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1

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

2

Highest-Resolution Ribosome Structure  

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

Highest-Resolution Ribosome Structure Print Highest-Resolution Ribosome Structure Print The last step in converting the genetic information stored in DNA into the major functional parts of cells is protein biosynthesis. Protein synthesis occurs on the ribosome, a cellular factory found in all forms of life. In contrast to most cellular machines, the ribosome contains a functional core of RNA that is enhanced by ribosomal proteins and accessory factors. Two structures of the intact ribosome from the common bacterium Escherichia coli, determined by a Berkeley-Berlin collaboration to a resolution of 3.5 Å, the highest yet achieved, provide many new insights into how the ribosome factory works. Ribosomes Ready for Extreme Close-Up In 1999, the first structure of the intact ribosome-a very large, asymmetric protein that is difficult to crystallize-was solved by x-ray crystallography at the ALS (see "Solving the Ribosome Puzzle"). Since then, scientists have developed quite an extensive photo gallery of ribosomes from various organisms and in various configurations. More importantly, they have sharpened the focus significantly, going from a resolution of 7.8 Å in 1999, to 5.5 Å in 2001 (see "Zooming in on Ribosomes"), to an amazing 3.5 Å in this latest work. What was initially seen as fuzzy "fingers" of electron density can now be resolved into individual nucleotides in the RNA strands. Serendipitously, the crystals used in this particular study contained two versions of the ribosome, each one in a different "pose," allowing the researchers to compare the positions of the various parts and deduce how they work. With these sharper images, scientists are now better able to interpret previous data, test models, and develop new theories, both practical (how do antibiotics that target the ribosome work?) and theoretical (how much has the ribosome evolved from bacteria to human?). Stay tuned.

3

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

4

Geothermal California: California Claims the World's Highest...  

Open Energy Info (EERE)

the World's Highest Geothermal Power Output with Potential for Even More Production With Advanced Techniques Jump to: navigation, search OpenEI Reference LibraryAdd to library...

5

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...

6

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

7

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

8

Highest weight Macdonald and Jack Polynomials  

E-Print Network (OSTI)

Fractional quantum Hall states of particles in the lowest Landau levels are described by multivariate polynomials. The incompressible liquid states when described on a sphere are fully invariant under the rotation group. Excited quasiparticle/quasihole states are member of multiplets under the rotation group and generically there is a nontrivial highest weight member of the multiplet from which all states can be constructed. Some of the trial states proposed in the literature belong to classical families of symmetric polynomials. In this paper we study Macdonald and Jack polynomials that are highest weight states. For Macdonald polynomials it is a (q,t)-deformation of the raising angular momentum operator that defines the highest weight condition. By specialization of the parameters we obtain a classification of the highest weight Jack polynomials. Our results are valid in the case of staircase and rectangular partition indexing the polynomials.

Th. Jolicoeur; J. G. Luque

2011-01-05T23:59:59.000Z

9

SPACE TECHNOLOGY Actual Estimate  

E-Print Network (OSTI)

SPACE TECHNOLOGY TECH-1 Actual Estimate Budget Authority (in $ millions) FY 2011 FY 2012 FY 2013 FY.7 247.0 Exploration Technology Development 144.6 189.9 202.0 215.5 215.7 214.5 216.5 Notional SPACE TECHNOLOGY OVERVIEW .............................. TECH- 2 SBIR AND STTR

10

A Vision of Demand Response - 2016  

SciTech Connect

Envision a journey about 10 years into a future where demand response is actually integrated into the policies, standards, and operating practices of electric utilities. Here's a bottom-up view of how demand response actually works, as seen through the eyes of typical customers, system operators, utilities, and regulators. (author)

Levy, Roger

2006-10-15T23:59:59.000Z

11

Alternative Detection Methods for Highest Energy Neutrinos  

E-Print Network (OSTI)

Several experimental techniques are currently under development, to measure the expected tiny fluxes of highest energy neutrinos above 10**18 eV. Projects in different stages of realisation are discussed here, which are based on optical and radio as well as acoustic detectors. For the detection of neutrino events in this energy range a combination of different detector concepts in one experiment seems to be most promising.

Rolf Nahnhauer

2004-11-26T23:59:59.000Z

12

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

13

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

14

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

15

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

16

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

17

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...

18

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

19

Occupancy Based Demand Response HVAC Control Strategy Varick L. Erickson  

E-Print Network (OSTI)

Occupancy Based Demand Response HVAC Control Strategy Varick L. Erickson University of California an efficient demand response HVAC control strategy, actual room usage must be considered. Temperature and CO2 are used for simulations but not for predictive demand response strategies. In this paper, we develop

Cerpa, Alberto E.

20

Sustainability brings BPA highest award in Federal Electronics...  

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

Sustainability-brings-BPA-highest-award-in-Federal-Electronics-Challenge Sign In About | Careers | Contact | Investors | bpa.gov Search News & Us Expand News & Us Projects &...

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

New Mexico Environment Department Presents WIPP Its Highest Recognition for  

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

Mexico Environment Department Presents WIPP Its Highest Mexico Environment Department Presents WIPP Its Highest Recognition for Environmental Excellence New Mexico Environment Department Presents WIPP Its Highest Recognition for Environmental Excellence April 30, 2013 - 12:00pm Addthis Media Contact Deb Gill, (575) 234-7270 U.S. DOE Carlsbad Field Office www.wipp.energy.gov CARLSBAD, N.M., April 30, 2013 - The U.S. Department of Energy's (DOE) Waste Isolation Pilot Plant (WIPP) was recognized by the New Mexico Environment Department (NMED) with Green Zia Environmental Leadership Program (GZELP) Gold Level membership for excellence. The GZELP annually recognizes organizations and businesses for their demonstration of environmental leadership in support of pollution prevention and sustainability. The Gold Level is the highest GZELP

22

Department of Energy Receives Highest Transportation Industry Safety Award  

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

Receives Highest Transportation Industry Receives Highest Transportation Industry Safety Award Department of Energy Receives Highest Transportation Industry Safety Award May 1, 2007 - 12:45pm Addthis WASHINGTON, DC - The U.S. Department of Energy (DOE) today received the Transportation Community Awareness and Emergency Response (TRANSCAER) Chairman's Award, one of industry's highest transportation safety awards, for helping local communities in emergency preparedness and response. TRANSCAER is a voluntary national organization that assists communities in emergency preparedness and response. "I'm very proud that The Department of Energy has raised the bar for community-based transportation emergency preparedness," Secretary of Energy Samuel W. Bodman said. "Safety is our number one priority, and we will

23

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

24

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

25

Nominate An Inspirational STEM Teacher for the Nation's Highest Honors |  

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

Nominate An Inspirational STEM Teacher for the Nation's Highest Nominate An Inspirational STEM Teacher for the Nation's Highest Honors Nominate An Inspirational STEM Teacher for the Nation's Highest Honors February 8, 2013 - 1:04pm Addthis President Barack Obama talks with Presidential Awards for Excellence in Mathematics and Science Teaching winners in the State Dining of the White House January 6, 2010. (Official White House Photo by Chuck Kennedy) President Barack Obama talks with Presidential Awards for Excellence in Mathematics and Science Teaching winners in the State Dining of the White House January 6, 2010. (Official White House Photo by Chuck Kennedy) How can I participate? The 2013 Awards will honor mathematics and science (including computer science) teachers working in grades 7-12. Nominations close on

26

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

27

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,

28

ORISE: Nuclear engineering degrees at highest ranges since 1980s  

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

ORISE report shows graduation, enrollment rates for nuclear engineering ORISE report shows graduation, enrollment rates for nuclear engineering candidates are still at highest ranges reported since 1980s Report also shows shifts in career opportunities beyond graduation in nuclear utilities FOR IMMEDIATE RELEASE Nov. 2, 2011 FY12-04 OAK RIDGE, Tenn.-After a one-year decline, the number of graduate and undergraduate nuclear engineering degrees earned in the United States bounced back in 2010. A recent report from the Oak Ridge Institute for Science and Education shows enrollments of both undergraduate and graduate nuclear engineering students are still in the highest ranges reported since the early 1980s. Despite the continued growth trend in enrollments and degrees, the report also revealed that the reported plans of graduates show fewer had plans to

29

Origin and propagation of the highest energy cosmic rays  

E-Print Network (OSTI)

In this lecture I give an overview of shock acceleration, interactions of high energy cosmic rays with, and propagation through, the background radiation, and the resulting electron-photon cascade. I argue that while the origin of the highest energy cosmic rays is still uncertain, it is not necessary to invoke exotic models such as emission by topological defects to explain the existing data. It seems likely that shock acceleration at Fanaroff-Riley Class II radio galaxies can account for the existing data. However, new cosmic ray data, as well as better estimates of the extragalactic radiation fields and magnetic fields will be necessary before we will be certain of the origin of the highest energy particles occurring in nature.

R. J. Protheroe

1996-12-22T23:59:59.000Z

30

Molten Air -- A new, highest energy class of rechargeable batteries  

E-Print Network (OSTI)

This study introduces the principles of a new class of batteries, rechargeable molten air batteries, and several battery chemistry examples are demonstrated. The new battery class uses a molten electrolyte, are quasi reversible, and have amongst the highest intrinsic battery electric energy storage capacities. Three examples of the new batteries are demonstrated. These are the iron, carbon and VB2 molten air batteries with respective intrinsic volumetric energy capacities of 10,000, 19,000 and 27,000 Wh per liter.

Licht, Stuart

2013-01-01T23:59:59.000Z

31

Astrophysical Origins of the Highest Energy Cosmic Rays  

E-Print Network (OSTI)

Theoretical aspects of potential astrophysical sources of the highest energy cosmic rays are discussed, including their energy budget and some issues on particle escape and propagation. After briefly addressing AGN jets and GRBs, we highlight the possibility of heavy nuclei originating from cluster accretion shocks. The importance of X-ray and gamma-ray signatures in addition to neutrinos as diagnostic tools for source identification is emphasized.

Susumu Inoue

2007-02-01T23:59:59.000Z

32

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

33

Strategies for Demand Response in Commercial Buildings  

SciTech Connect

This paper describes strategies that can be used in commercial buildings to temporarily reduce electric load in response to electric grid emergencies in which supplies are limited or in response to high prices that would be incurred if these strategies were not employed. The demand response strategies discussed herein are based on the results of three years of automated demand response field tests in which 28 commercial facilities with an occupied area totaling over 11 million ft{sup 2} were tested. Although the demand response events in the field tests were initiated remotely and performed automatically, the strategies used could also be initiated by on-site building operators and performed manually, if desired. While energy efficiency measures can be used during normal building operations, demand response measures are transient; they are employed to produce a temporary reduction in demand. Demand response strategies achieve reductions in electric demand by temporarily reducing the level of service in facilities. Heating ventilating and air conditioning (HVAC) and lighting are the systems most commonly adjusted for demand response in commercial buildings. The goal of demand response strategies is to meet the electric shed savings targets while minimizing any negative impacts on the occupants of the buildings or the processes that they perform. Occupant complaints were minimal in the field tests. In some cases, ''reductions'' in service level actually improved occupant comfort or productivity. In other cases, permanent improvements in efficiency were discovered through the planning and implementation of ''temporary'' demand response strategies. The DR strategies that are available to a given facility are based on factors such as the type of HVAC, lighting and energy management and control systems (EMCS) installed at the site.

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

2006-06-20T23:59:59.000Z

34

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

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

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

35

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

36

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

37

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...

38

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

39

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

40

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

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

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.

42

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

43

Quantifying Benefits of Demand Response and Look-ahead Dispatch in Systems  

E-Print Network (OSTI)

Quantifying Benefits of Demand Response and Look-ahead Dispatch in Systems with Variable Resources Electric Energy System #12;#12;Quantifying Benefits of Demand Response and Look-ahead Dispatch in Systems benefits correspond to a real-world power system, as we use actual data on demand-response and wind

44

EOD: European network of libraries for eBooks on demand  

Science Journals Connector (OSTI)

European libraries host millions of books published from 1500 to 1900. Due to age and value, they are often only accessible to users actually present at these libraries. EOD (eBooks on Demand) is a European wide service which gives an answer to this ... Keywords: digitisation on demand, eBooks, eBooks on demand, network

Zoltn Mez; Sonja Svoljak; Silvia Gstrein

2007-09-01T23:59:59.000Z

45

EOD - European Network of Libraries for eBooks on Demand  

Science Journals Connector (OSTI)

European libraries host millions of books published from 1500 to 1900. Due to age and value, they are often only accessible to users actually present at these libraries. EOD (eBooks on Demand) is a European wide service which gives an answer to this ... Keywords: Digitisation on Demand, Network, eBooks, eBooks on Demand

Zoltn Mez; Sonja Svoljak; Silvia Gstrein

2007-09-01T23:59:59.000Z

46

,"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...

47

The myth of the single mode man : how the mobility pass better meets actual travel demand  

E-Print Network (OSTI)

The goal of this thesis is to investigate how employer transportation subsidy programs can result in more sustainable outcomes. Cities are growth machines that increasingly seek to mitigate the effects of that growth caused ...

Block-Schachter, David

2009-01-01T23:59:59.000Z

48

,"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...

49

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

50

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

51

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

52

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

53

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

54

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

55

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

56

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

57

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

58

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

59

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

60

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.

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

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.

62

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

63

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

64

Barrier Immune Radio Communications for Demand Response  

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

Barrier Immune Radio Communications for Demand Response Barrier Immune Radio Communications for Demand Response Title Barrier Immune Radio Communications for Demand Response Publication Type Report LBNL Report Number LBNL-2294e Year of Publication 2009 Authors Rubinstein, Francis M., Girish Ghatikar, Jessica Granderson, Paul Haugen, Carlos Romero, and David S. Watson Keywords technologies Abstract Various wireless technologies were field-tested in a six-story laboratory building to identify wireless technologies that can scale for future DR applications through very low node density power consumption, and unit cost. Data analysis included analysis of the signal-to-noise ratio (SNR), packet loss, and link quality at varying power levels and node densities. The narrowband technologies performed well, penetrating the floors of the building with little loss and exhibiting better range than the wideband technology. 900 MHz provided full coverage at 1 watt and substantially complete coverage at 500 mW at the test site. 900 MHz was able to provide full coverage at 100 mW with only one additional relay transmitter, and was the highest-performing technology in the study. 2.4 GHz could not provide full coverage with only a single transmitter at the highest power level tested (63 mW). However, substantially complete coverage was provided at 2.4 GHz at 63 mW with the addition of one repeater node.

65

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

66

U.S. companies` capital outlays to hit highest level since 1991  

SciTech Connect

US oil and gas company capital spending is expected to climb in 1997 for the third year in a row and to the highest level since 1991. Plans call for higher outlays upstream and downstream this year. OGJ`s annual capital expenditure survey shows US companies plan to spend $35.8 billion on US projects in 1997, up 7.7% from about $33.2 billion in 1996. Upstream spending in the US is expected to increase 10.5% this year to $20.1 billion, following a 15.3% increase in 1996. Downstream outlays are to increase 4.3% to $15.7 billion. This follows a decline of 9.9% last year, when downstream outlays slipped to $15.1 billion. Companies plan to continue to boost investments in areas outside of the US and Canada. The increased international spending is supported by higher prices along with the surge in economic growth and oil and gas demand in industrial and developing countries, particularly in Asia. The paper gives details on prices, US upstream spending, US downstream spending, Canadian spending, and non-North American outlays.

Beck, R.J.

1997-02-17T23:59:59.000Z

67

EOD - European Network of Libraries for eBooks on Demand  

Science Journals Connector (OSTI)

European libraries host millions of books published from 1500 to 1900. Due to age and value, they are often only accessible to users actually present at these libraries. EOD (eBooks on Demand) is a European ... t...

Zoltn Mez; Sonja Svoljak; Silvia Gstrein

2007-01-01T23:59:59.000Z

68

Table 13. Coal Production, Projected vs. Actual  

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

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

69

Table 22. Energy Intensity, Projected vs. Actual  

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

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

70

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

71

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

72

Table 14. Coal Production, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

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

73

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

74

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

75

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

76

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

77

Demand Charges | Open Energy Information  

Open Energy Info (EERE)

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

78

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

79

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

80

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

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

China's Coal: Demand, Constraints, and Externalities  

SciTech Connect

This study analyzes China's coal industry by focusing on four related areas. First, data are reviewed to identify the major drivers of historical and future coal demand. Second, resource constraints and transport bottlenecks are analyzed to evaluate demand and growth scenarios. The third area assesses the physical requirements of substituting coal demand growth with other primary energy forms. Finally, the study examines the carbon- and environmental implications of China's past and future coal consumption. There are three sections that address these areas by identifying particular characteristics of China's coal industry, quantifying factors driving demand, and analyzing supply scenarios: (1) reviews the range of Chinese and international estimates of remaining coal reserves and resources as well as key characteristics of China's coal industry including historical production, resource requirements, and prices; (2) quantifies the largest drivers of coal usage to produce a bottom-up reference projection of 2025 coal demand; and (3) analyzes coal supply constraints, substitution options, and environmental externalities. Finally, the last section presents conclusions on the role of coal in China's ongoing energy and economic development. China has been, is, and will continue to be a coal-powered economy. In 2007 Chinese coal production contained more energy than total Middle Eastern oil production. The rapid growth of coal demand after 2001 created supply strains and bottlenecks that raise questions about sustainability. Urbanization, heavy industrial growth, and increasing per-capita income are the primary interrelated drivers of rising coal usage. In 2007, the power sector, iron and steel, and cement production accounted for 66% of coal consumption. Power generation is becoming more efficient, but even extensive roll-out of the highest efficiency units would save only 14% of projected 2025 coal demand for the power sector. A new wedge of future coal consumption is likely to come from the burgeoning coal-liquefaction and chemicals industries. If coal to chemicals capacity reaches 70 million tonnes and coal-to-liquids capacity reaches 60 million tonnes, coal feedstock requirements would add an additional 450 million tonnes by 2025. Even with more efficient growth among these drivers, China's annual coal demand is expected to reach 3.9 to 4.3 billion tonnes by 2025. Central government support for nuclear and renewable energy has not reversed China's growing dependence on coal for primary energy. Substitution is a matter of scale: offsetting one year of recent coal demand growth of 200 million tonnes would require 107 billion cubic meters of natural gas (compared to 2007 growth of 13 BCM), 48 GW of nuclear (compared to 2007 growth of 2 GW), or 86 GW of hydropower capacity (compared to 2007 growth of 16 GW). Ongoing dependence on coal reduces China's ability to mitigate carbon dioxide emissions growth. If coal demand remains on a high growth path, carbon dioxide emissions from coal combustion alone would exceed total US energy-related carbon emissions by 2010. Within China's coal-dominated energy system, domestic transportation has emerged as the largest bottleneck for coal industry growth and is likely to remain a constraint to further expansion. China has a low proportion of high-quality reserves, but is producing its best coal first. Declining quality will further strain production and transport capacity. Furthermore, transporting coal to users has overloaded the train system and dramatically increased truck use, raising transportation oil demand. Growing international imports have helped to offset domestic transport bottlenecks. In the long term, import demand is likely to exceed 200 million tonnes by 2025, significantly impacting regional markets.

Aden, Nathaniel; Fridley, David; Zheng, Nina

2009-07-01T23:59:59.000Z

82

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

83

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

84

Table 23. Energy Intensity, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

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

85

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

86

Industrial demand side management: A status report  

SciTech Connect

This report provides an overview of and rationale for industrial demand side management (DSM) programs. Benefits and barriers are described, and data from the Manufacturing Energy Consumption Survey are used to estimate potential energy savings in kilowatt hours. The report presents types and examples of programs and explores elements of successful programs. Two in-depth case studies (from Boise Cascade and Eli Lilly and Company) illustrate two types of effective DSM programs. Interviews with staff from state public utility commissions indicate the current thinking about the status and future of industrial DSM programs. A comprehensive bibliography is included, technical assistance programs are listed and described, and a methodology for evaluating potential or actual savings from projects is delineated.

Hopkins, M.F.; Conger, R.L.; Foley, T.J. [and others

1995-05-01T23:59:59.000Z

87

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

88

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

89

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

90

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

91

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

92

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

93

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

94

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

95

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

96

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

97

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

98

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

99

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

100

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

Note: This page contains sample records for the topic "highest actual 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 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)

102

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

103

National Action Plan on Demand Response  

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

6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 ACTUAL FORECAST National Action Plan on Demand Response the feDeRal eneRgy RegulatoRy commission staff 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 12 6 3 9 National Action Plan on Demand Response THE FEDERAL ENERGY REGULATORY COMMISSION STAFF June 17, 2010 Docket No. AD09-10 Prepared with the support of The Brattle Group * GMMB * Customer Performance Group Definitive Insights * Eastern Research Group The opinions and views expressed in this staff report do not necessarily represent those of the Federal Energy Regulatory Commission, its Chairman, or individual Commissioners, and are not binding on the Commission.

104

Industrial demand side management status report: Synopsis  

SciTech Connect

Industrial demand side management (DSM) programs, though not as developed or widely implemented as residential and commercial programs, hold the promise of significant energy savings-savings that will benefit industrial firms, utilities and the environment. This paper is a synopsis of a larger research report, Industrial Demand Side Management. A Status Report, prepared for the US Department of Energy. The report provides an overview of and rationale for DSM programs. Benefits and barriers are described, and data from the Manufacturing Energy Consumption Survey are used to estimate potential electricity savings from industrial energy efficiency measures. Overcoming difficulties to effective program implementation is worthwhile, since rough estimates indicate a substantial potential for electricity savings. The report categorizes types of DSM programs, presents several examples of each type, and explores elements of successful programs. Two in-depth case studies (of Boise Cascade and of Eli Lilly and Company) illustrate two types of effective DSM programs. Interviews with staff from state public utility commissions indicate the current thinking about the status and future of industrial DSM programs. Finally, the research report also includes a comprehensive bibliography, a description of technical assistance programs, and an example of a methodology for evaluating potential or actual savings from projects.

Hopkins, M.E.F.; Conger, R.L.; Foley, T.J.; Parker, J.W.; Placet, M.; Sandahl, L.J.; Spanner, G.E.; Woodruff, M.G.; Norland, D.

1995-08-01T23:59:59.000Z

105

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

106

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

107

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,...

108

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

109

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

110

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

111

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

112

Mirant: Summary of Monitored SO2 Concentrations During Periods of Highest  

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

Mirant: Summary of Monitored SO2 Concentrations During Periods of Mirant: Summary of Monitored SO2 Concentrations During Periods of Highest Impact Mirant: Summary of Monitored SO2 Concentrations During Periods of Highest Impact Docket No. EO-05-01: Tables showing a summary of monitored SO2 concentrations during periods of highest impact as well as ERMOD modeling results for SO2 scenarios. Mirant: Summary of Monitored SO2 Concentrations During Periods of Highest Impact More Documents & Publications Answer of Potomac Electric Power Company and PJM lnterconnection, L.L.C. to the October 6, 2005 motion filed by the Virginia Department of Environmental Quality Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by AERMOD-PRIME, Units 3, 1, 2 SO2 Case Mirant Potomac, Alexandria, Virginia: Maximum Impacts Predicted by

113

U.S. oil reserves highest since 1975, natural gas reserves set...  

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

U.S. oil reserves highest since 1975, natural gas reserves set new record U.S. proved oil reserves have topped 36 billion barrels for the first time in nearly four decades, while...

114

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

115

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.

116

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

117

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

118

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

119

,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected...  

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

January 23, 2008" ,"Next Update: October 2007" ,"Table 2b. Noncoincident Winter Peak Load, Actual and Projected by North American Electric Reliability Council Region, " ,"2005...

120

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...

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

122

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

123

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

124

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

125

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

126

Shale Gas Production: Potential versus Actual GHG Emissions  

E-Print Network (OSTI)

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

127

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

128

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

129

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

130

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

131

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

132

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

133

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

134

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"

135

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

136

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

137

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

138

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

139

Correlation of the highest energy cosmic rays with nearby extragalactic objects  

E-Print Network (OSTI)

Correlation of the highest energy cosmic rays with nearby extragalactic objects The Pierre Auger Collaboration Observatorio Pierre Auger, Avenida San Mart´in Norte 304, (5613) Malarg¨ue, Mendoza, Argentina a correlation between the arrival directions of cosmic rays with energy above 6 ? 1019 electron volts

140

A Bayesian analysis of the 27 highest energy cosmic rays detected by the Pierre Auger Observatory  

Science Journals Connector (OSTI)

......analysis of the 27 highest energy cosmic rays detected by the...is possible that ultrahigh energy cosmic rays (UHECRs) are...is located near Malargue in Argentina, at a longitude of 69.4...UHECRs with reliable detected energies of E obsE min = 5.7 1019......

Laura J. Watson; Daniel J. Mortlock; Andrew H. Jaffe

2011-11-21T23:59:59.000Z

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

Table 1 Highest tides (tide ranges) of the global ocean Country Site Tide range (m)  

E-Print Network (OSTI)

and Climate. Indian Ocean Equatorial Currents. Internal Waves. Island Wakes. Langmuir Circula- tion and Instability. Mesoscale Eddies. Open Ocean Convection. Paci\\c Ocean Equatorial Currents. TurbulenceTable 1 Highest tides (tide ranges) of the global ocean Country Site Tide range (m) Canada Bay

Gorban, Alexander N.

142

Are extragalactic gamma ray bursts the source of the highest energy cosmic rays?  

E-Print Network (OSTI)

Recent observations with the large air shower arrays of ultra high energy cosmic rays (UHECR) and recent measurements/estimates of the redshifts of gamma ray bursts (GRBs) seem to rule out extragalactic GRBs as the source of the cosmic rays that are observed near Earth, including those with the highest energies.

Arnon Dar

1999-01-03T23:59:59.000Z

143

NETL-Regional University Alliance Researcher to Receive Nations Highest Award for Young Scientists  

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

Dr. Brian Anderson, a research fellow of the NETL-Regional University Alliance and associate professor of chemical engineering at West Virginia University, was recognized during a special event at U.S. Department of Energy Headquarters April 14 for receiving the highest honor the U.S. government can bestow on an outstanding scientist in the early stages of his research career.

144

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

145

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

146

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...

147

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,...

148

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

149

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

150

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...

151

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...

152

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

153

Smart Buildings and Demand Response  

Science Journals Connector (OSTI)

Advances in communications and control technology the strengthening of the Internet and the growing appreciation of the urgency to reduce demand side energy use are motivating the development of improvements in both energy efficiency and demand response (DR) systems in buildings. This paper provides a framework linking continuous energy management and continuous communications for automated demand response (Auto?DR) in various times scales. We provide a set of concepts for monitoring and controls linked to standards and procedures such as Open Automation Demand Response Communication Standards (OpenADR). Basic building energy science and control issues in this approach begin with key building components systems end?uses and whole building energy performance metrics. The paper presents a framework about when energy is used levels of services by energy using systems granularity of control and speed of telemetry. DR when defined as a discrete event requires a different set of building service levels than daily operations. We provide examples of lessons from DR case studies and links to energy efficiency.

2011-01-01T23:59:59.000Z

154

Water demand management in Kuwait  

E-Print Network (OSTI)

Kuwait is an arid country located in the Middle East, with limited access to water resources. Yet water demand per capita is much higher than in other countries in the world, estimated to be around 450 L/capita/day. There ...

Milutinovic, Milan, M. Eng. Massachusetts Institute of Technology

2006-01-01T23:59:59.000Z

155

Estimation of Regional Actual Evapotranspiration in the Panama Canal Watershed  

Science Journals Connector (OSTI)

The upper Ro Chagres basin is a part of the Panama Canal Watershed. The least known water balance...SEBAL...). We use an image from March 27, 2000, for estimation of the distribution of the regional actual evapo...

Jan M.H. Hendrickx; Wim G.M. Bastiaanssen; Edwin J.M. Noordman

2005-01-01T23:59:59.000Z

156

The alchemy of demand response: turning demand into supply  

SciTech Connect

Paying customers to refrain from purchasing products they want seems to run counter to the normal operation of markets. Demand response should be interpreted not as a supply-side resource but as a secondary market that attempts to correct the misallocation of electricity among electric users caused by regulated average rate tariffs. In a world with costless metering, the DR solution results in inefficiency as measured by deadweight losses. (author)

Rochlin, Cliff

2009-11-15T23:59:59.000Z

157

New Energy Star Initiative Recognizes Cutting-Edge Products with Highest  

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

Star Initiative Recognizes Cutting-Edge Products with Star Initiative Recognizes Cutting-Edge Products with Highest Energy Efficiency New Energy Star Initiative Recognizes Cutting-Edge Products with Highest Energy Efficiency July 14, 2011 - 12:00am Addthis WASHINGTON - The U.S. Environmental Protection Agency (EPA) and U.S. Department of Energy (DOE) today are announcing for the first time products recognized as the most energy-efficient in their categories among those that have earned the Energy Star label. This pilot program is part of Energy Star's overall commitment to protect people's health and the environment by encouraging energy efficiency. The "Most Efficient" initiative also continues Energy Star's work to provide consumers with the best efficiency information so they can make investments that will lower

158

Rotational bands in odd-A Cm and Cf isotopes: Exploring the highest neutron orbitals  

SciTech Connect

Rotational bands have been identified up to high spins ({approx_equal}28({h_bar}/2{pi})) in the odd-A nuclei {sup 247,249}Cm and {sup 249}Cf through inelastic excitation and transfer reactions around the Z=100 region where stability results from shell effects. The [620]1/2 Nilsson configuration in {sup 249}Cm is the highest-lying neutron orbital, from above the N=164 spherical subshell gap, for which high-spin rotational behavior has been established. The data allow for an unambiguous experimental assignment of configurations to the observed bands, unusual for odd-A nuclei near Z=100. The high-spin properties are described in terms of Woods-Saxon cranking calculations.

Tandel, S. K.; Chowdhury, P.; Lakshmi, S.; Tandel, U. S. [Department of Physics, University of Massachusetts Lowell, Lowell, Massachusetts 01854 (United States); Ahmad, I.; Carpenter, M. P.; Gros, S.; Janssens, R. V. F.; Khoo, T. L.; Kondev, F. G.; Greene, J. P.; Lauritsen, T.; Lister, C. J.; Peterson, D.; Robinson, A.; Seweryniak, D.; Zhu, S. [Argonne National Laboratory, Argonne, Illinois 60439 (United States); Hartley, D. J. [Department of Physics, US Naval Academy, Annapolis, Maryland 21402 (United States)

2010-10-15T23:59:59.000Z

159

Q:\asufinal_0107_demand.vp  

Gasoline and Diesel Fuel Update (EIA)

00 00 (AEO2000) Assumptions to the January 2000 With Projections to 2020 DOE/EIA-0554(2000) Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Natural Gas Transmission and Distribution

160

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

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161

INTEGRATION OF PV IN DEMAND RESPONSE  

E-Print Network (OSTI)

INTEGRATION OF PV IN DEMAND RESPONSE PROGRAMS Prepared by Richard Perez et al. NREL subcontract response programs. This is because PV generation acts as a catalyst to demand response, markedly enhancing by solid evidence from three utility case studies. BACKGROUND Demand Response: demand response (DR

Perez, Richard R.

162

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

163

Building Technologies Office: Integrated Predictive Demand Response  

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

Integrated Predictive Integrated Predictive Demand Response Controller Research Project to someone by E-mail Share Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Facebook Tweet about Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Twitter Bookmark Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Google Bookmark Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Delicious Rank Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Digg Find More places to share Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on AddThis.com...

164

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

Report 2009. Open Automated Demand Response Communicationsand Techniques for Demand Response. California Energyand S. Kiliccote. Estimating Demand Response Load Impacts:

Kiliccote, Sila

2010-01-01T23:59:59.000Z

165

Incorporating Demand Response into Western Interconnection Transmission Planning  

E-Print Network (OSTI)

Aggregator Programs. Demand Response Measurement andIncorporating Demand Response into Western Interconnection13 Demand Response Dispatch

Satchwell, Andrew

2014-01-01T23:59:59.000Z

166

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network (OSTI)

and Techniques for Demand Response, report for theand Reliability Demand Response Programs: Final Report.Demand Response

McKane, Aimee T.

2009-01-01T23:59:59.000Z

167

Automated Demand Response Opportunities in Wastewater Treatment Facilities  

E-Print Network (OSTI)

Interoperable Automated Demand Response Infrastructure,study of automated demand response in wastewater treatmentopportunities for demand response control strategies in

Thompson, Lisa

2008-01-01T23:59:59.000Z

168

A fast chiller power demand response control strategy for buildings connected to smart grid  

Science Journals Connector (OSTI)

Abstract With the increasing integration of renewable energies into electrical grids, power imbalance has become one of the most critical issues in grid operations. The end-users at power demand side can actually make use of their demand reduction potentials to contribute to the grid power balance. Conventional demand responses of end-users can provide considerable power demand reductions, but the demand responses are usually subject to significant delay and cannot fulfill the needs of grid real time operation. In this paper, a fast chiller power demand response control strategy for commercial buildings is therefore proposed which facilitates buildings to act as grid operating reserves by providing rapid demand responses to grid request within minutes. However, simply shutting down some essential operating chillers would result in disordered chilled water flow distribution and uneven indoor thermal comfort degradation. This strategy has therefore taken essential measures to solve such problems effectively. Simulation case studies are conducted to investigate the operation dynamics and energy performance of HVAC systems in the demand response events controlled by the strategy. Results show that fast and significant power demand reductions can be achieved without sacrificing the thermal comfort too much.

Xue Xue; Shengwei Wang; Chengchu Yan; Borui Cui

2015-01-01T23:59:59.000Z

169

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

E-Print Network (OSTI)

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

Kiliccote, Sila

2010-01-01T23:59:59.000Z

170

Global energy demand to 2060  

SciTech Connect

The projection of global energy demand to the year 2060 is of particular interest because of its relevance to the current greenhouse concerns. The long-term growth of global energy demand in the time scale of climatic change has received relatively little attention in the public discussion of national policy alternatives. The sociological, political, and economic issues have rarely been mentioned in this context. This study emphasizes that the two major driving forces are global population growth and economic growth (gross national product per capita), as would be expected. The modest annual increases assumed in this study result in a year 2060 annual energy use of >4 times the total global current use (year 1986) if present trends continue, and >2 times with extreme efficiency improvements in energy use. Even assuming a zero per capita growth for energy and economics, the population increase by the year 2060 results in a 1.5 times increase in total annual energy use.

Starr, C. (Electric Power Research Institute, Palo Alto, CA (USA))

1989-01-01T23:59:59.000Z

171

Energy Demand | Open Energy Information  

Open Energy Info (EERE)

Energy Demand Energy Demand Jump to: navigation, search Click to return to AEO2011 page AEO2011 Data Figure 55 From AEO2011 report . Market Trends Growth in energy use is linked to population growth through increases in housing, commercial floorspace, transportation, and goods and services. These changes affect not only the level of energy use, but also the mix of fuels used. Energy consumption per capita declined from 337 million Btu in 2007 to 308 million Btu in 2009, the lowest level since 1967. In the AEO2011 Reference case, energy use per capita increases slightly through 2013, as the economy recovers from the 2008-2009 economic downturn. After 2013, energy use per capita declines by 0.3 percent per year on average, to 293 million Btu in 2035, as higher efficiency standards for vehicles and

172

Addressing the Highest Risk: Environmental Programs at Los Alamos National Laboratory  

SciTech Connect

Report topics: Current status of cleanup; Shift in priorities to address highest risk; Removal of above-ground waste; and Continued focus on protecting water resources. Partnership between the National Nuclear Security Administration's Los Alamos Site Office, DOE Carlsbad Field Office, New Mexico Environment Department, and contractor staff has enabled unprecedented cleanup progress. Progress on TRU campaign is well ahead of plan. To date, have completed 130 shipments vs. 104 planned; shipped 483 cubic meters of above-ground waste (vs. 277 planned); and removed 11,249 PE Ci of material at risk (vs. 9,411 planned).

Forbes, Elaine E [Los Alamos National Laboratory

2012-06-08T23:59:59.000Z

173

Cosmological Gamma-Ray Bursts and the Highest Energy Cosmic Rays  

Science Journals Connector (OSTI)

We discuss a scenario in which the highest energy cosmic rays (CR's) and cosmological ?-ray bursts (GRB's) have a common origin. This scenario is consistent with the observed CR flux above 1020 eV, provided that each burst produces similar energies in ? rays and in CR's above 1020 eV. Protons may be accelerated by Fermi's mechanism to energies ?1020 eV in a dissipative, ultrarelativistic wind, with luminosity and Lorentz factor high enough to produce a GRB. For a homogeneous GRB distribution, this scenario predicts an isotropic, time-independent CR flux.

Eli Waxman

1995-07-17T23:59:59.000Z

174

Self-actualization as it relates to aerobic physical fitness  

E-Print Network (OSTI)

higher than the aerobic and archery group on the TC, Ex, and C scales. The archery group was significantly higher than the preaerobic and aerobic groups on the Fr and S scales. Females from the preaerobic group were significantly lower than archery... Inventory Sav Self-actualization values measures how well a person holds and lives by values of se 1f- ac tualizing people Ex Existentiality measures ability to flexibly apply self-actualizing values to one's own life Fr Feeling reactivity measures...

Russell, Kathryn Terese Vecchio

2012-06-07T23:59:59.000Z

175

Demand Side Bidding. Final Report  

SciTech Connect

This document sets forth the final report for a financial assistance award for the National Association of Regulatory Utility Commissioners (NARUC) to enhance coordination between the building operators and power system operators in terms of demand-side responses to Location Based Marginal Pricing (LBMP). Potential benefits of this project include improved power system reliability, enhanced environmental quality, mitigation of high locational prices within congested areas, and the reduction of market barriers for demand-side market participants. NARUC, led by its Committee on Energy Resources and the Environment (ERE), actively works to promote the development and use of energy efficiency and clean distributive energy policies within the framework of a dynamic regulatory environment. Electric industry restructuring, energy shortages in California, and energy market transformation intensifies the need for reliable information and strategies regarding electric reliability policy and practice. NARUC promotes clean distributive generation and increased energy efficiency in the context of the energy sector restructuring process. NARUC, through ERE's Subcommittee on Energy Efficiency, strives to improve energy efficiency by creating working markets. Market transformation seeks opportunities where small amounts of investment can create sustainable markets for more efficient products, services, and design practices.

Spahn, Andrew

2003-12-31T23:59:59.000Z

176

Demand Response Programs Oregon Public Utility Commission  

E-Print Network (OSTI)

Demand Response Programs Oregon Public Utility Commission January 6, 2005 Mike Koszalka Director;Demand Response Results, 2004 Load Control ­ Cool Keeper ­ ID Irrigation Load Control Price Responsive

177

Industrial Equipment Demand and Duty Factors  

E-Print Network (OSTI)

Demand and duty factors have been measured for selected equipment (air compressors, electric furnaces, injection molding machines, centrifugal loads, and others) in industrial plants. Demand factors for heavily loaded air compressors were near 100...

Dooley, E. S.; Heffington, W. M.

178

ConservationandDemand ManagementPlan  

E-Print Network (OSTI)

; Introduction Ontario Regulation 397/11 under the Green Energy Act 2009 requires public agencies and implement energy Conservation and Demand Management (CDM) plans starting in 2014. Requirementsofthe ConservationandDemand ManagementPlan 2014-2019 #12

Abolmaesumi, Purang

179

Energy Demand Analysis at a Disaggregated Level  

Science Journals Connector (OSTI)

The purpose of this chapter is to consider energy demand at the fuel level or at the ... . This chapter first presents the disaggregation of energy demand, discusses the information issues and introduces framewor...

Subhes C. Bhattacharyya

2011-01-01T23:59:59.000Z

180

Seasonal temperature variations and energy demand  

Science Journals Connector (OSTI)

This paper presents an empirical study of the relationship between residential energy demand and temperature. Unlike previous studies in this ... different regions and to the contrasting effects on energy demand ...

Enrica De Cian; Elisa Lanzi; Roberto Roson

2013-02-01T23:59:59.000Z

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

experiment actually sees," Smith says. "When we were  

E-Print Network (OSTI)

experiment actually sees," Smith says. "When we were finished, we got much more ­ a method in science depend on atoms and molecules moving," Smith says. "We want to create movies of molecules science development," Smith says.--Morgan McCorkle A theoretical technique developed at ORNL is bringing

Pennycook, Steve

182

COORDINATING ADVICE AND ACTUAL TREATMENT Thomas A. Russ  

E-Print Network (OSTI)

. Unfortunately, this information is not always immediately available. For example, the exact fluid infused via an intravenous line can only be determined after someone checks the infusion bottle to determine how much fluid differ in timing and exact amount from what is actually done. For example, an infusion order might call

Russ, Thomas A.

183

Second highest-ranking U.S. military officer gets classified briefings  

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

U.S. military officer gets classified briefings U.S. military officer gets classified briefings Second highest-ranking U.S. military officer gets classified briefings Winnefield was at Los Alamos to receive a wide variety of classified briefings that covered the broad spectrum of national security science at the Lab. November 17, 2011 Los Alamos National Laboratory sits on top of a once-remote mesa in northern New Mexico with the Jemez mountains as a backdrop to research and innovation covering multi-disciplines from bioscience, sustainable energy sources, to plasma physics and new materials. Los Alamos National Laboratory sits on top of a once-remote mesa in northern New Mexico with the Jemez mountains as a backdrop to research and innovation covering multi-disciplines from bioscience, sustainable energy

184

The laser ion source trap for highest isobaric selectivity in online exotic isotope production  

SciTech Connect

The improvement in the performance of a conventional laser ion source in the laser ion source and trap (LIST) project is presented, which envisages installation of a repeller electrode and a linear Paul trap/ion guide structure. This approach promises highest isobaric purity and optimum temporal and spatial control of the radioactive ion beam produced at an online isotope separator facility. The functionality of the LIST was explored at the offline test separators of University of Mainz (UMz) and ISOLDE/CERN, using the UMz solid state laser system. Ionization efficiency and selectivity as well as time structure and transversal emittance of the produced ion beam was determined. Next step after complete characterization is the construction and installation of the radiation-hard final trap structure and its first online application.

Schwellnus, F.; Gottwald, T.; Mattolat, C.; Wendt, K. [Institut fuer Physik, Johannes Gutenberg-Universitaet, D-55099 Mainz (Germany); Blaum, K. [Max-Planck-Institut fuer Kernphysik, Saupfercheckweg 1, D-69117 Heidelberg (Germany); Catherall, R.; Crepieux, B.; Fedosseev, V.; Marsh, B.; Rothe, S.; Stora, T. [CERN, CH-1211 Geneva 23 (Switzerland); Kluge, H.-J. [GSI, Planckstrasse 1, D-64291 Darmstadt (Germany)

2010-02-15T23:59:59.000Z

185

A Magnetized Local Supercluster and the Origin of the Highest Energy Cosmic Rays  

E-Print Network (OSTI)

A sufficiently magnetized Local Supercluster can explain the spectrum and angular distribution of ultra-high energy cosmic rays. We show that the spectrum of extragalactic cosmic rays with energies below $\\sim 10^{20}$ eV may be due to the diffusive propagation in the Local Supercluster with fields of $\\sim 10^{-8} - 10^{-7}$ Gauss. Above $\\sim 10^{20}$ eV, cosmic rays propagate in an almost rectilinear way which is evidenced by the change in shape of the spectrum at the highest energies. The fit to the spectrum requires that at least one source be located relatively nearby at $\\sim 10-15$ Mpc away from the Milky Way. We discuss the origin of magnetic fields in the Local Supercluster and the observable predictions of this model.

Pasquale Blasi; Angela V. Olinto

1998-06-19T23:59:59.000Z

186

Regression Models for Demand Reduction based on Cluster Analysis of Load  

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

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

187

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

LBNL-62226 Demand Responsive Lighting: A Scoping Study F. Rubinstein, S. Kiliccote Energy Environmental Technologies Division January 2007 #12;LBNL-62226 Demand Responsive Lighting: A Scoping Study in this report was coordinated by the Demand Response Research Center and funded by the California Energy

188

Demand Response Resources in Pacific Northwest  

E-Print Network (OSTI)

Demand Response Resources in Pacific Northwest Chuck Goldman Lawrence Berkeley National Laboratory cagoldman@lbl.gov Pacific Northwest Demand Response Project Portland OR May 2, 2007 #12;Overview · Typology Annual Reports ­ Journal articles/Technical reports #12;Demand Response Resources · Incentive

189

Leveraging gamification in demand dispatch systems  

Science Journals Connector (OSTI)

Modern demand-side management techniques are an integral part of the envisioned smart grid paradigm. They require an active involvement of the consumer for an optimization of the grid's efficiency and a better utilization of renewable energy sources. ... Keywords: demand response, demand side management, direct load control, gamification, smart grid, sustainability

Benjamin Gnauk; Lars Dannecker; Martin Hahmann

2012-03-01T23:59:59.000Z

190

Demand Response and Ancillary Services September 2008  

E-Print Network (OSTI)

Demand Response and Ancillary Services September 2008 #12;© 2008 EnerNOC, Inc. All Rights Reserved programs The purpose of this presentation is to offer insight into the mechanics of demand response and industrial demand response resources across North America in both regulated and restructured markets As of 6

191

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 can help reduce the threat of planned rotational outages. Demand response is also widely regarded as having

192

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

193

Modeling Energy Demand Aggregators for Residential Consumers  

E-Print Network (OSTI)

The current world-wide increase of energy demand cannot be matched by energy production and power grid updateModeling Energy Demand Aggregators for Residential Consumers G. Di Bella, L. Giarr`e, M. Ippolito, A. Jean-Marie, G. Neglia and I. Tinnirello § January 2, 2014 Abstract Energy demand aggregators

Paris-Sud XI, Université de

194

Response to changes in demand/supply  

E-Print Network (OSTI)

Response to changes in demand/supply through improved marketing 21.2 #12;#12;111 Impacts of changes log demand in 1995. The composites board mills operating in Korea took advantage of flexibility environment changes on the production mix, some economic indications, statistics of demand and supply of wood

195

Response to changes in demand/supply  

E-Print Network (OSTI)

Response to changes in demand/supply through improved marketing 21.2 http with the mill consuming 450 000 m3 , amounting to 30% of total plywood log demand in 1995. The composites board, statistics of demand and supply of wood, costs and competitiveness were analysed. The reactions

196

Energy demand forecasting: industry practices and challenges  

Science Journals Connector (OSTI)

Accurate forecasting of energy demand plays a key role for utility companies, network operators, producers and suppliers of energy. Demand forecasts are utilized for unit commitment, market bidding, network operation and maintenance, integration of renewable ... Keywords: analytics, energy demand forecasting, machine learning, renewable energy sources, smart grids, smart meters

Mathieu Sinn

2014-06-01T23:59:59.000Z

197

Smart Buildings Using Demand Response March 6, 2011  

E-Print Network (OSTI)

Smart Buildings Using Demand Response March 6, 2011 Sila Kiliccote Deputy, Demand Response Division Lawrence Berkeley National Laboratory Demand Response Research Center 1 #12;Presentation Outline Demand Response Research Center ­ DRRC Vision and Research Portfolio Introduction to Demand

Kammen, Daniel M.

198

Energy demand and population changes  

SciTech Connect

Since World War II, US energy demand has grown more rapidly than population, so that per capita consumption of energy was about 60% higher in 1978 than in 1947. Population growth and the expansion of per capita real incomes have led to a greater use of energy. The aging of the US population is expected to increase per capita energy consumption, despite the increase in the proportion of persons over 65, who consume less energy than employed persons. The sharp decline in the population under 18 has led to an expansion in the relative proportion of population in the prime-labor-force age groups. Employed persons are heavy users of energy. The growth of the work force and GNP is largely attributable to the growing participation of females. Another important consequence of female employment is the growth in ownership of personal automobiles. A third factor pushing up labor-force growth is the steady influx of illegal aliens.

Allen, E.L.; Edmonds, J.A.

1980-12-01T23:59:59.000Z

199

Electricity demand analysis - unconstrained vs constrained scenarios  

Science Journals Connector (OSTI)

In India, the electricity systems are chronically constrained by shortage of both capital and energy resources. These result in rationing and interruptions of supply with a severely disrupted electricity usage pattern. From this background, we try to analyse the demand patterns with and without resource constraints. Accordingly, it is necessary to model appropriately the dynamic nature of electricity demand, which cannot be captured by methods like annual load duration curves. Therefore, we use the concept - Representative Load Curves (RLCs) - to model the temporal and structural variations in demand. As a case study, the electricity system of the state of Karnataka in India is used. Four years demand data, two unconstrained and two constrained, are used and RLCs are developed using multiple discriminant analysis. It is found that these RLCs adequately model the variations in demand and bring out distinctions between unconstrained and constrained demand patterns. The demand analysis attempted here helped to study the differences in demand patterns with and without constraints, and the success of rationing measures in reducing demand levels as well as greatly disrupting the electricity usage patterns. Multifactor ANOVA analyses are performed to find out the statistical significance of the ability of logically obtained factors in explaining overall variations in demand. The results showed that the factors that are taken into consideration accounted for maximum variations in demand at very high significance levels.

P. Balachandra; V. Chandru; M.H. Bala Subrahmanya

2003-01-01T23:59:59.000Z

200

Measurement and Verification for Demand Response  

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

Measurement and Verification for Measurement and Verification for Demand Response Prepared for the National Forum on the National Action Plan on Demand Response: Measurement and Verification Working Group AUTHORS: Miriam L. Goldberg & G. Kennedy Agnew-DNV KEMA Energy and Sustainability National Forum of the National Action Plan on Demand Response Measurement and Verification for Demand Response was developed to fulfill part of the Implementation Proposal for The National Action Plan on Demand Response, a report to Congress jointly issued by the U.S. Department of Energy (DOE) and the Federal Energy Regulatory Commission (FERC) in June 2011. Part of that implementation proposal called for a "National Forum" on demand response to be conducted by DOE and FERC. Given that demand response has matured, DOE and FERC decided that a "virtual" project

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

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

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

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

202

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

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

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

203

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

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

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

204

Table 12. Total Coal Consumption, Projected vs. Actual  

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

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

205

Table 4. Total Petroleum Consumption, Projected vs. Actual  

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

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

206

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

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

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

207

Tropical Africa: Calculated Actual Aboveground Live Biomass in Open and  

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

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

208

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

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

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

209

Secure Demand Shaping for Smart Grid On constructing probabilistic demand response schemes  

E-Print Network (OSTI)

Secure Demand Shaping for Smart Grid On constructing probabilistic demand response schemes. Developing novel schemes for demand response in smart electric gird is an increasingly active research area/SCADA for demand response in smart infrastructures face the following dilemma: On one hand, in order to increase

Sastry, S. Shankar

210

US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier  

E-Print Network (OSTI)

that energy intensity is not necessarily a good indicator of energy efficiency, whereas by controllingUS Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach Massimo www.cepe.ethz.ch #12;US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier

211

Optimization of extraction of high-ester pectin from passion fruit peel (Passiflora edulis flavicarpa) with citric acid by using  

E-Print Network (OSTI)

Optimization of extraction of high-ester pectin from passion fruit peel (Passiflora edulis for extraction of high-ester yellow passion fruit pectin. ? 2007 Elsevier Ltd. All rights reserved. Keywords: Pectin extraction; Passion fruit peel; Degree of esterification; Response surface methodology; Central

Ferreira, Márcia M. C.

212

The Role of Demand Response in Default Service Pricing  

SciTech Connect

Dynamic retail electricity pricing, especially real-time pricing (RTP), has been widely heralded as a panacea for providing much-needed demand response in electricity markets. However, in designing default service for competitive retail markets, demand response often appears to be an afterthought. But that may be changing as states that initiated customer choice in the past 5-7 years reach an important juncture in retail market design. Most states with retail choice established an initial transitional period, during which utilities were required to offer a default or ''standard offer'' generation service, often at a capped or otherwise administratively-determined rate. Many retail choice states have reached, or are nearing, the end of their transitional period and several states have adopted an RTP-type default service for large commercial and industrial (C&I) customers. Are these initiatives motivated by the desire to induce greater demand response, or is RTP being called upon to serve a different role in competitive markets? Surprisingly, we found that in most cases, the primary reason for adopting RTP as the default service was not to encourage demand response, but rather to advance policy objectives related to the development of competitive retail markets. However, we also find that, if efforts are made in its design and implementation, default RTP service can also provide a solid foundation for developing price responsive demand, creating an important link between wholesale and retail market transactions. This paper, which draws from a lengthier report, describes the experience to date with default RTP in the U.S., identifying findings related to its actual and potential role as an instrument for cultivating price responsive demand [1]. For each of the five states currently with default RTP, we conducted a detailed review of the regulatory proceedings leading to its adoption. To further understand the intentions and expectations of those involved in its design and implementation, we also interviewed regulatory staff and utilities in each state, as well as eight of the most prominent competitive retail suppliers operating in these markets which, together, comprised about 60-65% of competitive C&I sales in the U.S. in 2004 [2].

Barbose, Galen; Goldman, Chuck; Neenan, Bernie

2006-03-10T23:59:59.000Z

213

OUTDOOR RECREATION DEMAND AND EXPENDITURES: LOWER SNAKE RIVER RESERVOIRS  

E-Print Network (OSTI)

i OUTDOOR RECREATION DEMAND AND EXPENDITURES: LOWER SNAKE RIVER RESERVOIRS John R. Mc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v SECTION ONE - OUTDOOR RECREATION DEMAND . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Recreation Demand Methods

O'Laughlin, Jay

214

LEED Demand Response Credit: A Plan for Research towards Implementation  

E-Print Network (OSTI)

C. McParland, Open Automated Demand Response Communicationsand Open Automated Demand Response", Grid Interop Forum,Testing of Automated Demand Response for Integration of

Kiliccote, Sila

2014-01-01T23:59:59.000Z

215

Demand Response Opportunities in Industrial Refrigerated Warehouses in California  

E-Print Network (OSTI)

and Open Automated Demand Response. In Grid Interop Forum.work was sponsored by the Demand Response Research Center (load-management.php. Demand Response Research Center (2009).

Goli, Sasank

2012-01-01T23:59:59.000Z

216

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

A. Barat, D. Watson. Demand Response Spinning ReserveOpen Automated Demand Response Communication Standards:Dynamic Controls for Demand Response in a New Commercial

Piette, Mary Ann

2009-01-01T23:59:59.000Z

217

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

reliability signals for demand response GTA HTTPS HVAC IT kWand Commissioning Automated Demand Response Systems. and Techniques for Demand Response. California Energy

Kiliccote, Sila

2010-01-01T23:59:59.000Z

218

Open Automated Demand Response Communications Specification (Version 1.0)  

E-Print Network (OSTI)

and Techniques for Demand Response. May 2007. LBNL-59975.tofacilitateautomating demandresponseactionsattheInteroperable Automated Demand Response Infrastructure,

Piette, Mary Ann

2009-01-01T23:59:59.000Z

219

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network (OSTI)

ofFullyAutomatedDemand ResponseinLargeFacilities. FullyAutomatedDemandResponseTestsinLargeFacilities. OpenAutomated DemandResponseCommunicationStandards:

Dudley, June Han

2009-01-01T23:59:59.000Z

220

Scenarios for Consuming Standardized Automated Demand Response Signals  

E-Print Network (OSTI)

of Fully Automated Demand Response in Large Facilities.Fully Automated Demand Response Tests in Large Facilities.Interoperable Automated Demand Response Infrastructure.

Koch, Ed

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "highest actual 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 Response in U.S. Electricity Markets: Empirical Evidence  

E-Print Network (OSTI)

Reliability Corporation. Demand response data task force:Energy. Benefits of demand response in electricity marketsAssessment of demand response & advanced metering, staff

Cappers, Peter

2009-01-01T23:59:59.000Z

222

Direct versus Facility Centric Load Control for Automated Demand Response  

E-Print Network (OSTI)

Interoperable Automated Demand Response Infrastructure.and Techniques for Demand Response. LBNL Report 59975. Mayand Communications for Demand Response and Energy Efficiency

Piette, Mary Ann

2010-01-01T23:59:59.000Z

223

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

Goodin. 2009. Open Automated Demand Response Communicationsin Demand Response for Wholesale Ancillary Services. InOpen Automated Demand Response Demonstration Project. LBNL-

Ghatikar, Girish

2010-01-01T23:59:59.000Z

224

Modeling, Analysis, and Control of Demand Response Resources  

E-Print Network (OSTI)

advanced metering and demand response in electricityGoldman, and D. Kathan. Demand response in U.S. electricity29] DOE. Benefits of demand response in electricity markets

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

225

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network (OSTI)

Robinson, Michael, 2008, "Demand Response in Midwest ISOPresentation at MISO Demand Response Working Group Meeting,Coordination of Retail Demand Response with Midwest ISO

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

226

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network (OSTI)

13 Table 2. Demand Side Management Framework for IndustrialDR Strategies The demand-side management (DSM) frameworkpresented in Table 2. Demand Side Management Framework for

McKane, Aimee T.

2009-01-01T23:59:59.000Z

227

The Role of Demand Response in Default Service Pricing  

E-Print Network (OSTI)

THE ROLE OF DEMAND RESPONSE IN DEFAULT SERVICE PRICING Galenfor providing much-needed demand response in electricitycompetitive retail markets, demand response often appears to

Barbose, Galen; Goldman, Chuck; Neenan, Bernie

2006-01-01T23:59:59.000Z

228

The Role of Demand Response in Default Service Pricing  

E-Print Network (OSTI)

and coordinated by the Demand Response Research Center onThe Role of Demand Response in Default Service Pricing Galenfor providing much-needed demand response in electricity

Barbose, Galen; Goldman, Charles; Neenan, Bernie

2008-01-01T23:59:59.000Z

229

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

description of six energy and demand management concepts.how quickly it can modify energy demand. This is not a newimprovements in both energy efficiency and demand response (

Piette, Mary Ann

2009-01-01T23:59:59.000Z

230

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

Institute, Curbing Global Energy Demand Growth: The Energyup Assessment of Energy Demand in India Transportationa profound effect on energy demand. Policy analysts wishing

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

231

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

232

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

233

Distributed Intelligent Automated Demand Response (DIADR) Building  

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

Distributed Intelligent Automated Demand Distributed Intelligent Automated Demand Response (DIADR) Building Management System Distributed Intelligent Automated Demand Response (DIADR) Building Management System The U.S. Department of Energy (DOE) is currently conducting research into distributed intelligent-automated demand response (DIADR) building management systems. Project Description This project aims to develop a DIADR building management system with intelligent optimization and control algorithms for demand management, taking into account a multitude of factors affecting cost including: Comfort Heating, ventilating, and air conditioning (HVAC) Lighting Other building systems Climate Usage and occupancy patterns. The key challenge is to provide the demand response the ability to address more and more complex building systems that include a variety of loads,

234

Transportation Demand Management (TDM) Encyclopedia | Open Energy  

Open Energy Info (EERE)

Transportation Demand Management (TDM) Encyclopedia Transportation Demand Management (TDM) Encyclopedia Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Transportation Demand Management (TDM) Encyclopedia Agency/Company /Organization: Victoria Transport Policy Institute Sector: Energy Focus Area: Transportation Topics: Implementation Resource Type: Guide/manual Website: www.vtpi.org/tdm/tdm12.htm Cost: Free Language: English References: Victoria Transport Policy Institute[1] "The Online TDM Encyclopedia is the world's most comprehensive information resource concerning innovative transportation management strategies. It describes dozens of Transportation Demand Management (TDM) strategies and contains information on TDM planning, evaluation and implementation. It has thousands of hyperlinks that provide instant access

235

The Retail Planning Problem under Demand Uncertainty.  

E-Print Network (OSTI)

and Rajaram K. , (2000), Accurate Retail Testing of FashionThe Retail Planning Problem Under Demand Uncertainty GeorgeAbstract We consider the Retail Planning Problem in which

Georgiadis, G.; Rajaram, K.

2012-01-01T23:59:59.000Z

236

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

17 6. Barriers to Retail23 ii Retail Demand Response in SPP List of Figures and6 Table 3. SPP Retail DR Survey

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

237

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

water heaters with embedded demand responsive controls can be designed to automatically provide day-ahead and real-time response

Goldman, Charles

2010-01-01T23:59:59.000Z

238

Distributed Automated Demand Response - Energy Innovation Portal  

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

Transmission Find More Like This Return to Search Distributed Automated Demand Response Lawrence Livermore National Laboratory Contact LLNL About This Technology...

239

Demand Response (transactional control) - Energy Innovation Portal  

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

Transmission Electricity Transmission Find More Like This Return to Search Demand Response (transactional control) Pacific Northwest National Laboratory Contact PNNL About...

240

Regulation Services with Demand Response - Energy Innovation...  

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

Regulation Services with Demand Response Pacific Northwest National Laboratory Contact PNNL About This Technology Using grid frequency information, researchers have created...

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

Topics in Residential Electric Demand Response.  

E-Print Network (OSTI)

??Demand response and dynamic pricing are touted as ways to empower consumers, save consumers money, and capitalize on the smart grid and expensive advanced meter (more)

Horowitz, Shira R.

2012-01-01T23:59:59.000Z

242

Maximum-Demand Rectangular Location Problem  

E-Print Network (OSTI)

Oct 1, 2014 ... Demand and service can be defined in the most general sense. ... Industrial and Systems Engineering, Texas A&M University, September 2014.

Manish Bansal

2014-10-01T23:59:59.000Z

243

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

in the presence of renewable resources and on the amount ofprimarily from renewable resources, and to a limited extentintegration of renewable resources and deferrable demand. We

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

244

Basic Theory of Demand-Side Management  

Science Journals Connector (OSTI)

Demand-Side Management (DSM) is pivotal in Integrated Resource ... to realize sustainable development, and advanced energy management activity. A project can be implemented only...

Zhaoguang Hu; Xinyang Han; Quan Wen

2013-01-01T23:59:59.000Z

245

Demand response at the Naval Postgraduate School .  

E-Print Network (OSTI)

??The purpose of this MBA project is to assist the Naval Postgraduate School's Public Works department to assimilate into a Demand Response program that will (more)

Stouffer, Dean

2008-01-01T23:59:59.000Z

246

Demand response exchange in a deregulated environment .  

E-Print Network (OSTI)

??This thesis presents the development of a new and separate market for trading Demand Response (DR) in a deregulated power system. This market is termed (more)

Nguyen, DT

2012-01-01T23:59:59.000Z

247

Demand response exchange in a deregulated environment.  

E-Print Network (OSTI)

??This thesis presents the development of a new and separate market for trading Demand Response (DR) in a deregulated power system. This market is termed (more)

Nguyen, DT

2012-01-01T23:59:59.000Z

248

Geographically Based Hydrogen Demand and Infrastructure Rollout...  

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

Rollout Scenario Analysis Geographically Based Hydrogen Demand and Infrastructure Rollout Scenario Analysis Presentation by Margo Melendez at the 2010-2025 Scenario Analysis for...

249

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

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

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

250

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

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

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

251

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

Gasoline and Diesel Fuel Update (EIA)

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

252

Table 16. Total Electricity Sales, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

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

253

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

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

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

254

Table 16. Total Energy Consumption, Projected vs. Actual  

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

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

255

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

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

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

256

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

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

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

257

Table 4. Total Petroleum Consumption, Projected vs. Actual  

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

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

258

Table 9. Natural Gas Production, Projected vs. Actual  

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

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

259

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

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

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

260

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network (OSTI)

......................................................................... 11 3. Demand Side Management (DSM) Program Impacts................................... 13 4. Demand Sylvia Bender Manager DEMAND ANALYSIS OFFICE Scott W. Matthews Chief Deputy Director B.B. Blevins Forecast Methods and Models ....................................................... 14 5. Demand-Side

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

Demand Response and Electric Grid Reliability  

E-Print Network (OSTI)

Demand Response and Electric Grid Reliability Paul Wattles Senior Analyst, Market Design & Development, ERCOT CATEE Conference, Galveston October 10, 2012 2 North American Bulk Power Grids CATEE Conference October 10, 2012 ? The ERCOT... adequacy ? ?Achieving more DR participation would . . . displace some generation investments, but would achieve the same level of reliability... ? ?Achieving this ideal requires widespread demand response and market structures that enable loads...

Wattles, P.

2012-01-01T23:59:59.000Z

262

DEMAND SIMULATION FOR DYNAMIC TRAFFIC ASSIGNMENT  

E-Print Network (OSTI)

of the response of travelers to real-time pre- trip information. The demand simulator is an extension of dynamicDEMAND SIMULATION FOR DYNAMIC TRAFFIC ASSIGNMENT Constantinos Antoniou, Moshe Ben-Akiva, Michel Bierlaire, and Rabi Mishalani Massachusetts Institute of Technology, Cambridge, MA 02139 Abstract

Bierlaire, Michel

263

SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK DRAFTSTAFFREPORT May ELECTRICITY ANALYSIS OFFICE Sylvia Bender Acting Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION B. B assessment of the capability of the physical electricity system to provide power to meet electricity demand

264

An evaluation of forecasting methods for aircraft non-routine maintenance material demand  

Science Journals Connector (OSTI)

Aircraft maintenance can be divided into routine and non-routine activities. Material demand associated with non-routine maintenance is typically intermittent or lumpy: it has a large variance in frequency and quantity. Consequently, this type of demand is hard to predict. This paper introduces a method to collect time series datasets for aircraft non-routine maintenance material demand. Non-routine material consumption is linked to scheduled maintenance tasks to gain insight in demand patterns. A structural part selection of the Boeing 737NG fleet of an aviation partner has been sampled to generate various test cases. Subsequently, various forecasting methods are applied to these test cases and evaluated using various accuracy metrics. For the small time series datasets associated with non-routine maintenance, exponentially weighted moving average (EMA) outperformed smoothing methods such as Croston's method (CR) and the Syntetos-Boylan approximation (SBA). To validate the practical applicability of EMA for non-routine maintenance material demand, the method has been applied and verified in the prediction of actual demand for a separate maintenance C-check.

Maarten Zorgdrager; Wim J.C. Verhagen; Richard Curran

2014-01-01T23:59:59.000Z

265

Incorporating Demand Response into Western Interconnection Transmission Planning  

E-Print Network (OSTI)

response DSM Demand Side Management EE energy efficiencywith the development of demand-side management (DSM)-related

Satchwell, Andrew

2014-01-01T23:59:59.000Z

266

Demand Response Opportunities in Industrial Refrigerated Warehouses in California  

SciTech Connect

Industrial refrigerated warehouses that implemented energy efficiency measures and have centralized control systems can be excellent candidates for Automated Demand Response (Auto-DR) due to equipment synergies, and receptivity of facility managers to strategies that control energy costs without disrupting facility operations. Auto-DR utilizes OpenADR protocol for continuous and open communication signals over internet, allowing facilities to automate their Demand Response (DR). Refrigerated warehouses were selected for research because: They have significant power demand especially during utility peak periods; most processes are not sensitive to short-term (2-4 hours) lower power and DR activities are often not disruptive to facility operations; the number of processes is limited and well understood; and past experience with some DR strategies successful in commercial buildings may apply to refrigerated warehouses. This paper presents an overview of the potential for load sheds and shifts from baseline electricity use in response to DR events, along with physical configurations and operating characteristics of refrigerated warehouses. Analysis of data from two case studies and nine facilities in Pacific Gas and Electric territory, confirmed the DR abilities inherent to refrigerated warehouses but showed significant variation across facilities. Further, while load from California's refrigerated warehouses in 2008 was 360 MW with estimated DR potential of 45-90 MW, actual achieved was much less due to low participation. Efforts to overcome barriers to increased participation may include, improved marketing and recruitment of potential DR sites, better alignment and emphasis on financial benefits of participation, and use of Auto-DR to increase consistency of participation.

Goli, Sasank; McKane, Aimee; Olsen, Daniel

2011-06-14T23:59:59.000Z

267

Uranium 2009 resources, production and demand  

E-Print Network (OSTI)

With several countries currently building nuclear power plants and planning the construction of more to meet long-term increases in electricity demand, uranium resources, production and demand remain topics of notable interest. In response to the projected growth in demand for uranium and declining inventories, the uranium industry the first critical link in the fuel supply chain for nuclear reactors is boosting production and developing plans for further increases in the near future. Strong market conditions will, however, be necessary to trigger the investments required to meet projected demand. The "Red Book", jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency, is a recognised world reference on uranium. It is based on information compiled in 40 countries, including those that are major producers and consumers of uranium. This 23rd edition provides a comprehensive review of world uranium supply and demand as of 1 January 2009, as well as data on global ur...

Organisation for Economic Cooperation and Development. Paris

2010-01-01T23:59:59.000Z

268

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

269

Encryption-on-Demand, [EOD-g8516] Page #-1 Encryption-On-Demand  

E-Print Network (OSTI)

Encryption-on-Demand, [EOD-g8516] Page #-1 Encryption-On-Demand: Practical and Theoretical be served by an 'encryption-on-demand' (EoD) service which will enable them to communicate securely with no prior preparations, and no after effects. We delineate a possible EoD service, and describe some of its

270

Pose estimation of an uncooperative spacecraft from actual space imagery  

Science Journals Connector (OSTI)

This paper addresses the preliminary design of a spaceborne monocular vision-based navigation system for on-orbit-servicing and formation-flying applications. The aim is to estimate the pose of a passive space resident object using its known three-dimensional model and single low-resolution two-dimensional images collected on-board the active spacecraft. In contrast to previous work, no supportive means are available on the target satellite (e.g., light emitting diodes) and no a-priori knowledge of the relative position and attitude is available (i.e., lost-in-space scenario). Three fundamental mechanisms - perceptual organisation, true perspective projection, and random sample consensus - are exploited to overcome the limitations of monocular passive optical navigation in space. The preliminary design is conducted and validated making use of actual images collected in the frame of the PRISMA mission at about 700 km altitude and 10 m inter-spacecraft separation.

Simone D'Amico; Mathias Benn; John L. Jørgensen

2014-01-01T23:59:59.000Z

271

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.

272

Demand Response This is the first of the Council's power plans to treat demand response as a resource.1  

E-Print Network (OSTI)

Demand Response This is the first of the Council's power plans to treat demand response the resource and describes some of the potential advantages and problems of the development of demand response. WHAT IS DEMAND RESPONSE? Demand response is a change in customers' demand for electricity corresponding

273

Health Care Demand, Empirical Determinants of  

Science Journals Connector (OSTI)

Abstract Economic theory provides a powerful but incomplete guide to the empirical determinants of health care demand. This article seeks to provide guidance on the selection and interpretation of demand determinants in empirical models. The author begins by introducing some general rules of thumb derived from economic and statistical principles. A brief review of the recent empirical literature next describes the range of current practices. Finally, a representative example of health care demand is developed to illustrate the selection, use, and interpretation of empirical determinants.

S.H. Zuvekas

2014-01-01T23:59:59.000Z

274

Demand Response Opportunities in Industrial Refrigerated Warehouses in  

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

Response Opportunities in Industrial Refrigerated Warehouses in Response Opportunities in Industrial Refrigerated Warehouses in California Title Demand Response Opportunities in Industrial Refrigerated Warehouses in California Publication Type Conference Paper LBNL Report Number LBNL-4837E Year of Publication 2011 Authors Goli, Sasank, Aimee T. McKane, and Daniel Olsen Conference Name 2011 ACEEE Summer Study on Energy Efficiency in Industry Date Published 08/2011 Conference Location Niagara Falls, NY Keywords market sectors, openadr, refrigerated warehouses Abstract Industrial refrigerated warehouses that implemented energy efficiency measures and have centralized control systems can be excellent candidates for Automated Demand Response (Auto-DR) due to equipment synergies, and receptivity of facility managers to strategies that control energy costs without disrupting facility operations. Auto-DR utilizes OpenADR protocol for continuous and open communication signals over internet, allowing facilities to automate their Demand Response (DR). Refrigerated warehouses were selected for research because: They have significant power demand especially during utility peak periods; most processes are not sensitive to short-term (2-4 hours) lower power and DR activities are often not disruptive to facility operations; the number of processes is limited and well understood; and past experience with some DR strategies successful in commercial buildings may apply to refrigerated warehouses. This paper presents an overview of the potential for load sheds and shifts from baseline electricity use in response to DR events, along with physical configurations and operating characteristics of refrigerated warehouses. Analysis of data from two case studies and nine facilities in Pacific Gas and Electric territory, confirmed the DR abilities inherent to refrigerated warehouses but showed significant variation across facilities. Further, while load from California's refrigerated warehouses in 2008 was 360 MW with estimated DR potential of 45-90 MW, actual achieved was much less due to low participation. Efforts to overcome barriers to increased participation may include, improved marketing and recruitment of potential DR sites, better alignment and emphasis on financial benefits of participation, and use of Auto-DR to increase consistency of participation.

275

NCEP_Demand_Response_Draft_111208.indd  

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

National Council on Electricity Policy: Electric Transmission Series for State Offi National Council on Electricity Policy: Electric Transmission Series for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials Prepared by the U.S. Demand Response Coordinating Committee for The National Council on Electricity Policy Fall 2008 i National Council on Electricity Policy: Electric Transmission Series for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials The National Council on Electricity Policy is funded by the U.S. Department of Energy and the U.S. Environmental Protection Agency. The views and opinions expressed herein are strictly those of the

276

Solar in Demand | Department of Energy  

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

Solar in Demand Solar in Demand Solar in Demand June 15, 2012 - 10:23am Addthis Kyle Travis, left and Jon Jackson, with Lighthouse Solar, install microcrystalline PV modules on top of Kevin Donovan's town home. | Credit: Dennis Schroeder. Kyle Travis, left and Jon Jackson, with Lighthouse Solar, install microcrystalline PV modules on top of Kevin Donovan's town home. | Credit: Dennis Schroeder. April Saylor April Saylor Former Digital Outreach Strategist, Office of Public Affairs What does this mean for me? A new study says U.S. developers are likely to install about 3,300 megawatts of solar panels in 2012 -- almost twice the amount installed last year. In case you missed it... This week, the Wall Street Journal published an article, "U.S. Solar-Panel Demand Expected to Double," highlighting the successes of

277

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

278

EIA - Annual Energy Outlook 2008 - Electricity Demand  

Gasoline and Diesel Fuel Update (EIA)

Electricity Demand Electricity Demand Annual Energy Outlook 2008 with Projections to 2030 Electricity Demand Figure 60. Annual electricity sales by sector, 1980-2030 (billion kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 61. Electricity generation by fuel, 2006 and 2030 (billion kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. figure data Residential and Commercial Sectors Dominate Electricity Demand Growth Total electricity sales increase by 29 percent in the AEO2008 reference case, from 3,659 billion kilowatthours in 2006 to 4,705 billion in 2030, at an average rate of 1.1 percent per year. The relatively slow growth follows the historical trend, with the growth rate slowing in each succeeding

279

Demand Controlled Ventilation and Classroom Ventilation  

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

3 3 Authors Fisk, William J., Mark J. Mendell, Molly Davies, Ekaterina Eliseeva, David Faulkner, Tienzen Hong, and Douglas P. Sullivan Publisher Lawrence Berkeley National Laboratory City Berkeley Keywords absence, building s, carbon dioxide, demand - controlled ventilation, energy, indoor air quality, schools, ventilation Abstract This document summarizes a research effort on demand controlled ventilation and classroom ventilation. The research on demand controlled ventilation included field studies and building energy modeling. Major findings included:  The single-location carbon dioxide sensors widely used for demand controlled ventilation frequently have large errors and will fail to effectively control ventilation rates (VRs).  Multi-location carbon dioxide measurement systems with more expensive sensors connected to multi-location sampling systems may measure carbon dioxide more accurately.

280

China End-Use Energy Demand Modeling  

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

China End-Use Energy Demand Modeling China End-Use Energy Demand Modeling Speaker(s): Nan Zhou Date: October 8, 2009 (All day) Location: 90-3122 As a consequence of soaring energy demand due to the staggering pace of its economic growth, China overtook the United States in 2007 to become the world's biggest contributor to CO2 emissions (IEA, 2007). Since China is still in an early stage of industrialization and urbanization, economic development promises to keep China's energy demand growing strongly. Furthermore, China's reliance on fossil fuel is unlikely to change in the long term, and increased needs will only heighten concerns about energy security and climate change. In response, the Chinese government has developed a series of policies and targets aimed at improving energy efficiency, including both short-term targets and long-term strategic

Note: This page contains sample records for the topic "highest actual 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
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281

Integrated Predictive Demand Response Controller Research Project |  

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

Predictive Demand Response Predictive Demand Response Controller Research Project Integrated Predictive Demand Response Controller Research Project The U.S. Department of Energy (DOE) is currently conducting research into integrated predictive demand response (IPDR) controllers. The project team will attempt to design an IPDR controller so that it can be used in new or existing buildings or in collections of buildings. In the case of collections of buildings, they may be colocated on a single campus or remotely located as long as they are served by a single utility or independent service operator. Project Description This project seeks to perform the necessary applied research, development, and testing to provide a communications interface using industry standard open protocols and emerging National Institute of Standards and Technology

282

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

283

Power Consumption Analysis of Architecture on Demand  

Science Journals Connector (OSTI)

Abstract (40-Word Limit): Recently proposed Architecture on Demand (AoD) node shows considerable flexibility benefits against traditional ROADMs. We study the power consumption of AoD...

Garrich, Miquel; Amaya, Norberto; Zervas, Georgios; Giaccone, Paolo; Simeonidou, Dimitra

284

Integration of Demand Side Management, Distributed Generation...  

Open Energy Info (EERE)

States. Annex 8 provides a list of software tools for analysing various aspects of demand response, distributed generation, smart grid and energy storage. Annex 9 is a list of...

285

Capitalize on Existing Assets with Demand Response  

E-Print Network (OSTI)

Industrial facilities universally struggle with escalating energy costs. EnerNOC will demonstrate how commercial, industrial, and institutional end-users can capitalize on their existing assetsat no cost and no risk. Demand response, the voluntary...

Collins, J.

2008-01-01T23:59:59.000Z

286

SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY  

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

As a city that experiences seasonal spikes in energy demand and accompanying energy bills, San Antonio, Texas, wanted to help homeowners and businesses reduce their energy use and save on energy...

287

Global Energy: Supply, Demand, Consequences, Opportunities  

SciTech Connect

July 29, 2008 Berkeley Lab lecture: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

Arun Majumdar

2008-08-14T23:59:59.000Z

288

Volatile coal prices reflect supply, demand uncertainties  

SciTech Connect

Coal mine owners and investors say that supply and demand are now finally in balance. But coal consumers find that both spot tonnage and new contract coal come at a much higher price.

Ryan, M.

2004-12-15T23:59:59.000Z

289

Global Energy: Supply, Demand, Consequences, Opportunities  

ScienceCinema (OSTI)

July 29, 2008 Berkeley Lab lecture: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

Arun Majumdar

2010-01-08T23:59:59.000Z

290

Demand Controlled Ventilation and Classroom Ventilation  

E-Print Network (OSTI)

columnsindicatetheenergyandcostsavingsfor demandclasssize. (Theenergycosts ofclassroomventilationTotal Increase in Energy Costs ($) Increased State Revenue

Fisk, William J.

2014-01-01T23:59:59.000Z

291

Transportation energy demand: Model development and use  

Science Journals Connector (OSTI)

This paper describes work undertaken and sponsored by the Energy Commission to improve transportation energy demand forecasting and policy analysis for California. Two ... , the paper discusses some of the import...

Chris Kavalec

1998-06-01T23:59:59.000Z

292

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

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

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

293

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

Gasoline and Diesel Fuel Update (EIA)

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

294

Table 10. Natural Gas Production, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

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

295

Table 17. Total Energy Consumption, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

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

296

Table 3. Gross Domestic Product, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

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

297

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

Gasoline and Diesel Fuel Update (EIA)

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

298

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

Gasoline and Diesel Fuel Update (EIA)

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

299

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

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

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

300

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

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

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

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We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

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

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

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

302

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

Gasoline and Diesel Fuel Update (EIA)

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

303

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

Gasoline and Diesel Fuel Update (EIA)

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

304

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

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

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

305

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

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

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

306

Table 7. Petroleum Net Imports, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

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

307

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

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

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

308

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

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

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

309

Table 22. Energy Intensity, Projected vs. Actual Projected  

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

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

310

Table 15. Average Electricity Prices, Projected vs. Actual  

Gasoline and Diesel Fuel Update (EIA)

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

311

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

Gasoline and Diesel Fuel Update (EIA)

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

312

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

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

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

313

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

314

Real-Time Demand Side Energy Management  

E-Print Network (OSTI)

Real-Time Demand Side Energy Management Annelize Victor Michael Brodkorb Sr. Business Consultant Business Development Manager Aspen Technology, Inc. Aspen Technology Espaa, S.A. Houston, TX Barcelona, Spain ABSTRACT To remain... competitive, manufacturers must capture opportunities to increase bottom-line profitability. The goal of this paper is to present a new methodology for reducing energy costs Demand-Side Energy Management. Learn how process manufacturers assess energy...

Victor, A.; Brodkorb, M.

2006-01-01T23:59:59.000Z

315

Electric Utility Demand-Side Evaluation Methodologies  

E-Print Network (OSTI)

"::. ELECTRIC UTILITY DEMAND-SIDE EVALUATION METHODOLOGIES* Nat Treadway Public Utility Commission of Texas Austin, Texas ABSTRACT The electric. util ity industry's demand-side management programs can be analyzed ?from various points... of view using a standard benefit-cost methodology. The methodology now in use by several. electric utilities and the Public Utility Commlsslon of Texas includes measures of efficiency and equity. The nonparticipant test as a measure of equity...

Treadway, N.

316

Aviation fuel demand development in China  

Science Journals Connector (OSTI)

Abstract This paper analyzes the core factors and the impact path of aviation fuel demand in China and conducts a structural decomposition analysis of the aviation fuel cost changes and increase of the main aviation enterprises business profits. Through the establishment of an integrated forecast model for Chinas aviation fuel demand, this paper confirms that the significant rise in Chinas aviation fuel demand because of increasing air services demand is more than offset by higher aviation fuel efficiency. There are few studies which use a predictive method to decompose, estimate and analyze future aviation fuel demand. Based on a structural decomposition with indirect prediction, aviation fuel demand is decomposed into efficiency and total amount (aviation fuel efficiency and air transport total turnover). The core influencing factors for these two indexes are selected using path analysis. Then, univariate and multivariate models (ETS/ARIMA model and Bayesian multivariate regression) are used to analyze and predict both aviation fuel efficiency and air transport total turnover. At last, by integrating results, future aviation fuel demand is forecast. The results show that the aviation fuel efficiency goes up by 0.8% as the passenger load factor increases 1%; the air transport total turnover goes up by 3.8% and 0.4% as the urbanization rate and the per capita GDP increase 1%, respectively. By the end of 2015, Chinas aviation fuel demand will have increased to 28 million tonnes, and is expected to be 50 million tonnes by 2020. With this in mind, increases in the main aviation enterprises business profits must be achieved through the further promotion of air transport.

Jian Chai; Zhong-Yu Zhang; Shou-Yang Wang; Kin Keung Lai; John Liu

2014-01-01T23:59:59.000Z

317

Ethanol Demand in United States Gasoline Production  

SciTech Connect

The Oak Ridge National Laboratory (OWL) Refinery Yield Model (RYM) has been used to estimate the demand for ethanol in U.S. gasoline production in year 2010. Study cases examine ethanol demand with variations in world oil price, cost of competing oxygenate, ethanol value, and gasoline specifications. For combined-regions outside California summer ethanol demand is dominated by conventional gasoline (CG) because the premised share of reformulated gasoline (RFG) production is relatively low and because CG offers greater flexibility for blending high vapor pressure components like ethanol. Vapor pressure advantages disappear for winter CG, but total ethanol used in winter RFG remains low because of the low RFG production share. In California, relatively less ethanol is used in CG because the RFG production share is very high. During the winter in California, there is a significant increase in use of ethanol in RFG, as ethanol displaces lower-vapor-pressure ethers. Estimated U.S. ethanol demand is a function of the refiner value of ethanol. For example, ethanol demand for reference conditions in year 2010 is 2 billion gallons per year (BGY) at a refiner value of $1.00 per gallon (1996 dollars), and 9 BGY at a refiner value of $0.60 per gallon. Ethanol demand could be increased with higher oil prices, or by changes in gasoline specifications for oxygen content, sulfur content, emissions of volatile organic compounds (VOCS), and octane numbers.

Hadder, G.R.

1998-11-24T23:59:59.000Z

318

Performance analysis of demand planning approaches for aggregating, forecasting and disaggregating interrelated demands  

Science Journals Connector (OSTI)

A synchronized and responsive flow of materials, information, funds, processes and services is the goal of supply chain planning. Demand planning, which is the very first step of supply chain planning, determines the effectiveness of manufacturing and logistic operations in the chain. Propagation and magnification of the uncertainty of demand signals through the supply chain, referred to as the bullwhip effect, is the major cause of ineffective operation plans. Therefore, a flexible and robust supply chain forecasting system is necessary for industrial planners to quickly respond to the volatile demand. Appropriate demand aggregation and statistical forecasting approaches are known to be effective in managing the demand variability. This paper uses the bivariate VAR(1) time series model as a study vehicle to investigate the effects of aggregating, forecasting and disaggregating two interrelated demands. Through theoretical development and systematic analysis, guidelines are provided to select proper demand planning approaches. A very important finding of this research is that disaggregation of a forecasted aggregated demand should be employed when the aggregated demand is very predictable through its positive autocorrelation. Moreover, the large positive correlation between demands can enhance the predictability and thus result in more accurate forecasts when statistical forecasting methods are used.

Argon Chen; Jakey Blue

2010-01-01T23:59:59.000Z

319

E-Print Network 3.0 - actual results satellitenexperiment Sample...  

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

The actual case here corresponds to the minor windows (U0.5) case in Table 6. Table A1: Load and energy... .96) 6343.77 (3316.14) 933.65 (901.44) Major windows (Actual) Diff. - -...

320

Institutional Code of Ethics The University seeks to promote the highest standards of scientific and professional integrity  

E-Print Network (OSTI)

of Development and Alumni Relations reporting to the Vice-Chancellor's Group g. environmental impacts of energy is responsible for the development and implementation of the institutional ethics strategy as it relatesInstitutional Code of Ethics The University seeks to promote the highest standards of scientific

Burton, Geoffrey R.

Note: This page contains sample records for the topic "highest actual demand" from the National Library of EnergyBeta (NLEBeta).
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321

EP Rossby M-dwarfs have the highest population in the Universe. Because M-dwarfs have much lower  

E-Print Network (OSTI)

;8 21000 hPa(a)(b) 15 ms-1 5 K Figure 2Distribution of near-surface (1000 hPa) air temperature and winds the highest population in the Universe. Because M-dwarfs have much lower luminosity than Sun's, the habitable causes strong temperature contrast between day and night sides. In the present paper, we use a modified

Hu, Yongyun

322

THE HIGHEST-ENERGY COSMIC RAYS What in the cosmos can possibly be accelerating protons to 1020  

E-Print Network (OSTI)

the implications of the energy spectrum measurements on our understanding of the origin of cosmic rays, and we of origin Below 1015 eV the cosmic-ray energy spectrum obeys an approximate power law, falling like E-2THE HIGHEST-ENERGY COSMIC RAYS What in the cosmos can possibly be accelerating protons to 1020

323

An Operational Model for Optimal NonDispatchable Demand Response  

E-Print Network (OSTI)

An Operational Model for Optimal NonDispatchable Demand Response for Continuous PowerintensiveFACTS, $ Demand Response Energy Storage HVDC Industrial Customer PEV Renewable Energy Source: U.S.-Canada Power: To balance supply and demand of a power system, one can manipulate both: supply and demand demand response

Grossmann, Ignacio E.

324

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.

325

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

Gasoline and Diesel Fuel Update (EIA)

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

326

DemandDirect | Open Energy Information  

Open Energy Info (EERE)

DemandDirect DemandDirect Jump to: navigation, search Name DemandDirect Place Woodbury, Connecticut Zip 6798 Sector Efficiency, Renewable Energy, Services Product DemandDirect provides demand response, energy efficiency, load management, and distributed generation services to end-use electricity customers in order to reduce electricity consumption, improve grid reliability, and promote renewable energy. Coordinates 44.440496°, -72.414991° 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":44.440496,"lon":-72.414991,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

327

U.S. Coal Supply and Demand  

Gasoline and Diesel Fuel Update (EIA)

U.S. Coal Supply and Demand > U.S. Coal Supply and Demand U.S. Coal Supply and Demand > U.S. Coal Supply and Demand U.S. Coal Supply and Demand 2010 Review (entire report also available in printer-friendly format ) Previous Editions 2009 Review 2008 Review 2007 Review 2006 Review 2005 Review 2004 Review 2003 Review 2002 Review 2001 Review 2000 Review 1999 Review Data for: 2010 Released: May 2011 Next Release Date: April 2012 Table 3. Electric Power Sector Net Generation, 2009-2010 (Million Kilowatthours) New England Coal 14,378 14,244 -0.9 Hydroelectric 7,759 6,861 -11.6 Natural Gas 48,007 54,680 13.9 Nuclear 36,231 38,361 5.9 Other (1) 9,186 9,063 -1.3 Total 115,559 123,210 6.6 Middle Atlantic Coal 121,873 129,935 6.6 Hydroelectric 28,793 26,463 -8.1 Natural Gas 89,808 104,341 16.2 Nuclear 155,140 152,469 -1.7

328

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network (OSTI)

LABORATORY Coordination of Retail Demand Response withXXXXX Coordination of Retail Demand Response with MidwestAC02-05CH11231. Coordination of Retail Demand Response with

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

329

Analysis of Open Automated Demand Response Deployments in California  

E-Print Network (OSTI)

LBNL-6560E Analysis of Open Automated Demand Response Deployments in California and Guidelines The work described in this report was coordinated by the Demand Response Research. #12; #12;Abstract This report reviews the Open Automated Demand Response

330

PIER: Demand Response Research Center Director, Mary Ann Piette  

E-Print Network (OSTI)

1 PIER: Demand Response Research Center Director, Mary Ann Piette Program Development and Outreach Response Research Plan #12;2 Demand Response Research Center Objective Scope Stakeholders Develop, prioritize, conduct and disseminate multi- institutional research to facilitate Demand Response. Technologies

331

Automated Demand Response Strategies and Commissioning Commercial Building Controls  

E-Print Network (OSTI)

4 9 . Piette et at Automated Demand Response Strategies andDynamic Controls for Demand Response in New and ExistingFully Automated Demand Response Tests in Large Facilities"

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

2006-01-01T23:59:59.000Z

332

Demand Response Enabling Technologies and Approaches for Industrial Facilities  

E-Print Network (OSTI)

, there are also huge opportunities for demand response in the industrial sector. This paper describes some of the demand response initiatives that are currently active in New York State, explaining applicability of industrial facilities. Next, we discuss demand...

Epstein, G.; D'Antonio, M.; Schmidt, C.; Seryak, J.; Smith, C.

2005-01-01T23:59:59.000Z

333

LEED Demand Response Credit: A Plan for Research towards Implementation  

E-Print Network (OSTI)

DRs growing role in demand-side management activities andhow DR fits with demand-side management activities, DRemissions rates The demand-side management (DSM) framework

Kiliccote, Sila

2014-01-01T23:59:59.000Z

334

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network (OSTI)

Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the4. Status of Demand Side Management in Midwest ISO 5.

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

335

A Survey on Privacy in Residential Demand Side Management Applications  

Science Journals Connector (OSTI)

Demand Side Management (DSM) is an auspicious concept for ... on privacy energy issues and potential solutions in Demand Response systems. For this we give an ... the BSI and indicate three technical types of Demand

Markus Karwe; Jens Strker

2014-01-01T23:59:59.000Z

336

Demand-Side Management and Energy Efficiency Revisited  

E-Print Network (OSTI)

EPRI). 1984. Demand Side Management. Vol. 1:Overview of Key1993. Industrial Demand-Side Management Programs: WhatsJ. Kulick. 2004. Demand side management and energy e?ciency

Auffhammer, Maximilian; Blumstein, Carl; Fowlie, Meredith

2007-01-01T23:59:59.000Z

337

Commercial Fleet Demand for Alternative-Fuel Vehicles in California  

E-Print Network (OSTI)

Precursors of demand for alternative-fuel vehicles: resultsFLEET DEMAND FOR ALTERNATIVE-FUEL VEHICLES IN CALIFORNIA*AbstractFleet demand for alternative-fuel vehicles (AFVs

Golob, Thomas F; Torous, Jane; Bradley, Mark; Brownstone, David; Crane, Soheila Soltani; Bunch, David S

1996-01-01T23:59:59.000Z

338

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

ED2, September. CEC (2005b) Energy demand forecast methodsCalifornia Baseline Energy Demands to 2050 for Advancedof a baseline scenario for energy demand in California for a

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

2008-01-01T23:59:59.000Z

339

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network (OSTI)

Importance Total off- site energy demand (2030) 20% decreaseImportance Total off-site energy demand (2030) 20% decreaseImportance Total off-site energy demand (2030) 20% decrease

Stadler, Michael

2011-01-01T23:59:59.000Z

340

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network (OSTI)

iv Chapter 5: National energy demand and potential energyAs Figure 1-2 shows, HVAC energy demand is comparable to thefor reducing this high energy demand reaches beyond

Shehabi, Arman

2010-01-01T23:59:59.000Z

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

EIA - AEO2010 - Natural Gas Demand  

Gasoline and Diesel Fuel Update (EIA)

Gas Demand Gas Demand Annual Energy Outlook 2010 with Projections to 2035 Natural Gas Demand Figure 68. Regional growth in nonhydroelectric renewable electricity capacity including end-use capacity, 2008-2035 Click to enlarge » Figure source and data excel logo Figure 69. Annual average lower 48 wellhead and Henry Hub spot market prices for natural gas, 1990-2035. Click to enlarge » Figure source and data excel logo Figure 70. Ratio of low-sulfur light crude oil price to Henry Hub natural gas price on an energy equivalent basis, 1990-2035 Click to enlarge » Figure source and data excel logo Figure 71. Annual average lower 48 wellhead prices for natural gas in three technology cases, 1990-2035. Click to enlarge » Figure source and data excel logo Figure 72. Annual average lower 48 wellhead prices for natural gas in three oil price cases, 1990-2035

342

Production Will Meet Demand Increase This Summer  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: Production must meet increases in demand this year. Last year, increased imports met most of the summer demand increase, and increases in stock draws met almost all of the remainder. Production did not increase much. But this year, inventories will not be available, and increased imports seem unlikely. Thus, increases in production will be needed to meet increased demand. Imports availability is uncertain this summer. Imports in 1999 were high, and with Phase II RFG product requirements, maintaining this level could be challenging since not all refineries exporting to the U.S. will be able to meet the new gasoline specifications. Stocks will also contribute little supply this summer. Last year's high gasoline stocks allowed for a stock draw that was 58 MB/D higher than

343

EIA - Annual Energy Outlook 2008 - Energy Demand  

Gasoline and Diesel Fuel Update (EIA)

Energy Demand Energy Demand Annual Energy Outlook 2008 with Projections to 2030 Energy Demand Figure 40. Energy use per capita and per dollar of gross domestic product, 1980-2030 (index, 1980 = 1). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 41. Primary energy use by fuel, 2006-2030 (quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. figure data Average Energy Use per Person Levels Off Through 2030 Because energy use for housing, services, and travel in the United States is closely linked to population levels, energy use per capita is relatively stable (Figure 40). In addition, the economy is becoming less dependent on energy in general. Energy intensity (energy use per 2000 dollar of GDP) declines by an average

344

International Oil Supplies and Demands. Volume 1  

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

345

Energy demand simulation for East European countries  

Science Journals Connector (OSTI)

The analysis and created statistical models of energy consumption tendencies in the European Union (EU25), including new countries in transition, are presented. The EU15 market economy countries and countries in transition are classified into six clusters by relative indicators of Gross Domestic Product (GDP/P) and energy demand (W/P) per capita. The specified statistical models of energy intensity W/GDP non-linear stochastic tendencies have been discovered with respect to the clusters of classified countries. The new energy demand simulation models have been developed for the demand management in time??territory hierarchy in various scenarios of short-term and long-term perspective on the basis of comparative analysis methodology. The non-linear statistical models were modified to GDP, W/P and electricity (E/P) final consumption long-term forecasts for new associated East European countries and, as an example, for the Baltic Countries, including Lithuania.

Jonas Algirdas Kugelevicius; Algirdas Kuprys; Jonas Kugelevicius

2007-01-01T23:59:59.000Z

346

Utility Sector Impacts of Reduced Electricity Demand  

SciTech Connect

This report presents a new approach to estimating the marginal utility sector impacts associated with electricity demand reductions. The method uses publicly available data and provides results in the form of time series of impact factors. The input data are taken from the Energy Information Agency's Annual Energy Outlook (AEO) projections of how the electric system might evolve in the reference case, and in a number of side cases that incorporate different effciency and other policy assumptions. The data published with the AEO are used to define quantitative relationships between demand-side electricity reductions by end use and supply-side changes to capacity by plant type, generation by fuel type and emissions of CO2, Hg, NOx and SO2. The impact factors define the change in each of these quantities per unit reduction in site electricity demand. We find that the relative variation in these impacts by end use is small, but the time variation can be significant.

Coughlin, Katie

2014-12-01T23:59:59.000Z

347

International Oil Supplies and Demands. Volume 2  

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

348

Demand Management Institute (DMI) | Open Energy Information  

Open Energy Info (EERE)

Demand Management Institute (DMI) Demand Management Institute (DMI) Jump to: navigation, search Name Demand Management Institute (DMI) Address 35 Walnut Street Place Wellesley, Massachusetts Zip 02481 Sector Buildings Product Provides analysis for buildings on reducing energy use Website http://www.dmiinc.com/ Coordinates 42.3256508°, -71.2530294° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":42.3256508,"lon":-71.2530294,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

349

Uranium 2014 resources, production and demand  

E-Print Network (OSTI)

Published every other year, Uranium Resources, Production, and Demand, or the "Red Book" as it is commonly known, is jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency. It is the recognised world reference on uranium and is based on official information received from 43 countries. It presents the results of a thorough review of world uranium supplies and demand and provides a statistical profile of the world uranium industry in the areas of exploration, resource estimates, production and reactor-related requirements. It provides substantial new information from all major uranium production centres in Africa, Australia, Central Asia, Eastern Europe and North America. Long-term projections of nuclear generating capacity and reactor-related uranium requirements are provided as well as a discussion of long-term uranium supply and demand issues. This edition focuses on recent price and production increases that could signal major changes in the industry.

Organisation for Economic Cooperation and Development. Paris

2014-01-01T23:59:59.000Z

350

DEMAND CONTROLLED VENTILATION AND CLASSROOM VENTILATION  

SciTech Connect

This document summarizes a research effort on demand controlled ventilation and classroom ventilation. The research on demand controlled ventilation included field studies and building energy modeling. Major findings included: ? The single-location carbon dioxide sensors widely used for demand controlled ventilation frequently have large errors and will fail to effectively control ventilation rates (VRs).? Multi-location carbon dioxide measurement systems with more expensive sensors connected to multi-location sampling systems may measure carbon dioxide more accurately.? Currently-available optical people counting systems work well much of the time but have large counting errors in some situations. ? In meeting rooms, measurements of carbon dioxide at return-air grilles appear to be a better choice than wall-mounted sensors.? In California, demand controlled ventilation in general office spaces is projected to save significant energy and be cost effective only if typical VRs without demand controlled ventilation are very high relative to VRs in codes. Based on the research, several recommendations were developed for demand controlled ventilation specifications in the California Title 24 Building Energy Efficiency Standards.The research on classroom ventilation collected data over two years on California elementary school classrooms to investigate associations between VRs and student illness absence (IA). Major findings included: ? Median classroom VRs in all studied climate zones were below the California guideline, and 40percent lower in portable than permanent buildings.? Overall, one additional L/s per person of VR was associated with 1.6percent less IA. ? Increasing average VRs in California K-12 classrooms from the current average to the required level is estimated to decrease IA by 3.4percent, increasing State attendance-based funding to school districts by $33M, with $6.2 M in increased energy costs. Further VR increases would provide additional benefits.? Confirming these findings in intervention studies is recommended. ? Energy costs of heating/cooling unoccupied classrooms statewide are modest, but a large portion occurs in relatively few classrooms.

Fisk, William J.; Mendell, Mark J.; Davies, Molly; Eliseeva, Ekaterina; Faulkner, David; Hong, Tienzen; Sullivan, Douglas P.

2014-01-06T23:59:59.000Z

351

Rice Supply, Demand and Related Government Programs.  

E-Print Network (OSTI)

, 1930-55 Year Weighted Year Weighted beginning average price beginning average price August per cwt. August per cwt. Dollars Dollars 'Includes an allowance for unredeemed loans. response to the strengthening of foreign demand, rice prices by 1952... 91 percent of the average parity price during 1935-54, with !he 4 years of World War I1 omitted. The elasticity of demand was assumed to be about -.2. The annually derived price based on the assumed elasticity and the percentage change in price...

Kincannon, John A.

1957-01-01T23:59:59.000Z

352

Demand Response Initiatives at CPS Energy  

E-Print Network (OSTI)

Demand Response Initiatives at CPS Energy Clean Air Through Energy Efficiency (CATEE) Conference December 17, 2013 ESL-KT-13-12-53 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 CPSEs DR Program DR... than the military bases and Toyota combined. Schools & Universities contributed 6 MWs of Demand Response in 2013. 2013 DR Participants Trinity University - $5,654 Fort Sam ISD - $18,860 Judson ISD - $45,540 Alamo Colleges - $98,222 UTSA - $168...

Luna, R.

2013-01-01T23:59:59.000Z

353

Demand Response and Smart Metering Policy Actions Since the Energy...  

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

Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials Demand Response and Smart Metering Policy Actions Since the...

354

Overview of Demand Side Response | Department of Energy  

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

and Energy Officials Need to Know High Electric Demand Days: Clean Energy Strategies for Improving Air Quality Demand Response in U.S. Electricity Markets: Empirical Evidence...

355

Robust Unit Commitment Problem with Demand Response and ...  

E-Print Network (OSTI)

Oct 29, 2010 ... sion, both Demand Response (DR) strategy and intermittent renewable ... Key Words: unit commitment, demand response, wind energy, robust...

2010-10-31T23:59:59.000Z

356

National Action Plan on Demand Response | Department of Energy  

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

National Action Plan on Demand Response National Action Plan on Demand Response Presentation-given at the Federal Utility Partnership Working Group (FUPWG) Fall 2008...

357

ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES  

E-Print Network (OSTI)

ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES BY ANUPAMA SUNIL KOWLI B of consumers - called demand response resources (DRRs) - whose role has become increasingly important

Gross, George

358

The business value of demand response for balance responsible parties.  

E-Print Network (OSTI)

?? By using IT-solutions, the flexibility on the demand side in the electrical systems could be increased. This is called demand response and is part (more)

Jonsson, Mattias

2014-01-01T23:59:59.000Z

359

Aggregator-Assisted Residential Participation in Demand Response Program.  

E-Print Network (OSTI)

??The demand for electricity of a particular location can vary significantly based on season, ambient temperature, time of the day etc. High demand can result (more)

Hasan, Mehedi

2012-01-01T23:59:59.000Z

360

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

energy storage and demand management can complement solarwith energy storage to firm the resource, or solar thermaland solar generation. And demand response or energy storage

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

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

BUILDINGS SECTOR DEMAND-SIDE EFFICIENCY TECHNOLOGY SUMMARIES  

E-Print Network (OSTI)

............................................................................................... 2 Demand-Side Efficiency Technologies I. Energy Management Systems (EMSsLBL-33887 UC-000 BUILDINGS SECTOR DEMAND-SIDE EFFICIENCY TECHNOLOGY SUMMARIES Jonathan G. Koomey

362

Modeling, Analysis, and Control of Demand Response Resources.  

E-Print Network (OSTI)

??While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role in (more)

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

363

Modeling, Analysis, and Control of Demand Response Resources.  

E-Print Network (OSTI)

?? While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role (more)

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

364

Response to several FOIA requests - Renewable Energy. Demand...  

Energy Savers (EERE)

Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. nepdg251500.pdf....

365

Draft Chapter 3: Demand-Side Resources | Department of Energy  

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

3: Demand-Side Resources Draft Chapter 3: Demand-Side Resources Utilities in many states have been implementing energy efficiency and load management programs (collectively called...

366

Chapter 3: Demand-Side Resources | Department of Energy  

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

: Demand-Side Resources Chapter 3: Demand-Side Resources Utilities in many states have been implementing energy efficiency and load management programs (collectively called...

367

Tool Improves Electricity Demand Predictions to Make More Room...  

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

Tool Improves Electricity Demand Predictions to Make More Room for Renewables Tool Improves Electricity Demand Predictions to Make More Room for Renewables October 3, 2011 -...

368

A comparative study on conventional and advanced exergetic analyses of geothermal district heating systems based on actual operational data  

Science Journals Connector (OSTI)

This paper comparatively evaluates exergy destructions of a geothermal district heating system (GDHS) using both conventional and advanced exergetic analysis methods to identify the potential for improvement and the interactions among the components. As a real case study, the Afyon GDHS in Afyonkarahisar, Turkey, is considered based on actual operational data. For the first time, advanced exergetic analysis is applied to the GDHSs, in which the exergy destruction rate within each component is split into unavoidable/avoidable and endogenous/exogenous parts. The results indicate that the interconnections among all the components are not very strong. Thus, one should focus on how to reduce the internal inefficiency (destruction) rates of the components. The highest priority for improvement in the advanced exergetic analysis is in the re-injection pump (PM-IX), while it is the heat exchanger (HEX-III) in the conventional analysis. In addition, there is a substantial influence on the overall system as the total avoidable exergy destruction rate of the heat exchanger (HEX-V) has the highest value. On the overall system basis, the value for the conventional exergetic efficiency is determined to be 29.29% while that for the modified exergetic efficiency is calculated to be 34.46% through improving the overall components.

Arif Hepbasli; Ali Keeba?

2013-01-01T23:59:59.000Z

369

A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data  

E-Print Network (OSTI)

changes of HVAC source EUI between AMY and TMY3. (a) largeof total building source EUI. (a) large office, 90.1-2004a) changes in HVAC source EUI; (b) changes in total source

Hong, Tianzhen

2014-01-01T23:59:59.000Z

370

A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data  

E-Print Network (OSTI)

53: Total energy use in buildings evaluation and analysisTY. A design day for building load and energy estimation.Building and Environment, 1999; 34(4): 469-477. [5] Hong TZ,

Hong, Tianzhen

2014-01-01T23:59:59.000Z

371

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-

372

SHORT-RUN MONEY DEMAND Laurence Ball  

E-Print Network (OSTI)

SHORT-RUN MONEY DEMAND Laurence Ball Johns Hopkins University August 2002 I am grateful with Goldfeld's partial adjustment model. A key innovation is the choice of the interest rate in the money on "near monies" -- close substitutes for M1 such as savings accounts and money market mutual funds

Niebur, Ernst

373

Indianapolis Offers a Lesson on Driving Demand  

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

Successful program managers know that understanding the factors that drive homeowners to make upgrades is critical to the widespread adoption of energy efficiency. What better place to learn about driving demand for upgrades than in Indianapolis, America's most famous driving city?

374

Senior Center Network Redesign Under Demand Uncertainty  

E-Print Network (OSTI)

Senior Center Network Redesign Under Demand Uncertainty Osman Y. ¨Ozaltin Department of Industrial of Massachusetts Boston, Boston, MA 02125-3393, USA, michael.johnson@umb.edu Andrew J. Schaefer Department. In response, we propose a two-echelon network of senior centers. We for- mulate a two-stage stochastic

Schaefer, Andrew

375

PUBLISH ON DEMAND Recasting the Textbook  

E-Print Network (OSTI)

of history helped students evaluate the sources of information and better understand the perspectives from which history is written? WHAT WE SET OUT TO DO We recast the history textbook as an edited on- demand- source documents and interactive technology. WHAT WE FOUND High school students accessed our database

Das, Rhiju

376

Energy technologies and their impact on demand  

SciTech Connect

Despite the uncertainties, energy demand forecasts must be made to guide government policies and public and private-sector capital investment programs. Three principles can be identified in considering long-term energy prospects. First energy demand will continue to grow, driven by population growth, economic development, and the current low per capita energy consumption in developing countries. Second, energy technology advancements alone will not solve the problem. Energy-efficient technologies, renewable resource technologies, and advanced electric power technologies will all play a major role but will not be able to keep up with the growth in world energy demand. Third, environmental concerns will limit the energy technology choices. Increasing concern for environmental protection around the world will restrict primarily large, centralized energy supply facilities. The conclusion is that energy system diversity is the only solution. The energy system must be planned with consideration of both supply and demand technologies, must not rely on a single source of energy, must take advantage of all available technologies that are specially suited to unique local conditions, must be built with long-term perspectives, and must be able to adapt to change.

Drucker, H.

1995-06-01T23:59:59.000Z

377

Industry continues to cut energy demand  

Science Journals Connector (OSTI)

The U.S.'s 10 most energy-intensive industries are continuing to reduce their energy demand, with the chemical industry emerging as a leader in industrial energy conservation, says the Department of Energy in a report to Congress.The chemical industry is ...

1981-01-12T23:59:59.000Z

378

Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration  

SciTech Connect

Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generator and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.

Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.; Chassin, David P.; Djilali, Ned

2014-01-31T23:59:59.000Z

379

Decentralized demandsupply matching using community microgrids and consumer demand response: A scenario analysis  

Science Journals Connector (OSTI)

Abstract Developing countries constantly face the challenge of reliably matching electricity supply to increasing consumer demand. The traditional policy decisions of increasing supply and reducing demand centrally, by building new power plants and/or load shedding, have been insufficient. Locally installed microgrids along with consumer demand response can be suitable decentralized options to augment the centralized grid based systems and plug the demandsupply gap. The objectives of this paper are to: (1) develop a framework to identify the appropriate decentralized energy options for demandsupply matching within a community, and, (2) determine which of these options can suitably plug the existing demandsupply gap at varying levels of grid unavailability. A scenario analysis framework is developed to identify and assess the impact of different decentralized energy options at a community level and demonstrated for a typical urban residential community Vijayanagar, Bangalore in India. A combination of LPG based CHP microgrid and proactive demand response by the community is the appropriate option that enables the Vijayanagar community to meet its energy needs 24/7 in a reliable, cost-effective manner. The paper concludes with an enumeration of the barriers and feasible strategies for the implementation of community microgrids in India based on stakeholder inputs.

Kumudhini Ravindra; Parameshwar P. Iyer

2014-01-01T23:59:59.000Z

380

D:\assumptions_2001\assumptions2002\currentassump\demand.vp  

Gasoline and Diesel Fuel Update (EIA)

2 2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Petroleum Market Module. . . . . . . . . . . . .

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

The Role of Demand Response Policy Forum Series  

E-Print Network (OSTI)

The Role of Demand Response Policy Forum Series Beyond 33 Percent: California's Renewable Future and Demand Response #12;Historic focus on Seasonal Grid Stress PG&E Demand Bid Test Day 0 2000 4000 6000 8000 Communication Latency #12;Bottom Up Review of End-Use Loads for Demand Response 5 Commercial Residential

California at Davis, University of

382

A Simulation Study of Demand Responsive Transit System Design  

E-Print Network (OSTI)

A Simulation Study of Demand Responsive Transit System Design Luca Quadrifoglio, Maged M. Dessouky changed the landscape for demand responsive transit systems. First, the demand for this type of transit experiencing increased usage for demand responsive transit systems. The National Transit Summaries and Trends

Dessouky, Maged

383

Electricity Markets Meet the Home through Demand Response Lazaros Gkatzikis  

E-Print Network (OSTI)

Electricity Markets Meet the Home through Demand Response Lazaros Gkatzikis CERTH, University Hegde, Laurent Massouli´e Technicolor Paris Research Lab Paris, France Abstract-- Demand response (DR the alternative option of dynamic demand adaptation. In this direction, demand response (DR) programs provide

384

Autonomous Demand Response in Heterogeneous Smart Grid Topologies  

E-Print Network (OSTI)

1 Autonomous Demand Response in Heterogeneous Smart Grid Topologies Hamed Narimani and Hamed-mails: narimani-hh@ec.iut.ac.ir and hamed@ee.ucr.edu Abstract--Autonomous demand response (DR) is scalable and has demand response systems in heterogeneous smart grid topologies. Keywords: Autonomous demand response

Mohsenian-Rad, Hamed

385

Climate, extreme heat, and electricity demand in California  

E-Print Network (OSTI)

demand responses to climate change: Methodology and application to the Commonwealth of Massachusetts.

Miller, N.L.

2008-01-01T23:59:59.000Z

386

Construction of a Demand Side Plant with Thermal Energy Storage  

E-Print Network (OSTI)

storage and its potential impact on the electric utilities and introduces the demand side plant concept....

Michel, M.

1989-01-01T23:59:59.000Z

387

Global food demand and the sustainable intensification of agriculture  

Science Journals Connector (OSTI)

...analyzed crop demand (utilization...ZZQQhy2007 per capita real (inflation-adjusted) GDP (Table S1...nut oil, an energy dense commodity...future crop demand that we present...nation the mean per capita crop demands...per capita GDP). Crop Demand...

David Tilman; Christian Balzer; Jason Hill; Belinda L. Befort

2011-01-01T23:59:59.000Z

388

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network (OSTI)

industrial demand response (DR) with energy efficiency (EE) to most effectively use electricity and natural gas

McKane, Aimee T.

2009-01-01T23:59:59.000Z

389

Reducing Energy Demand: What Are the Practical Limits?  

Science Journals Connector (OSTI)

Reducing Energy Demand: What Are the Practical Limits? ... Global demand for energy could be reduced by up to 73% through practical efficiency improvements passive systems, the last technical components in each energy chain. ... This paper aims to draw attention to the opportunity for major reduction in energy demand, by presenting an analysis of how much of current global energy demand could be avoided. ...

Jonathan M. Cullen; Julian M. Allwood; Edward H. Borgstein

2011-01-12T23:59:59.000Z

390

AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.  

E-Print Network (OSTI)

AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

Povinelli, Richard J.

391

Market and Policy Barriers for Demand Response Providing Ancillary Services in U.S. Markets  

E-Print Network (OSTI)

Wholesale Electricity Demand Response Program Comparison,J. (2009) Open Automated Demand Response Communicationsin Demand Response for Wholesale Ancillary Services.

Cappers, Peter

2014-01-01T23:59:59.000Z

392

A Cooperative Demand Response Scheme UsingPunishment Mechanism and Application to IndustrialRefrigerated Warehouses  

E-Print Network (OSTI)

Garcia, Autonomous demand-side management based on game-and D. Dietrich, Demand side management: Demand re- sponse,

Ma, Kai; Hu, Guoqiang; Spanos, Costas J

2014-01-01T23:59:59.000Z

393

E-Print Network 3.0 - actuales relacionadas con Sample Search...  

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

for: actuales relacionadas con Page: << < 1 2 3 4 5 > >> 1 Departamento de Fsica (EPS) Universidad Carlos III de Madrid Summary: fsica relacionada con la implosin de los...

394

E-Print Network 3.0 - actuales clasificaciones del Sample Search...  

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

Collection: Mathematics 30 MTODO DE CENSO Y ESTIMA DE POBLACIN DEL PINZN AZUL DE GRAN CANARIA Summary: distribucin actual de la especie en Inagua, Ojeda y Pajonales. El...

395

E-Print Network 3.0 - actuales del sector Sample Search Results  

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

Collection: Engineering 60 MTODO DE CENSO Y ESTIMA DE POBLACIN DEL PINZN AZUL DE GRAN CANARIA Summary: distribucin actual de la especie en Inagua, Ojeda y Pajonales. El...

396

Data centres power profile selecting policies for Demand Response: Insights of Green Supply Demand Agreement  

Science Journals Connector (OSTI)

Abstract Demand Response mechanisms serve to preserve the stability of the power grid by shedding the electricity load of the consumers during power shortage situations in order to match power generation to demand. Data centres have been identified as excellent candidates to participate in such mechanisms. Recently a novel supply demand agreement have been proposed to foster power adaptation collaboration between energy provider and data centres. In this paper, we analyse the contractual terms of this agreement by proposing and studying different data centres power profile selecting policies. To this end, we setup a discrete event simulation and analysed the power grids state of a German energy provider. We believe that our analysis provides insight and knowledge for any energy utility in setting up the corresponding demand supply agreements.

Robert Basmadjian; Lukas Mller; Hermann De Meer

2015-01-01T23:59:59.000Z

397

Managing Energy Demand With Standards and Information  

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

Managing Energy Demand With Standards and Information Managing Energy Demand With Standards and Information Speaker(s): Sebastien Houde Date: September 13, 2012 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Christopher Payne The goal of this talk is to discuss two interrelated research projects that aim to assess the welfare effects of energy policies that rely on standards and information. The first project focuses on the Energy Star certification program. Using unique micro-data on the US refrigerator market, I first show that consumers respond to certification in different ways. Some consumers appear to rely heavily on Energy Star and pay little attention to electricity costs, others are the reverse, and still others appear to be insensitive to both electricity costs and Energy Star. I then develop a

398

Is Demand-Side Management Economically Justified?  

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

7 7 Is Demand-Side Management Economically Justified? With billions of dollars being spent on demand-side management programs in the U.S. every year, the rationale for and performance of these programs are coming under increasing scrutiny. Three projects in the Energy Analysis Program are making significant contributions to the DSM debate. *Total Resource Cost Test Ratio = ratio of utility avoided costs (i.e., benefits) divided by total cost of program (i.e., Administrative Cost + Incentive Cost + Consumer Cost) In May, Joe Eto, Ed Vine, Leslie Shown, Chris Payne, and I released the first in a series of reports we authored from the Database on Energy Efficiency Programs (DEEP) project. The objective of DEEP is to document the measured cost and performance of utility-sponsored energy-efficiency

399

System Demand-Side Management: Regional results  

SciTech Connect

To improve the Bonneville Power Administration's (Bonneville's) ability to analyze the value and impacts of demand-side programs, Pacific Northwest Laboratory (PNL) developed and implemented the System Demand-Side Management (SDSM) model, a microcomputer-based model of the Pacific Northwest Public Power system. This document outlines the development and application of the SDSM model, which is an hourly model. Hourly analysis makes it possible to examine the change in marginal revenues and marginal costs that accrue from the movement of energy consumption from daytime to nighttime. It also allows a more insightful analysis of programs such as water heater control in the context of hydroelectric-based generation system. 7 refs., 10 figs., 10 tabs.

Englin, J.E.; Sands, R.D.; De Steese, J.G.; Marsh, S.J.

1990-05-01T23:59:59.000Z

400

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

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

What is a High Electric Demand Day?  

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

This presentation by T. McNevin of the New Jersey Bureau of Air Quality Planning was part of the July 2008 Webcast sponsored by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Weatherization and Intergovernmental Program Clean Energy and Air Quality Integration Initiative that was titled Role of Energy Efficiency and Renewable Energy in Improving Air Quality and Addressing Greenhouse Gas Reduction Goals on High Electric Demand Days.

402

Only tough choices in Meeting growing demand  

SciTech Connect

U.S. electricity demand is not growing very fast by international or historical standards. Yet meeting this relatively modest growth is proving difficult because investment in new capacity is expected to grow at an even slower pace. What is more worrisome is that a confluence of factors has added considerable uncertainties, making the investment community less willing to make the long-term commitments that will be needed during the coming decade.

NONE

2007-12-15T23:59:59.000Z

403

ERCOT's Weather Sensitive Demand Response Pilot  

E-Print Network (OSTI)

ERCOTs Weather Sensitive Demand Response Pilot CATEE 12-17-13 ESL-KT-13-12-21 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 Disclaimer The information contained in this report has been obtained from... Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 Weather Sensitive Loads Pilot CATEE 121313 - Tim Carter 713-646-5476 tim.carter@constellation.com4 Constellation's Integrated Power Products 2013. Constellation Energy Resources, LLC...

Carter, T.

2013-01-01T23:59:59.000Z

404

Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California  

E-Print Network (OSTI)

in significant energy and demand savings for refrigeratedbe modified to reduce energy demand during demand responsein refrigerated warehouse energy demand if they are not

Lekov, Alex

2009-01-01T23:59:59.000Z

405

Chinese Oil Demand: Steep Incline Ahead  

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

Chinese Oil Demand: Chinese Oil Demand: Steep Incline Ahead Malcolm Shealy Alacritas, Inc. April 7, 2008 Oil Demand: China, India, Japan, South Korea 0 2 4 6 8 1995 2000 2005 2010 Million Barrels/Day China South Korea Japan India IEA China Oil Forecast 0 2 4 6 8 10 12 14 16 18 2000 2005 2010 2015 2020 2025 2030 Million Barrels/Day WEO 2007 16.3 mbd 12.7 mbd IEA China Oil Forecasts 0 2 4 6 8 10 12 14 16 18 2000 2005 2010 2015 2020 2025 2030 Million Barrels/Day WEO 2007 WEO 2006 WEO 2004 WEO 2002 Vehicle Sales in China 0 2 4 6 8 10 1990 1995 2000 2005 2010 Million Vehicles/Year Vehicle Registrations in China 0 10 20 30 40 50 1990 1995 2000 2005 2010 Million Vehicles/Year Vehicle Density vs GDP per Capita 0 20 40 60 80 100 120 140 160 180 200 0 4,000 8,000 12,000 16,000 GDP per capita, 2005$ PPP Vehicles per thousand people Taiwan South Korea China Vehicle Density vs GDP per Capita

406

A hybrid inventory management system respondingto regular demand and surge demand  

SciTech Connect

This paper proposes a hybrid policy for a stochastic inventory system facing regular demand and surge demand. The combination of two different demand patterns can be observed in many areas, such as healthcare inventory and humanitarian supply chain management. The surge demand has a lower arrival rate but higher demand volume per arrival. The solution approach proposed in this paper incorporates the level crossing method and mixed integer programming technique to optimize the hybrid inventory policy with both regular orders and emergency orders. The level crossing method is applied to obtain the equilibrium distributions of inventory levels under a given policy. The model is further transformed into a mixed integer program to identify an optimal hybrid policy. A sensitivity analysis is conducted to investigate the impact of parameters on the optimal inventory policy and minimum cost. Numerical results clearly show the benefit of using the proposed hybrid inventory model. The model and solution approach could help healthcare providers or humanitarian logistics providers in managing their emergency supplies in responding to surge demands.

Mohammad S. Roni; Mingzhou Jin; Sandra D. Eksioglu

2014-06-01T23:59:59.000Z

407

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

SciTech Connect

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

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

2008-01-01T23:59:59.000Z

408

Building Energy Software Tools Directory: Demand Response Quick Assessment  

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

Demand Response Quick Assessment Tool Demand Response Quick Assessment Tool Demand response quick assessment tool image The opportunities for demand reduction and cost savings with building demand responsive controls vary tremendously with building type and location. This assessment tool will predict the energy and demand savings, the economic savings, and the thermal comfort impact for various demand responsive strategies. Users of the tool will be asked to enter the basic building information such as types, square footage, building envelope, orientation, utility schedule, etc. The assessment tool will then use the prototypical simulation models to calculate the energy and demand reduction potential under certain demand responsive strategies, such as precooling, zonal temperature set up, and chilled water loop and air loop set points

409

LNG demand, shipping will expand through 2010  

SciTech Connect

The 1990s, especially the middle years, have witnessed a dramatic turnaround in the growth of liquefied-natural-gas demand which has tracked equally strong natural-gas demand growth. This trend was underscored late last year by several annual studies of world LNG demand and shipping. As 1998 began, however, economic turmoil in Asian financial markets has clouded near-term prospects for LNG in particular and all energy in general. But the extent of damage to energy markets is so far unclear. A study by US-based Institute of Gas Technology, Des Plaines, IL, reveals that LNG imports worldwide have climbed nearly 8%/year since 1980 and account for 25% of all natural gas traded internationally. In the mid-1970s, the share was only 5%. In 1996, the most recent year for which complete data are available, world LNG trade rose 7.7% to a record 92 billion cu m, outpacing the overall consumption for natural gas which increased 4.7% in 1996. By 2015, says the IGT study, natural-gas use would surpass coal as the world`s second most widely used fuel, after petroleum. Much of this growth will occur in the developing countries of Asia where gas use, before the current economic crisis began, was projected to grow 8%/year through 2015. Similar trends are reflected in another study of LNG trade released at year end 1997, this from Ocean Shipping Consultants Ltd., Surrey, U.K. The study was done too early, however, to consider the effects of the financial problems roiling Asia.

True, W.R.

1998-02-09T23:59:59.000Z

410

Barrier Immune Radio Communications for Demand Response  

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

94E 94E Barrier Immune Radio Communications for Demand Response F. Rubinstein, G. Ghatikar, J. Granderson, D. Watson Lawrence Berkeley National Laboratory P. Haugen, C. Romero Lawrence Livermore National Laboratory February 2009 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, apparatus, product, or process disclosed, or represents that its use would not infringe

411

Gasoline demand in developing Asian countries  

SciTech Connect

This paper presents econometric estimates of motor gasoline demand in eleven developing countries of Asia. The price and GDP per capita elasticities are estimated for each country separately, and for several pooled combinations of the countries. The estimated elasticities for the Asian countries are compared with those of the OECD countries. Generally, one finds that the OECD countries have GDP elasticities that are smaller, and price elasticities that are larger (in absolute value). The price elasticities for the low-income Asian countries are more inelastic than for the middle-income Asian countries, and the GDP elasticities are generally more elastic. 13 refs., 6 tabs.

McRae, R. [Univ. of Calgary, Alberta (Canada)

1994-12-31T23:59:59.000Z

412

Demand Controlled Filtration in an Industrial Cleanroom  

SciTech Connect

In an industrial cleanroom, significant energy savings were realized by implementing two types of demand controlled filtration (DCF) strategies, one based on particle counts and one on occupancy. With each strategy the speed of the recirculation fan filter units was reduced to save energy. When the control was based on particle counts, the energy use was 60% of the baseline configuration of continuous fan operation. With simple occupancy sensors, the energy usage was 63% of the baseline configuration. During the testing of DCF, no complaints were registered by the operator of the cleanroom concerning processes and products being affected by the DCF implementation.

Faulkner, David; DiBartolomeo, Dennis; Wang, Duo

2007-09-01T23:59:59.000Z

413

Modeling supermarket refrigeration energy use and demand  

SciTech Connect

A computer model has been developed that can predict the performance of supermarket refrigeration equipment to within 3% of field test measurements. The Supermarket Refrigeration Energy Use and Demand Model has been used to simulate currently available refrigerants R-12, R-502 and R-22, and is being further developed to address alternative refrigerants. This paper reports that the model is expected to be important in the design, selection and operation of cost-effective, high-efficiency refrigeration systems. It can profile the operation and performance of different types of compressors, condensors, refrigerants and display cases. It can also simulate the effects of store humidity and temperature on display cases; the efficiency of various floating head pressure setpoints, defrost alternatives and subcooling methods; the efficiency and amount of heat reclaim from refrigeration systems; and the influence of other variables such as store lighting and building design. It can also be used to evaluate operational strategies such as variable-speed drive or cylinder unloading for capacity control. Development of the model began in 1986 as part of a major effort, sponsored by the U.S. electric utility industry, to evaluate energy performance of then conventional single compressor and state-of-the-art multiplex refrigeration systems, and to characterize the contribution of a variety of technology enhancement features on system energy use and demand.

Blatt, M.H.; Khattar, M.K. (Electric Power Research Inst., Palo Alto, CA (US)); Walker, D.H. (Foster Miller Inc., Waltham, MA (US))

1991-07-01T23:59:59.000Z

414

Optimal Demand Response with Energy Storage Management  

E-Print Network (OSTI)

In this paper, we consider the problem of optimal demand response and energy storage management for a power consuming entity. The entity's objective is to find an optimal control policy for deciding how much load to consume, how much power to purchase from/sell to the power grid, and how to use the finite capacity energy storage device and renewable energy, to minimize his average cost, being the disutility due to load- shedding and cost for purchasing power. Due to the coupling effect of the finite size energy storage, such problems are challenging and are typically tackled using dynamic programming, which is often complex in computation and requires substantial statistical information of the system dynamics. We instead develop a low-complexity algorithm called Demand Response with Energy Storage Management (DR-ESM). DR-ESM does not require any statistical knowledge of the system dynamics, including the renewable energy and the power prices. It only requires the entity to solve a small convex optimization pr...

Huang, Longbo; Ramchandran, Kannan

2012-01-01T23:59:59.000Z

415

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

these trends lead to declining natural gas consumption byNatural gas demand has been rising in California and this trendnatural gas demands regionally, to account for variability in energy usage trends

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

2008-01-01T23:59:59.000Z

416

Strategic dynamic vehicle routing with spatio-temporal dependent demands  

E-Print Network (OSTI)

Dynamic vehicle routing problems address the issue of determining optimal routes for a set of vehicles, to serve a given set of demands that arrive sequentially in time. Traditionally, demands are assumed to be generated ...

Feijer, Diego (Diego Francisco Feijer Rovira)

2011-01-01T23:59:59.000Z

417

Demand Response Analysis in Smart Grids Using Fuzzy Clustering Model  

Science Journals Connector (OSTI)

This paper focuses on an analysis of demand response in a smart grid context, presenting the ... A fuzzy subtractive clustering method is applied to demand response on several domestic consumption scenarios and r...

R. Pereira; A. Fagundes; R. Melcio

2013-01-01T23:59:59.000Z

418

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.

419

Quantifying the Variable Effects of Systems with Demand Response Resources  

E-Print Network (OSTI)

Quantifying the Variable Effects of Systems with Demand Response Resources Anupama Kowli and George in the electricity industry. In particular, there is a new class of consumers, called demand response resources (DRRs

Gross, George

420

Software components for demand side integration at a container terminal  

Science Journals Connector (OSTI)

Local energy management and demand response are established methods to raise energy ... in industrial enterprises the intelligent use of power demand draws significantly increased importance. Due to the ... energ...

Norman Ihle; Serge Runge; Claas Meyer-Barlag

2014-11-01T23:59:59.000Z

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

Research on the Demand Side Management Under Smart Grid  

Science Journals Connector (OSTI)

From the 1970 of the twentieth century demand side management has gradually become standardized management mode in electric power industry in developed ... coverage, full collection, full prepayment to demand-side

Litong Dong; Jun Xu; Haibo Liu; Ying Guo

2014-01-01T23:59:59.000Z

422

Enhanced Oil Recovery to Fuel Future Oil Demands | GE Global...  

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

to Fuel Future Oil Demands Enhanced Oil Recovery to Fuel Future Oil Demands Trevor Kirsten 2013.10.02 I'm Trevor Kirsten and I lead a team of GE researchers that investigate a...

423

The Energy Demand Forecasting System of the National Energy Board  

Science Journals Connector (OSTI)

This paper presents the National Energy Boards long term energy demand forecasting model in its present state of ... results of recent research at the NEB. Energy demand forecasts developed with the aid of this....

R. A. Preece; L. B. Harsanyi; H. M. Webster

1980-01-01T23:59:59.000Z

424

Competitive Technologies, Equipment Vintages and the Demand for Energy  

Science Journals Connector (OSTI)

Macroeconometric modelling of energy demand resorts to two approaches leading to models ... of view. The first approach specifies the demand of a group of consumers for a single form of energy, independent of the...

F. Carlevaro

1988-01-01T23:59:59.000Z

425

Forecasting Energy Demand Using Fuzzy Seasonal Time Series  

Science Journals Connector (OSTI)

Demand side energy management has become an important issue for energy management. In order to support energy planning and policy decisions forecasting the future demand is very important. Thus, forecasting the f...

?Irem Ual Sar?; Basar ztaysi

2012-01-01T23:59:59.000Z

426

Indianapolis Offers a Lesson on Driving Demand | Department of...  

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

Indianapolis Offers a Lesson on Driving Demand Indianapolis Offers a Lesson on Driving Demand The flier for EcoHouse, with the headline 'Save energy, save money, improve your home'...

427

Examining Synergies between Energy Management and Demand Response: A Case Study at Two California Industrial Facilities  

E-Print Network (OSTI)

and Demand Response History Energy Management Activities o #and Demand Response History Energy Management Activities

Olsen, Daniel

2013-01-01T23:59:59.000Z

428

Analytical Frameworks to Incorporate Demand Response in Long-term Resource Planning  

E-Print Network (OSTI)

management system demand-side management energy efficiencyresource plans and demand side management (DSM) program

Satchwell, Andrew

2014-01-01T23:59:59.000Z

429

Analysis of order-up-to-level inventory systems with compound Poisson demand  

Science Journals Connector (OSTI)

We analyse a single echelon single item inventory system where the demand and the lead time are stochastic. Demand is modelled as a compound Poisson process and the stock is controlled according to a continuous time order-up-to (OUT) level policy. We propose a method for determining the optimal OUT level for cost oriented inventory systems where unfilled demands are backordered. We first establish an analytical characterization of the optimal OUT level. The actual calculation is based on a numerical procedure the accuracy of which can be set as highly as desired. By means of a numerical investigation, we show that the method is very efficient in calculating the optimal OUT level. We compare our results with those obtained using an approximation proposed in the literature and we show that there is a significant difference in accuracy for slow moving items. Our work allows insights to be gained on stock control related issues for both fast and slow moving Stock Keeping Units (SKUs).

M.Z. Babai; Z. Jemai; Y. Dallery

2011-01-01T23:59:59.000Z

430

Demand or No Demand: Electrical Rates for Standard 90.1-2010  

SciTech Connect

ASHRAE is developing the 2010 version of Standard 90.1 with the goal of reaching 30% savings beyond the 2004 edition of the standard. Economics are used to inform the process of setting criteria and the assumed electricity rates are crucial to these calculations. Previously the committee used national average electrical rates in the criteria setting but recently a number of voices have been heard in support of using demand rates instead. This article explores the issues surrounding the use of a pure consumption rate vs. the use of demand rates and looks at the implications for HVAC equipment efficiency.

Jarnagin, Ronald E.; McBride, Merle F.; Trueman, Cedric; Liesen, Richard J.

2008-04-30T23:59:59.000Z

431

Micro-Based Estimatesof Demand Functions for Local School Expenditures  

E-Print Network (OSTI)

demand functions from individual qualitative responses to a survey. This leads to estimates of income and price elasticities

Bergstrom, Ted; Rubinfeld, Daniel L.; Shapiro, Perry

1982-01-01T23:59:59.000Z

432

Maintaining Privacy in Data Rich Demand Response Applications  

Science Journals Connector (OSTI)

The paper introduces the privacy problem of demand response applications performed with the OpenADR standard. A...

Markus Karwe; Jens Strker

2013-01-01T23:59:59.000Z

433

The Important Participants in Demand-Side Management: Power Consumers  

Science Journals Connector (OSTI)

Electric power consumers are the basis for demand-side management (DSM) practice. Increased power consumption efficiency...

Zhaoguang Hu; Xinyang Han; Quan Wen

2013-01-01T23:59:59.000Z

434

An Integrated Architecture for Demand Response Communications and Control  

E-Print Network (OSTI)

An Integrated Architecture for Demand Response Communications and Control Michael LeMay, Rajesh for the MGA and ZigBee wireless communications. Index Terms Demand Response, Advanced Meter Infrastructure. In principle this can be done with demand response techniques in which electricity users take measures

Gross, George

435

Factors Influencing Productivity and Operating Cost of Demand Responsive Transit  

E-Print Network (OSTI)

Factors Influencing Productivity and Operating Cost of Demand Responsive Transit Kurt Palmer Maged of the Americans with Disabilities Act in 1991 operating expenses for Demand Responsive Transit have more than and practices upon productivity and operating cost. ii #12;1 Introduction Demand Responsive Transit (DRT

Dessouky, Maged

436

Application of a Combination Forecasting Model in Logistics Parks' Demand  

Science Journals Connector (OSTI)

Logistics parks demand is an important basis of establishing the development policy of logistics industry and logistics infrastructure for planning. In order to improve the forecast accuracy of logistics parks demand, a combination forecasting ... Keywords: Logistics parks' demand, combine, simulated annealing algorithm, grey forecast model, exponential smoothing method

Chen Qin; Qi Ming

2010-05-01T23:59:59.000Z

437

A First Look at Colocation Demand Response Shaolei Ren  

E-Print Network (OSTI)

A First Look at Colocation Demand Response Shaolei Ren Florida International University Mohammad A. Islam Florida International University ABSTRACT Large data centers can participate in demand response, the existing research has only considered demand response by owner-operated data centers (e.g., Google

Ren, Shaolei

438

Examining Synergies between Energy Management and Demand Response: A  

E-Print Network (OSTI)

LBNL-5719E Examining Synergies between Energy Management and Demand Response: A Case Study at Two Summary #12;Introduction Energy Management · · · · · · · · · · #12;Demand Response #12;#12;Bentley Prince-Project Personnel Changes #12;Enablement of Demand Response Capabilities due to Energy Management Improvement

439

Retrofitting Existing Buildings for Demand Response & Energy Efficiency  

E-Print Network (OSTI)

Retrofitting Existing Buildings for Demand Response & Energy Efficiency www, enable demand response, improve productivity for older facilities. - Use technologies which minimize are notified by PG&E by 3pm the day prior to the critical event. - Customers with Auto-Demand Response enabled

California at Los Angeles, University of

440

Assessing the Control Systems Capacity for Demand Response in  

E-Print Network (OSTI)

LBNL-5319E Assessing the Control Systems Capacity for Demand Response in California Industries in this report was coordinated by the Demand Response Research Center and funded by the California Energy of the Demand Response Research Center Industrial Controls Experts Working Group: · Jim Filanc, Southern

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441

Optimal Power Flow Based Demand Response Offer Price Optimization  

E-Print Network (OSTI)

Optimal Power Flow Based Demand Response Offer Price Optimization Zhen Qiu 1 Introduction-time energy balance. Demand response programs are offered by the utility companies to reduce the load response cost in exchange for load reduction. A considerable amount of papers have discussed the demand

Lavaei, Javad

442

A Successful Implementation with the Smart Grid: Demand Response Resources  

E-Print Network (OSTI)

1 A Successful Implementation with the Smart Grid: Demand Response Resources Contribution of intelligent line switching, demand response resources (DRRs), FACTS devices and PMUs is key in the smart grid events as a result of voluntary load curtailments. Index Terms--Electricity Markets, Demand Response re

Gross, George

443

Optimal demand response: problem formulation and deterministic case  

E-Print Network (OSTI)

Optimal demand response: problem formulation and deterministic case Lijun Chen, Na Li, Libin Jiang load through real-time demand response and purchases balancing power on the spot market to meet, optimal demand response reduces to joint scheduling of the procurement and consumption decisions

Low, Steven H.

444

Ris-R-1565(EN) Analyses of Demand Response  

E-Print Network (OSTI)

Risø-R-1565(EN) Analyses of Demand Response in Denmark Frits Møller Andersen Stine Grenaa Jensen. Larsen, Peter Meibom, Hans Ravn, Klaus Skytte, Mikael Togeby Title: Analyses of Demand Response and security of supply, the report describes demand response from a microeconomic perspective and provides

445

Optimal Demand Response Based on Utility Maximization in Power Networks  

E-Print Network (OSTI)

Optimal Demand Response Based on Utility Maximization in Power Networks Na Li, Lijun Chen different appliances including PHEVs and batteries and propose a demand response approach based on utility. The utility company can thus use dynamic pricing to coordinate demand responses to the benefit of the overall

Low, Steven H.

446

Date: June 12, 2007 To: Pacific Northwest Demand Response Project  

E-Print Network (OSTI)

Date: June 12, 2007 To: Pacific Northwest Demand Response Project From: Rich Sedano/RAP and Chuck, 2007 meeting of the Pacific Northwest Demand Response Project, we agreed to form three Working Groups for the evaluation of cost-effectiveness of Demand Response resources. One potential outcome would be for state

447

Examining Uncertainty in Demand Response Baseline Models and  

E-Print Network (OSTI)

LBNL-5096E Examining Uncertainty in Demand Response Baseline Models and Variability in Automated of California. #12;Examining Uncertainty in Demand Response Baseline Models and Variability in Automated.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR

448

Graphical language for identification of control strategies allowing Demand Response  

E-Print Network (OSTI)

Graphical language for identification of control strategies allowing Demand Response David DA SILVA. This will allow the identification of the electric appliance availability for demand response control strategies to be implemented in terms of demand response for electrical appliances. Introduction An important part

Paris-Sud XI, Université de

449

Demand Response Providing Ancillary A Comparison of Opportunities and  

E-Print Network (OSTI)

LBNL-5958E Demand Response Providing Ancillary Services A Comparison of Opportunities Government or any agency thereof or The Regents of the University of California. #12;Demand Response System Reliability, Demand Response (DR), Electricity Markets, Smart Grid Abstract Interest in using

450

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

451

Nordic TSOs' Action Plans in enhancing and monitoring Demand Response  

E-Print Network (OSTI)

Nordic TSOs' Action Plans in enhancing and monitoring Demand Response Nordel Market Committee.............................................................................................. 3 2. TSOS' ROLE IN ENHANCING DEMAND RESPONSE.............................. 3 3. ACTIONS TO ENSURE improvment ­ activate the energy efficiency actors 13 5. SYSTEMATIC MONITORING OF REALISED DEMAND RESPONSE 13

452

Optimal Demand Response Capacity of Automatic Lighting Control  

E-Print Network (OSTI)

1 Optimal Demand Response Capacity of Automatic Lighting Control Seyed Ataollah Raziei and Hamed-mails: razieis1@udayton.edu and hamed@ee.ucr.edu Abstract--Demand response programs seek to ad- just the normal prior studies have extensively studied the capacity of offering demand response in buildings

Mohsenian-Rad, Hamed

453

Towards Continuous Policy-driven Demand Response in Data Centers  

E-Print Network (OSTI)

Towards Continuous Policy-driven Demand Response in Data Centers David Irwin, Navin Sharma, and Prashant Shenoy University of Massachusetts, Amherst {irwin,nksharma,shenoy}@cs.umass.edu ABSTRACT Demand response (DR) is a technique for balancing electricity sup- ply and demand by regulating power consumption

Shenoy, Prashant

454

Opportunities for Demand Response in California Agricultural Irrigation: A  

E-Print Network (OSTI)

LBNL-6108E Opportunities for Demand Response in California Agricultural Irrigation: A Scoping Study was sponsored in part by the Demand Response Research Center which is funded by the California .................................. 2 Best Opportunities for Demand Response and Permanent Load Shifting Programs.............. 3

455

EnerNOC Inc. Commercial & Industrial Demand Response  

E-Print Network (OSTI)

© EnerNOC Inc. Commercial & Industrial Demand Response: An Overview of the Utility/Aggregator Business Model Pacific Northwest Demand Response Project April 28, 2011 #12;22 Agenda Introduction Ener #12;77 Whos EnerNOC? Market Leader in C&I Demand Response and Industrial Energy Efficiency More than

456

Fast Automated Demand Response to Enable the Integration of Renewable  

E-Print Network (OSTI)

LBNL-5555E Fast Automated Demand Response to Enable the Integration of Renewable Resources David S The work described in this report was coordinated by the Demand Response Research Center and funded ABSTRACT This study examines how fast automated demand response (AutoDR) can help mitigate grid balancing

457

Two Market Models for Demand Response in Power Networks  

E-Print Network (OSTI)

Two Market Models for Demand Response in Power Networks Lijun Chen, Na Li, Steven H. Low and John C-- In this paper, we consider two abstract market models for designing demand response to match power supply as oligopolistic markets, and propose distributed demand response algorithms to achieve the equilibria. The models

Low, Steven H.

458

Value of Demand Response Theoretical thoughts Klaus Skytte  

E-Print Network (OSTI)

Value of Demand Response ­ Theoretical thoughts Klaus Skytte Systems Analysis Department February 7 A B C MB C' B' DR q'load CP #12;Innovative tariffs · Intelligent demand response · Energy tariffs if the consumers are price elastic. · The value of DR also depends on the fuel and supply mix · Intelligent demand

459

Opportunities, Barriers and Actions for Industrial Demand Response in  

E-Print Network (OSTI)

LBNL-1335E Opportunities, Barriers and Actions for Industrial Demand Response in California A.T. Mc of Global Energy Partners. This work described in this report was coordinated by the Demand Response Demand Response in California. PIER Industrial/Agricultural/Water EndUse Energy Efficiency Program. CEC

460

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

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they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Demand forecasting for multiple slow-moving items with short requests history and unequal demand variance  

Science Journals Connector (OSTI)

Modeling the lead-time demand for the multiple slow-moving inventory items in the case when the available requests history is very short is a challenge for inventory management. The classical forecasting technique, which is based on the aggregation of the stock keeping units to overcome the mentioned historical data peculiarity, is known to lead to very poor performance in many cases important for industrial applications. An alternative approach to the demand forecasting for the considered problem is based on the Bayesian paradigm, when the initially developed population-averaged demand probability distribution is modified for each item using its specific requests history. This paper follows this approach and presents a new model, which relies on the beta distribution as a prior for the request probability, and allows to account for disparity in variance of demand between different stock keeping units. To estimate the model parameters, a special computationally effective technique based on the generalized method of moments is developed. Simulation results indicate the superiority of the proposed model over the known ones, while the computational burden does not increase.

Alexandre Dolgui; Maksim Pashkevich

2008-01-01T23:59:59.000Z

462

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.

463

XAFS Study of Phase-Change Recording Material Using Actual Media  

Science Journals Connector (OSTI)

The influence of the interface layer to the local structure for atomic arrangement of a GeBiTe phase-change material was investigated by using XAFS on the actual rewritable HD DVD...

Nakai, Tsukasa; Yoshiki, Masahiko; Satoh, Yasuhiro

464

E-Print Network 3.0 - actual del ultrasonido Sample Search Results  

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Summary: : evolucin histrica y situacin actual. 8 l) Evaluacin de la capacidad de carga del Parque para los... Proyectos A lo largo del ao 2010 han estado vigentes 85...

465

E-Print Network 3.0 - anciano consideraciones actuales Sample...  

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mitigacin de los efectos del cambio climtico y con... polticas De proseguir las emisiones de GEI a una tasa igual o superior a la actual, el calentamiento Source: Binette,...

466

E-Print Network 3.0 - actual terrestrial rabies Sample Search...  

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and Information Sciences 56 innovati nNREL Advances a Unique Crystalline Silicon Solar Cell Summary: actually begins at another of the U.S. Department of Energy (DOE)...

467

E-Print Network 3.0 - actual del huemul Sample Search Results  

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and Information Sciences 88 MTODO DE CENSO Y ESTIMA DE POBLACIN DEL PINZN AZUL DE GRAN CANARIA Summary: distribucin actual de la especie en Inagua, Ojeda y Pajonales. El...

468

E-Print Network 3.0 - actual del franciscanismo Sample Search...  

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and Information Sciences 75 MTODO DE CENSO Y ESTIMA DE POBLACIN DEL PINZN AZUL DE GRAN CANARIA Summary: distribucin actual de la especie en Inagua, Ojeda y Pajonales. El...

469

E-Print Network 3.0 - actual del control Sample Search Results  

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and Information Sciences 30 MTODO DE CENSO Y ESTIMA DE POBLACIN DEL PINZN AZUL DE GRAN CANARIA Summary: distribucin actual de la especie en Inagua, Ojeda y Pajonales. El...

470

E-Print Network 3.0 - actual del tabaquismo Sample Search Results  

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and Information Sciences 91 MTODO DE CENSO Y ESTIMA DE POBLACIN DEL PINZN AZUL DE GRAN CANARIA Summary: distribucin actual de la especie en Inagua, Ojeda y Pajonales. El...

471

E-Print Network 3.0 - actual del no-acceso Sample Search Results  

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and Information Sciences 73 MTODO DE CENSO Y ESTIMA DE POBLACIN DEL PINZN AZUL DE GRAN CANARIA Summary: distribucin actual de la especie en Inagua, Ojeda y Pajonales. El...

472

E-Print Network 3.0 - actual del rabdomiosarcoma Sample Search...  

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and Information Sciences 74 MTODO DE CENSO Y ESTIMA DE POBLACIN DEL PINZN AZUL DE GRAN CANARIA Summary: distribucin actual de la especie en Inagua, Ojeda y Pajonales. El...

473

E-Print Network 3.0 - actual del estreptococo Sample Search Results  

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and Information Sciences 80 MTODO DE CENSO Y ESTIMA DE POBLACIN DEL PINZN AZUL DE GRAN CANARIA Summary: distribucin actual de la especie en Inagua, Ojeda y Pajonales. El...

474

Driving Demand for Home Energy Improvements  

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

Driving Demand for Home Energy Improvements Driving Demand for Home Energy Improvements Title Driving Demand for Home Energy Improvements Publication Type Report Year of Publication 2010 Authors Fuller, Merrian C., Cathy Kunkel, Mark Zimring, Ian M. Hoffman, Katie L. Soroye, and Charles A. Goldman Tertiary Authors Borgeson, Merrian Pagination 136 Date Published 09/2010 Publisher LBNL City Berkeley Keywords electricity markets and policy group, energy analysis and environmental impacts department Abstract Policy makers and program designers in the U.S. and abroad are deeply concerned with the question of how to scale up energy efficiency to a level that is commensurate both to the energy and climate challenges we face, and to the potential for energy savings that has been touted for decades. When policy makers ask what energy efficiency can do, the answers usually revolve around the technical and economic potential of energy efficiency-they rarely hone in on the element of energy demand that matters most for changing energy usage in existing homes: the consumer. A growing literature is concerned with the behavioral underpinnings of energy consumption. We examine a narrower, related subject: How can millions of Americans be persuaded to divert valued time and resources into upgrading their homes to eliminate energy waste, avoid high utility bills, and spur the economy? With hundreds of millions of public dollars1 flowing into incentives, workforce training, and other initiatives to support comprehensive home energy improvements2, it makes sense to review the history of these programs and begin gleaning best practices for encouraging comprehensive home energy improvements. Looking across 30 years of energy efficiency programs that targeted the residential market, many of the same issues that confronted past program administrators are relevant today: How do we cost-effectively motivate customers to take action? Who can we partner with to increase program participation? How do we get residential efficiency programs to scale? While there is no proven formula-and only limited success to date with reliably motivating large numbers of Americans to invest in comprehensive home energy improvements, especially if they are being asked to pay for a majority of the improvement costs-there is a rich and varied history of experiences that new programs can draw upon. Our primary audiences are policy makers and program designers-especially those that are relatively new to the field, such as the over 2,000 towns, cities, states, and regions who are recipients of American Reinvestment and Recovery Act funds for clean energy programs. This report synthesizes lessons from first generation programs, highlights emerging best practices, and suggests methods and approaches to use in designing, implementing, and evaluating these programs. We examined 14 residential energy efficiency programs, conducted an extensive literature review, interviewed industry experts, and surveyed residential contractors to draw out these lessons.

475

Retail Demand Response in Southwest Power Pool  

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

LBNL-1470E LBNL-1470E Retail Demand Response in Southwest Power Pool Ranjit Bharvirkar, Grayson Heffner and Charles Goldman Lawrence Berkeley National Laboratory Environmental Energy Technologies Division January 2009 The work described in this report was funded by the Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY 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

476

Coordination of Energy Efficiency and Demand Response  

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044E 044E ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Coordination of Energy Efficiency and Demand Response Charles Goldman, Michael Reid, Roger Levy and Alison Silverstein Environmental Energy Technologies Division January 2010 The work described in this report was funded by the Department of Energy Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the U.S. Department of Energy under Contract No. DE-AC02- 05CH11231. 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

477

Math 115 Excel Group Project 3 Worksheet Price Elasticity of Demand: U.S. Demand for Gasoline  

E-Print Network (OSTI)

Math 115 Excel Group Project 3 Worksheet Price Elasticity of Demand: U.S. Demand for Gasoline 1 for Gasoline 2 4. Consider the two price-demand graphs below. The labels give the x-value. Which graph for Gasoline 3 6. Jewelry This quote is from the article "Americans Snap Up Gold Jewelry as Metal's Price Sinks

Newberger, Florence

478

Unlocking the potential for efficiency and demand response through advanced  

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

Unlocking the potential for efficiency and demand response through advanced Unlocking the potential for efficiency and demand response through advanced metering Title Unlocking the potential for efficiency and demand response through advanced metering Publication Type Conference Paper LBNL Report Number LBNL-55673 Year of Publication 2004 Authors Levy, Roger, Karen Herter, and John Wilson Conference Name 2004 ACEEE Summer Study on Energy Efficiency in Buildings Date Published 06/2004 Publisher ACEEE Conference Location Pacific Grove, CA Call Number California Energy Commission Keywords demand response, demand response and distributed energy resources center, demand response research center, energy efficiency demand response advanced metering, rate programs & tariffs Abstract Reliance on the standard cumulative kilowatt-hour meter substantially compromises energy efficiency and demand response programs. Without advanced metering, utilities cannot support time-differentiated rates or collect the detailed customer usage information necessary to (1) educate the customer to the economic value of efficiency and demand response options, or (2) distribute load management incentives proportional to customer contribution. These deficiencies prevent the customer feedback mechanisms that would otherwise encourage economically sound demand-side investments and behaviors. Thus, the inability to collect or properly price electricity usage handicaps the success of almost all efficiency and demand response options.

479

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

480

Demand Response - Policy: More Information | Department of Energy  

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

Demand Response - Policy: More Information Demand Response - Policy: More Information Demand Response - Policy: More Information OE's commitment to ensuring non-wires options to modernize the nation's electricity delivery system includes ongoing support of a number of national and regional activities in support of demand response. The New England Demand Response Initiative (NEDRI), OE's initial endeavor to assist states with non-wire solutions, was created to develop a comprehensive, coordinated set of demand response programs for the New England regional power markets. NEDRI's goal was to outline workable market rules, public policies, and regulatory criteria to incorporate customer-based demand response resources into New England's electricity markets and power systems. NEDRI promoted best practices and coordinated

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

FERC Presendation: Demand Response as Power System Resources, October 29,  

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

FERC Presendation: Demand Response as Power System Resources, FERC Presendation: Demand Response as Power System Resources, October 29, 2010 FERC Presendation: Demand Response as Power System Resources, October 29, 2010 Federal Energy Regulatory Commission (FERC) presentation on demand response as power system resources before the Electicity Advisory Committee, October 29, 2010 Demand Response as Power System Resources More Documents & Publications A National Forum on Demand Response: Results on What Remains to Be Done to Achieve Its Potential - Cost-Effectiveness Working Group Loads Providing Ancillary Services: Review of International Experience Benefits of Demand Response in Electricity Markets and Recommendations for Achieving Them. A report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005 (February 2006)

482

GRB 090510: A DISGUISED SHORT GAMMA-RAY BURST WITH THE HIGHEST LORENTZ FACTOR AND CIRCUMBURST MEDIUM  

SciTech Connect

GRB 090510, observed by both Fermi and AGILE satellites, is the first bright short-hard gamma-ray burst (GRB) with an emission from the keV up to the GeV energy range. Within the Fireshell model, we interpret the faint precursor in the light curve as the emission at the transparency of the expanding e {sup +} e {sup -} plasma: the Proper-GRB. From the observed isotropic energy, we assume a total plasma energy E{sup tot}{sub e{sup +}e{sup -}}=(1.10{+-}0.06) Multiplication-Sign 10{sup 53} erg and derive a Baryon load B = (1.45 {+-} 0.28) Multiplication-Sign 10{sup -3} and a Lorentz factor at transparency {Gamma}{sub tr} = (6.7 {+-} 1.6) Multiplication-Sign 10{sup 2}. The main emission {approx}0.4 s after the initial spike is interpreted as the extended afterglow, due to the interaction of the ultrarelativistic baryons with the CircumBurst Medium (CBM). Using the condition of fully radiative regime, we infer a CBM average spherically symmetric density of (n{sub CBM}) = (1.85 {+-} 0.14) Multiplication-Sign 10{sup 3} particles cm{sup -3}, one of the highest found in the Fireshell model. The value of the filling factor, 1.5 Multiplication-Sign 10{sup -10}{<=}R{<=}3.8 Multiplication-Sign 10{sup -8}, leads to the estimate of filaments with densities n{sub fil} = n{sub CBM}/R approx. (10{sup 6}-10{sup 14}) particles cm{sup -3}. The sub-MeV and the MeV emissions are well reproduced. When compared to the canonical GRBs with (n{sub CBM}) Almost-Equal-To 1 particles cm{sup -3} and to the disguised short GRBs with (n{sub CBM}) Almost-Equal-To 10{sup -3} particles cm{sup -3}, the case of GRB 090510 leads to the existence of a new family of bursts exploding in an overdense galactic region with (n{sub CBM}) Almost-Equal-To 10{sup 3} particles cm{sup -3}. The joint effect of the high {Gamma}{sub tr} and the high density compresses in time and 'inflates' in intensity the extended afterglow, making it appear as a short burst, which we here define as a 'disguised short GRB by excess'. The determination of the above parameter values may represent an important step toward the explanation of the GeV emission.

Muccino, M.; Ruffini, R.; Bianco, C. L.; Izzo, L.; Penacchioni, A. V.; Pisani, G. B. [Dip. di Fisica and ICRA, Sapienza Universita di Roma, Piazzale Aldo Moro 5, I-00185 Rome (Italy)

2013-07-20T23:59:59.000Z

483

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

484

Opportunities for Automated Demand Response in Wastewater Treatment  

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

Opportunities for Automated Demand Response in Wastewater Treatment Opportunities for Automated Demand Response in Wastewater Treatment Facilities in California - Southeast Water Pollution Control Plant Case Study Title Opportunities for Automated Demand Response in Wastewater Treatment Facilities in California - Southeast Water Pollution Control Plant Case Study Publication Type Report LBNL Report Number LBNL-6056E Year of Publication 2012 Authors Olsen, Daniel, Sasank Goli, David Faulkner, and Aimee T. McKane Date Published 12/2012 Publisher CEC/LBNL Keywords market sectors, technologies Abstract This report details a study into the demand response potential of a large wastewater treatment facility in San Francisco. Previous research had identified wastewater treatment facilities as good candidates for demand response and automated demand response, and this study was conducted to investigate facility attributes that are conducive to demand response or which hinder its implementation. One years' worth of operational data were collected from the facility's control system, submetered process equipment, utility electricity demand records, and governmental weather stations. These data were analyzed to determine factors which affected facility power demand and demand response capabilities.

485

Rates and technologies for mass-market demand response  

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Rates and technologies for mass-market demand response Rates and technologies for mass-market demand response Title Rates and technologies for mass-market demand response Publication Type Conference Paper LBNL Report Number LBNL-50626 Year of Publication 2002 Authors Herter, Karen, Roger Levy, John Wilson, and Arthur H. Rosenfeld Conference Name 2002 ACEEE Summer Study on Energy Efficiency in Buildings Conference Location Pacific Grove, CA Keywords demand response, demand response and distributed energy resources center, demand response research center, rate programs & tariffs Abstract 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, system-operator controlled, contingency program, and (2) a voluntary, customer controlled, bill management program with rate-based incentives. Any demand response program based on this system could consist of either or both of these components. Ideally, these programs would be bundled, providing automatic load management through customer-programmed price response, plus up to 10 GW of emergency load shedding capability in California. Finally, we discuss options for and barriers to implementation of such a program in California.

486

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

SciTech Connect

The Pacific Gas and Electric Company (PG&E) is conducting a pilot program to investigate the technical feasibility of bidding certain demand response (DR) resources into the California Independent System Operator's (CAISO) day-ahead market for ancillary services nonspinning reserve. Three facilities, a retail store, a local government office building, and a bakery, are recruited into the pilot program. For each facility, hourly demand, and load curtailment potential are forecasted two days ahead and submitted to the CAISO the day before the operation as an available resource. These DR resources are optimized against all other generation resources in the CAISO ancillary service. Each facility is equipped with four-second real time telemetry equipment to ensure resource accountability and visibility to CAISO operators. When CAISO requests DR resources, PG&E's OpenADR (Open Automated DR) communications infrastructure is utilized to deliver DR signals to the facilities energy management and control systems (EMCS). The pre-programmed DR strategies are triggered without a human in the loop. This paper describes the automated system architecture and the flow of information to trigger and monitor the performance of the DR events. We outline the DR strategies at each of the participating facilities. At one site a real time electric measurement feedback loop is implemented to assure the delivery of CAISO dispatched demand reductions. Finally, we present results from each of the facilities and discuss findings.

Kiliccote, Sila; Piette, Mary Ann; Ghatikar, Girish; Koch, Ed; Hennage, Dan; Hernandez, John; Chiu, Albert; Sezgen, Osman; Goodin, John

2009-11-06T23:59:59.000Z

487

Incentives for demand-side management  

SciTech Connect

This report is the first product of an ongoing project to monitor the efforts of states to remove regulatory barriers to, and provide financial incentives for, utility investment in demand-side management (DSM) resources. The project was commissioned by the National Association of Regulatory Utility Commissioners (NARUC) in response to growing interest among regulators for a comprehensive survey of developments in this area. Each state report beings with an overview of the state`s progress toward removing regulatory barriers and providing incentives for DSM. Information is organized under five headings: status; IRP regulations and practice; current treatment of DSM, directions and trends; commission contact person. Where applicable, each overview is followed by one or more sections that report on specific incentive proposals or mechanisms within the state. Information on each proposal or mechanism is organized under eight headings. A notation on each page identifies the utility or other group associated with the proposal or mechanism. The eight headings are as follows: status; background; treatment of cost recovery; treatment of lost revenues/decoupling; treatment of profitability; other features; issues, and additional observations.

Reid, M.W.; Brown, J.B. [Barakat and Chamberlin, Inc., Oakland, CA (United States)] [Barakat and Chamberlin, Inc., Oakland, CA (United States)

1992-01-01T23:59:59.000Z

488

Incentives for demand-side management  

SciTech Connect

This report is the first product of an ongoing project to monitor the efforts of states to remove regulatory barriers to, and provide financial incentives for, utility investment in demand-side management (DSM) resources. The project was commissioned by the National Association of Regulatory Utility Commissioners (NARUC) in response to growing interest among regulators for a comprehensive survey of developments in this area. Each state report beings with an overview of the state's progress toward removing regulatory barriers and providing incentives for DSM. Information is organized under five headings: status; IRP regulations and practice; current treatment of DSM, directions and trends; commission contact person. Where applicable, each overview is followed by one or more sections that report on specific incentive proposals or mechanisms within the state. Information on each proposal or mechanism is organized under eight headings. A notation on each page identifies the utility or other group associated with the proposal or mechanism. The eight headings are as follows: status; background; treatment of cost recovery; treatment of lost revenues/decoupling; treatment of profitability; other features; issues, and additional observations.

Reid, M.W.; Brown, J.B. (Barakat and Chamberlin, Inc., Oakland, CA (United States)) [Barakat and Chamberlin, Inc., Oakland, CA (United States)

1992-01-01T23:59:59.000Z

489

The European Community feed grain substitute problem: an econometric analysis of import demand for feedstuffs in the European Community  

E-Print Network (OSTI)

-62, Overall and 1976-78 278 C-2. Derived Two-State Least Squares Reduced-Forms from the TSLS1 (Barley-FGS) Model 279 C-3. Derived Two-Stage Least Squares Reduced-Forms from the TSLS2 (Corn-FGS) Model 281 C-4. Derived Two-Stage Lease Squares Reduced... wheat, barley, corn, oats sorghum, soybeans, soybean meal, snd cassava supply and demand averages for 1975-78 in 1, 000 metric tons and percentages . 122 Actual and Estimated Quantity of United States Corn Imported into the European Community 208...

Tucker, James Leroy

1981-01-01T23:59:59.000Z

490

Estimating Large-Customer Demand Response Market Potential: Integrating Price and Customer Behavior  

E-Print Network (OSTI)

Estimating Large-Customer Demand Response Market Potential:Syracuse, NY ABSTRACT Demand response (DR) is increasinglyestimated. Introduction Demand response (DR) is increasingly

Goldman, Charles; Hopper, Nicole; Bharvirkar, Ranjit; Neenan, Bernie; Cappers, Peter

2007-01-01T23:59:59.000Z

491

Analysis of Open Automated Demand Response Deployments in California and Guidelines to Transition to Industry Standards  

E-Print Network (OSTI)

to Automated Demand Response and the OpenADR Automated Demand Response Program. https://Data for Automated Demand Response in Commercial

Ghatikar, Girish

2014-01-01T23:59:59.000Z

492

Automated Demand Response Technologies and Demonstration in New York City using OpenADR  

E-Print Network (OSTI)

C. McParland, "Open Automated Demand Response Communications2011. Utility & Demand Response Programs Energy ProviderAnnual Consumption (kWh) Demand Response Program Curtailment

Kim, Joyce Jihyun

2014-01-01T23:59:59.000Z

493

Automated Demand Response: The Missing Link in the Electricity Value Chain  

E-Print Network (OSTI)

Laboratory. Berkeley. Demand Response Research Center,and Automated Demand Response in Wastewater TreatmentLaboratory. Berkeley. Demand Response Research Center,

McKane, Aimee

2010-01-01T23:59:59.000Z

494

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

Energy Resources and Demand Response under Uncertainty AfzalEnergy Resources and Demand Response under Uncertainty ?DER in conjunction with demand response (DR): the expected

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

495

Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response  

E-Print Network (OSTI)

S. Kiliccote. EstimatingDemandResponseLoad Impacts:inCalifornia. DemandResponseResearchCenter,LawrenceandTechniquesforDemandResponse. LBNLReport59975.

Kiliccote, Sila

2011-01-01T23:59:59.000Z

496

Opportunities for Demand Response in California Agricultural Irrigation: A Scoping Study  

E-Print Network (OSTI)

Grower Acceptance of Demand Response and Permanent LoadCommission. (n.d. ). Demand Response. Retrieved fromLead Product Manager, Demand Response Department, Pacific

Marks, Gary

2014-01-01T23:59:59.000Z

497

A Methodology for Estimating Large-Customer Demand Response Market Potential  

E-Print Network (OSTI)

Estimating Large-Customer Demand Response Market PotentialEstimating Large-Customer Demand Response Market PotentialSyracuse, NY ABSTRACT Demand response (DR) is increasingly

Goldman, Charles; Hopper, Nicole; Bharvirkar, Ranjit; Neenan, Bernie; Cappers, Peter

2008-01-01T23:59:59.000Z

498

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network (OSTI)

for Automated Demand Response in Commercial Buildings. In2010. Open Automated Demand Response Dynamic Pricing2009. Open Automated Demand Response Communications

Ghatikar, Girish

2010-01-01T23:59:59.000Z

499

Intelligent Building Energy Information and Control Systems for Low-Energy Operations and Optimal Demand Response  

E-Print Network (OSTI)

Open Automated Demand Response Communicationsfrom 7YearsofAutomatedDemandResponseinCommercialManagementandDemandResponseinCommercial Buildings. ,

Piette, Mary Ann

2014-01-01T23:59:59.000Z

500

Automated Demand Response: The Missing Link in the Electricity Value Chain  

E-Print Network (OSTI)

and Open Automated Demand Response. In Grid Interop Forum.Berkeley National Laboratory. Demand Response ResearchCenter, Demand Response Research Center PIER Team Briefing,

McKane, Aimee

2010-01-01T23:59:59.000Z