Chiller powerFigure 10 Supply Fan Power in Pre- Cooling Tests response ofthe extended pre-cooling tests, the power increased at night

Xu, Peng

2010-01-01T23:59:59.000Z

283

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

E-Print Network (OSTI)

control system does not support global reset of zone temperatures, strategies involving reset of supply air temperature

Xu, Peng

2010-01-01T23:59:59.000Z

284

Wind Power Generations Impact on Peak Time Demand and on Future Power Mix  

Science Journals Connector (OSTI)

Although wind power is regarded as one of the ways to actively respond to climate change, the stability of the whole power system could be a serious problem in the future due to wind powers uncertainties. These ...

Jinho Lee; Suduk Kim

2010-01-01T23:59:59.000Z

285

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

286

ResourceTask Network Formulations for Industrial Demand Side Management of a Steel Plant  

Science Journals Connector (OSTI)

In the industrial demand side management (iDSM) or demand response (DR) grid-consumer interface, the electricity provider gives economic incentives to the industry to alter their electricity usage behavior and there are generally two approaches: ... It can be used as an important tool for industrial demand side management or demand response, a concept in which the plant adapts its operational behavior by changing the timing of electricity usage from on-peak to off-peak hours for the collective benefit of society. ...

Pedro M. Castro; Lige Sun; Iiro Harjunkoski

2013-08-13T23:59:59.000Z

287

Understanding and Analysing Energy Demand  

Science Journals Connector (OSTI)

This chapter introduces the concept of energy demand using basic micro-economics and presents the three-stage decision making process of energy demand. It then provides a set of simple ... (such as price and inco...

Subhes C. Bhattacharyya

2011-01-01T23:59:59.000Z

288

Marketing Demand-Side Management  

E-Print Network (OSTI)

they the only game in town, enjoying a captive market. Demand-side management (DSM) again surfaced as a method for increasing customer value and meeting these competitive challenges. In designing and implementing demand-side management (DSM) programs we... have learned a great deal about what it takes to market and sell DSM. This paper focuses on how to successfully market demand-side management. KEY STEPS TO MARKETING DEMAND-SIDE MANAGEMENT Management Commitment The first key element in marketing...

O'Neill, M. L.

1988-01-01T23:59:59.000Z

289

Demand Charges | Open Energy Information  

Open Energy Info (EERE)

Charges Jump to: navigation, search Retrieved from "http:en.openei.orgwindex.php?titleDemandCharges&oldid488967"...

290

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

291

Assessment of Demand Response Resource  

E-Print Network (OSTI)

Assessment of Demand Response Resource Potentials for PGE and Pacific Power Prepared for: Portland January 15, 2004 K:\\Projects\\2003-53 (PGE,PC) Assess Demand Response\\Report\\Revised Report_011504.doc #12;#12;quantec Assessment of Demand Response Resource Potentials for I-1 PGE and Pacific Power I. Introduction

292

ERCOT Demand Response Paul Wattles  

E-Print Network (OSTI)

ERCOT Demand Response Paul Wattles Senior Analyst, Market Design & Development, ERCOT Whitacre;Definitions of Demand Response · `The short-term adjustment of energy use by consumers in response to price to market or reliability conditions.' (NAESB) #12;Definitions of Demand Response · The common threads

Mohsenian-Rad, Hamed

293

Pricing data center demand response  

Science Journals Connector (OSTI)

Demand response is crucial for the incorporation of renewable energy into the grid. In this paper, we focus on a particularly promising industry for demand response: data centers. We use simulations to show that, not only are data centers large loads, ... Keywords: data center, demand response, power network, prediction based pricing

Zhenhua Liu; Iris Liu; Steven Low; Adam Wierman

2014-06-01T23:59:59.000Z

294

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

January 2012 | Release Date: Mar. 27, January 2012 | Release Date: Mar. 27, 2012 | Next Release Date: Apr. 27, 2012 | Re-Release Date: November 28, 2012 (correction) Previous Issues Issue: November 2013 October 2013 September 2013 August 2013 July 2013 June 2013 May 2013 April 2013 March 2013 February 2013 January 2013 December 2012 November 2012 Previous issues Format: html xls Go Highlights: January 2012 Warm temperatures across much of the U.S. led to lower retail sales of electricity during January 2012. Coal-fired generation decreased in every region of the United States when compared to January 2011. Coal stocks recovered due to decreased consumption this January compared to the same month of 2011. Key Indicators Jan 2012 % Change from Jan. 2011 Total Net Generation (Thousand MWh) 340,743 -6.4%

295

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Highlights: January 2012 Highlights: January 2012 Warm temperatures across much of the U.S. led to lower retail sales of electricity during January 2012. Coal-fired generation decreased in every region of the United States when compared to January 2011. Coal stocks recovered due to decreased consumption this January compared to the same month of 2011. Key Indicators Jan 2012 % Change from Jan. 2011 Total Net Generation (Thousand MWh) 340,743 -6.4% Residential Retail Price (cents/kWh) 11.43 4.4% Retail Sales (Thousand MWh) 310,859 -6.5% Heating Degree-Days 751 -21.4% Natural Gas Price, Henry Hub ($/MMBtu) 2.75 -40.3% Coal Stocks (Thousand Tons) 181,621 10.2% Coal Consumption (Thousand Tons) 70,595 -21.7% Natural Gas Consumption (Mcf) 676,045 19.9% Nuclear Outages (MW) 9,567 2.1%

296

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electric Power Sector Coal Stocks: December 2011 Electric Power Sector Coal Stocks: December 2011 Stocks Temperate weather throughout the fall has allowed electric power sector coal stocks to replenish from the summer burn. All coal stockpile levels were essentially flat when compared to December 2010 and were a mostly up year-to-date. Days of Burn Days of burn Coal capacity The average number of days of burn held at electric power plants is a forward looking estimate of coal supply given a power plantâ€(tm)s current stockpile and past consumption patterns. The average number of days of burn held on hand at electric power plants was essentially flat compared to last month and remained below levels seen in December of 2010 or 2009. While stockpile levels have recovered from summer lows, the increasing

297

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

August 2011 | Release Date: October 25, August 2011 | Release Date: October 25, 2011 | Next Release Date: November 21, 2011 Previous Issues Issue: November 2013 October 2013 September 2013 August 2013 July 2013 June 2013 May 2013 April 2013 March 2013 February 2013 January 2013 December 2012 November 2012 Previous issues Format: html xls Go Highlights: August 2011 Extreme heat in Texas, New Mexico, Colorado and Arizona drove significant increases in the retail sales of electricity in the Southwest. Wind generation increased in much of the United States, except the middle of the country where total generation declined. Bituminous coal stocks dropped 14% from August 2010. Key indicators Same Month 2010 Year to date Total Net Generation -1% 11% Residential Retail Price -6% 11% Cooling Degree-Days -3% 2%

298

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Coal Stocks: August 2011 Coal Stocks: August 2011 Stocks Coal stocks continued the usual summer decline as utilities burned into their summer stockpile in August. Sigificant declines from August 2010 were seen in total coal stockpiles, driven by a 14 percent drop in bituminous coal stockpiles as well as a 10 percent drop in subbituminous coal stockpiles. Lignite stockpiles declined by 6 percent over the same time period. Days of burn The average number of days of burn held at electric power plants is a forward looking estimate of coal supply given a power plant's current stockpile and past consumption patterns. The average number of days of burn held on hand at electric power plants increased slightly in August 2011 compared to previous months. This was largely driven by increases in

299

March Natural Gas Monthly  

Gasoline and Diesel Fuel Update (EIA)

'PGTI[+PHQTOCVKQP#FOKPKUVTCVKQP0CVWTCN)CU/QPVJN[/CTEJ 'PGTI[+PHQTOCVKQP#FOKPKUVTCVKQP0CVWTCN)CU/QPVJN[/CTEJ EIA Corrects Errors in Its Drilling Activity Estimates Series William Trapmann and Phil Shambaugh Introduction The Energy Information Administration (EIA) has published monthly and annual estimates of oil and gas drilling activity since 1978. These data are key information for many industry analysts, serving as a leading indicator of trends in the industry and a barometer of general industry status. They are assessed directly for trends, as well as in combination with other measures to assess the productivity and profitability of upstream industry operations. They are a major reference point for policymakers at both the Federal and State level. Users in the private sector include financial

300

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electric Power Sector Coal Stocks: September 2011 Electric Power Sector Coal Stocks: September 2011 Stocks Electric power sector coal stocks continued to replenish after the summer burn in October, though stockpile levels remain well below 2010 levels. All coal stockpile levels declined from October 2010, with bituminous coal stockpile levels 12 percent lower than the same month of 2010. Days of Burn Days of burn Coal capacity The average number of days of burn held at electric power plants is a forward looking estimate of coal supply given a power plant's current stockpile and past consumption patterns. The average number of days of burn held on hand at electric power plants was generally flat in October 2011 compared to September of this year. The summer of 2011 saw significant declines in total U.S. stockpile levels, which were replenished in the

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


301

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Reports Electricity Reports Electricity Monthly Update With Data for October 2013 | Release Date: Dec. 20, 2013 | Next Release Date: Jan. 22, 2014 Previous Issues Issue: November 2013 October 2013 September 2013 August 2013 July 2013 June 2013 May 2013 April 2013 March 2013 February 2013 January 2013 December 2012 November 2012 Previous issues Format: html xls Go Highlights: October 2013 Thirty-one states saw the average cost of electricity increase by more than two percent, with fourteen states experiencing increases of at least five percent compared to a year ago. Texas (ERCOT) and the Midwest (MISO) experienced above average wholesale electricity prices for October due to unseasonable temperatures. The New York City (Transco Zone 6 NY) natural gas price was

302

AUTOMATED CRITICAL PEAK PRICING FIELD TESTS  

E-Print Network (OSTI)

AUTOMATED CRITICAL PEAK PRICING FIELD TESTS: 2006 PROGRAM DESCRIPTION AND RESULTS APPENDICES.................................................................................... 5 B.2. DR Automation Server User Guide

303

Home Network Technologies and Automating Demand Response  

SciTech Connect

Over the past several years, interest in large-scale control of peak energy demand and total consumption has increased. While motivated by a number of factors, this interest has primarily been spurred on the demand side by the increasing cost of energy and, on the supply side by the limited ability of utilities to build sufficient electricity generation capacity to meet unrestrained future demand. To address peak electricity use Demand Response (DR) systems are being proposed to motivate reductions in electricity use through the use of price incentives. DR systems are also be design to shift or curtail energy demand at critical times when the generation, transmission, and distribution systems (i.e. the 'grid') are threatened with instabilities. To be effectively deployed on a large-scale, these proposed DR systems need to be automated. Automation will require robust and efficient data communications infrastructures across geographically dispersed markets. The present availability of widespread Internet connectivity and inexpensive, reliable computing hardware combined with the growing confidence in the capabilities of distributed, application-level communications protocols suggests that now is the time for designing and deploying practical systems. Centralized computer systems that are capable of providing continuous signals to automate customers reduction of power demand, are known as Demand Response Automation Servers (DRAS). The deployment of prototype DRAS systems has already begun - with most initial deployments targeting large commercial and industrial (C & I) customers. An examination of the current overall energy consumption by economic sector shows that the C & I market is responsible for roughly half of all energy consumption in the US. On a per customer basis, large C & I customers clearly have the most to offer - and to gain - by participating in DR programs to reduce peak demand. And, by concentrating on a small number of relatively sophisticated energy consumers, it has been possible to improve the DR 'state of the art' with a manageable commitment of technical resources on both the utility and consumer side. Although numerous C & I DR applications of a DRAS infrastructure are still in either prototype or early production phases, these early attempts at automating DR have been notably successful for both utilities and C & I customers. Several factors have strongly contributed to this success and will be discussed below. These successes have motivated utilities and regulators to look closely at how DR programs can be expanded to encompass the remaining (roughly) half of the state's energy load - the light commercial and, in numerical terms, the more important residential customer market. This survey examines technical issues facing the implementation of automated DR in the residential environment. In particular, we will look at the potential role of home automation networks in implementing wide-scale DR systems that communicate directly to individual residences.

McParland, Charles

2009-12-01T23:59:59.000Z

304

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

305

A Bayesian approach to forecast intermittent demand for seasonal products  

Science Journals Connector (OSTI)

This paper investigates the forecasting of a large fluctuating seasonal demand prior to peak sale season using a practical time series, collected from the US Census Bureau. Due to the extreme natural events (e.g. excessive snow fall and calamities), sales may not occur, inventory may not replenish and demand may set off unrecorded during the peak sale season. This characterises a seasonal time series to an intermittent category. A seasonal autoregressive integrated moving average (SARIMA), a multiplicative exponential smoothing (M-ES) and an effective modelling approach using Bayesian computational process are analysed in the context of seasonal and intermittent forecast. Several forecast error indicators and a cost factor are used to compare the models. In cost factor analysis, cost is measured optimally using dynamic programming model under periodic review policy. Experimental results demonstrate that Bayesian model performance is much superior to SARIMA and M-ES models, and efficient to forecast seasonal and intermittent demand.

Mohammad Anwar Rahman; Bhaba R. Sarker

2012-01-01T23:59:59.000Z

306

World Crude Production Not Keeping Pace with Demand  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: The crude market is the major factor behind today’s low stocks. This graph shows the balance between world production and demand for petroleum. Normally, production exceeds demand in the summer, building stocks, and is less than demand in the winter months, drawing the stocks back down (dark blue areas). However, production exceeded demand through most of 1997 and 1998, building world stocks to very high levels and driving prices down. But the situation reversed in 1999. Recently, there has been more petroleum demand than supply, requiring the use of stocks to meet petroleum needs. Following the extremely low crude oil prices at the beginning of 1999, OPEC agreed to remove about 6% of world production from the market in order to work off excess inventories and bring prices back up.

307

The benefits of combining utility-controlled demand response with residential zoned cooling  

Science Journals Connector (OSTI)

This paper evaluates the effectiveness of combining direct load control with a residential zoned-cooling technology in meeting the objectives of reducing peak demand and maintaining home comfort level. In cont...

Wen Zhou; Dean C. Mountain

2014-12-01T23:59:59.000Z

308

Oxygenate Supply/Demand Balances  

Gasoline and Diesel Fuel Update (EIA)

Oxygenate Supply/Demand Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model By Tancred C.M. Lidderdale This article first appeared in the Short-Term Energy Outlook Annual Supplement 1995, Energy Information Administration, DOE/EIA-0202(95) (Washington, DC, July 1995), pp. 33-42, 83-85. The regression results and historical data for production, inventories, and imports have been updated in this presentation. Contents * Introduction o Table 1. Oxygenate production capacity and demand * Oxygenate demand o Table 2. Estimated RFG demand share - mandated RFG areas, January 1998 * Fuel ethanol supply and demand balance o Table 3. Fuel ethanol annual statistics * MTBE supply and demand balance o Table 4. EIA MTBE annual statistics * Refinery balances

309

Decentralized Control of Aggregated Loads for Demand Response Di Guo, Wei Zhang, Gangfeng Yan, Zhiyun Lin, and Minyue Fu  

E-Print Network (OSTI)

Decentralized Control of Aggregated Loads for Demand Response Di Guo, Wei Zhang, Gangfeng Yan of residential responsive loads for vari- ous demand response applications. We propose a general hybrid system and effectively reduce the peak power consumption. I. INTRODUCTION Demand response has the potential to shift

Zhang, Wei

310

Deep Demand Response: The Case Study of the CITRIS Building at the University of California-Berkeley  

E-Print Network (OSTI)

Deep Demand Response: The Case Study of the CITRIS Building at the University of California quality. We have made progress towards achieving deep demand response of 30% reduction of peak loads modeling expertise), and UC Berkeley (related demand response research including distributed wireless

Culler, David E.

311

Demand Response Opportunities and Enabling Technologies for Data Centers:  

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

Demand Response Opportunities and Enabling Technologies for Data Centers: Demand Response Opportunities and Enabling Technologies for Data Centers: Findings From Field Studies Title Demand Response Opportunities and Enabling Technologies for Data Centers: Findings From Field Studies Publication Type Report LBNL Report Number LBNL-5763E Year of Publication 2012 Authors Ghatikar, Girish, Venkata Ganti, Nance Matson, and Mary Ann Piette Publisher PG&E/SDG&E/CEC/LBNL Keywords communication and standards, control systems, data centers, demand response, enabling technologies, end-use technologies, load migration, market sectors, technologies Abstract The energy use in data centers is increasing and, in particular, impacting the data center energy cost and electric grid reliability during peak and high price periods. As per the 2007 U.S. Environmental Protection Agency (EPA), in the Pacific Gas and Electric Company territory, data centers are estimated to consume 500 megawatts of annual peak electricity. The 2011 data confirm the increase in data center energy use, although it is slightly lower than the EPA forecast. Previous studies have suggested that data centers have significant potential to integrate with supply-side programs to reduce peak loads. In collaboration with California data centers, utilities, and technology vendors, this study conducted field tests to improve the understanding of the demand response opportunities in data centers. The study evaluated an initial set of control and load migration strategies and economic feasibility for four data centers. The findings show that with minimal or no impact to data center operations a demand savings of 25% at the data center level or 10% to 12% at the whole building level can be achieved with strategies for cooling and IT equipment, and load migration. These findings should accelerate the grid-responsiveness of data centers through technology development, integration with the demand response programs, and provide operational cost savings.

312

OFF-SHORE WIND AND GRID-CONNECTED PV: HIGH PENETRATION PEAK SHAVING FOR NEW YORK CITY  

E-Print Network (OSTI)

OFF-SHORE WIND AND GRID-CONNECTED PV: HIGH PENETRATION PEAK SHAVING FOR NEW YORK CITY Richard Perez-shore wind and PV generation using the city of New York as a test case. While wind generation is not known the source of the energy that can meet the demand. While the peak-time availability of wind generation

Perez, Richard R.

313

Monthly Energy Review - January 2007  

Gasoline and Diesel Fuel Update (EIA)

publications: Other monthly EIA reports are Petroleum Supply Monthly, Petroleum publications: Other monthly EIA reports are Petroleum Supply Monthly, Petroleum Marketing Monthly, Natural Gas Monthly, Electric Power Monthly, and International Petroleum Monthly. Readers of the MER may also be interested in EIA's Annual Energy Review, where many of the same data series are provided annually beginning with 1949. For more information, contact the National Energy Information Center at 202-586-8800 or InfoCtr@eia.doe.gov. Electronic Access The MER is available on EIA's Web site in a variety of formats at: http://www.eia.doe.gov/mer. Complete MER, and individual MER sections: Portable Document Format (PDF) files. Individual table and graph pages: PDF files. Data files for individual tables: Excel (XLS) files and ASCII comma-delimited (CSV) files.

314

National Safety Month- June 2013  

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

National Safety Month is recognized by employers, employees, and safety and health professionals throughout the country. During the month of June, HSS provided information, activities, and events pertaining to weekly themes.

315

Monthly News Blast: March 2013  

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

In the March 2013 Monthly News Blast, read about two upcoming webinars, two recently announced BETO events, recent blog posts, the monthly staff spotlight video, upcoming events, and more.

316

Energy Information Administration/Natural Gas Monthly October 2000  

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

Natural Gas Monthly October 2000 Natural Gas Monthly October 2000 vii Status of Natural Gas Pipeline System Capacity Entering the 2000-2001 Heating Season During the summer and fall of 2000 natural gas prices reached record highs for a nonheating season period. The dramatic rise in prices resulted from an upsurge in natural gas demand, mainly from electric generation needs during a warmer-than-usual spring and summer. The increased demand has occurred while domestic production levels have continued to decrease over the past several years. 1 Low natural gas prices during 1998 and 1999 dampened exploration and development efforts and caused some lower producing wells to be shut in or abandoned. Natural gas pipeline capacity, on the other hand, has grown with end-use demand, and as sources of new supply have developed, new pipelines have been

317

Demand Response Programs, 6. edition  

SciTech Connect

The report provides a look at the past, present, and future state of the market for demand/load response based upon market price signals. It is intended to provide significant value to individuals and companies who are considering participating in demand response programs, energy providers and ISOs interested in offering demand response programs, and consultants and analysts looking for detailed information on demand response technology, applications, and participants. The report offers a look at the current Demand Response environment in the energy industry by: defining what demand response programs are; detailing the evolution of program types over the last 30 years; discussing the key drivers of current initiatives; identifying barriers and keys to success for the programs; discussing the argument against subsidization of demand response; describing the different types of programs that exist including:direct load control, interruptible load, curtailable load, time-of-use, real time pricing, and demand bidding/buyback; providing examples of the different types of programs; examining the enablers of demand response programs; and, providing a look at major demand response programs.

NONE

2007-10-15T23:59:59.000Z

318

Assessing the Control Systems Capacity for Demand Response in California  

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

the Control Systems Capacity for Demand Response in California the Control Systems Capacity for Demand Response in California Industries Title Assessing the Control Systems Capacity for Demand Response in California Industries Publication Type Report LBNL Report Number LBNL-5319E Year of Publication 2012 Authors Ghatikar, Girish, Aimee T. McKane, Sasank Goli, Peter L. Therkelsen, and Daniel Olsen Date Published 01/2012 Publisher CEC/LBNL Keywords automated dr, controls and automation, demand response, dynamic pricing, industrial controls, market sectors, openadr Abstract California's electricity markets are moving toward dynamic pricing models, such as real-time pricing, within the next few years, which could have a significant impact on an industrial facility's cost of energy use during the times of peak use. Adequate controls and automated systems that provide industrial facility managers real-time energy use and cost information are necessary for successful implementation of a comprehensive electricity strategy; however, little is known about the current control capacity of California industries. To address this gap, Lawrence Berkeley National Laboratory, in close collaboration with California industrial trade associations, conducted a survey to determine the current state of controls technologies in California industries. This study identifies sectors that have the technical capability to implement Demand Response (DR) and Automated Demand Response (Auto-DR). In an effort to assist policy makers and industry in meeting the challenges of real-time pricing, facility operational and organizational factors were taken into consideration to generate recommendations on which sectors Demand Response efforts should be focused. Analysis of the survey responses showed that while the vast majority of industrial facilities have semi- or fully automated control systems, participation in Demand Response programs is still low due to perceived barriers. The results also showed that the facilities that use continuous processes are good Demand Response candidates. When comparing facilities participating in Demand Response to those not participating, several similarities and differences emerged. Demand Response-participating facilities and non-participating facilities had similar timings of peak energy use, production processes, and participation in energy audits. Though the survey sample was smaller than anticipated, the results seemed to support our preliminary assumptions. Demonstrations of Auto-Demand Response in industrial facilities with good control capabilities are needed to dispel perceived barriers to participation and to investigate industrial subsectors suggested of having inherent Demand Response potential.

319

Monthly Project Bulletin: July 2012  

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

This document contains the Guidelines for Home Energy Professionals Project bulletin for the month of July 2012.

320

Monthly Project Bulletin: August 2012  

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

This document contains the Guidelines for Home Energy Professionals Project bulletin for the month of August 2012.

Note: This page contains sample records for the topic "monthly peak demand" 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

Monthly Project Bulletin: October 2012  

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

This document contains the Guidelines for Home Energy Professionals Project bulletin for the month of September 2012.

322

Monthly Project Bulletin: April 2012  

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

This document contains the Guidelines for Home Energy Professionals Project bulletin for the month of April 2012.

323

Monthly Project Bulletin: June 2012  

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

This document contains the Guidelines for Home Energy Professionals Project bulletin for the month of June 2012.

324

Monthly Project Bulletin: May 2012  

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

This document contains the Guidelines for Home Energy Professionals Project bulletin for the month of May 2012.

325

Monthly Project Bulletin: September 2012  

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

This document contains the Guidelines for Home Energy Professionals Project bulletin for the month of September 2012.

326

April 2013 Monthly News Blast  

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

The monthly news blast for April 2013 highlights the Project Peer Review, upcoming events, BETO blog posts, and more.

327

Detailed Modeling and Response of Demand Response Enabled Appliances  

SciTech Connect

Proper modeling of end use loads is very important in order to predict their behavior, and how they interact with the power system, including voltage and temperature dependencies, power system and load control functions, and the complex interactions that occur between devices in such an interconnected system. This paper develops multi-state time variant residential appliance models with demand response enabled capabilities in the GridLAB-DTM simulation environment. These models represent not only the baseline instantaneous power demand and energy consumption, but the control systems developed by GE Appliances to enable response to demand response signals and the change in behavior of the appliance in response to the signal. These DR enabled appliances are simulated to estimate their capability to reduce peak demand and energy consumption.

Vyakaranam, Bharat; Fuller, Jason C.

2014-04-14T23:59:59.000Z

328

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network (OSTI)

of control. Water heater demand response options are notcurrent water heater and air conditioning demand responsecustomer response Demand response water heater participation

Levy, Roger

2014-01-01T23:59:59.000Z

329

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

and D. Kathan (2009). Demand Response in U.S. ElectricityEnergy Financial Group. Demand Response Research Center [2008). Assessment of Demand Response and Advanced Metering.

Goldman, Charles

2010-01-01T23:59:59.000Z

330

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network (OSTI)

Like HECO actual utility demand response implementations canindustry-wide utility demand response applications tend toobjective. Figure 4. Demand Response Objectives 17

Levy, Roger

2014-01-01T23:59:59.000Z

331

Installation and Commissioning Automated Demand Response Systems  

E-Print Network (OSTI)

their partnership in demand response automation research andand Techniques for Demand Response. LBNL Report 59975. Mayof Fully Automated Demand Response in Large Facilities.

Kiliccote, Sila; Global Energy Partners; Pacific Gas and Electric Company

2008-01-01T23:59:59.000Z

332

Barrier Immune Radio Communications for Demand Response  

E-Print Network (OSTI)

of Fully Automated Demand Response in Large Facilities,Fully Automated Demand Response Tests in Large Facilities.for Automated Demand Response. Technical Document to

Rubinstein, Francis

2010-01-01T23:59:59.000Z

333

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

23 ii Retail Demand Response in SPP List of Figures and10 Figure 3. Demand Response Resources by11 Figure 4. Existing Demand Response Resources by Type of

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

334

Home Network Technologies and Automating Demand Response  

E-Print Network (OSTI)

and Automating Demand Response Charles McParland, Lawrenceand Automating Demand Response Charles McParland, LBNLCommercial and Residential Demand Response Overview of the

McParland, Charles

2010-01-01T23:59:59.000Z

335

Wireless Demand Response Controls for HVAC Systems  

E-Print Network (OSTI)

Strategies Linking Demand Response and Energy Efficiency,Fully Automated Demand Response Tests in Large Facilities,technical support from the Demand Response Research Center (

Federspiel, Clifford

2010-01-01T23:59:59.000Z

336

Strategies for Demand Response in Commercial Buildings  

E-Print Network (OSTI)

Fully Automated Demand Response Tests in Large Facilitiesof Fully Automated Demand Response in Large Facilities,was coordinated by the Demand Response Research Center and

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

2006-01-01T23:59:59.000Z

337

Option Value of Electricity Demand Response  

E-Print Network (OSTI)

Table 1. Economic demand response and real time pricing (Implications of Demand Response Programs in CompetitiveAdvanced Metering, and Demand Response in Electricity

Sezgen, Osman; Goldman, Charles; Krishnarao, P.

2005-01-01T23:59:59.000Z

338

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

3 2.1 Demand-Side Managementbuildings. The demand side management framework is discussedIssues 2.1 Demand-Side Management Framework Forecasting

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

339

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

of Energy demand-side management energy information systemdemand response. Demand-side management (DSM) program goalsa goal for demand-side management (DSM) coordination and

Goldman, Charles

2010-01-01T23:59:59.000Z

340

China's Coal: Demand, Constraints, and Externalities  

E-Print Network (OSTI)

raising transportation oil demand. Growing internationalcoal by wire could reduce oil demand by stemming coal roadEastern oil production. The rapid growth of coal demand

Aden, Nathaniel

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "monthly peak demand" 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

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

World: Renewable Energy and Demand Response Proliferation intogether the renewable energy and demand response communityimpacts of renewable energy and demand response integration

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

342

electricity demand | OpenEI  

Open Energy Info (EERE)

demand demand Dataset Summary Description The New Zealand Ministry of Economic Development publishes energy data including many datasets related to electricity. Included here are three electricity consumption and demand datasets, specifically: annual observed electricity consumption by sector (1974 to 2009); observed percentage of consumers by sector (2002 - 2009); and regional electricity demand, as a percentage of total demand (2009). Source New Zealand Ministry of Economic Development Date Released Unknown Date Updated July 03rd, 2009 (5 years ago) Keywords Electricity Consumption electricity demand energy use by sector New Zealand Data application/vnd.ms-excel icon Electricity Consumption by Sector (1974 - 2009) (xls, 46.1 KiB) application/vnd.ms-excel icon Percentage of Consumers by Sector (2002 - 2009) (xls, 43.5 KiB)

343

Annual World Oil Demand Growth  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: Following relatively small increases of 1.3 million barrels per day in 1999 and 0.9 million barrels per day in 2000, EIA is estimating world demand may grow by 1.6 million barrels per day in 2001. Of this increase, about 3/5 comes from non-OECD countries, while U.S. oil demand growth represents more than half of the growth projected in OECD countries. Demand in Asia grew steadily during most of the 1990s, with 1991-1997 average growth per year at just above 0.8 million barrels per day. However, in 1998, demand dropped by 0.3 million barrels per day as a result of the Asian economic crisis that year. Since 1998, annual growth in oil demand has rebounded, but has not yet reached the average growth seen during 1991-1997. In the Former Soviet Union, oil demand plummeted during most of the

344

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":""}]}

345

Dynamic forecasting and adaptation for demand optimization in the smart grid  

Science Journals Connector (OSTI)

The daily peaks and valleys in energy demand create inefficiencies and expense in the operation of the electricity grid. Valley periods force utilities to curtail renewable energy sources such as wind as their unpredictable nature makes it difficult ... Keywords: cross-layer, demand optimization, dynamic adaptation, prediction, smart grid

Eamonn O'Toole, Siobhn Clarke

2012-06-01T23:59:59.000Z

346

The Effects of Residential Energy Efficiency on Electric Demand Response Programs  

Science Journals Connector (OSTI)

Design and efficiency of houses can affect the amount of peak load reduction available from a residential demand response program. Twenty-four houses were simulated with varying thermal integrity and air conditioner size during the summer cooling season ... Keywords: demand response, efficiency, residential, hvac, conservation

Ward Jewell

2014-01-01T23:59:59.000Z

347

Comfort-Aware Home Energy Management Under Market-Based Demand-Response  

E-Print Network (OSTI)

Comfort-Aware Home Energy Management Under Market-Based Demand-Response Jin Xiao, Jian Li, Raouf-based pricing. In peak capping, each home is allocated an energy quota. In market-based pricing, the price of energy varies based on market supply-demand. Market-based This research was supported by World Class

Boutaba, Raouf

348

Peak Treatment Systems | Open Energy Information  

Open Energy Info (EERE)

Agreement Partnership Year 1998 Link to project description http:www.nrel.govnewspress199804licns.html Peak Treatment Systems is a company located in Golden, CO....

349

Measured Peak Equipment Loads in Laboratories  

E-Print Network (OSTI)

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

Mathew, Paul A.

2008-01-01T23:59:59.000Z

350

Electric Power Monthly - Monthly Data Tables | OpenEI  

Open Energy Info (EERE)

Power Monthly - Monthly Data Tables Power Monthly - Monthly Data Tables Dataset Summary Description Monthly electricity generation figures (and the fuel consumed to produce it). Source information available at EIA. Source EIA Date Released July 20th, 2010 (4 years ago) Date Updated July 20th, 2010 (4 years ago) Keywords consumption EIA Electricity Electricity Consumption Electricity Generation Data application/vnd.ms-excel icon generation_state_mon.xls (xls, 32.5 MiB) application/vnd.ms-excel icon consumption_state_mon.xls (xls, 14.7 MiB) Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage Frequency Monthly Time Period License License Other or unspecified, see optional comment below Comment Work of the U.S. Federal Government Rate this dataset Usefulness of the metadata

351

Demand-Aware Price Policy Synthesis and Verification Services for Smart Grids  

E-Print Network (OSTI)

at the same time (peak hour), this may result in an economical damage (both for usage of peak power plants forcing residential end users to cut their power demand. On the other hand, if all users require energy interconnection. The first service, which we call EDN Virtual Tomography (EVT) service, considers the whole EDN

Tronci, Enrico

352

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...

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

353

Harnessing the power of demand  

SciTech Connect

Demand response can provide a series of economic services to the market and also provide ''insurance value'' under low-likelihood, but high-impact circumstances in which grid reliablity is enhanced. Here is how ISOs and RTOs are fostering demand response within wholesale electricity markets. (author)

Sheffrin, Anjali; Yoshimura, Henry; LaPlante, David; Neenan, Bernard

2008-03-15T23:59:59.000Z

354

China, India demand cushions prices  

SciTech Connect

Despite the hopes of coal consumers, coal prices did not plummet in 2006 as demand stayed firm. China and India's growing economies, coupled with solid supply-demand fundamentals in North America and Europe, and highly volatile prices for alternatives are likely to keep physical coal prices from wide swings in the coming year.

Boyle, M.

2006-11-15T23:59:59.000Z

355

Honeywell Demonstrates Automated Demand Response Benefits for...  

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

Honeywell Demonstrates Automated Demand Response Benefits for Utility, Commercial, and Industrial Customers Honeywell Demonstrates Automated Demand Response Benefits for Utility,...

356

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

357

Automated Demand Response and Commissioning  

SciTech Connect

This paper describes the results from the second season of research to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve the electric grid reliability and manage electricity costs. Fully-Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. We refer to this as Auto-DR. The evaluation of the control and communications must be properly configured and pass through a set of test stages: Readiness, Approval, Price Client/Price Server Communication, Internet Gateway/Internet Relay Communication, Control of Equipment, and DR Shed Effectiveness. New commissioning tests are needed for such systems to improve connecting demand responsive building systems to the electric grid demand response systems.

Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

2005-04-01T23:59:59.000Z

358

Monthly Energy Review - December 2009  

Gasoline and Diesel Fuel Update (EIA)

Formats Formats (PDF) files; however, all annual data are shown in the Excel and comma-separated values (CSV) files. Also, only two to three years of monthly data are displayed in the PDF files; however, for many series, monthly data beginning with January 1973 are available in the Excel and CSV files. Comprehensive Changes: Each month, most MER tables and figures carry a new month of data, which is usually preliminary (and sometimes estimated or even forecast) and likely to be revised in the succeeding month. Annual Data From 1949: The emphasis of the MER is on recent monthly and annual data trends. Analysts may wish to use the data in this report in conjunction with EIA's Annual Energy Review (AER) that offers annual data beginning in 1949 for many of the data series found in the

359

Prompt-Month Energy Futures  

Gasoline and Diesel Fuel Update (EIA)

Prompt-Month Energy Futures Prompt-Month Energy Futures Prices and trading activity shown are for prompt-month (see definition below) futures contracts for the energy commodities listed in the table below. Note that trading for prompt-month futures contracts ends on different dates at the end of the month for the various commodities; therefore, some commodity prices may reference delivery for the next month sooner than other commodity prices. Product Description Listed With Crude Oil ($/barrel) West Texas Intermediate (WTI) light sweet crude oil delivered to Cushing, Oklahoma More details | Contract specifications New York Mercantile Exchange (Nymex) Gasoline-RBOB ($/gallon) Reformulated gasoline blendstock for oxygenate blending (RBOB) gasoline delivered to New York Harbor More details | Contract specifications Nymex

360

A New Market for an Old Food: the U.S. Demand for Olive Oil , Daniel Sumner  

E-Print Network (OSTI)

A New Market for an Old Food: the U.S. Demand for Olive Oil Bo Xiong , Daniel Sumner , William olive oil continues to be imported. Estimation of a demand system using monthly import data reveals that the income elasticity for virgin oils sourced from EU is above one, but demand for non-virgin oils is income

Schladow, S. Geoffrey

Note: This page contains sample records for the topic "monthly peak demand" 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

Monthly energy review, January 1998  

SciTech Connect

This report presents an overview of recent monthly energy statistics. Major activities covered include production, consumption, trade, stocks, and prices for fossil fuels, electricity, and nuclear energy.

NONE

1998-01-01T23:59:59.000Z

362

Natural gas monthly, July 1997  

SciTech Connect

The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The feature article this month is entitled ``Intricate puzzle of oil and gas reserves growth.`` A special report is included on revisions to monthly natural gas data. 6 figs., 24 tabs.

NONE

1997-07-01T23:59:59.000Z

363

Windpower Monthly | Open Energy Information  

Open Energy Info (EERE)

energy Product: Windpower Monthly is a energy news magazine. It features articles on political, industrial, environmental and technical developments in the global wind energy...

364

Natural gas monthly, August 1995  

SciTech Connect

The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. This month`s feature article is on US Natural Gas Imports and Exports 1994.

NONE

1995-08-24T23:59:59.000Z

365

Monthly News Blast: January 2013  

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

In the January 2013 Monthly News Blast, read about two new funding opportunities, the latest MYPP update, upcoming events, and more.

366

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

global gasoline and diesel price and income elasticities.shift in the short-run price elasticity of gasoline demand.Habits and Uncertain Relative Prices: Simulating Petrol Con-

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

367

Peak CO2? China's Emissions Trajectories to 2050  

E-Print Network (OSTI)

demand, bunker fuel (heavy oil) demand will continue to risea gasoline exporter, as demand for other oil products is notgasoline demand by 100 million tonnes of oil equivalent, but

Zhou, Nan

2012-01-01T23:59:59.000Z

368

Peak CO2? China's Emissions Trajectories to 2050  

E-Print Network (OSTI)

technology and demand side management. This study uses twoGeneration Growth Demand Side Management EV mandates or

Zhou, Nan

2012-01-01T23:59:59.000Z

369

Monthly energy review: April 1996  

SciTech Connect

This monthly report presents an overview of energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. A section is also included on international energy. The feature paper which is included each month is entitled ``Energy equipment choices: Fuel costs and other determinants.`` 37 figs., 59 tabs.

NONE

1996-04-01T23:59:59.000Z

370

Monthly Energy Review, February 1996  

SciTech Connect

This monthly publication presents an overview of EIA`s recent monthly energy statistics, covering the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. Two brief descriptions (`energy plugs`) on two EIA publications are presented at the start.

NONE

1996-02-26T23:59:59.000Z

371

Monthly energy review, November 1996  

SciTech Connect

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 75 tabs.

NONE

1996-11-01T23:59:59.000Z

372

Fact #769: March 4, 2013 Monthly Trend in Light Vehicle Sales, 2008-2012  

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

Over the last five years, there have been peaks in light vehicle sales in the months of March, May, and December. There are two notable exceptions: in 2009, the Cash for Clunkers program caused a...

373

Monthly Energy Review - December 2012  

Gasoline and Diesel Fuel Update (EIA)

EIA's Office of Communications via email EIA's Office of Communications via email at infoctr@eia.gov. Important Notes About the Data Data Displayed: For tables beginning in 1973, some annual data (usually 1974, 1976-1979, 1981-1984, 1986-1989, and 1991-1994) are not shown in the tables in Portable Document Format (PDF) files; however, all annual data are shown in the Excel and comma-separated values (CSV) files. Also, only two to three years of monthly data are displayed in the PDF files; however, for many series, monthly data beginning with January 1973 are available in the Excel and CSV files. Comprehensive Changes: Each month, most MER tables and figures carry a new month of data, which is usually preliminary (and sometimes estimated or even forecast) and likely to be revised in the succeeding month.

374

Peak Oil Futures: Same Crisis, Different Responses  

Science Journals Connector (OSTI)

Peak oil theory predicts that global oil production will soon start a terminal decline. ... resource and technology will be available to replace oil as the backbone resource of industrial society. ... understand ...

Jrg Friedrichs

2012-01-01T23:59:59.000Z

375

A perspective on the CMB acoustic peak  

E-Print Network (OSTI)

CMB angular spectrum measurements suggest a flat universe. This paper clarifies the relation between geometry and the spherical harmonic index of the first acoustic peak ($\\ell_{peak}$). Numerical and analytic calculations show that $\\ell_{peak}$ is approximately a function of $\\Omega_K/\\Omega_M$ where $\\Omega_K$ and $\\Omega_M$ are the curvature ($\\Omega_K > 0$ implies an open geometry) and mass density today in units of critical density. Assuming $\\Omega_K/\\Omega_M \\ll 1$, one obtains a simple formula for $\\ell_{peak}$, the derivation of which gives another perspective on the widely-recognized $\\Omega_M$-$\\Omega_\\Lambda$ degeneracy in flat models. This formula for near-flat cosmogonies together with current angular spectrum data yields familiar parameter constraints.

T. A. Marriage

2002-03-11T23:59:59.000Z

376

EIA - AEO2010 - Electricity Demand  

Gasoline and Diesel Fuel Update (EIA)

Electricity Demand Electricity Demand Annual Energy Outlook 2010 with Projections to 2035 Electricity Demand Figure 69. U.S. electricity demand growth 1950-2035 Click to enlarge » Figure source and data excel logo Figure 60. Average annual U.S. retail electricity prices in three cases, 1970-2035 Click to enlarge » Figure source and data excel logo Figure 61. Electricity generation by fuel in three cases, 2008 and 2035 Click to enlarge » Figure source and data excel logo Figure 62. Electricity generation capacity additions by fuel type, 2008-2035 Click to enlarge » Figure source and data excel logo Figure 63. Levelized electricity costs for new power plants, 2020 and 2035 Click to enlarge » Figure source and data excel logo Figure 64. Electricity generating capacity at U.S. nuclear power plants in three cases, 2008, 2020, and 2035

377

Full Rank Rational Demand Systems  

E-Print Network (OSTI)

as a nominal income full rank QES. R EFERENCES (A.84)S. G. Donald. Inferring the Rank of a Matrix. Journal of97-102. . A Demand System Rank Theorem. Econometrica 57 (

LaFrance, Jeffrey T; Pope, Rulon D.

2006-01-01T23:59:59.000Z

378

Demand Forecasting of New Products  

E-Print Network (OSTI)

Keeping Unit or SKU) employing attribute analysis techniques. The objective of this thesis is to improve Abstract This thesis is a study into the demand forecasting of new products (also referred to as Stock

Sun, Yu

379

Demand Response and Energy Efficiency  

E-Print Network (OSTI)

Demand Response & Energy Efficiency International Conference for Enhanced Building Operations ESL-IC-09-11-05 Proceedings of the Ninth International Conference for Enhanced Building Operations, Austin, Texas, November 17 - 19, 2009 2 ?Less than 5..., 2009 4 An Innovative Solution to Get the Ball Rolling ? Demand Response (DR) ? Monitoring Based Commissioning (MBCx) EnerNOC has a solution involving two complementary offerings. ESL-IC-09-11-05 Proceedings of the Ninth International Conference...

380

Demand Response Spinning Reserve Demonstration  

SciTech Connect

The Demand Response Spinning Reserve project is a pioneeringdemonstration of how existing utility load-management assets can providean important electricity system reliability resource known as spinningreserve. Using aggregated demand-side resources to provide spinningreserve will give grid operators at the California Independent SystemOperator (CAISO) and Southern California Edison (SCE) a powerful, newtool to improve system reliability, prevent rolling blackouts, and lowersystem operating costs.

Eto, Joseph H.; Nelson-Hoffman, Janine; Torres, Carlos; Hirth,Scott; Yinger, Bob; Kueck, John; Kirby, Brendan; Bernier, Clark; Wright,Roger; Barat, A.; Watson, David S.

2007-05-01T23:59:59.000Z

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


381

EIA - Annual Energy Outlook 2008 - Natural Gas Demand  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Demand Natural Gas Demand Annual Energy Outlook 2008 with Projections to 2030 Natural Gas Demand Figure 72. Natural gas consumption by sector, 1990-2030 (trillion cubic feet). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 73. Total natural gas consumption, 1990-2030 (trillion cubic feet). Need help, contact the National Energy Information Center at 202-586-8800. figure data Fastest Increase in Natural Gas Use Is Expected for the Buildings Sectors In the reference case, total natural gas consumption increases from 21.7 trillion cubic feet in 2006 to a peak value of 23.8 trillion cubic feet in 2016, followed by a decline to 22.7 trillion cubic feet in 2030. The natural gas share of total energy consumption drops from 22 percent in 2006

382

U.S. electric utility demand-side management 1995  

SciTech Connect

The US Electric Utility Demand-Side Management report is prepared by the Coal and Electric Data and Renewables Division; Office of Coal, Nuclear, Electric and Alternative Fuels; Energy Information Administration (EIA); US Department of Energy. The report presents comprehensive information on electric power industry demand-side management (DSM) activities in the US at the national, regional, and utility levels. The objective of the publication is to provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it relates to the US electric power industry. The first chapter, ``Profile: US Electric Utility Demand-Side Management``, presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions and costs attributable to DSM. 9 figs., 24 tabs.

NONE

1997-01-01T23:59:59.000Z

383

U.S. electric utility demand-side management 1996  

SciTech Connect

The US Electric Utility Demand-Side Management report presents comprehensive information on electric power industry demand-side management (DSM) activities in the US at the national, regional, and utility levels. The objective of the publication is to provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it related to the US electric power industry. The first chapter, ``Profile: U.S. Electric Utility Demand-Side Management,`` presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions and costs attributable to DSM. 9 figs., 24 tabs.

NONE

1997-12-01T23:59:59.000Z

384

Monthly petroleum-product price report  

SciTech Connect

This report provides Congress and the public with information on monthly national weighted average prices for refined petroleum products. the data published are the primary source of price data for refined products for the refining, reselling, and retailing sectors necessary for the Department of Energy (DOE) to execute its role in monitoring prices. In addition, the data provide the information necessary for Congress, DOE, and the public to perform analyses and projections related to energy supplies, demands, and prices. The legislative authority for this survey is the Federal Energy Administration Act of 1974 (PL 93-275). Price data in this publication were collected fronm separate surveys. Average prices are derived from a survey of refiners, large resellers and/or retailers, and independent gas plant operators. Data from this monthly survey are available from July 1975. Average No. 2 heating oil prices were derived from a sample survye of refiners, resellers, and retailers who sell heating oil. The geographic coverage for this report is the 50 states and the District of Columbia.

Not Available

1982-07-01T23:59:59.000Z

385

MONTHLY NATURAL GAS PRODUCTION REPORT  

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

No. 1905-0205 No. 1905-0205 Expiration Date: 05/31/2015 Burden: 3 hours MONTHLY NATURAL GAS PRODUCTION REPORT Version No.: 2011.001 REPORT PERIOD: Month: Year: If any respondent identification data has changed since the last report, enter an "X" in the box: - - - - Mail to: - Oklahoma 2. Natural Gas Lease Production 1. Gross Withdrawals of Natural Texas Contact Title: COMMENTS: Identify any unusual aspects of your operations during the report month. (To start a new line, use alt + enter.) Wyoming Other States Alaska New Mexico City: Gas Louisiana Company Name: Address 1:

386

Natural gas monthly, June 1996  

SciTech Connect

The natural gas monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The feature article for this month is Natural Gas Industry Restructuring and EIA Data Collection.

NONE

1996-06-24T23:59:59.000Z

387

President Obama's Native American Heritage Month Proclamation | Department  

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

President Obama's Native American Heritage Month Proclamation President Obama's Native American Heritage Month Proclamation President Obama's Native American Heritage Month Proclamation November 5, 2013 - 2:25pm Addthis BY THE PRESIDENT OF THE UNITED STATES OF AMERICA A PROCLAMATION From Alaskan mountain peaks to the Argentinian pampas to the rocky shores of Newfoundland, Native Americans were the first to carve out cities, domesticate crops, and establish great civilizations. When the Framers gathered to write the United States Constitution, they drew inspiration from the Iroquois Confederacy, and in the centuries since, American Indians and Alaska Natives from hundreds of tribes have shaped our national life. During Native American Heritage Month, we honor their vibrant cultures and strengthen the government-to-government relationship between the United

388

President Obama's Native American Heritage Month Proclamation | Department  

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

President Obama's Native American Heritage Month Proclamation President Obama's Native American Heritage Month Proclamation President Obama's Native American Heritage Month Proclamation November 5, 2013 - 2:25pm Addthis BY THE PRESIDENT OF THE UNITED STATES OF AMERICA A PROCLAMATION From Alaskan mountain peaks to the Argentinian pampas to the rocky shores of Newfoundland, Native Americans were the first to carve out cities, domesticate crops, and establish great civilizations. When the Framers gathered to write the United States Constitution, they drew inspiration from the Iroquois Confederacy, and in the centuries since, American Indians and Alaska Natives from hundreds of tribes have shaped our national life. During Native American Heritage Month, we honor their vibrant cultures and strengthen the government-to-government relationship between the United

389

National Action Plan on Demand Response  

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

Action Plan on Demand National Action Plan on Demand Action Plan on Demand National Action Plan on Demand Response Response Federal Utilities Partnership Working Group Federal Utilities Partnership Working Group November 18, 2008 November 18, 2008 Daniel Gore Daniel Gore Office of Energy Market Regulation Office of Energy Market Regulation Federal Energy Regulatory Commission Federal Energy Regulatory Commission The author's views do not necessarily represent the views of the Federal Energy Regulatory Commission Presentation Contents Presentation Contents Statutory Requirements Statutory Requirements National Assessment [Study] of Demand Response National Assessment [Study] of Demand Response National Action Plan on Demand Response National Action Plan on Demand Response General Discussion on Demand Response and Energy Outlook

390

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

E-Print Network (OSTI)

A. Barat, D. Watson. 2006 Demand Response Spinning ReserveKueck, and B. Kirby 2008. Demand Response Spinning ReserveReport 2009. Open Automated Demand Response Communications

Kiliccote, Sila

2010-01-01T23:59:59.000Z

391

Demand Response and Open Automated Demand Response Opportunities for Data Centers  

E-Print Network (OSTI)

Standardized Automated Demand Response Signals. Presented atand Automated Demand Response in Industrial RefrigeratedActions for Industrial Demand Response in California. LBNL-

Mares, K.C.

2010-01-01T23:59:59.000Z

392

Monthly Energy Review - June 2000  

Gasoline and Diesel Fuel Update (EIA)

June June 27, 2000 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(2000/06) Monthly Energy Review

393

Monthly Energy Review - October 1999  

Gasoline and Diesel Fuel Update (EIA)

October October 26, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(99/10) Monthly Energy

394

Monthly Energy Review - August 2003  

Gasoline and Diesel Fuel Update (EIA)

3 3 E n e r g y P l u g : N e w R e a c t o r D e s i g n s Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: August 26, 2003 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy

395

Monthly Energy Review - February 2003  

Gasoline and Diesel Fuel Update (EIA)

3 3 E n e r g y P l u g : M a j o r E n e r g y P r o d u c e r s Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: February 28, 2003 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics.

396

Monthly Energy Review - May 2000  

Gasoline and Diesel Fuel Update (EIA)

May May 26, 2000 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(2000/05) Monthly Energy Review

397

Monthly Energy Review - April 2001  

Gasoline and Diesel Fuel Update (EIA)

April April 30, 2001 Electronic Access The Monthly Energy Review (MER) is available on the Energy Information Administration (EIA) website in a wide variety of formats at: http://www.eia.doe.gov/mer * Tables: ASCII text (TXT) and Portable Document Format (PDF) files. * Table Data Files: Excel (XLS) and Lotus (WK1). * Database Files (unrounded monthly data 1973 forward): Excel (XLS) files. * Graph pages, MER sections, and complete MER: PDF files. Complete MER PDF files are also available on the EIA "Energy Info Disk" through the U.S. De- partment of Commerce at 1-800-STAT-USA. Also available are ASCII comma delimited data files at: http://www.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following

398

Monthly Energy Review - January 2004  

Gasoline and Diesel Fuel Update (EIA)

4 4 E n e r g y P l u g : A n n u a l E n e r g y O u t l o o k Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: January 29, 2004 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics.

399

Monthly Energy Review - April 2003  

Gasoline and Diesel Fuel Update (EIA)

3 3 E n e r g y P l u g : E l e c t r i c P o w e r A n n u a l 2 0 0 1 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: May 22, 2003 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics.

400

Monthly Energy Review - January 2010  

Gasoline and Diesel Fuel Update (EIA)

Full report and sections: PDF files Report tables: PDF files Table data (unrounded): Excel and CSV files Graphs: PDF files Note: PDF files display selected annual and monthly data; Excel and CSV files display all available annual and monthly data, often at a greater level of precision than the PDF files. Timing of Release: MER updates are usually posted electronically by the third-to-the-last workday of each month. Released: January 29, 2010 DOE/EIA-0035(2010/01) Monthly Energy Review January 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the

Note: This page contains sample records for the topic "monthly peak demand" 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

Monthly Energy Review - December 2002  

Gasoline and Diesel Fuel Update (EIA)

2 2 E n e r g y P l u g : R e n e w a b l e E n e r g y A n n u a l Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: December 23, 2002 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics.

402

Monthly Energy Review - January 2003  

Gasoline and Diesel Fuel Update (EIA)

3 3 E n e r g y P l u g : A n n u a l E n e r g y O u t l o o k Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: January 30, 2003 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics.

403

Monthly Energy Review - October 2000  

Gasoline and Diesel Fuel Update (EIA)

October October 25, 2000 Electronic Access The Monthly Energy Review (MER) is available on the Energy Information Administration (EIA) website in a wide variety of formats at: http://www.eia.doe.gov/mer * Tables: ASCII text (TXT) and Portable Document Format (PDF) files. * Table Data Files: Excel (XLS) and Lotus (WK1). * Database Files (unrounded monthly data 1973 forward): Excel (XLS) files. * Graph pages, MER sections, and complete MER: PDF files. Complete MER PDF files are also available on the EIA "Energy Info Disk" through the U.S. De- partment of Commerce at 1-800-STAT-USA. Also available are ASCII comma delimited data files at: http://www.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following

404

Monthly Energy Review - December 1999  

Gasoline and Diesel Fuel Update (EIA)

December December 22, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(99/12) Monthly Energy

405

Monthly Energy Review - November 2003  

Gasoline and Diesel Fuel Update (EIA)

3 3 E n e r g y P l u g : A n n u a l C o a l R e p o r t 2 0 0 2 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: November 24, 2003 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics.

406

Monthly Energy Review - June 2003  

Gasoline and Diesel Fuel Update (EIA)

3 3 E n e r g y P l u g : U r a n i u m I n d u s t r y A n n u a l 2 0 0 2 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: June 30, 2003 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics.

407

Monthly Energy Review - September 2000  

Gasoline and Diesel Fuel Update (EIA)

September September 26, 2000 Electronic Access The Monthly Energy Review (MER) is available on the Energy Information Administration (EIA) website in a wide variety of formats at: http://www.eia.doe.gov/mer * Tables: ASCII text (TXT) and Portable Document Format (PDF) files. * Table Data Files: Excel (XLS) and Lotus (WK1). * Database Files (unrounded monthly data 1973 forward): Excel (XLS) files. * Graph pages, MER sections, and complete MER: PDF files. Complete MER PDF files are also available on the EIA "Energy Info Disk" through the U.S. De- partment of Commerce at 1-800-STAT-USA. Also available are ASCII comma delimited data files at: http://www.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following

408

Monthly Energy Review - April 200  

Gasoline and Diesel Fuel Update (EIA)

April April 26, 2000 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(2000/04) Monthly Energy

409

Monthly Energy Review - November 2002  

Gasoline and Diesel Fuel Update (EIA)

2 2 E n e r g y P l u g : A n n u a l E n e r g y R e v i e w Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: December 6, 2002 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics.

410

Monthly Energy Review - January 2000  

Gasoline and Diesel Fuel Update (EIA)

January January 28, 2000 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(00/01) Monthly Energy

411

Monthly Energy Review - February 2000  

Gasoline and Diesel Fuel Update (EIA)

February February 24, 2000 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(00/02) Monthly Energy

412

Monthly Energy Review - June 2001  

Gasoline and Diesel Fuel Update (EIA)

June June 28, 2001 Electronic Access The Monthly Energy Review (MER) is available on the Energy Information Administration (EIA) website in a wide variety of formats at: http://www.eia.doe.gov/mer * Tables: ASCII text (TXT) and Portable Document Format (PDF) files. * Table Data Files: Excel (XLS) and Lotus (WK1). * Database Files (unrounded monthly data 1973 forward): Excel (XLS) files. * Graph pages, MER sections, and complete MER: PDF files. Complete MER PDF files are also available on the EIA "Energy Info Disk" through the U.S. De- partment of Commerce at 1-800-STAT-USA. Also available are ASCII comma delimited data files at: http://www.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following

413

Monthly Energy Review - February 2004  

Gasoline and Diesel Fuel Update (EIA)

4 4 E n e r g y P l u g : N a t u r a l G a s A n n u a l 2 0 0 2 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: February 24, 2004 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics.

414

Monthly Energy Review - September 1999  

Gasoline and Diesel Fuel Update (EIA)

September September 27, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(99/09) Monthly Energy

415

Monthly energy review, August 1993  

SciTech Connect

This publication presents information for the month of August, 1993 on the following: Energy overview; energy consumption; petroleum; natural gas; oil and gas resource development; coal; electricity; nuclear energy; energy prices, and international energy.

Not Available

1993-08-26T23:59:59.000Z

416

May 2013 Monthly News Blast  

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

The Bioenergy Technologies Office's May 2013 Monthly News Blast highlights the upcoming Biomass 2013 conference, a webinar on ionic liquids, the new Multi-Year Program Plan, and more.

417

Monthly Performance Report October 2009  

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

an internal MSA verification is in process. EXECUTIVE OVERVIEW MSC Monthly Performance Report October 2009 DOERL-2009-113 REV 1 3 2.0 ANALYSIS OF FUNDS Table 2-1. Mission...

418

Monthly Energy Review - January 2015  

Gasoline and Diesel Fuel Update (EIA)

Overview, 1949-2013 Overview, Monthly Overview, October 2014 Net Imports, January-October Web Page: http:www.eia.govtotalenergydatamonthlysummary. Source: Table 1.1. 2 U.S....

419

Monthly Energy Review - December 2014  

Gasoline and Diesel Fuel Update (EIA)

1949-2013 Overview, Monthly Overview, September 2014 Net Imports, January-September Web Page: http:www.eia.govtotalenergydatamonthlysummary. Source: Table 1.1. 2 U.S....

420

Monthly Energy Review - September 2014  

Gasoline and Diesel Fuel Update (EIA)

Btu) Overview, 1949-2013 Overview, Monthly Overview, June 2014 Net Imports, January-June Web Page: http:www.eia.govtotalenergydatamonthlysummary. Source: Table 1.1. 2 U.S....

Note: This page contains sample records for the topic "monthly peak demand" 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

Monthly Energy Review - July 2014  

Gasoline and Diesel Fuel Update (EIA)

Overview, 1949-2013 Overview, Monthly Overview, April 2014 Net Imports, January-April Web Page: http:www.eia.govtotalenergydatamonthlysummary. Source: Table 1.1. 2 U.S....

422

Monthly Energy Review - August 2014  

Gasoline and Diesel Fuel Update (EIA)

Btu) Overview, 1949-2013 Overview, Monthly Overview, May 2014 Net Imports, January-May Web Page: http:www.eia.govtotalenergydatamonthlysummary. Source: Table 1.1. 2 U.S....

423

Recapping National Energy Action Month  

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

Energy Department officials spent National Energy Action Month on the road, meeting and learning from Americans who are advancing our energy security, growing the economy and protecting the environment.

424

Flow shop scheduling with peak power consumption constraints  

E-Print Network (OSTI)

Mar 29, 2012 ... Flow shop scheduling with peak power consumption constraints ... Keywords: scheduling, flow shop, energy, peak power consumption, integer...

K. Fang

2012-03-29T23:59:59.000Z

425

Natural gas monthly: December 1993  

SciTech Connect

The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. Articles are included which are designed to assist readers in using and interpreting natural gas information.

Not Available

1993-12-01T23:59:59.000Z

426

Natural gas monthly, June 1997  

SciTech Connect

The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. 6 figs., 24 tabs.

NONE

1997-06-01T23:59:59.000Z

427

Natural gas monthly, August 1994  

SciTech Connect

The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

Not Available

1994-08-24T23:59:59.000Z

428

Natural gas monthly: September 1996  

SciTech Connect

The Natural Gas Monthly highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. 6 figs., 24 tabs.

NONE

1996-09-01T23:59:59.000Z

429

Natural gas monthly, November 1993  

SciTech Connect

The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground state data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information.

Not Available

1993-11-29T23:59:59.000Z

430

Facilitating Renewable Integration by Demand Response  

Science Journals Connector (OSTI)

Demand response is seen as one of the resources ... expected to incentivize small consumers to participate in demand response. This chapter models the involvement of small consumers in demand response programs wi...

Juan M. Morales; Antonio J. Conejo

2014-01-01T23:59:59.000Z

431

Demand Response as a System Reliability Resource  

E-Print Network (OSTI)

Barat, and D. Watson. 2007. Demand Response Spinning ReserveKueck, and B. Kirby. 2009. Demand Response Spinning ReserveFormat of 2009-2011 Demand Response Activity Applications.

Joseph, Eto

2014-01-01T23:59:59.000Z

432

Demand response-enabled residential thermostat controls.  

E-Print Network (OSTI)

human dimension of demand response technology from a caseArens, E. , et al. 2008. Demand Response Enabling TechnologyArens, E. , et al. 2006. Demand Response Enabling Technology

Chen, Xue; Jang, Jaehwi; Auslander, David M.; Peffer, Therese; Arens, Edward A

2008-01-01T23:59:59.000Z

433

Value of Demand Response -Introduction Klaus Skytte  

E-Print Network (OSTI)

Value of Demand Response - Introduction Klaus Skytte Systems Analysis Department February 7, 2006 Energinet.dk, Ballerup #12;What is Demand Response? Demand response (DR) is the short-term response

434

World Energy Use Trends in Demand  

Science Journals Connector (OSTI)

In order to provide adequate energy supplies in the future, trends in energy demand must be evaluated and projections of future demand developed. World energy use is far from static, and an understanding of the demand

Randy Hudson

1996-01-01T23:59:59.000Z

435

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

California Energy Demand Scenario Projections to 2050 RyanCEC (2003a) California energy demand 2003-2013 forecast.CEC (2005a) California energy demand 2006-2016: Staff energy

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

436

Balancing of Energy Supply and Residential Demand  

Science Journals Connector (OSTI)

Power demand of private households shows daily fluctuations and ... (BEV) and heat pumps. This additional demand, especially when it remains unmanaged, will ... to an increase in fluctuations. To balance demand,

Martin Bock; Grit Walther

2014-01-01T23:59:59.000Z

437

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":""}]}

438

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":""}]}

439

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":""}]}

440

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":""}]}

Note: This page contains sample records for the topic "monthly peak demand" 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

First Tracer Test After Circulation in Desert Peak 27-15  

DOE Data Explorer (OSTI)

Following the successful stimulation of Desert Peak target EGS well 27-15, a circulation test was initiated by injecting a conservative tracer (1,5-nds) in combination with a reactive tracer (7-amino-1,3-naphthalene disulfonate). The closest production well 74-21 was monitored over the subsequent several months.

Peter Rose

442

First Tracer Test After Circulation in Desert Peak 27-15  

SciTech Connect

Following the successful stimulation of Desert Peak target EGS well 27-15, a circulation test was initiated by injecting a conservative tracer (1,5-nds) in combination with a reactive tracer (7-amino-1,3-naphthalene disulfonate). The closest production well 74-21 was monitored over the subsequent several months.

Rose, Peter

2013-11-16T23:59:59.000Z

443

Definition: Demand | Open Energy Information  

Open Energy Info (EERE)

form form View source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Definition Edit with form History Facebook icon Twitter icon » Definition: Demand Jump to: navigation, search Dictionary.png Demand The rate at which electric energy is delivered to or by a system or part of a system, generally expressed in kilowatts or megawatts, at a given instant or averaged over any designated interval of time., The rate at which energy is being used by the customer.[1] Related Terms energy, electricity generation References ↑ Glossary of Terms Used in Reliability Standards An i Like Like You like this.Sign Up to see what your friends like. nline Glossary Definition Retrieved from "http://en.openei.org/w/index.php?title=Definition:Demand&oldid=480555"

444

Winter Demand Impacted by Weather  

Gasoline and Diesel Fuel Update (EIA)

8 8 Notes: Heating oil demand is strongly influenced by weather. The "normal" numbers are the expected values for winter 2000-2001 used in EIA's Short-Term Energy Outlook. The chart indicates the extent to which the last winter exhibited below-normal heating degree-days (and thus below-normal heating demand). Temperatures were consistently warmer than normal throughout the 1999-2000 heating season. This was particularly true in November 1999, February 2001 and March 2001. For the heating season as a whole (October through March), the 1999-2000 winter yielded total HDDs 10.7% below normal. Normal temperatures this coming winter would, then, be expected to bring about 11% higher heating demand than we saw last year. Relative to normal, the 1999-2000 heating season was the warmest in

445

Turkey's energy demand and supply  

SciTech Connect

The aim of the present article is to investigate Turkey's energy demand and the contribution of domestic energy sources to energy consumption. Turkey, the 17th largest economy in the world, is an emerging country with a buoyant economy challenged by a growing demand for energy. Turkey's energy consumption has grown and will continue to grow along with its economy. Turkey's energy consumption is high, but its domestic primary energy sources are oil and natural gas reserves and their production is low. Total primary energy production met about 27% of the total primary energy demand in 2005. Oil has the biggest share in total primary energy consumption. Lignite has the biggest share in Turkey's primary energy production at 45%. Domestic production should be to be nearly doubled by 2010, mainly in coal (lignite), which, at present, accounts for almost half of the total energy production. The hydropower should also increase two-fold over the same period.

Balat, M. [Sila Science, Trabzon (Turkey)

2009-07-01T23:59:59.000Z

446

International Oil Supplies and Demands  

SciTech Connect

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

Not Available

1991-09-01T23:59:59.000Z

447

International Oil Supplies and Demands  

SciTech Connect

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

Not Available

1992-04-01T23:59:59.000Z

448

Vad r 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)

Wlimaa, Peter

2013-01-01T23:59:59.000Z

449

Demand Response as a System Reliability Resource  

E-Print Network (OSTI)

for Demand Response Technology Development The objective ofin planning demand response technology RD&D by conductingNew and Emerging Technologies into the California Smart Grid

Joseph, Eto

2014-01-01T23:59:59.000Z

450

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

California Long-term Energy Efficiency Strategic Plan. B-2 Coordination of Energy Efficiency and Demand Response> B-4 Coordination of Energy Efficiency and Demand Response

Goldman, Charles

2010-01-01T23:59:59.000Z

451

Demand Response - Policy | Department of Energy  

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

Demand Response - Policy Demand Response - Policy Since its inception, the Office of Electricity Delivery and Energy Reliability (OE) has been committed to modernizing the nation's...

452

Sandia National Laboratories: demand response inverter  

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

demand response inverter ECIS-Princeton Power Systems, Inc.: Demand Response Inverter On March 19, 2013, in DETL, Distribution Grid Integration, Energy, Energy Surety, Facilities,...

453

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

and Demand Response A pilot program from NSTAR in Massachusetts,Massachusetts, aiming to test whether an intensive program of energy efficiency and demand response

Goldman, Charles

2010-01-01T23:59:59.000Z

454

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

annual per-capita electricity consumption by demand15 California electricity consumption projections by demandannual per-capita electricity consumption by demand

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

455

Marketing & Driving Demand: Social Media Tools & Strategies ...  

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

Demand: Social Media Tools & Strategies - January 16, 2011 Marketing & Driving Demand: Social Media Tools & Strategies - January 16, 2011 January 16, 2011 Conference Call...

456

Marketing & Driving Demand Collaborative - Social Media Tools...  

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

Demand Collaborative - Social Media Tools & Strategies Marketing & Driving Demand Collaborative - Social Media Tools & Strategies Presentation slides from the BetterBuildings...

457

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

Vehicle Conventional and Alternative Fuel Response Simulatormodified to include alternative fuel demand scenarios (whichvehicle adoption and alternative fuel demand) later in the

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

458

\\{HEMSs\\} and enabled demand response in electricity market: An overview  

Science Journals Connector (OSTI)

Abstract Traditional electricity grid offers demand side management (DSM) programs for industrial plants and commercial buildings; there is no such program for residential consumers because of the lack of effective automation tools and efficient information and communication technologies (ICTs). Smart Grid is, by definition, equipped with modern automation tools such as home energy management system (HEMS), and ICTs. HEMS is an intelligent system that performs planning, monitoring and control functions of the energy utilization within premises. It is intended to offer desirable demand response according to system conditions and price value signaled by the utility. HEMS enables smart appliances to counter demand response programs according to the comfort level and priority set by the consumer. Demand response can play a key role to ensure sustainable and reliable electricity supply by reducing future generation cost, electricity prices, CO2 emission and electricity consumption at peak times. This paper focuses on the review of \\{HEMSs\\} and enabled demand response (DR) programs in various scenarios as well as incorporates various DR architectures and models employed in the smart grid. A comprehensive case study along with simulations and numerical analysis has also been presented.

Aftab Ahmed Khan; Sohail Razzaq; Asadullah Khan; Fatima Khursheed; Owais

2015-01-01T23:59:59.000Z

459

An Open Architecture Platform for Demand Resources from AutoDR and MBCx:  

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

An Open Architecture Platform for Demand Resources from AutoDR and MBCx: An Open Architecture Platform for Demand Resources from AutoDR and MBCx: National Virtual Power Plant Speaker(s): Jung In Choi Date: December 20, 2013 - 2:00pm - 3:00pm Location: 90-3122 Seminar Host/Point of Contact: Philip Haves The presentation lays out the technology and business model for National Virtual Power Plant (NVPP). NAPP is a Korean initiative to develop a cluster of demand resources from consumers by peak reduction or energy saving. Demand resources from NVPP are collectively traded in the open architecture platform for energy market. The platform enables 3rd parties to develop new business models and applications through open API s. It will bring a long tail market for demand response and energy efficiency in small and medium size buildings as well as large ones. Automated Demand

460

Demand Side Management by controlling refrigerators and its effects on consumers  

Science Journals Connector (OSTI)

Demand Side Management in power grids has become more and more important in recent years. Continuously growing energy demand both increases the need for distributed generation from renewable energy sources and brings out the topic of Demand Side Management. One of the major application areas of Demand Side Management in smart grids is cooling systems. In this paper, Demand Side Management with control of a refrigerator and its economic effects on consumers are analyzed. With a refrigerator model based on real measurements, several cooling schedules are simulated and annual energy fees for different pricing methods in use in Turkey are calculated and discussed. The results revealed that, 37.9% of refrigerators demand in peak period can be shifted to other periods and annual electricity bills for customers can be reduced by 11.4%.

M. Alparslan Zehir; Mustafa Bagriyanik

2012-01-01T23:59:59.000Z

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


461

Monthly Energy Review - April 2005  

Gasoline and Diesel Fuel Update (EIA)

5 5 E n e r g y P l u g : A l t e r n a t i v e M e r c u r y C o n t r o l S t r a t e g i e s Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: April 27, 2005 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin-

462

Monthly Energy Review - February 2006  

Gasoline and Diesel Fuel Update (EIA)

6 6 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: February 23, 2006 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

463

Monthly Energy Review - May 1999  

Gasoline and Diesel Fuel Update (EIA)

May May 25, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website. Go to http://www.eia.doe.gov and click on "Energy Overview." Data are available in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/emeu/mer/contents.html) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. DOE/EIA-0035(99/05) Monthly Energy Review May 1999 Energy Information Administration Office

464

Monthly Energy Review, October 1998  

Gasoline and Diesel Fuel Update (EIA)

October October 27, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/ multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/10) Distribution Category UC-950 Monthly Energy

465

Monthly Energy Review - September 2005  

Gasoline and Diesel Fuel Update (EIA)

5 5 E n e r g y P l u g : I n t e r n a t i o n a l E n e r g y O u t l o o k 2 0 0 5 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: September 27, 2005 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin-

466

Monthly Energy Review - November 2000  

Gasoline and Diesel Fuel Update (EIA)

November 2000 November 2000 www.eia.doe.gov Energy Information Administration On the Web at: www.eia.doe.gov/mer Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics. The statisti cs cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and ther- mal and metric conversion factors. Publication of this report is in keeping with responsibilities given to the Energy Information Administration (EIA) in Public Law 95-91 (Department of Energy Organization Act), which states, in part, in Section 205(a)(2), that: The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes

467

Monthly Energy Review - July 2000  

Gasoline and Diesel Fuel Update (EIA)

July July 26, 2000 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Cover Image: Optical glass fibers, though

468

Monthly Energy Review, July 1998  

Gasoline and Diesel Fuel Update (EIA)

July July 28, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/ multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/07) Distribution Category UC-950 Monthly Energy Review

469

Monthly Energy Review - October 2002  

Gasoline and Diesel Fuel Update (EIA)

2 2 E n e r g y P l u g : W i n t e r F u e l s O u t l o o k Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statis- tics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are interna- tional energy and thermal and metric conversion factors. Publication of this report is in keeping with responsibilities given to the Energy Information Administration (EIA) in Public Law 95-91 (Department of Energy Organization Act), which states, in part, in Section 205(a)(2), that: The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the MER and in other EIA

470

Monthly Energy Review - October 2003  

Gasoline and Diesel Fuel Update (EIA)

3 3 E n e r g y P l u g : A n n u a l E n e r g y R e v i e w 2 0 0 2 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: October 27, 2003 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the

471

Monthly Energy Review, September 1998  

Gasoline and Diesel Fuel Update (EIA)

September September 25, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/ multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/09) Distribution Category UC-950 Monthly Energy

472

Monthly Energy Review - August 2004  

Gasoline and Diesel Fuel Update (EIA)

4 4 E n e r g y P l u g : B i o d i e s e l P e r f o r m a n c e , C o s t s , a n d U s e Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: August 25, 2004 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin-

473

MONTHLY NATURAL GAS PRODUCTION REPORT  

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

205 205 Expiration Date: 09/20/2012 Burden: 3 hours MONTHLY NATURAL GAS PRODUCTION REPORT Version No.: 2011.001 REPORT PERIOD: Month: Year: If any respondent identification data has changed since the last report, enter an "X" in the box: - - - - Mail to: - Oklahoma 2. Natural Gas Lease Production 1. Gross Withdrawals of Natural Texas Contact Title: COMMENTS: Identify any unusual aspects of your operations during the report month. (To start a new line, use alt + enter.) Wyoming Other States Alaska New Mexico City: Gas Louisiana Company Name: Address 1: Address 2: Questions? Contact Name: Phone No.: Email: If this is a resubmission, enter an "X" in the box: This form may be submitted to the EIA by mail, fax, e-mail, or secure file transfer. Should you choose to submit your data via e-mail, we must advise you that e-mail is an insecure means of transmission because the data are not encrypted, and there is

474

Monthly Energy Review - October 2005  

Gasoline and Diesel Fuel Update (EIA)

5 5 E n e r g y P l u g : W i n t e r F u e l s O u t l o o k Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: October 26, 2005 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

475

Monthly Energy Review - July 2005  

Gasoline and Diesel Fuel Update (EIA)

5 5 E n e r g y P l u g : E l e c t r i c P o w e r F l a s h E s t i m a t e s Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: July 26, 2005 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin-

476

Monthly Energy Review - March 2006  

Gasoline and Diesel Fuel Update (EIA)

6 6 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: March 27, 2006 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

477

Monthly Energy Review - September 2004  

Gasoline and Diesel Fuel Update (EIA)

4 4 E n e r g y P l u g : S t a t e R e n e w a b l e E n e r g y P r o g r a m s Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: September 28, 2004 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin-

478

Monthly Energy Review - July 2001  

Gasoline and Diesel Fuel Update (EIA)

E E n e r g y P l u g : C o a l I n d u s t r y A n n u a l July 2001 Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics. The statistics cover the major activities of U.S. pro- duction, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also in- cluded are international energy and thermal and metric conversion factors. Publication of this report is in keeping with responsibilities given to the Energy Information Administration (EIA) in Public Law 95-91 (Department of Energy Organization Act), which states, in part, in Section 205(a)(2), that: The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the MER and

479

Monthly Energy Review, July 1997  

Gasoline and Diesel Fuel Update (EIA)

use by use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the MER and in other EIA publications. Related Publication: Readers of the MER may also be interested in EIA's Annual Energy Review, where many of the same data series are provided annually beginning with 1949. Contact our National Energy Information Center at 202-586-8800 for more information. Timing of Release: MER data are normally released in the afternoon of the third-from-the-last workday of each month and are usually available electronically late that day. Internet Addresses: E-Mail: infoctr@eia.doe.gov World Wide Web Site: http://www.eia.doe.gov Gopher Site: gopher://gopher.eia.doe.gov FTP Site: ftp://ftp.eia.doe.gov The Monthly Energy Review (ISSN 0095-7356) is published monthly

480

Monthly Energy Review - November 2004  

Gasoline and Diesel Fuel Update (EIA)

4 4 E n e r g y P l u g : O i l M a r k e t B a s i c s Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: November 23, 2004 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

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


481

Monthly Energy Review - February 1999  

Gasoline and Diesel Fuel Update (EIA)

February February 26, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website. Go to http://www.eia.doe.gov and click on "Energy Overview." Data are available in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/emeu/mer/contents.html) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. DOE/EIA-0035(99/02) Monthly Energy Review February 1999 Energy Information Administration

482

Monthly Energy Review - November 2005  

Gasoline and Diesel Fuel Update (EIA)

5 5 E n e r g y P l u g : A n n u a l C o a l R e p o r t 2 0 0 4 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: November 23, 2005 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin-

483

Monthly Energy Review - April 2006  

Gasoline and Diesel Fuel Update (EIA)

6 6 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: April 25, 2006 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

484

Monthly Energy Review, November 1998  

Gasoline and Diesel Fuel Update (EIA)

November November 24, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/ multi.htm * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at: ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/11) Distribution Category UC-950 Monthly Energy

485

Monthly Energy Review, June 1998  

Gasoline and Diesel Fuel Update (EIA)

June June 25, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/06) Distribution Category UC-950 Monthly Energy Review

486

Monthly Energy Review - March 2001  

Gasoline and Diesel Fuel Update (EIA)

98.00 98.00 per year (price subject to change without advance notice). Periodical postage paid at Washington, DC 20066-9998, and additional mailing offices. POSTMASTER: Send address changes to Monthly Energy Review, Energy Information Administration, EI-30, 1000 Independence Avenue, SW, Washington, DC 20585-0623. Printed with soy ink on recycled paper. Released for Printing: March 27, 2001 Electronic Access The Monthly Energy Review (MER) is available on the Energy Information Administration (EIA) website in a wide variety of formats at: http://www.eia.doe.gov/mer * Tables: ASCII text (TXT) and Portable Document Format (PDF) files. * Table Data Files: Excel (XLS) and Lotus (WK1). * Database Files (unrounded monthly data 1973 forward): Excel (XLS) files. * Graph pages, MER sections, and complete MER: PDF files. Complete MER PDF files are also available on the EIA "Energy

487

Monthly Energy Review - January 1999  

Gasoline and Diesel Fuel Update (EIA)

January January 26, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website. Go to http://www.eia.doe.gov and click on "Energy Overview." Data are available in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/emeu/mer/contents.html) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. DOE/EIA-0035(99/01) Distribution Category UC-950 Monthly Energy Review January 1999 Energy

488

Monthly Energy Review April 1999  

Gasoline and Diesel Fuel Update (EIA)

April April 27, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website. Go to http://www.eia.doe.gov and click on "Energy Overview." Data are available in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/emeu/mer/contents.html) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. DOE/EIA-0035(99/04) Monthly Energy Review April 1999 Energy Information Administration Office

489

Monthly Energy Review, August 1998  

Gasoline and Diesel Fuel Update (EIA)

August August 25, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/ multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/08) Distribution Category UC-950 Monthly Energy Review

490

Monthly Energy Review - December 1998  

Gasoline and Diesel Fuel Update (EIA)

December December 22, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/ multi.htm * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at: ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/12) Distribution Category UC-950 Monthly Energy

491

Monthly Energy Review - July 2004  

Gasoline and Diesel Fuel Update (EIA)

4 4 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: July 27, 2004 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's primary report of recent energy statistics. Included are

492

Monthly Energy Review - May 2004  

Gasoline and Diesel Fuel Update (EIA)

4 4 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: May 26, 2004 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's primary report of recent energy statistics. Included are

493

Monthly Energy Review - September 2003  

Gasoline and Diesel Fuel Update (EIA)

September September 2003 E n e r g y P l u g : F o r e i g n D i r e c t I n v e s t m e n t Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: September 26, 2003 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the

494

Monthly Energy Review - December 2006  

Gasoline and Diesel Fuel Update (EIA)

6 6 NOTICE Last Issue in Print (See page iii) Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: December 21, 2006 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin-

495

Monthly Energy Review - January 2006  

Gasoline and Diesel Fuel Update (EIA)

6 6 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: January 25, 2006 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

496

Monthly Energy Review - July 2006  

Gasoline and Diesel Fuel Update (EIA)

6 6 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: July 26, 2006 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

497

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":""}]}

498

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":""}]}

499

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":""}]}

500

Preliminary Assumptions for Natural Gas Peaking  

E-Print Network (OSTI)

Preliminary Assumptions for Natural Gas Peaking Technologies Gillian Charles GRAC 2/27/14 #12;Today Vernon, WA PSE Klamath Generation Peakers June 2002 (2) 54 MW P&W FT8 Twin- pac 95 MW Klamath, OR IPP; winter-only PPA w/ PSE Dave Gates Generating Station Jan 2011 (3) P&W SWIFTPAC 150 MW Anaconda, MT North