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Note: This page contains sample records for the topic "total energy 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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1

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

2

Effect of window type, size and orientation on the total energy demand for a building in Indian climatic conditions  

Science Journals Connector (OSTI)

Windows in a building allow daylight to enter a building space but simultaneously they also result in heat gains and losses affecting energy balance. This requires an optimisation of window area from the point of view of total energy demand viz., for lighting and cooling/heating. This paper is devoted to this kind of study for Indian climatic conditions, which are characterised by six climatic zones varying from extreme cold to hot, dry and humid conditions. Different types of windows have been considered because the optimised size will also depend on the thermo-optical parameters like heat transfer coefficient (U-value), solar heat gain coefficient (g), visual (?), and total transmittance (T) of the glazing in the window. It is observed that in a non-insulated building, cooling/heating energy demand far exceeds lighting energy demand, making the optimisation of window area a futile exercise from the point of view of total energy demand. Only for buildings with U-value below 0.6 W/m²K can optimisation be achieved. The optimised window area and the corresponding specific energy consumption have been calculated for different climates in India, for different orientations, and for three different advanced window systems.

Inderjeet Singh; N.K. Bansal

2004-01-01T23:59:59.000Z

3

Projections up for total energy demand by IEA nations in 1990  

SciTech Connect (OSTI)

The author reviews the most recent IEA projections for energy demand to the year 2000 in IEA countries. These show that the expectations for 1990 are now higher than estimates made last year. Production of solid fuels is expected to increase from 814 million toe in 1983 to 1044 million toe in 1990 and 1345 million toe by 2000. Nearly all the increase is expected in the US, Canada and Australia.

Vielvoye, R.

1985-06-17T23:59:59.000Z

4

Turkey's energy demand and supply  

SciTech Connect (OSTI)

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

5

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

6

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

7

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

8

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

9

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

10

Global energy demand to 2060  

SciTech Connect (OSTI)

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

11

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

12

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

13

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

14

How Can China Lighten Up? Urbanization, Industrialization and Energy Demand Scenarios  

E-Print Network [OSTI]

on the forecast of total energy demand. Based on this, weadjustment spurred energy demand for construction of newenergy services. Primary energy demand grew at an average

Aden, Nathaniel T.

2010-01-01T23:59:59.000Z

15

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

16

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

17

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

18

Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards "Top-Runner Approach"  

E-Print Network [OSTI]

Energy Source Demand per Household Coal, Oil, Gas, Heat, Electricity Total Energy Source Demand Coal, Oil, Gas, Heat, Electricity Demography Japan

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

19

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

20

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

Note: This page contains sample records for the topic "total energy 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

Energy Demand and Supply  

Science Journals Connector (OSTI)

The world consumption of primary energy has been on the increase ever since the Industrial Revolution . The energy consumption in 1860 is estimated to have ... particularly marked since WWII when the sources of primary

Kimio Uno

1995-01-01T23:59:59.000Z

22

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

23

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

24

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

25

Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards "Top-Runner Approach"  

E-Print Network [OSTI]

Total Energy Source Demand Coal, Oil, Gas, Heat, ElectricityEnergy Source Demand per Household Coal, Oil, Gas, Heat,ton of oil equivalent Considerable increases in demand for

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

26

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

27

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

28

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...

29

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

30

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"

31

Energy Demand-Energy Supplies  

Science Journals Connector (OSTI)

Just a few years after the U.S. celebrated its first centennial it passed another milestone. In about 1885, coal replaced wood as the nations primary energy source. Wood, properly managed, is a renewable reso...

V. P. Kenney; J. W. Lucey

1985-01-01T23:59:59.000Z

32

Demand Response - Policy | Department of Energy  

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

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...

33

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

34

Energy demand and population changes  

SciTech Connect (OSTI)

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

35

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

36

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

37

EIA - International Energy Outlook 2009-World Energy Demand and Economic  

Gasoline and Diesel Fuel Update (EIA)

World Energy and Economic Outlook World Energy and Economic Outlook International Energy Outlook 2009 Chapter 1 - World Energy Demand and Economic Outlook In the IEO2009 projections, total world consumption of marketed energy is projected to increase by 44 percent from 2006 to 2030. The largest projected increase in energy demand is for the non-OECD economies. Figure 10. World Marketed Energy Consumption, 1980-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 11. World Marketed Energy Consumption: OECD and Non-OECD, 1980-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 12. Marketed Energy Use by Region, 1990-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800.

38

EIA - International Energy Outlook 2008-World Energy Demand and Economic  

Gasoline and Diesel Fuel Update (EIA)

World Energy and Economic Outlook World Energy and Economic Outlook International Energy Outlook 2008 Chapter 1 - World Energy Demand and Economic Outlook In the IEO2008 projections, total world consumption of marketed energy is projected to increase by 50 percent from 2005 to 2030. The largest projected increase in energy demand is for the non-OECD economies. Figure 9. World Marketed EnergyConsumption, 1980-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 10. World Marketed Energy Consumption: OECD and Non-OECD, 1980-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 11. Marketed Energy Use in the Non-OECD Economies by Region, 1990-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800.

39

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

40

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

Note: This page contains sample records for the topic "total energy 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

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

42

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

43

Demand Response | Department of Energy  

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

44

Demand Charges | Open Energy Information  

Open Energy Info (EERE)

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

45

SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY  

Broader source: Energy.gov [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...

46

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

47

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

48

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

49

Energy Perspectives, Total Energy - Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

Total Energy Total Energy Glossary › FAQS › Overview Data Monthly Annual Analysis & Projections this will be filled with a highchart PREVIOUSNEXT Energy Perspectives 1949-2011 September 2012 PDF | previous editions Release Date: September 27, 2012 Introduction Energy Perspectives is a graphical overview of energy history in the United States. The 42 graphs shown here reveal sweeping trends related to the Nation's production, consumption, and trade of energy from 1949 through 2011. Energy Flow, 2011 (Quadrillion Btu) Total Energy Flow diagram image For footnotes see here. Energy can be grouped into three broad categories. First, and by far the largest, is the fossil fuels-coal, petroleum, and natural gas. Fossil fuels have stored the sun's energy over millennia past, and it is primarily

50

Coordination of Energy Efficiency and Demand Response  

SciTech Connect (OSTI)

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

51

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

52

Global Energy: Supply, Demand, Consequences, Opportunities  

SciTech Connect (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

2008-08-14T23:59:59.000Z

53

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

54

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

55

Drivers of Future Energy Demand  

Gasoline and Diesel Fuel Update (EIA)

trends - Household income migration urbanization * Policy: China Energy Outlook - Air pollution - Climate change 4 (1) Industrial energy intensity: The energy intensity of...

56

Coordination of Energy Efficiency and Demand Response  

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

57

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

58

Energy Demand Forecasting in China Based on Dynamic RBF Neural Network  

Science Journals Connector (OSTI)

A dynamic radial basis function (RBF) network model is proposed for energy demand forecasting in this paper. Firstly, we ... detail. At last, the data of total energy demand in China are analyzed and experimental...

Dongqing Zhang; Kaiping Ma; Yuexia Zhao

2011-01-01T23:59:59.000Z

59

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network [OSTI]

of locational renewable energy production in each renewableto total renewable energy production, although accountingproduction data from the 2006 data set of the National Renewable Energy

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

60

EIA - Annual Energy Outlook 2008 - Natural Gas Demand  

Gasoline and Diesel Fuel Update (EIA)

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

Note: This page contains sample records for the topic "total energy 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

China End-Use Energy Demand Modeling  

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

62

Driving Demand | Department of Energy  

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

how they should invest in energy efficiency for their homes and buildings. Effective marketing can address this issue. By providing relevant information in compelling ways, energy...

63

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

64

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

65

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

66

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

67

Assumptions to the Annual Energy Outlook - Transportation Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumption to the Annual Energy Outlook Transportation Demand Module The NEMS Transportation Demand Module estimates 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, light trucks, sport utility vehicles and vans), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger airplanes, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

68

EIA - Assumptions to the Annual Energy Outlook 2008 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2008 Transportation Demand Module The NEMS Transportation Demand Module estimates 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), freight and passenger aircraft, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

69

EIA - Assumptions to the Annual Energy Outlook 2009 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2009 Transportation Demand Module The NEMS Transportation Demand Module estimates 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), freight and passenger aircraft, freight, rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

70

total energy | OpenEI  

Open Energy Info (EERE)

total energy total energy Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion BTUs, and quantifies the energy prices using U.S. dollars. The data is broken down into total production, imports, exports, consumption, and prices for energy types. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption EIA export import production reference case total energy Data application/vnd.ms-excel icon AEO2011: Total Energy Supply, Disposition, and Price Summary - Reference Case (xls, 112.8 KiB) Quality Metrics Level of Review Peer Reviewed

71

Energy technologies and their impact on demand  

SciTech Connect (OSTI)

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

72

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

73

Cumulative energy demand for selected renewable energy technologies  

Science Journals Connector (OSTI)

Calculation of Cumulative Energy Demand (CED) of various energy systems and the computation of their Energy Yield Ratio (EYR) suggests that one single renewable energy technology cannot be said to be the ... Due ...

Dirk Grzenich; Jyotirmay Mathur

1999-05-01T23:59:59.000Z

74

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

75

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

76

Table A19. Components of Total Electricity Demand by Census Region and  

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

Components of Total Electricity Demand by Census Region and" Components of Total Electricity Demand by Census Region and" " Economic Characteristics of the Establishment, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)","Generation(c)","Offsite","Net Demand(d)","Factors" ,"Total United States" "RSE Column Factors:",0.5,1.4,1.3,1.9,0.5 "Value of Shipments and Receipts" "(million dollars)"

77

"Table A16. Components of Total Electricity Demand by Census Region, Industry"  

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

6. Components of Total Electricity Demand by Census Region, Industry" 6. Components of Total Electricity Demand by Census Region, Industry" " Group, and Selected Industries, 1991" " (Estimates in Million Kilowatthours)" " "," "," "," "," "," "," "," " " "," "," "," "," ","Sales and/or"," ","RSE" "SIC"," "," ","Transfers","Total Onsite","Transfers","Net Demand for","Row" "Code(a)","Industry Groups and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)","Factors"

78

Table A26. Components of Total Electricity Demand by Census Region, Census Di  

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

Components of Total Electricity Demand by Census Region, Census Division, and" Components of Total Electricity Demand by Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," ","Sales/"," ","RSE" " "," ","Transfers","Onsite","Transfers"," ","Row" "Economic Characteristics(a)","Purchases","In(b)","Generation(c)","Offsite","Net Demand(d)","Factors" ,"Total United States" "RSE Column Factors:",0.5,2.1,1.2,2,0.4 "Value of Shipments and Receipts"

79

Overview of Demand Side Response | Department of Energy  

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

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...

80

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....

Note: This page contains sample records for the topic "total energy 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

Managing Energy Demand With Standards and Information  

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

82

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":""}]}

83

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

84

Assumptions to the Annual Energy Outlook 2001 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions 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, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. Key Assumptions Macroeconomic Sector Inputs

85

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.

86

Building Energy Software Tools Directory: Energy Demand Modeling  

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

Energy Demand Modeling Energy Demand Modeling The software is intended to be used for Energy Demand Modeling. This can be utilized from regional to national level. A Graphical User Interface of the software takes the input from the user in a quite logical and sequential manner. These input leads to output in two distinct form, first, it develops a Reference Energy System, which depicts the flow of energy from the source to sink with all the losses incorporated and second, it gives a MATLAB script file for advance post processing like graphs, visualization and optimizations to develop and evaluate the right energy mix policy frame work for a intended region. Keywords Reference Energy System, Software, GUI, Planning, Energy Demand Model EDM, Energy Policy Planning Validation/Testing

87

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":""}]}

88

Photo-Ionic Cells: Two Solutions to Store Solar Energy and Generate Electricity on Demand  

Science Journals Connector (OSTI)

Photo-Ionic Cells: Two Solutions to Store Solar Energy and Generate Electricity on Demand ... potential of solar energy all over the world is many times larger than the current total primary energy demanded. ... The magnitudes of the free energies derived from formal potentials are detd. ...

Manuel A. Mndez; Pekka Peljo; Michel D. Scanlon; Heron Vrubel; Hubert H. Girault

2014-02-27T23:59:59.000Z

89

National Fuel Cell and Hydrogen Energy Overview: Total Energy...  

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

and Hydrogen Energy Overview: Total Energy USA 2012 National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012 Presentation by Sunita Satyapal at the Total Energy USA...

90

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

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

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...

91

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

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

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...

92

Chapter 3: Demand-Side Resources | Department of Energy  

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

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

93

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... ment of the total energy and vice versa. From a measurement of spectral irradi- ance ... unit energy (for the wavelength region specified).

2000-01-02T23:59:59.000Z

94

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

95

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

96

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network [OSTI]

services provided to the energy markets, Order 745 advancesin the wholesale energy market (both day-ahead and real-the capacity market is. The energy market does not feature

Shen, Bo

2013-01-01T23:59:59.000Z

97

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

98

Coordination of Energy Efficiency and Demand Response  

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

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

99

Driving Demand for Home Energy Improvements  

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

100

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

Note: This page contains sample records for the topic "total energy 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

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

102

Energy Efficiency Funds and Demand Response Programs - National Overview  

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

Funds and Demand Funds and Demand Response Programs - National Overview Charles Goldman Lawrence Berkeley National Laboratory November 2, 2006 Federal Utility Partnership Working Group San Francisco CA Overview of Talk * National Overview * Energy Efficiency Programs and Funds * Demand Response Programs and Funds * FEMP Resources on Public Benefit Funds *Suggestions for Federal Customers DSM Spending is increasing! * 2006 Utility DSM and Public Benefit spending is ~$2.5B$ - $1B for C&I EE programs * CA utilities account for 35% of total spending 0.0 0.5 1.0 1.5 2.0 2.5 3.0 1994 2000 2005 2006 Costs (in billion $) DSM Costs Load Management Gas EE Other States Electric EE California Electric EE EE Spending in 2006 (by State) $ Million < 1 (23) 1 - 10 (2) 11 - 50 (13) 51 - 100 (7) > 100 (5) 790 101 257

103

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

104

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

105

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

106

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

107

Modeling supermarket refrigeration energy use and demand  

SciTech Connect (OSTI)

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

108

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

109

Relation between total quanta and total energy for aquatic ...  

Science Journals Connector (OSTI)

Jan 22, 1974 ... havior of the ratio of total quanta to total energy (Q : W) within the spectral region of photosynthetic ..... For blue-green waters, where hRmax lies.

2000-01-02T23:59:59.000Z

110

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

111

Assumptions to the Annual Energy Outlook 2000 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module estimates energy consumption across the nine Census Divisions 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, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, mass transit, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. Transportation Demand Module estimates energy consumption across the nine Census Divisions 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, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, mass transit, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. Key Assumptions Macroeconomic Sector Inputs

112

Energy and Security in Northeast Asia: Supply and Demand, Conflict and  

E-Print Network [OSTI]

3 Energy Policies and Energy Demand in Northeastissue of whether rising energy demand generates new securityoverall regional energy demand (Fesharaki, Sara Banaszak,

Fesharaki, Fereidun; Banaszak, Sarah; WU, Kang; Valencia, Mark J.; Dorian, James P.

1998-01-01T23:59:59.000Z

113

Chapter 3 Demand-Side Resources | Department of Energy  

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

resources result from one of two methods of reducing load: energy efficiency or demand response load management. The energy efficiency method designs and deploys technologies...

114

Solar total energy project Shenandoah  

SciTech Connect (OSTI)

This document presents the description of the final design for the Solar Total Energy System (STES) to be installed at the Shenandoah, Georgia, site for utilization by the Bleyle knitwear plant. The system is a fully cascaded total energy system design featuring high temperature paraboloidal dish solar collectors with a 235 concentration ratio, a steam Rankine cycle power conversion system capable of supplying 100 to 400 kW(e) output with an intermediate process steam take-off point, and a back pressure condenser for heating and cooling. The design also includes an integrated control system employing the supervisory control concept to allow maximum experimental flexibility. The system design criteria and requirements are presented including the performance criteria and operating requirements, environmental conditions of operation; interface requirements with the Bleyle plant and the Georgia Power Company lines; maintenance, reliability, and testing requirements; health and safety requirements; and other applicable ordinances and codes. The major subsystems of the STES are described including the Solar Collection Subysystem (SCS), the Power Conversion Subsystem (PCS), the Thermal Utilization Subsystem (TUS), the Control and Instrumentation Subsystem (CAIS), and the Electrical Subsystem (ES). Each of these sections include design criteria and operational requirements specific to the subsystem, including interface requirements with the other subsystems, maintenance and reliability requirements, and testing and acceptance criteria. (WHK)

None

1980-01-10T23:59:59.000Z

115

National Fuel Cell and Hydrogen Energy Overview: Total Energy...  

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

National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012 National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012 Presentation by Sunita Satyapal at the...

116

Modelling future private car energy demand in Ireland  

Science Journals Connector (OSTI)

Targeted measures influencing vehicle technology are increasingly a tool of energy policy makers within the EU as a means of meeting energy efficiency, renewable energy, climate change and energy security goals. This paper develops the modelling capacity for analysing and evaluating such legislation, with a focus on private car energy demand. We populate a baseline car stock and car activity model for Ireland to 2025 using historical car stock data. The model takes account of the lifetime survival profile of different car types, the trends in vehicle activity over the fleet and the fuel price and income elasticities of new car sales and total fleet activity. The impacts of many policy alternatives may only be simulated by such a bottom-up approach, which can aid policy development and evaluation. The level of detail achieved provides specific insights into the technological drivers of energy consumption, thus aiding planning for meeting climate targets. This paper focuses on the methodology and baseline scenario. Baseline results for Ireland forecast a decline in private car energy demand growth (0.2%, compared with 4% in the period 20002008), caused by the relative growth in fleet efficiency compared with activity.

Hannah E. Daly; Brian P. Gallachir

2011-01-01T23:59:59.000Z

117

EnergySolve Demand Response | Open Energy Information  

Open Energy Info (EERE)

EnergySolve Demand Response EnergySolve Demand Response Jump to: navigation, search Name EnergySolve Demand Response Place Somerset, New Jersey Product Somerset-based utility bill outsourcing company that provides electronic utility bill auditing, tariff analysis, late fee avoidance, and flexible bill payment solutions. Coordinates 45.12402°, -92.675379° 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":45.12402,"lon":-92.675379,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

118

Reducing Energy Demand in Buildings Through State Energy Codes  

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

Codes Assistance Project Codes Assistance Project Maureen Guttman, AIA Executive Director, BCAP Alliance to Save Energy 202-530-2211 mguttman@ase.org Tuesday, April 2, 2013 - Thursday, April 4, 2013 Reducing Energy Demand in Buildings Through State Energy Codes - Providing Technical Support and Assistance to States - 2 | Building Technologies Office eere.energy.gov Purpose & Objectives Problem Statement: Buildings = largest sector of energy consumption in America * Energy codes are a ready-made regulatory mechanism * States need support for implementation Impact of Project:

119

Reducing Energy Demand in Buildings Through State Energy Codes  

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

Codes Assistance Project Codes Assistance Project Maureen Guttman, AIA Executive Director, BCAP Alliance to Save Energy 202-530-2211 mguttman@ase.org Tuesday, April 2, 2013 - Thursday, April 4, 2013 Reducing Energy Demand in Buildings Through State Energy Codes - Providing Technical Support and Assistance to States - 2 | Building Technologies Office eere.energy.gov Purpose & Objectives Problem Statement: Buildings = largest sector of energy consumption in America * Energy codes are a ready-made regulatory mechanism * States need support for implementation Impact of Project:

120

Residential Energy Demand Reduction Analysis and Monitoring Platform - REDRAMP  

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

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

Note: This page contains sample records for the topic "total energy 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

Building Energy Software Tools Directory: Demand Response Quick Assessment  

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

122

Energy and Demand Savings from Implementation Costs in Industrial Facilities  

E-Print Network [OSTI]

.g., natural gas) in each code [6]. Table 1. Energy Streams STREAM CODE Electrical Consumption EC Electrical Demand ED Other Electrical Fees EF Electricity E1 Natural Gas E2 L.P.G. E3 #1 Fuel Oil E4 #2 Fuel Oil E5 #4 Fuel Oil E6 #6 Fuel... that are widely scattered). Therefore, the correlations of implementation costs with electrical consumption and natural gas are also investigated in Tables 2 and 4, because they are highly important both nationally and in Texas. In fact, the total number...

Razinha, J. A.; Heffington, W. M.

123

Oncor Energy Efficiency Programs Solar Photovoltaic and Demand Response  

E-Print Network [OSTI]

Oncor Energy Efficiency Programs Solar Photovoltaic and Demand Response October 10, 2012 ENERGY EFFICIENCY PROGRAMS OVERVIEW ?Program rules and guidelines established by Public Utility Commission of Texas (PUCT) ?All Texas investor...Oncor Energy Efficiency Programs Solar Photovoltaic and Demand Response October 10, 2012 ENERGY EFFICIENCY PROGRAMS OVERVIEW ?Program rules and guidelines established by Public Utility Commission of Texas (PUCT) ?All Texas investor...

Tyra, K.; Hanel, J.

2012-01-01T23:59:59.000Z

124

Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards "Top-Runner Approach"  

E-Print Network [OSTI]

ABORATORY Japans Residential Energy Demand Outlook to 2030o r n i a Japans Residential Energy Demand Outlook to 2030residential sector, where energy demand has grown vigorously

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

125

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network [OSTI]

of Distributed Energy Resources and Demand Response underof Distributed Energy Resources and Demand Response underof Distributed Energy Resources and Demand Response under

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

126

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

127

Distributed Automated Demand Response - Energy Innovation Portal  

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

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

128

Demand Response (transactional control) - Energy Innovation Portal  

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

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

129

Regulation Services with Demand Response - Energy Innovation...  

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

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

130

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

131

Assumptions to the Annual Energy Outlook 2002 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. 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 19). The Industrial Demand Module forecasts energy consumption at the four Census region levels; energy consumption at the Census Division level is allocated

132

New Zealand Energy Data: Electricity Demand and Consumption | OpenEI  

Open Energy Info (EERE)

Electricity Demand and Consumption Electricity Demand and Consumption 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). The sectors included are: agriculture, forestry and fishing; industrial (mining, food processing, wood and paper, chemicals, basic metals, other minor sectors); commercial; and residential. Source New Zealand Ministry of Economic Development Date Released Unknown Date Updated July 03rd, 2009 (5 years ago)

133

Demand Response Energy Consulting LLC | Open Energy Information  

Open Energy Info (EERE)

Response Energy Consulting LLC Response Energy Consulting LLC Jump to: navigation, search Name Demand Response & Energy Consulting LLC Place Delanson, New York Zip NY 12053 Sector Efficiency Product Delanson-based demand response and energy efficiency consultants. Coordinates 42.748995°, -74.185794° 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":42.748995,"lon":-74.185794,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

134

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

both types of programs. Xcel Energy markets both energyEnergy Efficiency Marketing Xcel Energy Paul Suskie Chairman

Goldman, Charles

2010-01-01T23:59:59.000Z

135

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

136

Assumptions to the Annual Energy Outlook 1999 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

transportation.gif (5318 bytes) transportation.gif (5318 bytes) The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions 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, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, mass transit, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

137

Energy demand and economic consequences of transport policy  

Science Journals Connector (OSTI)

Transport sector is a major consumer of energy. Concern of energy scarcity and price fluctuations enhanced significance of ... sector in national planning. This paper analyses energy demand for transport services...

J. B. Alam; Z. Wadud; J. B. Alam

2013-09-01T23:59:59.000Z

138

Energy Demand and the Environmental Effects of CSF  

Science Journals Connector (OSTI)

In Greece the demand for energy is a substantial element in the analysis... energy is a crucial determinant of production costs. Thus, energy prices play a key role in assessing.....

Nicos Christodoulakis; Sarantis Kalyvitis

2001-01-01T23:59:59.000Z

139

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network [OSTI]

an estimated total energy consumption of 19 GWh (0.07PJ),to 28% in 2005. Total energy consumption in 2020 in thecan have similar total energy consumption but produce very

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

140

Network-Driven Demand Side Management Website | Open Energy Informatio...  

Open Energy Info (EERE)

UtilityElectricity Service Costs) for this property. This task of the International Energy Agency is a broad, systematic examination of the potential for demand-side...

Note: This page contains sample records for the topic "total energy 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

Energy Efficient Grooming of Scheduled Sub-wavelength Traffic Demands  

Science Journals Connector (OSTI)

We investigate how awareness of demand holding times can be exploited for energy efficient traffic grooming in optical networks. We present an optimal formulation for minimizing the...

Chen, Ying; Jaekel, Arunita

142

Assisting Mexico in Developing Energy Supply and Demand Projections | Open  

Open Energy Info (EERE)

Assisting Mexico in Developing Energy Supply and Demand Projections Assisting Mexico in Developing Energy Supply and Demand Projections Jump to: navigation, search Name Assisting Mexico in Developing Energy Supply and Demand Projections Agency/Company /Organization Argonne National Laboratory Sector Energy Topics GHG inventory, Background analysis Resource Type Software/modeling tools Website http://www.dis.anl.gov/news/Me Country Mexico UN Region Latin America and the Caribbean References Assisting Mexico in Developing Energy Supply and Demand Projections[1] "CEEESA and the team of experts from Mexico analyzed the country's entire energy supply and demand system using CEEESA's latest version of the popular ENPEP-BALANCE software. The team developed a system representation, a so-called energy network, using ENPEP's powerful graphical user

143

Solar in Demand | Department of Energy  

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

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

144

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network [OSTI]

Renewable energy spillage, operating costs and capacityfocused on renewable energy utilization, cost of operationssystem operating costs, renewable energy utilization,

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

145

California Energy Demand Scenario Projections to 2050  

E-Print Network [OSTI]

energy scenarios to explore alternative energy pathways indo not include the alternative energy pathways (such asmodeling to investigate alternative energy supply strategies

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

2008-01-01T23:59:59.000Z

146

Model for Analysis of Energy Demand (MAED-2) | Open Energy Information  

Open Energy Info (EERE)

Analysis of Energy Demand (MAED-2) AgencyCompany Organization: International Atomic Energy Agency Sector: Energy Focus Area: Renewable Energy, Energy Efficiency Topics: Pathways...

147

The Integration of Energy Efficiency, Renewable Energy, Demand Response and Climate Change: Challenges and Opportunities for Evaluators and Planners  

E-Print Network [OSTI]

to inform projected energy and demand reductions in regionaldown to reflect energy and demand savings due to spillover (market and estimate the energy and demand savings associated

Vine, Edward

2007-01-01T23:59:59.000Z

148

"Table A25. Components of Total Electricity Demand by Census Region, Census Division, Industry"  

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

Components of Total Electricity Demand by Census Region, Census Division, Industry" Components of Total Electricity Demand by Census Region, Census Division, Industry" " Group, and Selected Industries, 1994" " (Estimates in Million Kilowatthours)" " "," "," "," "," "," "," "," " " "," "," "," "," ","Sales and/or"," ","RSE" "SIC"," "," ","Transfers","Total Onsite","Transfers","Net Demand for","Row" "Code(a)","Industry Group and Industry","Purchases","In(b)","Generation(c)","Offsite","Electricity(d)","Factors"

149

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

150

EIA - Assumptions to the Annual Energy Outlook 2008 - Industrial Demand  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2008 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 21 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 projects 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 projection using the SEDS1 data.

151

EIA - Assumptions to the Annual Energy Outlook 2010 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2010 Residential Demand Module Figure 5. United States Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. 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 use 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" by appliance (or UEC-in million Btu per household per year). The projection process adds new housing units to the stock,

152

EIA - Assumptions to the Annual Energy Outlook 2008 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2008 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2030. 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 Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.1

153

EIA - Assumptions to the Annual Energy Outlook 2009 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2009 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2030. 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 Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.1

154

EIA - Assumptions to the Annual Energy Outlook 2010 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2009 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 Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services [1].

155

Compare All CBECS Activities: Total Energy Use  

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

Total Energy Use Total Energy Use Compare Activities by ... Total Energy Use Total Major Fuel Consumption by Building Type Commercial buildings in the U.S. used a total of approximately 5.7 quadrillion Btu of all major fuels (electricity, natural gas, fuel oil, and district steam or hot water) in 1999. Office buildings used the most total energy of all the building types, which was not a surprise since they were the most common commercial building type and had an above average energy intensity. Figure showing total major fuel consumption by building type. If you need assistance viewing this page, please call 202-586-8800. Major Fuel Consumption per Building by Building Type Because there were relatively few inpatient health care buildings and they tend to be large, energy intensive buildings, their energy consumption per building was far above that of any other building type.

156

Energy Demand and Emission from Transport Sector in China  

Science Journals Connector (OSTI)

This paper aims to present a comprehensive overview of the current status and future trends of energy demand and emissions from transportation sector in China. ... a brief review of the national profile of energy

Yin Huang; Mengjun Wang

2013-01-01T23:59:59.000Z

157

Transaction Costs and their Impact on Energy Demand Behaviour  

Science Journals Connector (OSTI)

The very recent trends in energy demand are incompatible with empirically fitted price elasticities. ... associated with investment decisions of households for energy conservation and/or fuel substitution may...

Erich Unterwurzacher; Franz Wirl

1989-01-01T23:59:59.000Z

158

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network [OSTI]

1.2 Limitations to Large-Scale Renewable EnergyImpacts of Renewable Energy Supply . . . . . . . . . . . . .1.3 Coupling Renewable Energy with Deferrable

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

159

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

Programs Integrated Energy Audit Provide engineeringtechnicians performed energy audits and provided advice to8 PG&Es Integrated Energy Audit, a program for businesses

Goldman, Charles

2010-01-01T23:59:59.000Z

160

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

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

Response to several FOIA requests - Renewable Energy. Demand for Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. nepdg_251_500.pdf. Demand for Fossil Fuels. Renewable sources of power. Demand for fossil fuels surely will overrun supply sooner or later, as indeed it already has in the casc of United States domestic oil drilling. Recognition also is growing that our air and land can no longer absorb unlimited quantities of waste from fossil fuel extraction and combustion. As that day draws nearer, policymakers will have no realistic alternative but to turn to sources of power that today make up a viable but small part of America's energy picture. And they will be

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


161

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

has for years used New York Energy $mart as the umbrellaevent days. The New York State Energy Research & DevelopmentEnergy Challenge). The New York State Energy Research and

Goldman, Charles

2010-01-01T23:59:59.000Z

162

A Full Demand Response Model in Co-Optimized Energy and  

SciTech Connect (OSTI)

It has been widely accepted that demand response will play an important role in reliable and economic operation of future power systems and electricity markets. Demand response can not only influence the prices in the energy market by demand shifting, but also participate in the reserve market. In this paper, we propose a full model of demand response in which demand flexibility is fully utilized by price responsive shiftable demand bids in energy market as well as spinning reserve bids in reserve market. A co-optimized day-ahead energy and spinning reserve market is proposed to minimize the expected net cost under all credible system states, i.e., expected total cost of operation minus total benefit of demand, and solved by mixed integer linear programming. Numerical simulation results on the IEEE Reliability Test System show effectiveness of this model. Compared to conventional demand shifting bids, the proposed full demand response model can further reduce committed capacity from generators, starting up and shutting down of units and the overall system operating costs.

Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

2014-01-01T23:59:59.000Z

163

Serck standard packages for total energy  

Science Journals Connector (OSTI)

Although the principle of combined heat and power generation is attractive, practical problems have hindered its application. In the U.K. the scope for small scale combined heat and power (total energy) systems has been improved markedly by the introduction of new Electricity Board regulations which allow the operation of small a.c. generators in parallel with the mains low voltage supply. Following this change, Serck have developed a standard total energy unit, the CG100, based on the 2.25 1 Land Rover gas engine with full engine (coolant and exhaust gas) heat recovery. The unit incorporates an asynchronous generator, which utilising mains power for its magnetising current and speed control, offers a very simple means of generating electricity in parallel with the mains supply, without the need for expensive synchronising controls. Nominal output is 15 kW 47 kW heat; heat is available as hot water at temperatures up to 85C, allowing the heat output to be utilised directly in low pressure hot water systems. The CG100 unit can be used in any application where an appropriate demand exists for heat and electricity, and the annual utilisation will give an acceptable return on capital cost; it produces base load heat and electricity, with LPHW boilers and the mains supply providing top-up/stand-by requirements. Applications include residential use (hospitals, hotels, boarding schools, etc.), swimming pools and industrial process systems. The unit also operates on digester gas produced by anaerobic digestion of organic waste. A larger unit based on a six cylinder Ford engine (45 kWe output) is now available.

R. Kelcher

1984-01-01T23:59:59.000Z

164

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

energy efficiency savings that are achieved through monitoring- based commissioning, as well as documenting best practicesEnergy Efficiency Alliance Sue Gander Director, Environment, Energy, and Natural Resources Division National Governors AssociationCenter for Best Practices

Goldman, Charles

2010-01-01T23:59:59.000Z

165

The National Energy Modeling System: An Overview 1998 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

COMMERCIAL DEMAND MODULE COMMERCIAL DEMAND MODULE blueball.gif (205 bytes) Floorspace Submodule blueball.gif (205 bytes) Energy Service Demand Submodule blueball.gif (205 bytes) Equipment Choice Submodule blueball.gif (205 bytes) Energy Consumption Submodule The commercial demand module (CDM) forecasts energy consumption by Census division for eight marketed energy sources plus solar thermal energy. For the three major commercial sector fuels, electricity, natural gas and distillate oil, the CDM is a "structural" model and its forecasts are built up from projections of the commercial floorspace stock and of the energy-consuming equipment contained therein. For the remaining five marketed "minor fuels," simple econometric projections are made. The commercial sector encompasses business establishments that are not

166

EIA - Assumptions to the Annual Energy Outlook 2009 - Industrial Demand  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2009 Industrial Demand Module Table 6.1. Industry Categories. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Table 6.2.Retirement Rates. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 nonmanufacturing 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

167

ENABLING ENERGY DEMAND RESPONSE WITH VEHICULAR MESH NETWORKS  

E-Print Network [OSTI]

ENABLING ENERGY DEMAND RESPONSE WITH VEHICULAR MESH NETWORKS Howard CheHao Chang1, Haining Du2. Using VMesh to connect disjoint sensor networks One of our expectations for VMesh is to enable demand response (DR) [1] for automatic utility usage retrievals and price dispatching. DR is a project in- itiated

Chuah, Chen-Nee

168

Assumptions to the Annual Energy Outlook 2001 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. 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 Commercial Buildings Energy Consumption Survey (CBECS) for

169

Assumptions to the Annual Energy Outlook 2002 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. 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 Commercial Buildings Energy Consumption Survey (CBECS) for

170

Energy Demand Modelling Introduction to the PhD project  

E-Print Network [OSTI]

Energy Demand Modelling Introduction to the PhD project Erika Zvingilaite Risø DTU System Analysis for optimization of energy systems Environmental effects Global externalities cost of CO2 Future scenarios for the Nordic energy systems 2010, 2020, 2030, 2040, 2050 (energy-production, consumption, emissions, net costs

171

USA Energy Demand and World Markets  

Science Journals Connector (OSTI)

In the AEO95 model reference case scenario, the United States is projected to consume 104 quadrillion Btu of primary energy resources in 2010, 19 percent more than in 1993. Primary energy consumption includes ...

Charles E. Brown Ph.D.

2002-01-01T23:59:59.000Z

172

High Energy Demand and Supply Scenario  

Science Journals Connector (OSTI)

An adequate energy supply system is a key issue in ... industrialization that will call for a significantly larger energy supply. Sustaining economic growth in the industrialized ... will add considerably to the ...

H.-H. Rogner; W. Sassin

1980-01-01T23:59:59.000Z

173

Estimating Demand Response Market Potential | Open Energy Information  

Open Energy Info (EERE)

Estimating Demand Response Market Potential Estimating Demand Response Market Potential Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Estimating Demand Response Market Potential Focus Area: Energy Efficiency, - Utility Topics: Socio-Economic Website: www.ieadsm.org/Files/Tasks/Task%20XIII%20-%20Demand%20Response%20Resou Equivalent URI: cleanenergysolutions.org/content/estimating-demand-response-market-pot Language: English Policies: "Deployment Programs,Regulations" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Demonstration & Implementation Regulations: Resource Integration Planning This resource presents demand response (DR) potential results from top-performing programs in the United States and Canada, as well as a DR

174

Advanced Control Technologies and Strategies Linking Demand Response and Energy Efficiency  

E-Print Network [OSTI]

fits into historical demand side management (DSM) concepts.response. Demand Side Management Energy Efficiency (Daily) -requirements and demand side management issues have also

Kiliccote, Sila; Piette, Mary Ann

2005-01-01T23:59:59.000Z

175

Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumption to the Annual Energy Outlook Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—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 (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions (see Figure 5). The Residential Demand Module also requires projections of available equipment and their installed costs over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

176

EIA - Assumptions to the Annual Energy Outlook 2009 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2009 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 use 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” by appliance (or UEC—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 (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions (see Figure 5). The Residential Demand Module also requires projections of available equipment and their installed costs over the projection horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the projection horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

177

Assumptions to the Annual Energy Outlook 2002 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—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 (single-family, multifamily and mobile homes) and

178

Assumptions to the Annual Energy Outlook 2001 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—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 (single-family, multifamily and mobile homes) and

179

Agreement for Energy Conservation and Demand Side Management Services Template  

Broader source: Energy.gov [DOE]

Document features a template agreement between a U.S. Federal agency and a utility company for the implementation of energy conservation measures (ECMs) and demand side management (DSM) services.

180

Outlook for Energy Supply and Demand in China  

Science Journals Connector (OSTI)

In the new century, China has entered the phase of Homeland Construction. As the process of urbanization and industrialization accelerates, demand on energy has experienced unprecedentedly rapid growth. By far .....

Yande Dai

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total energy 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

Hydrogen Demand and Resource Assessment Tool | Open Energy Information  

Open Energy Info (EERE)

Hydrogen Demand and Resource Assessment Tool Hydrogen Demand and Resource Assessment Tool Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Hydrogen Demand and Resource Assessment Tool Agency/Company /Organization: National Renewable Energy Laboratory Sector: Energy Focus Area: Hydrogen, Transportation Topics: Technology characterizations Resource Type: Dataset, Software/modeling tools User Interface: Website Website: maps.nrel.gov/ Web Application Link: maps.nrel.gov/hydra Cost: Free Language: English References: http://maps.nrel.gov/hydra Logo: Hydrogen Demand and Resource Assessment Tool Use HyDRA to view, download, and analyze hydrogen data spatially and dynamically. HyDRA provides access to hydrogen demand, resource, infrastructure, cost, production, and distribution data. A user account is

182

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

to ensure reliability. Capacity market programs: Customerswholesale, forward capacity markets offer new opportunitiesinto the forward-capacity market. Coordination of Energy

Goldman, Charles

2010-01-01T23:59:59.000Z

183

Opportunities for Energy Efficiency and Demand Response in the California Cement Industry  

E-Print Network [OSTI]

OpportunitiesforEnergy EfficiencyandDemandResponseinAgricultural/WaterEnd?UseEnergyEfficiencyProgram. i1 4.0 EnergyEfficiencyandDemandResponse

Olsen, Daniel

2012-01-01T23:59:59.000Z

184

EIA-Assumptions to the Annual Energy Outlook - Transportation Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2007 Transportation Demand Module The NEMS Transportation Demand Module estimates 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 isthe 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), freight and passenger aircraft, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

185

Energy Demand and GHG Mitigation Options  

Science Journals Connector (OSTI)

N. African countries, although not committed to reduce their GHG emissions, can take advantage of their high ... CSP potential in order to contribute to the GHG mitigation effort by providing clean energy (potent...

Leonidas Paroussos; Pantelis Capros

2013-01-01T23:59:59.000Z

186

Modelling and Assessment of Energy Demand  

Science Journals Connector (OSTI)

Until the four-fold increase in oil prices in 1973 energy* was generally taken as abundantly available cheap commodity with the result that its consumption was increasing very rapidly. It increased by a factor...

A. M. Khan

1984-01-01T23:59:59.000Z

187

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

SciTech Connect (OSTI)

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

Neubauer, J.; Simpson, M.

2013-10-01T23:59:59.000Z

188

LEAPs and Boundsan Energy Demand and Constraint Optimised Model of the Irish Energy System  

Science Journals Connector (OSTI)

This paper builds a model of energy demand and supply for Ireland with a focus on evaluating, and providing insights for, energy efficiency policies. The demand-side comprises sectoral sub-models, with a ... line...

Fionn Rogan; Caiman J. Cahill; Hannah E. Daly; Denis Dineen

2014-06-01T23:59:59.000Z

189

The National Energy Modeling System: An Overview 1998 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

RESIDENTIAL DEMAND MODULE RESIDENTIAL DEMAND MODULE blueball.gif (205 bytes) Housing Stock Submodule blueball.gif (205 bytes) Appliance Stock Submodule blueball.gif (205 bytes) Technology Choice Submodule blueball.gif (205 bytes) Shell Integrity Submodule blueball.gif (205 bytes) Fuel Consumption Submodule The residential demand module (RDM) forecasts energy consumption by Census division for seven marketed energy sources plus solar thermal and geothermal energy. The RDM is a structural model and its forecasts are built up from projections of the residential housing stock and of the energy-consuming equipment contained therein. The components of the RDM and its interactions with the NEMS system are shown in Figure 5. NEMS provides forecasts of residential energy prices, population, and housing starts,

190

Assessment of Achievable Potential from Energy Efficiency and Demand  

Open Energy Info (EERE)

Assessment of Achievable Potential from Energy Efficiency and Demand Assessment of Achievable Potential from Energy Efficiency and Demand Response Programs in the United States (U.S.) (2010-2030) Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Assessment of Achievable Potential from Energy Efficiency and Demand Response Programs in the United States (U.S.) (2010-2030) Focus Area: Energy Efficiency, - Utility Topics: Policy Impacts Website: www.edisonfoundation.net/IEE/Documents/EPRI_AssessmentAchievableEEPote Equivalent URI: cleanenergysolutions.org/content/assessment-achievable-potential-energ Language: English Policies: Regulations Regulations: Mandates/Targets This report discusses the 2008 U.S. Energy Information Administration statistic that electricity consumption in the United States is predicted to

191

EIA - International Energy Outlook 2009-World Energy Demand and Economic  

Gasoline and Diesel Fuel Update (EIA)

Liquid Fuels Liquid Fuels International Energy Outlook 2009 Chapter 2 - Liquid Fuels World liquids consumption in the IEO2009 reference case increases from 85 million barrels per day in 2006 to 107 million barrels per day in 2030. Unconventional liquids, at 13.4 million barrels per day, make up 12.6 percent of total liquids production in 2030. Figure 25. World Liquids Consumption by Region and Country Group, 2006 and 2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 26. World Liquids Supply in Three Cases, 2006 and 2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 27. World Production of Unconventional Liquid Fuels, 2006-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800.

192

Driving change : evaluating strategies to control automotive energy demand growth in China ; Evaluating strategies to control automotive energy demand growth in China .  

E-Print Network [OSTI]

??As the number of vehicles in China has relentlessly grown in the past decade, the energy demand, fuel demand and greenhouse gas emissions associated with (more)

Bonde kerlind, Ingrid Gudrun

2013-01-01T23:59:59.000Z

193

Tankless or Demand-Type Water Heaters | Department of Energy  

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

Tankless or Demand-Type Water Heaters Tankless or Demand-Type Water Heaters Tankless or Demand-Type Water Heaters May 2, 2012 - 6:47pm Addthis Diagram of a tankless water heater. Diagram of a tankless water heater. How does it work? Tankless water heaters deliver hot water as it is needed, eliminating the need for storage tanks. Tankless water heaters, also known as demand-type or instantaneous water heaters, provide hot water only as it is needed. They don't produce the standby energy losses associated with storage water heaters, which can save you money. Here you'll find basic information about how they work, whether a tankless water heater might be right for your home, and what criteria to use when selecting the right model. Check out the Energy Saver 101: Water Heating infographic to learn if a tankless water heater is right for you.

194

COMBINING DIVERSE DATA SOURCES FOR CEDSS, AN AGENT-BASED MODEL OF DOMESTIC ENERGY DEMAND  

E-Print Network [OSTI]

purposes of calculating energy demand for water-heating, thethese questions, and energy demand. Given the lack of real-to calculate useful energy demand for space heating. With

Gotts, Nicholas Mark; Polhill, Gary; Craig, Tony; Galan-Diaz, Carlos

2014-01-01T23:59:59.000Z

195

Water supply and demand in an energy supply model  

SciTech Connect (OSTI)

This report describes a tool for water and energy-related policy analysis, the development of a water supply and demand sector in a linear programming model of energy supply in the United States. The model allows adjustments in the input mix and plant siting in response to water scarcity. Thus, on the demand side energy conversion facilities can substitute more costly dry cooling systems for conventional evaporative systems. On the supply side groundwater and water purchased from irrigators are available as more costly alternatives to unappropriated surface water. Water supply data is developed for 30 regions in 10 Western states. Preliminary results for a 1990 energy demand scenario suggest that, at this level of spatial analysis, water availability plays a minor role in plant siting. Future policy applications of the modeling system are discussed including the evaluation of alternative patterns of synthetic fuels development.

Abbey, D; Loose, V

1980-12-01T23:59:59.000Z

196

Energy Conservation and Commercialization in Gujarat: Report On Demand Side  

Open Energy Info (EERE)

Energy Conservation and Commercialization in Gujarat: Report On Demand Side Energy Conservation and Commercialization in Gujarat: Report On Demand Side Management (DSM) In Gujarat Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Energy Conservation and Commercialization in Gujarat: Report On Demand Side Management (DSM) In Gujarat Focus Area: Crosscutting Topics: Opportunity Assessment & Screening Website: eco3.org/wp-content/plugins/downloads-manager/upload/Report%20on%20Dem Equivalent URI: cleanenergysolutions.org/content/energy-conservation-and-commercializa Language: English Policies: "Deployment Programs,Financial Incentives,Regulations" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Technical Assistance Regulations: Resource Integration Planning

197

Energy and Demand Savings from Implementation Costs in Industrial Facilities  

E-Print Network [OSTI]

, electrical consumption, demand and fees were tracked separately. The remaining data include only one energy stream (e.g., natural gas) in each code [6]. Table 1. Energy Streams STREAM CODE Electrical Consumption EC Electrical Demand ED Other... Electrical Fees EF Electricity E1 Natural Gas E2 L.P.G. E3 #1 Fuel Oil E4 #2 Fuel Oil E5 #4 Fuel Oil E6 #6 Fuel Oil E7 Coal E8 Wood E9 Paper E10 Other Gas E11 Other Energy E12 ESL-IE-00-04-17 Proceedings from the Twenty-second National...

Razinha, J. A.; Heffington, W. M.

198

ADB-Methods and Tools for Energy Demand Projection | Open Energy  

Open Energy Info (EERE)

ADB-Methods and Tools for Energy Demand Projection ADB-Methods and Tools for Energy Demand Projection Jump to: navigation, search Tool Summary Name: Methods and Tools for Energy Demand Projection Agency/Company /Organization: Asian Development Bank Sector: Energy Topics: Pathways analysis Resource Type: Presentation, Software/modeling tools Website: cdm-mongolia.com/files/2_Methods_Hoseok_16May2010.pdf Cost: Free Methods and Tools for Energy Demand Projection Screenshot References: Methods and Tools for Energy Demand Projection[1] This article is a stub. You can help OpenEI by expanding it. References ↑ "Methods and Tools for Energy Demand Projection" Retrieved from "http://en.openei.org/w/index.php?title=ADB-Methods_and_Tools_for_Energy_Demand_Projection&oldid=398945" Categories:

199

Energy demand and indoor climate of a traditional low-energy building in a hot climate.  

E-Print Network [OSTI]

?? Energy demand in the built environment is quite important. China holds a large population and the energy use in the building sector is about (more)

Li, Ang

2009-01-01T23:59:59.000Z

200

Opportunities for Energy Efficiency and Demand Response in the California  

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

Opportunities for Energy Efficiency and Demand Response in the California Opportunities for Energy Efficiency and Demand Response in the California Cement Industry Title Opportunities for Energy Efficiency and Demand Response in the California Cement Industry Publication Type Report LBNL Report Number LBNL-4849E Year of Publication 2010 Authors Olsen, Daniel, Sasank Goli, David Faulkner, and Aimee T. McKane Date Published 12/2010 Publisher CEC/LBNL Keywords cement industry, cement sector, demand response, electricity use, energy efficiency, market sectors, mineral manufacturing, technologies Abstract This study examines the characteristics of cement plants and their ability to shed or shift load to participate in demand response (DR). Relevant factors investigated include the various equipment and processes used to make cement, the operational limitations cement plants are subject to, and the quantities and sources of energy used in the cement-making process. Opportunities for energy efficiency improvements are also reviewed. The results suggest that cement plants are good candidates for DR participation. The cement industry consumes over 400 trillion Btu of energy annually in the United States, and consumes over 150 MW of electricity in California alone. The chemical reactions required to make cement occur only in the cement kiln, and intermediate products are routinely stored between processing stages without negative effects. Cement plants also operate continuously for months at a time between shutdowns, allowing flexibility in operational scheduling. In addition, several examples of cement plants altering their electricity consumption based on utility incentives are discussed. Further study is needed to determine the practical potential for automated demand response (Auto-DR) and to investigate the magnitude and shape of achievable sheds and shifts.

Note: This page contains sample records for the topic "total energy 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

Application-oriented modelling of domestic energy demand  

Science Journals Connector (OSTI)

Abstract Detailed residential energy consumption data can be used to offer advanced services and provide new business opportunities to all participants in the energy supply chain, including utilities, distributors and customers. The increasing interest in the residential consumption data is behind the roll-out of smart meters in large areas and led to intensified research efforts in new data acquisition technologies for the energy sector. This paper introduces a novel model for generation of residential energy consumption profiles based on the energy demand contribution of each household appliance and calculated by using a probabilistic approach. The model takes into consideration a wide range of household appliances and its modular structure provides a high degree of flexibility. Residential consumption data generated by the proposed model are suitable for development of new services and applications such as residential real-time pricing schemes or tools for energy demand prediction. To demonstrate the main features of the model, an individual household consumption was created and the effects of a possible change in the user behaviour and the appliance configuration presented. In order to show the flexibility offered in creation of the aggregated demand, the detailed simulation results of an energy demand management algorithm applied to an aggregated user group are used.

J.K. Gruber; S. Jahromizadeh; M. Prodanovi?; V. Rako?evi?

2014-01-01T23:59:59.000Z

202

Page 1 of 23 Decreasing Demand: Attempting to Facilitate Energy Conservation by  

E-Print Network [OSTI]

gas emissions, 82% are carbon dioxide emissions related to energy consumption (EIA, 2006).The average demand-side methods to reduce emissions is also crucial and is an area ripe for research. Reducing CO2's population and produces 25% of the world's total CO2 emissions (EPA, 2000).Of the United States greenhouse

Attari, Shahzeen Z.

203

TENESOL formerly known as TOTAL ENERGIE | Open Energy Information  

Open Energy Info (EERE)

TENESOL formerly known as TOTAL ENERGIE TENESOL formerly known as TOTAL ENERGIE Jump to: navigation, search Name TENESOL (formerly known as TOTAL ENERGIE) Place la Tour de Salvagny, France Zip 69890 Sector Solar Product Makes polycrystalline silicon modules, and PV-based products such as solar powered pumps. References TENESOL (formerly known as TOTAL ENERGIE)[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. TENESOL (formerly known as TOTAL ENERGIE) is a company located in la Tour de Salvagny, France . References ↑ "TENESOL (formerly known as TOTAL ENERGIE)" Retrieved from "http://en.openei.org/w/index.php?title=TENESOL_formerly_known_as_TOTAL_ENERGIE&oldid=352112" Categories:

204

Assumptions to the Annual Energy Outlook 2000 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. The energy-intensive industries are modeled through the use of a detailed process flow accounting procedure, whereas the nonenergy-intensive and the nonmanufacturing industries are modeled with substantially less detail (Table 14). The Industrial Demand Module forecasts energy consumption at the four Census region levels; energy consumption at the Census Division level is allocated by using the SEDS24 data.

205

Measured energy savings and demand reduction from a reflective roof membrane on a large retail store in Austin  

E-Print Network [OSTI]

the abated annual energy and demand expenditures, simplea/c annual abated energy and demand expenditures and presentof future abated energy and demand expenditures is estimated

Konopacki, Steven J.; Akbari, Hashem

2001-01-01T23:59:59.000Z

206

The impact of future energy demand on renewable energy production Case of Norway  

Science Journals Connector (OSTI)

Abstract Projections of energy demand are an important part of analyses of policies to promote conservation, efficiency, technology implementation and renewable energy production. The development of energy demand is a key driver of the future energy system. This paper presents long-term projections of the Norwegian energy demand as a two-step methodology of first using activities and intensities to calculate a demand of energy services, and secondly use this as input to the energy system model TIMES-Norway to optimize the Norwegian energy system. Long-term energy demand projections are uncertain and the purpose of this paper is to illustrate the impact of different projections on the energy system. The results of the analyses show that decreased energy demand results in a higher renewable fraction compared to an increased demand, and the renewable energy production increases with increased energy demand. The most profitable solution to cover increased demand is to increase the use of bio energy and to implement energy efficiency measures. To increase the wind power production, an increased renewable target or higher electricity export prices have to be fulfilled, in combination with more electricity export.

Eva Rosenberg; Arne Lind; Kari Aamodt Espegren

2013-01-01T23:59:59.000Z

207

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

commercial.gif (5196 bytes) commercial.gif (5196 bytes) The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. 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 Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

208

The National Energy Modeling System: An Overview 2000 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

residential demand module (RDM) forecasts energy consumption by Census division for seven marketed energy sources plus solar and geothermal energy. RDM is a structural model and its forecasts are built up from projections of the residential housing stock and of the energy-consuming equipment contained therein. The components of RDM and its interactions with the NEMS system are shown in Figure 5. NEMS provides forecasts of residential energy prices, population, and housing starts, which are used by RDM to develop forecasts of energy consumption by fuel and Census division. residential demand module (RDM) forecasts energy consumption by Census division for seven marketed energy sources plus solar and geothermal energy. RDM is a structural model and its forecasts are built up from projections of the residential housing stock and of the energy-consuming equipment contained therein. The components of RDM and its interactions with the NEMS system are shown in Figure 5. NEMS provides forecasts of residential energy prices, population, and housing starts, which are used by RDM to develop forecasts of energy consumption by fuel and Census division. Figure 5. Residential Demand Module Structure RDM incorporates the effects of four broadly-defined determinants of energy consumption: economic and demographic effects, structural effects, technology turnover and advancement effects, and energy market effects. Economic and demographic effects include the number, dwelling type (single-family, multi-family or mobile homes), occupants per household, and location of housing units. Structural effects include increasing average dwelling size and changes in the mix of desired end-use services provided by energy (new end uses and/or increasing penetration of current end uses, such as the increasing popularity of electronic equipment and computers). Technology effects include changes in the stock of installed equipment caused by normal turnover of old, worn out equipment with newer versions which tend to be more energy efficient, the integrated effects of equipment and building shell (insulation level) in new construction, and in the projected availability of even more energy-efficient equipment in the future. Energy market effects include the short-run effects of energy prices on energy demands, the longer-run effects of energy prices on the efficiency of purchased equipment and the efficiency of building shells, and limitations on minimum levels of efficiency imposed by legislated efficiency standards.

209

Assumptions to the Annual Energy Outlook - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumption to the Annual Energy Outlook Industrial Demand Module Table 17. Industry Categories Printer Friendly Version Energy-Intensive Manufacturing Nonenergy-Intensive Manufacturing Nonmanufacturing Industries Food and Kindred Products (NAICS 311) Metals-Based Durables (NAICS 332-336) Agricultural Production -Crops (NAICS 111) Paper and Allied Products (NAICS 322) Balance of Manufacturing (all remaining manufacturing NAICS) Other Agriculture Including Livestock (NAICS112- 115) Bulk Chemicals (NAICS 32B) Coal Mining (NAICS 2121) Glass and Glass Products (NAICS 3272) Oil and Gas Extraction (NAICS 211) Hydraulic Cement (NAICS 32731) Metal and Other Nonmetallic Mining (NAICS 2122- 2123) Blast Furnaces and Basic Steel (NAICS 331111) Construction (NAICS233-235)

210

The National Energy Modeling System: An Overview 2000 - Industrial Demand  

Gasoline and Diesel Fuel Update (EIA)

industrial demand module (IDM) forecasts energy consumption for fuels and feedstocks for nine manufacturing industries and six nonmanufactur- ing industries, subject to delivered prices of energy and macroeconomic variables representing the value of output for each industry. The module includes industrial cogeneration of electricity that is either used in the industrial sector or sold to the electricity grid. The IDM structure is shown in Figure 7. industrial demand module (IDM) forecasts energy consumption for fuels and feedstocks for nine manufacturing industries and six nonmanufactur- ing industries, subject to delivered prices of energy and macroeconomic variables representing the value of output for each industry. The module includes industrial cogeneration of electricity that is either used in the industrial sector or sold to the electricity grid. The IDM structure is shown in Figure 7. Figure 7. Industrial Demand Module Structure Industrial energy demand is projected as a combination of “bottom up” characterizations of the energy-using technology and “top down” econometric estimates of behavior. The influence of energy prices on industrial energy consumption is modeled in terms of the efficiency of use of existing capital, the efficiency of new capital acquisitions, and the mix of fuels utilized, given existing capital stocks. Energy conservation from technological change is represented over time by trend-based “technology possibility curves.” These curves represent the aggregate efficiency of all new technologies that are likely to penetrate the future markets as well as the aggregate improvement in efficiency of 1994 technology.

211

A Supply-Demand Model Based Scalable Energy Management System for Improved Energy  

E-Print Network [OSTI]

the dependency of an electronic system to primary energy sources (i.e. AC power or battery). For reliable energy generation and consumption parameters. The system uses economics inspired supply-demand modelA Supply-Demand Model Based Scalable Energy Management System for Improved Energy Utilization

Bhunia, Swarup

212

Assumptions to the Annual Energy Outlook 2001 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Comleted Copy in PDF Format Comleted Copy in PDF Format Related Links Annual Energy Outlook 2001 Supplemental Data to the AEO 2001 NEMS Conference To Forecasting Home Page EIA Homepage Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. 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 19). The

213

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network [OSTI]

that energy efficiency or energy intensity for a particularbased upon trends in energy intensity parameters which areBuilding type (12) Energy intensity Industrial Shipments

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

2008-01-01T23:59:59.000Z

214

Modeling Fossil Energy Demands of Primary Nonferrous Metal Production: The Case of Copper  

Science Journals Connector (OSTI)

Modeling Fossil Energy Demands of Primary Nonferrous Metal Production: The Case of Copper ... Alumbrera (Argentina) ...

Pilar Swart; Jo Dewulf

2013-11-22T23:59:59.000Z

215

An On-demand Minimum Energy Routing Protocol for a Wireless Ad Hoc Network  

E-Print Network [OSTI]

An On-demand Minimum Energy Routing Protocol for a Wireless Ad Hoc Network Sheetalkumar Doshi of an on-demand minimum energy routing protocol and suggests mechanisms for their imple- mentation. We of an on-demand minimum energy routing protocol in terms of energy savings with an existing on-demand ad

216

Assumptions to the Annual Energy Outlook 1999 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

residential.gif (5487 bytes) residential.gif (5487 bytes) The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—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 (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

217

Assumptions to the Annual Energy Outlook 2000 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—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 (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

218

National patterns of energy demand and expenditures by Hispanics  

SciTech Connect (OSTI)

This paper is based on ongoing research, at Argonne National Laboratory, being done for the Office of Minority Economic Impact (MI) of the US Department of Energy. Under its legislative mandate MI is required to assess the impact of government policy, programs, and actions on US minorities. In line with this mission Argonne is currently involved in characterizing and analyzing the patterns of energy demand and expenditures of minorities. A major barrier associated with this task is the availability of sufficient data. With the possible exception of blacks, analysis of the patterns of energy demand for most minority population categories is all but impossible because of small sample sizes. The major source of residential energy consumption data, the Residential Energy Consumption Survey, only collects data on 5000 to 7000 households. For many minority population categories, this number of observations make any meaningful statistical analysis at least at the regional Census level practically impossible, with any further refinement of the analysis becoming even more difficult. In this paper our primary purpose is to describe the patterns of energy demand for Hispanics and nonhispanics but ancillary to that briefly present one possible solution to the data availability problem.

Poyer, D.A.

1987-01-01T23:59:59.000Z

219

Breaking down the silos: the integration of energy efficiency, renewable energy, demand response and climate change  

Science Journals Connector (OSTI)

This paper explores the feasibility of integrating energy efficiency program evaluation with the emerging need for the evaluation of programs from different energy cultures (demand response, renewable energy, a...

Edward Vine

2008-02-01T23:59:59.000Z

220

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

Note: This page contains sample records for the topic "total energy 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

Automated Demand Response Approaches to Household Energy Management in a Smart Grid Environment.  

E-Print Network [OSTI]

??The advancement of renewable energy technologies and the deregulation of theelectricity market have seen the emergence of Demand response (DR) programs. Demand response is a (more)

Adika, Christopher Otieno

2014-01-01T23:59:59.000Z

222

Outlook for Light-Duty-Vehicle Fuel Demand | Department of Energy  

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

Outlook for Light-Duty-Vehicle Fuel Demand Outlook for Light-Duty-Vehicle Fuel Demand Gasoline and distillate demand impact of the Energy Independance and Security Act of 2007...

223

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Total Energy Flow, (Quadrillion Btu) Total Energy Flow, (Quadrillion Btu) Total Energy Flow diagram image Footnotes: 1 Includes lease condensate. 2 Natural gas plant liquids. 3 Conventional hydroelectric power, biomass, geothermal, solar/photovoltaic, and wind. 4 Crude oil and petroleum products. Includes imports into the Strategic Petroleum Reserve. 5 Natural gas, coal, coal coke, biofuels, and electricity. 6 Adjustments, losses, and unaccounted for. 7 Natural gas only; excludes supplemental gaseous fuels. 8 Petroleum products, including natural gas plant liquids, and crude oil burned as fuel. 9 Includes 0.01 quadrillion Btu of coal coke net exports. 10 Includes 0.13 quadrillion Btu of electricity net imports. 11 Total energy consumption, which is the sum of primary energy consumption, electricity retail sales, and electrical system energy losses.

224

Experts Meeting: Behavioral Economics as Applied to Energy Demand Analysis and Energy Efficiency Programs  

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

Experts Meeting: Behavioral Economics Experts Meeting: Behavioral Economics as Applied to Energy Demand Analysis and Energy Efficiency Programs EIA Office of Energy Consumption and Efficiency Analysis July 17, 2013 | Washington, DC Meeting Agenda Jim Turnure, Director, Office of Energy Consumption and Efficiency Analysis July 17, 2013 2 * EIA WELCOME AND INTRODUCTION (15 minutes) * ORIENTATION/PRESENTATION: OVERVIEW OF EIA RESIDENTIAL AND COMMERCIAL DEMAND MODELS AND CURRENT METHODS FOR INCORPORATING ENERGY EFFICIENCY/EFFICIENCY PROGRAMS (30 minutes) * ORIENTATION/PRESENTATION: BEHAVIORAL ECONOMICS GENERAL OVERVIEW AND DISCUSSION (45 minutes) * EXPERTS ROUNDTABLE DISCUSSION/BRAINSTROMING: HOW CAN EIA BENEFIT FROM APPLICATION OF BEHAVIORAL ECONOMICS TO RESIDENTIAL AND COMMERCIAL ENERGY DEMAND MODELING?

225

Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report  

E-Print Network [OSTI]

produce the greatest energy and demand savings. Aeration andand C.Y. Chang (2005). "Energy Demand in Sludge Dewatering."be modified to reduce energy demand during demand response

Lekov, Alex

2010-01-01T23:59:59.000Z

226

Modeling Energy Demand Dependency in Smart Multi-Energy Systems  

Science Journals Connector (OSTI)

Smart local energy networks provide an opportunity for more penetration of distributed energy resources. However, these resources cause an ... for internal and external dependencies in Smart Multi-Energy Systems ...

N. Neyestani; Maziar Yazdani Damavandi

2014-01-01T23:59:59.000Z

227

Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;  

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

Next MECS will be conducted in 2010 Table 5.8 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal Net Demand Residual and LPG and (excluding Coal End Use for Electricity(a) Fuel Oil Diesel Fuel(b) Natural Gas(c) NGL(d) Coke and Breeze) Total United States TOTAL FUEL CONSUMPTION 3,335 251 129 5,512 79 1,016 Indirect Uses-Boiler Fuel 84 133 23 2,119 8 547 Conventional Boiler Use 84 71 17 1,281 8 129 CHP and/or Cogeneration Process 0 62 6 838 1 417 Direct Uses-Total Process 2,639 62 52 2,788 39 412 Process Heating 379 59 19 2,487 32 345 Process Cooling and Refrigeration

228

Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;  

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

7 End Uses of Fuel Consumption, 2006; 7 End Uses of Fuel Consumption, 2006; Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Demand Residual and Natural Gas(c) LPG and Coke and Breeze) for Electricity(a) Fuel Oil Diesel Fuel(b) (billion NGL(d) (million End Use (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) Total United States TOTAL FUEL CONSUMPTION 977,338 40 22 5,357 21 46 Indirect Uses-Boiler Fuel 24,584 21 4 2,059 2 25 Conventional Boiler Use 24,584 11 3 1,245 2 6 CHP and/or Cogeneration Process 0 10 1 814 * 19 Direct Uses-Total Process 773,574 10 9 2,709 10 19 Process Heating

229

Demand Response Resources for Energy and Ancillary Services (Presentation)  

SciTech Connect (OSTI)

Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind an solar power generation. However, DR in grid models is limited by data availability and modeling complexity. This presentation focuses on the co-optimization of DR resources to provide energy and ancillary services in a production cost model of the Colorado test system. We assume each DR resource can provide energy services by either shedding load or shifting its use between different times, as well as operating

Hummon, M.

2014-04-01T23:59:59.000Z

230

Behavioral Economics Applied to Energy Demand Analysis: A Foundation  

Reports and Publications (EIA)

Neoclassical economics has shaped our understanding of human behavior for several decades. While still an important starting point for economic studies, neoclassical frameworks have generally imposed strong assumptions, for example regarding utility maximization, information, and foresight, while treating consumer preferences as given or external to the framework. In real life, however, such strong assumptions tend to be less than fully valid. Behavioral economics refers to the study and formalizing of theories regarding deviations from traditionally-modeled economic decision-making in the behavior of individuals. The U.S. Energy Information Administration (EIA) has an interest in behavioral economics as one influence on energy demand.

2014-01-01T23:59:59.000Z

231

Meeting the Clean Energy Demand:? Nanostructure Architectures for Solar Energy Conversion  

Science Journals Connector (OSTI)

Meeting the Clean Energy Demand:? Nanostructure Architectures for Solar Energy Conversion ... This account further highlights some of the recent developments in these areas and points out the factors that limit the efficiency optimization. ...

Prashant V. Kamat

2007-02-01T23:59:59.000Z

232

CALIFORNIA ENERGY CALIFORNIA ENERGY DEMAND 2010-2020  

E-Print Network [OSTI]

prepared the industrial forecast. Mark Ciminelli forecasted energy for transportation, communication developed the energy efficiency program estimates. Glen Sharp prepared the residential sector forecast ................................................................................................................... 2 EndUser Natural Gas Forecast Results

233

Division of IT Convergence Engineering Optimal Demand-Side Energy Management Under  

E-Print Network [OSTI]

Division of IT Convergence Engineering Optimal Demand-Side Energy Management Under Real-time Demand and wastage through better demand-side management and control is considered a key solution ingredient of appliance specific adapters. Designed and implemented GHS Modeled the demand-side energy management

Boutaba, Raouf

234

Total Energy Facilities Biomass Facility | Open Energy Information  

Open Energy Info (EERE)

Total Energy Facilities Biomass Facility Total Energy Facilities Biomass Facility Jump to: navigation, search Name Total Energy Facilities Biomass Facility Facility Total Energy Facilities Sector Biomass Facility Type Non-Fossil Waste Location Los Angeles County, California Coordinates 34.3871821°, -118.1122679° 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":34.3871821,"lon":-118.1122679,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

235

An On-demand Minimum Energy Routing Protocol for a Wireless Ad Hoc Network  

E-Print Network [OSTI]

An On-demand Minimum Energy Routing Protocol for a Wireless Ad Hoc Network Sheetalkumar Doshi the necessary features of an on-demand minimum energy routing protocol and suggests mechanisms the performance of an on-demand minimum energy routing protocol in terms of energy savings with an existing on

Brown, Timothy X.

236

STRENGTH AND ENERGY DEMANDS FROM THE AUGUST 1999 KOCAELI EARTHQUAKE GROUND MOTIONS  

E-Print Network [OSTI]

STRENGTH AND ENERGY DEMANDS FROM THE AUGUST 1999 KOCAELI EARTHQUAKE GROUND MOTIONS A. Sari 1 and L the demands placed on structures during earthquakes one might also employ an energy-based approach, especially such as absorbed energy (Chou and Uang, 2000) and input energy (Chapman, 1999). Understanding seismic demands

Manuel, Lance

237

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

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

238

Energy Use in the Australian Manufacturing Industry: An Analysis of Energy Demand Elasticity  

E-Print Network [OSTI]

Energy Use in the Australian Manufacturing Industry: An Analysis of Energy Demand Elasticity Chris in this paper. Energy consumption data was sourced from the Bureau of Resources and Energy Economics' Australian Energy Statistics publication. Price and income data were sourced from the Australian Bureau

239

U.S. Energy Demand: Some Low Energy Futures  

Science Journals Connector (OSTI)

...sophistication for energy consumption. | Journal Article...ac-tivities related to fuel conservation. The...processes, not only in fuel con-servation...History ofthe Steam Engine (Cambridge Univ...coal-fired steam to diesel) but much is at-tributable...sophistication for energy consumption. The scenarios...

1978-04-14T23:59:59.000Z

240

National Action Plan on Demand Response | Department of Energy  

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

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

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


241

Energy demand of German households and saving potential  

Science Journals Connector (OSTI)

The implementation of the principles of sustainable development requires both using potentialities in saving resources and cutting down emissions (efficiency strategies) as well as more conscious patterns of behaviour of the actors involved (sufficiency strategies). Starting from the current situation of annual CO2 emissions of about 10 t and a sustainability goal of 1??2 t CO2 emissions per inhabitant and year, the question arises in how far households can contribute to achieve this goal. Therefore, in this paper, the environmental impacts of the energy demand of German households will be evaluated by means of describing its status quo and there from deriving saving potentials.

Anke Eber; Dominik Most; Otto Rentz; Thomas Lutzkendorf

2008-01-01T23:59:59.000Z

242

AVTA: PHEV Demand and Energy Cost Demonstration Report  

Broader source: Energy.gov [DOE]

The Vehicle Technologies Office's Advanced Vehicle Testing Activity carries out testing on a wide range of advanced vehicles and technologies on dynamometers, closed test tracks, and on-the-road. These results provide benchmark data that researchers can use to develop technology models and guide future research and development. The following report describes results from a demonstration with Tacoma Power on plug-in hybrid electric vehicle demand and energy cost, as informed by the AVTA's testing on plug-in electric vehicle charging equipment. This research was conducted by Idaho National Laboratory.

243

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

September 2012 PDF | previous editions September 2012 PDF | previous editions Release Date: September 27, 2012 A report of historical annual energy statistics. For many series, data begin with the year 1949. Included are data on total energy production, consumption, and trade; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, as well as financial and environmental indicators; and data unit conversion tables. About the data Previous Editions + EXPAND ALL Annual Energy Review 2011 Edition PDF (Full issue) Annual Energy Review 2011 - Released on September 27, 2012 PDF Annual Energy Review 2010 Edition PDF (Full issue) Annual Energy Review 2010 - Released on October 19, 2011 PDF Annual Energy Review 2009 Edition PDF (Full issue) Annual Energy Review 2009 - Released on August 19, 2010 PDF

244

A critical review of single fuel and interfuel substitution residential energy demand models  

E-Print Network [OSTI]

The overall purpose of this paper is to formulate a model of residential energy demand that adequately analyzes all aspects of residential consumer energy demand behavior and properly treats the penetration of new technologies, ...

Hartman, Raymond Steve

1978-01-01T23:59:59.000Z

245

A Novel Harmony Search Algorithm for One-Year-Ahead Energy Demand Estimation Using Macroeconomic Variables  

Science Journals Connector (OSTI)

In this paper we tackle a problem of one-year ahead energy demand estimation from macroeconomic variables. A modified Harmony ... the proposed approach in a real problem of Energy demand estimation in Spain, from...

Sancho Salcedo-Sanz

2014-01-01T23:59:59.000Z

246

Projecting household energy consumption within a conditional demand framework  

SciTech Connect (OSTI)

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-12-31T23:59:59.000Z

247

Projecting household energy consumption within a conditional demand framework  

SciTech Connect (OSTI)

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-01-01T23:59:59.000Z

248

Japan's Long-term Energy Demand and Supply Scenario to 2050 - Estimation for the Potential of Massive CO2 Mitigation  

E-Print Network [OSTI]

No.4 Japan's Long-term Energy Demand and Supply Scenario towe projected Japan's energy demand/supply and energy-relatedcrises (to cut primary energy demand per GDP ( T P E S / G D

Komiyama, Ryoichi

2010-01-01T23:59:59.000Z

249

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

E-Print Network [OSTI]

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

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

2013-01-01T23:59:59.000Z

250

Residential Energy Consumption Survey Results: Total Energy Consumption,  

Open Energy Info (EERE)

Survey Results: Total Energy Consumption, Survey Results: Total Energy Consumption, Expenditures, and Intensities (2005) Dataset Summary Description The Residential Energy Consumption Survey (RECS) is a national survey that collects residential energy-related data. The 2005 survey collected data from 4,381 households in housing units statistically selected to represent the 111.1 million housing units in the U.S. Data were obtained from residential energy suppliers for each unit in the sample to produce the Consumption & Expenditures data. The Consumption & Expenditures and Intensities data is divided into two parts: Part 1 provides energy consumption and expenditures by census region, population density, climate zone, type of housing unit, year of construction and ownership status; Part 2 provides the same data according to household size, income category, race and age. The next update to the RECS survey (2009 data) will be available in 2011.

251

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

252

Household energy consumption and its demand elasticity in Thailand  

Science Journals Connector (OSTI)

This study concentrates on the analysis of energy consumption, expenditure on oil and LPG use in cars and aims to examine the elasticity effect of various types of oil consumption. By using the Deaton's analysis framework, the cross-sectional data of Thai households economic survey 2009 were used. By defining energy goods in the scope of automobile fuel, the results reflect the low importance of high-quality automobile fuel on all income level households. Thai households tend to vary the quality rather than the quantity of thermal energy. All income groups have a tendency to switch to lower quality fuel. Middle and high-middle households (Q3 and Q4) are the income groups with the greatest tendency to switch to lower-quality fuel when a surge in the price of oil price occurs. The poorest households (Q1) are normally insensitive to a change of energy expenditure in terms of quality and quantity. This finding illustrates the LPG price subsidy policy favours middle and high-middle income households. The price elasticity of energy quantity demand is negative in all income levels. High to middle income families are the most sensitive to changes in the price of energy.

Montchai Pinitjitsamut

2012-01-01T23:59:59.000Z

253

CSEM WP 165R Demand-Side Management and Energy Efficiency  

E-Print Network [OSTI]

CSEM WP 165R Demand-Side Management and Energy Efficiency Revisited Maximilian Auffhammer, Carl, California 94720-5180 www.ucei.org #12;Demand-Side Management and Energy Efficiency Revisited Maximilian associated with energy efficiency demand side management (DSM) programs. This claim is based on point

Auffhammer, Maximilian

254

Energy demand and supply, energy policies, and energy security in the Republic of Korea  

Science Journals Connector (OSTI)

The Republic of Korea (ROK) has enjoyed rapid economic growth and development over the last 30 years. Rapid increases in energy useespecially petroleum, natural gas, and electricity, and especially in the industrial and transport sectorshave fueled the ROK's economic growth, but with limited fossil fuel resources of its own, the result has been that the ROK is almost entirely dependent on energy imports. The article that follows summarizes the recent trends in the ROK energy sector, including trends in energy demand and supply, and trends in economic, demographic, and other activities that underlie trends in energy use. The ROK has been experiencing drastic changes in its energy system, mainly induced by industrial, supply security, and environmental concerns, and energy policies in the ROK have evolved over the years to address such challenges through measures such as privatization of energy-sector activities, emphases on enhancing energy security through development of energy efficiency, nuclear power, and renewable energy, and a related focus on reducing greenhouse gas emissions. The assembly of a model for evaluating energy futures in the ROK (ROK2010 LEAP) is described, and results of several policy-based scenarios focused on different levels of nuclear energy utilization are described, and their impacts on of energy supply and demand in the ROK through the year 2030 are explored, along with their implications for national energy security and long-term policy plans. Nuclear power continues to hold a crucial position in the ROK's energy policy, but aggressive expansion of nuclear power alone, even if possible given post-Fukushima global concerns, will not be sufficient to attain the ROK's green economy and greenhouse gas emissions reduction goals.

Hoseok Kim; Eui-soon Shin; Woo-jin Chung

2011-01-01T23:59:59.000Z

255

39610 Energy Conversion & Supply (6) 39611 Energy Demand &Utilization (6)  

E-Print Network [OSTI]

. Energy & Environment (12) 19740 (24740) Combustion & Air Pollution Cntrl (12) 19612 Int. Life Cycle:20 12711 Adv. Project Management for Construction (12) 12742 Data Mining in Infrastructure (6) 12750 Infrastructure Systems (12) 12651/751 Air Quality Engr. (9/12) TR10:3011:50/NA 12740 Data Acq

McGaughey, Alan

256

39610 Energy Conversion & Supply (6) 39611 Energy Demand &Utilization (6)  

E-Print Network [OSTI]

() 19740 (24740) Comb. & Air Pollution Ctrl 19612 Int. Life Cycle Assessment (12) 19739 (18875) Econ& Engr Combustion & Air Pollution (12) 24642 Fuel Cell Systems (12)MW9:3011:20 24643 S.T. Electrochem. Energy Course (18) 12711 Adv. Project Management for Construction (12) 12742 Data Mining

McGaughey, Alan

257

U.S. Energy Demand: Some Low Energy Futures  

Science Journals Connector (OSTI)

...energy consumption per unit of output fell...I to 1.5 percent per year from 1950 to...en-ergy consumption per capita rose by 50...Between 1946 and 1973 amenities such as...enable resource production from low-grade ores...Exporting Countries (OPEC) (fall 1973) and...

1978-04-14T23:59:59.000Z

258

Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards"Top-Runner Approach"  

SciTech Connect (OSTI)

As one of the measures to achieve the reduction in greenhouse gas emissions agreed to in the"Kyoto Protocol," an institutional scheme for determining energy efficiency standards for energy-consuming appliances, called the"Top-Runner Approach," was developed by the Japanese government. Its goal is to strengthen the legal underpinnings of various energy conservation measures. Particularly in Japan's residential sector, where energy demand has grown vigorously so far, this efficiency standard is expected to play a key role in mitigating both energy demand growth and the associated CO2 emissions. This paper presents an outlook of Japan's residential energy demand, developed by a stochastic econometric model for the purpose of analyzing the impacts of the Japan's energy efficiency standards, as well as the future stochastic behavior of income growth, demography, energy prices, and climate on the future energy demand growth to 2030. In this analysis, we attempt to explicitly take into consideration more than 30 kinds of electricity uses, heating, cooling and hot water appliances in order to comprehensively capture the progress of energy efficiency in residential energy end-use equipment. Since electricity demand, is projected to exhibit astonishing growth in Japan's residential sector due to universal increasing ownership of electric and other appliances, it is important to implement an elaborate efficiency standards policy for these appliances.

Lacommare, Kristina S H; Komiyama, Ryoichi; Marnay, Chris

2008-05-15T23:59:59.000Z

259

A cloud computing framework on demand side management game in smart energy hubs  

Science Journals Connector (OSTI)

Abstract The presence of energy hubs in the future vision of energy networks creates an opportunity for electrical engineers to move toward more efficient energy systems. At the same time, it is envisioned that smart grid can cover the natural gas network in the near future. This paper modifies the classic Energy Hub model to present an upgraded model in the smart environment entitling Smart Energy Hub. Supporting real time, two-way communication between utility companies and smart energy hubs, and allowing intelligent infrastructures at both ends to manage power consumption necessitates large-scale real-time computing capabilities to handle the communication and the storage of huge transferable data. To manage communications to large numbers of endpoints in a secure, scalable and highly-available environment, in this paper we provide a cloud computing framework for a group of smart energy hubs. Then, we use game theory to model the demand side management among the smart energy hubs. Simulation results confirm that at the Nash equilibrium, peak to average ratio of the total electricity demand reduces significantly and at the same time the hubs will pay less considerably for their energy bill.

Aras Sheikhi; Mohammad Rayati; Shahab Bahrami; Ali Mohammad Ranjbar; Sourena Sattari

2015-01-01T23:59:59.000Z

260

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Total Energy Total Energy Glossary › FAQS › Overview Data Monthly Annual Analysis & Projections All Reports Most Requested Annual Monthly Projections U.S. States Annual Energy Review September 2012 PDF | previous editions Release Date: September 27, 2012 Important notes about the data Note: The emphasis of the Annual Energy Review (AER) is on long-term trends. Analysts may wish to use the data in this report in conjunction with EIA's monthly releases that offer updates to the most recent years' data. In particular, see the Monthly Energy Review for statistics that include updates to many of the annual series in this report. Data Years Displayed: For tables beginning in 1949, some early years (usually 1951-1954, 1956-1959, 1961-1964, 1966-1969, and 1971-1974) are not

Note: This page contains sample records for the topic "total energy 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

Real-Time Demand Response with Uncertain Renewable Energy in Smart Grid  

E-Print Network [OSTI]

Real-Time Demand Response with Uncertain Renewable Energy in Smart Grid Libin Jiang and Steven Low manages user load through real-time demand response and purchases balancing power on the spot market and demand response in the presence of uncertain renewable supply and time-correlated demand. The overall

Low, Steven H.

262

Evaluation of ground energy storage assisted electric vehicle DC fast charger for demand charge reduction and providing demand response  

Science Journals Connector (OSTI)

Abstract In 2012 there was approximately 2400 electric vehicle DC Fast Charging stations sold globally. According to Pike Research (Jerram and Gartner, 2012), it is anticipated that by 2020 there will be approximately 460,000 of them installed worldwide. A typical public DC fast charger delivers a maximum power output of 50kW which allows a typical passenger vehicle to be 80% charged in 1015min, compared with 68h for a 6.6kW AC level 2 charging unit. While DC fast chargers offer users the convenience of being able to rapidly charge their vehicle, the unit's high power demand has the potential to put sudden strain on the electricity network, and incur significant demand charges. Depending on the utility rate structure, a DC fast charger can experience annual demand charges of several thousand dollars. Therefore in these cases there is an opportunity to mitigate or even avoid the demand charges incurred by coupling the unit with an appropriately sized energy storage system and coordinating the way in which it integrates. This paper explores the technical and economical suitability of coupling a ground energy storage system with a DC fast charge unit for mitigation or avoidance of demand charges and lessening the impact on the local electricity network. This paper also discusses the concept of having the system participate in demand response programs in order to provide grid support and to further improve the economic suitability of an energy storage system.

Donald McPhail

2014-01-01T23:59:59.000Z

263

Analysis of the influence of residential location on light passenger vehicle energy demand.  

E-Print Network [OSTI]

??New Zealand???s current urban environment assumes a constant availability and affordability of energy (oil) and as such the energy demand of private vehicles is rarely (more)

Williamson, Mark

2013-01-01T23:59:59.000Z

264

Energy Transfer on Demand: Photoswitch-Directed Behavior of MetalPorphyrin Frameworks  

Science Journals Connector (OSTI)

Energy Transfer on Demand: Photoswitch-Directed Behavior of MetalPorphyrin Frameworks ... were used to est. the ligand strain energies in the and all other topol. ...

Derek E. Williams; Joseph A. Rietman; Josef M. Maier; Rui Tan; Andrew B. Greytak; Mark D. Smith; Jeanette A. Krause; Natalia B. Shustova

2014-08-12T23:59:59.000Z

265

Regional Allocation of Biomass to U.S. Energy Demands under a Portfolio of Policy Scenarios  

Science Journals Connector (OSTI)

This study develops a spatially explicit, best-use framework to optimally allocate cellulosic biomass feedstocks to energy demands in transportation, electricity, and residential heating sectors, while minimizing total system costs and tracking greenhouse gas emissions. ... Steubing et al.(6) consider the optimal use of several biomass feedstocks to substitute fossil energy technologies in Europe, which is broader than the previously listed studies, but the authors use a ranking method to identify preferred allocation strategies with a nonspatial model. ... This study builds on these studies in developing a spatially explicit, best-use framework for model year 2020 that optimally allocates cellulosic biomass feedstocks to competing energy end uses (heating, transportation, electricity) based on minimizing total system costs. ...

Kimberley A. Mullins; Aranya Venkatesh; Amy L. Nagengast; Matt Kocoloski

2014-02-10T23:59:59.000Z

266

Energy Demands and Efficiency Strategies in Data Center Buildings  

SciTech Connect (OSTI)

Information technology (IT) is becoming increasingly pervasive throughout society as more data is digitally processed, stored, and transferred. The infrastructure that supports IT activity is growing accordingly, and data center energy demands haveincreased by nearly a factor of four over the past decade. Data centers house IT equipment and require significantly more energy to operate per unit floor area thanconventional buildings. The economic and environmental ramifications of continued data center growth motivate the need to explore energy-efficient methods to operate these buildings. A substantial portion of data center energy use is dedicated to removing the heat that is generated by the IT equipment. Using economizers to introduce large airflow rates of outside air during favorable weather could substantially reduce the energy consumption of data center cooling. Cooling buildings with economizers is an established energy saving measure, but in data centers this strategy is not widely used, partly owing to concerns that the large airflow rates would lead to increased indoor levels of airborne particles, which could damage IT equipment. The environmental conditions typical of data centers and the associated potential for equipment failure, however, are not well characterized. This barrier to economizer implementation illustrates the general relationship between energy use and indoor air quality in building design and operation. This dissertation investigates how building design and operation influence energy use and indoor air quality in data centers and provides strategies to improve both design goals simultaneously.As an initial step toward understanding data center air quality, measurements of particle concentrations were made at multiple operating northern California data centers. Ratios of measured particle concentrations in conventional data centers to the corresponding outside concentrations were significantly lower than those reported in the literature for office or residential buildings. Estimates using a material-balance model match well with empirical results, indicating that the dominant particle sources and losses -- ventilation and filtration -- have been characterized. Measurements taken at a data center using economizers show nearly an order of magnitude increase in particle concentration during economizer activity. However, even with the increase, themeasured particle concentrations are still below concentration limits recommended in most industry standards. The research proceeds by exploring the feasibility of using economizers in data centers while simultaneously controlling particle concentrations with high-quality air filtration. Physical and chemical properties of indoor and outdoor particles were analyzed at a data center using economizers and varying levels of air filtration efficiency. Results show that when improved filtration is used in combination with an economizer, the indoor/outdoor concentration ratios for most measured particle types were similar to the measurements when using conventional filtration without economizers. An energy analysis of the data center reveals that, even during the summer months, chiller savings from economizer use greatly outweigh the increase in fan power associated with improved filtration. These findings indicate that economizer use combined with improved filtration couldsignificantly reduce data center energy demand while providing a level of protection from particles of outdoor origin similar to that observed with conventional design. The emphasis of the dissertation then shifts to evaluate the energy benefits of economizer use in data centers under different design strategies. Economizer use with high ventilation rates is compared against an alternative, water-side economizer design that does not affect indoor particle concentrations. Building energy models are employed to estimate energy savings of both economizer designs for data centers in

Shehabi, Arman

2009-09-01T23:59:59.000Z

267

Employing demand response in energy procurement plans of electricity retailers  

Science Journals Connector (OSTI)

Abstract This paper proposes a new framework in which demand response (DR) is incorporated as an energy resource of electricity retailers in addition to the commonly used forward contracts and pool markets. In this way, a stepwise reward-based DR is proposed as a real-time resource of the retailer. In addition, the unpredictable behavior of customers participating in the proposed reward-based DR is modeled through a scenario-based participation factor. The overall problem is formulated as a stochastic optimization approach in which pool prices and customers participation in DR are uncertain variables. The feasibility of the problem is evaluated on a realistic case of the Australian National Electricity Market (NEM) and solved using General Algebraic Modeling System (GAMS) software.

Nadali Mahmoudi; Mehdi Eghbal; Tapan K. Saha

2014-01-01T23:59:59.000Z

268

Demand Response Architectures and Load Management Algorithms for Energy-Efficient Power Grids: A Survey  

Science Journals Connector (OSTI)

A power grid has four segments: generation, transmission, distribution and demand. Until now, utilities have been focusing on streamlining their generation, transmission and distribution operations for energy efficiency. While loads have traditionally ... Keywords: Smart grid, energy efficiency, demand-side load management, demand response, load shifting

Yee Wei Law; Tansu Alpcan; Vincent C. S. Lee; Anthony Lo; Slaven Marusic; Marimuthu Palaniswami

2012-11-01T23:59:59.000Z

269

Demand-Side Load Scheduling Incentivized by Dynamic Energy Hadi Goudarzi, Safar Hatami, and Massoud Pedram  

E-Print Network [OSTI]

Demand-Side Load Scheduling Incentivized by Dynamic Energy Prices Hadi Goudarzi, Safar Hatami growth in electrical energy consumption under worst- case demand conditions [1]. To avoid expending 90089 {hgoudarz, shatami, pedram}@usc.edu Abstract--Demand response is an important part of the smart

Pedram, Massoud

270

Does financial development contribute to SAARC?S energy demand? From energy crisis to energy reforms  

Science Journals Connector (OSTI)

Abstract SAARC members urgently need to secure sustainable energy supplies at affordable prices. Alarmingly high oil prices in the face of ever increasing energy demand have resulted in severe pressure on resources of SAARC members. The objective of this study examine the relationship among energy consumption, economic growth, relative prices of energy, FDI and different financial development indicators (i.e., broad money supply, liquid liabilities, domestic credit provided by banking sector and domestic credit to private sector) in the panel of selected SAARC countries namely Bangladesh, India, Nepal, Pakistan and Sri Lanka over a period of 19752011. Panel cointegration test suggest that the variables are cointegrated and have a long-run relationship between them. In addition, three different panel data methods i.e. pooled least square, fixed effects and random effects have been used to test the validity of the energy-growth nexus via financial development in the SAARC region. Specification tests (i.e., F-test and Hausman test) indicate that the fixed effect model considered as the best model to examine the relationship between energy and growth determinants, this implies that variables are apparently influenced by country effects only. The fixed effect model shows that there is a significant relationship among energy consumption, economic growth, FDI and financial development (FD) proxies, however, FD indicators has a larger impact on increasing energy demand, followed by GDP per capita and FDI. Therefore, it is concluded that there is a trade-off between the energy and growth variables in SAARC region, collective efforts is required to transform SAARC region from an energy-starved to an energy efficient region.

Arif Alam; Ihtisham Abdul Malik; Alias Bin Abdullah; Asmadi Hassan; Faridullah; Usama Awan; Ghulam Ali; Khalid Zaman; Imran Naseem

2015-01-01T23:59:59.000Z

271

Future scenarios and trends in energy generation in brazil: supply and demand and mitigation forecasts  

Science Journals Connector (OSTI)

Abstract The structure of the Brazilian energy matrix defines Brazil as a global leader in power generation from renewable sources. In 2011, the share of renewable sources in electricity production reached 88.8%, mainly due to the large national water potential. Although the Brazilian energy model presents a strong potential for expansion, the total energy that could be used with most current renewable technologies often outweighs the national demand. The current composition of the national energy matrix has outstanding participation of hydropower, even though the country has great potential for the exploitation of other renewable energy sources such as wind, solar and biomass. This document therefore refers to the trend of evolution of the Brazilian Energy Matrix and exposes possible mitigation scenarios, also considering climate change. The methodology to be used in the modeling includes the implementation of the LEAP System (Long-range Energy Alternatives Planning) program, developed by the Stockholm Environment Institute, which allows us to propose different scenarios under the definition of socioeconomic scenarios and base power developed in the context of the REGSA project (Promoting Renewable Electricity Generation in South America). Results envision future scenarios and trends in power generation in Brazil, and the projected demand and supply of electricity for up to 2030.

Jos Baltazar Salgueirinho Osrio De Andrade Guerra; Luciano Dutra; Norma Beatriz Camiso Schwinden; Suely Ferraz de Andrade

2014-01-01T23:59:59.000Z

272

Demand Reduction  

Broader source: Energy.gov [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...

273

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

274

Driving change : evaluating strategies to control automotive energy demand growth in China  

E-Print Network [OSTI]

As the number of vehicles in China has relentlessly grown in the past decade, the energy demand, fuel demand and greenhouse gas emissions associated with these vehicles have kept pace. This thesis presents a model to project ...

Bonde kerlind, Ingrid Gudrun

2013-01-01T23:59:59.000Z

275

Demand Response - Policy: More Information | Department of Energy  

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

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

276

U.S. Coal Supply and Demand: 2010 Year in Review - Energy Information  

Gasoline and Diesel Fuel Update (EIA)

U.S. Coal Supply and Demand: 2010 Year in Review U.S. Coal Supply and Demand: 2010 Year in Review Release Date: June 1, 2011 | Next Release Date: Periodically | full report Introduction Coal production in the United States in 2010 increased to a level of 1,085.3 million short tons according to preliminary data from the U.S. Energy Information Administration (EIA), an increase of 1.0 percent, or 10.4 million short tons above the 2009 level of 1,074.9 million short tons (Table 1). In 2010 U.S. coal consumption increased in all sectors except commercial and institutional while total coal stocks fell slightly for the year. Coal consumption in the electric power sector in 2010 was higher by 4.5 percent, while coking coal consumption increased by 37.9 percent and the other industrial sector increased by 7.1 percent. The commercial and

277

A study of industrial equipment energy use and demand control.  

E-Print Network [OSTI]

??Demand and duty factors were measured for selected equipment [air compressors, electric furnaces, injection-molding machines, a welder, a granulator (plastics grinder), a sheet metal press (more)

Dooley, Edward Scott

2012-01-01T23:59:59.000Z

278

Achieving Total Employee Engagement in Energy Efficiency  

Broader source: Energy.gov [DOE]

Ratheon and GM share their experiences with employee engagement to achieve energy efficiency and sustainability goals in this presentation.

279

Energy-Agile Laptops: Demand Response of Mobile Plug Loads Using Sensor/Actuator Networks  

E-Print Network [OSTI]

Energy-Agile Laptops: Demand Response of Mobile Plug Loads Using Sensor/Actuator Networks Nathan@me.berkeley.edu Abstract--This paper explores demand response techniques for managing mobile, distributed loads with on observed. Our first simulation study explores a classic demand response scenario in which a large number

Culler, David E.

280

Definition: Interruptible Load Or Interruptible Demand | Open Energy  

Open Energy Info (EERE)

Interruptible Load Or Interruptible Demand Interruptible Load Or Interruptible Demand Jump to: navigation, search Dictionary.png Interruptible Load Or Interruptible Demand Demand that the end-use customer makes available to its Load-Serving Entity via contract or agreement for curtailment.[1] View on Wikipedia Wikipedia Definition View on Reegle Reegle Definition No reegle definition available. Also Known As non-firm service Related Terms transmission lines, electricity generation, transmission line, firm transmission service, 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 "http://en.openei.org/w/index.php?title=Definition:Interruptible_Load_Or_Interruptible_Demand&oldid=502615"

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


281

Tankless Demand Water Heater Basics | Department of Energy  

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

Demand Water Heater Basics Demand Water Heater Basics Tankless Demand Water Heater Basics August 19, 2013 - 2:57pm Addthis Illustration of an electric demand water heater. At the top of the image, the heating unit is shown. Cold water flows in one end of a pipe, flows through and around several curved pipes over the heating elements, and out the other end as hot water. Beneath the heating unit, a typical sink setup is shown. The sink has two pipes coming out the bottom, one for the hot water line and one for the cold water line. Both pipes lead to the heating unit, which is installed in close proximity to the area of hot water use, and is connected to a power source (110 or 220 volts). Demand (tankless or instantaneous) water heaters have heating devices that are activated by the flow of water, so they provide hot water only as

282

Tankless Demand Water Heater Basics | Department of Energy  

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

Tankless Demand Water Heater Basics Tankless Demand Water Heater Basics Tankless Demand Water Heater Basics August 19, 2013 - 2:57pm Addthis Illustration of an electric demand water heater. At the top of the image, the heating unit is shown. Cold water flows in one end of a pipe, flows through and around several curved pipes over the heating elements, and out the other end as hot water. Beneath the heating unit, a typical sink setup is shown. The sink has two pipes coming out the bottom, one for the hot water line and one for the cold water line. Both pipes lead to the heating unit, which is installed in close proximity to the area of hot water use, and is connected to a power source (110 or 220 volts). Demand (tankless or instantaneous) water heaters have heating devices that are activated by the flow of water, so they provide hot water only as

283

Program Strategies and Results for Californias Energy Efficiency and Demand Response Markets  

E-Print Network [OSTI]

Global Energy Partners provides a review of Californias strategic approach to energy efficiency and demand response implementation, with a focus on the industrial sector. The official role of the state, through the California Energy Commission (CEC...

Ehrhard, R.; Hamilton, G.

2008-01-01T23:59:59.000Z

284

A method to calculate the cumulative energy demand (CED) of lignite extraction  

Science Journals Connector (OSTI)

For the utilisation of an energy carrier such as lignite, the whole life cycle including necessary energy supply processes have to be considered. Therefore using the Cumulative Energy Demand (CED) is especially...

Michael Rhrlich; Mark Mistry

2000-11-01T23:59:59.000Z

285

Modelling useful energy demand system as derived from basic needs in the household sector  

Science Journals Connector (OSTI)

Inter-fuel substitution in the household sector depends on whether their target energy use is similar or not. To account ... for the effect of end-use application on energy demand, the concept of useful energy is...

Zahra A. Barkhordar; Yadollah Saboohi

2014-10-01T23:59:59.000Z

286

Achieving Total Employee Engagement in Energy Efficiency  

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

Raytheon Employee Engagement Raytheon Employee Engagement in Energy Conservation Department of Energy August 5, 2010 Steve Fugarazzo Raytheon Company Enterprise Energy Team Copyright © 2007 Raytheon Company. All rights reserved. Customer Success Is Our Mission is a trademark of Raytheon Company. Page 2 8/9/2010 Presentation Overview  Company Background  Communication & Outreach Initiatives - Internal Partnerships - Energy Champions - Energy Citizens - Energy Awareness Events & Contests Page 3 8/9/2010 Raytheon ... What We Do Raytheon is a global technology company that provides innovative solutions to customers in 80 nations. Through strategic vision, disciplined management and world-class talent, Raytheon is delivering operational advantages for customers every day while helping them prepare for the

287

Property:TotalValue | Open Energy Information  

Open Energy Info (EERE)

TotalValue TotalValue Jump to: navigation, search This is a property of type Number. Pages using the property "TotalValue" Showing 25 pages using this property. (previous 25) (next 25) 4 44 Tech Inc. Smart Grid Demonstration Project + 10,000,000 + A ALLETE Inc., d/b/a Minnesota Power Smart Grid Project + 3,088,007 + Amber Kinetics, Inc. Smart Grid Demonstration Project + 10,000,000 + American Transmission Company LLC II Smart Grid Project + 22,888,360 + American Transmission Company LLC Smart Grid Project + 2,661,650 + Atlantic City Electric Company Smart Grid Project + 37,400,000 + Avista Utilities Smart Grid Project + 40,000,000 + B Baltimore Gas and Electric Company Smart Grid Project + 451,814,234 + Battelle Memorial Institute, Pacific Northwest Division Smart Grid Demonstration Project + 177,642,503 +

288

SolarTotal | Open Energy Information  

Open Energy Info (EERE)

SolarTotal SolarTotal Jump to: navigation, search Name SolarTotal Place Bemmel, Netherlands Zip 6681 LN Sector Solar Product The company sells and installs PV solar instalations Coordinates 51.894112°, 5.89881° 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":51.894112,"lon":5.89881,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

289

How Can China Lighten Up? Urbanization, Industrialization and Energy Demand Scenarios  

E-Print Network [OSTI]

urban and rural total energy consumption per square meter ofas % Industry Total Energy Consumption Source: NBS 1.3.2its share of total primary energy consumption surged even

Aden, Nathaniel T.

2010-01-01T23:59:59.000Z

290

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

E-Print Network [OSTI]

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

Boutaba, Raouf

291

Generation Scheduling for Power Systems with Demand Response and a High Penetration of Wind Energy.  

E-Print Network [OSTI]

??With renewable energy sources and demand response programs expanding in many power systems, traditional unit commitment and economic dispatch approaches are inadequate. The power system (more)

Liu, Guodong

2014-01-01T23:59:59.000Z

292

Sustainable Energy Resources for Consumers (SERC)- On-Demand Tankless Water Heaters  

Broader source: Energy.gov [DOE]

This presentation, aimed at Sustainable Energy Resources for Consumers (SERC) grantees, provides information on Monitoring Checklists for the installation of On-Demand Tankless Water Heaters.

293

The Impact on Consumer Behavior of Energy Demand Side Management Programs Measurement Techniques and Methods.  

E-Print Network [OSTI]

??Much effort has gone into measuring the impact of Demand Side Management (DSM) programs on energy usage, particularly in regards to electric usage. However, there (more)

Pursley, Jeffrey L

2014-01-01T23:59:59.000Z

294

ELECTRICITY DEMAND AND SUPPLY PROJECTIONS IN IEA WORLD ENERGY SCENARIOS: HOW MUCH, HOW CLEAN?  

Science Journals Connector (OSTI)

Abstract (40-Word Limit): The presentation will highlight and discuss projections for electricity demand up to 2050 based on the recent publication Energy Technology Perspectives 2012:...

Frankl, Paolo

295

Comfort demand leading the optimization to energy supply from the Smart Grid  

E-Print Network [OSTI]

). The control of loads in the building, may also be a resource to the grid using the flexibilities in service of the grid in Demand Side Management (DSM) scenarios as so called Demand Response (DR) or Load Control (LC). (Callaway and Hiskens 2011) However... of energy management, building management, and comfort management have to be developed to anticipate on the coming possible changes on Demand Side Management by Demand Response (DR) and Load Control (LC). This study is a first step towards...

Aduba,K.; Zeiler,W.; Boxem,G.

2014-01-01T23:59:59.000Z

296

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

Science Journals Connector (OSTI)

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

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

2014-01-01T23:59:59.000Z

297

EQUUS Total Return Inc | Open Energy Information  

Open Energy Info (EERE)

EQUUS Total Return Inc EQUUS Total Return Inc Jump to: navigation, search Name EQUUS Total Return Inc Place Houston, Texas Product A business development company and VC investor that trades as a closed-end fund. EQUUS is managed by MCC Global NV, a Frankfurt stock exchange listed management and merchant banking group. Coordinates 29.76045°, -95.369784° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":29.76045,"lon":-95.369784,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

298

Retail Demand Response in Southwest Power Pool | Department of Energy  

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

Demand Response in Southwest Power Pool Demand Response in Southwest Power Pool Retail Demand Response in Southwest Power Pool In 2007, the Southwest Power Pool (SPP) formed the Customer Response Task Force (CRTF) to identify barriers to deploying demand response (DR) resources in wholesale markets and develop policies to overcome these barriers. One of the initiatives of this Task Force was to develop more detailed information on existing retail DR programs and dynamic pricing tariffs, program rules, and utility operating practices. This report describes the results of a comprehensive survey conducted by LBNL in support of the Customer Response Task Force and discusses policy implications for integrating legacy retail DR programs and dynamic pricing tariffs into wholesale markets in the SPP region.

299

Correlation Of Surface Heat Loss And Total Energy Production...  

Open Energy Info (EERE)

Correlation Of Surface Heat Loss And Total Energy Production For Geothermal Systems Jump to: navigation, search OpenEI Reference LibraryAdd to library Conference Paper: Correlation...

300

EIA-Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2007 Residential Demand Module Figure 5. United States Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use 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" by appliance (or UEC-in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new

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


301

EIA-Assumptions to the Annual Energy Outlook - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2007 Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2030. 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 Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

302

EIA-Assumptions to the Annual Energy Outlook - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2007 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 21 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 SEDS25 data.

303

Is Cumulative Fossil Energy Demand a Useful Indicator for the Environmental Performance of Products?  

Science Journals Connector (OSTI)

Is Cumulative Fossil Energy Demand a Useful Indicator for the Environmental Performance of Products? ... The Ecoinvent database v1.2 (4), containing life-cycle information for many products consumed in the western economy, has been used to derive cumulative fossil energy demands and life-cycle impact scores. ... The project work proved to be demanding in terms of co-ordination efforts required and consent identification. ...

Mark A. J. Huijbregts; Linda J. A. Rombouts; Stefanie Hellweg; Rolf Frischknecht; A. Jan Hendriks; Dik van de Meent; Ad M. J. Ragas; Lucas Reijnders; Jaap Struijs

2005-12-27T23:59:59.000Z

304

Total Pollution Effect and Total Energy Cost per Output of Different Products for Polish Industrial System  

Science Journals Connector (OSTI)

For many years a broad use has been made of the indices of total energy requirements in the whole large production system corresponding to unit output of particular goods (Boustead I., Hancock G.F., 1979). The...

Henryk W. Balandynowicz

1988-01-01T23:59:59.000Z

305

Poster abstract: wireless sensor network characterization - application to demand response energy pricing  

Science Journals Connector (OSTI)

This poster presents latency and reliability characterization of wireless sensor network as applied to an advanced building control system for demand response energy pricing. A test network provided the infrastructure to extract round trip time and packet ... Keywords: advanced building control, demand response energy pricing

Nathan Ota; Dan Hooks; Paul Wright; David Auslander; Therese Peffer

2003-11-01T23:59:59.000Z

306

The Impact of Technological Change and Lifestyles on the Energy Demand  

E-Print Network [OSTI]

demand into a model of total private consumption. Private consumption is determined by economic variables of technological and socio- demographic variables on the demand for gasoline/diesel, heating and electricity. Key, households' electricity and heat consumption are growing rapidly despite of technological progress

Steininger, Karl W.

307

Residential energy demand modeling and the NIECS data base : an evaluation  

E-Print Network [OSTI]

The purpose of this report is to evaluate the 1978-79 National Interim Energy Consumption Survey (NIECS) data base in terms of its usefulness for estimating residential energy demand models based on household appliance ...

Cowing, Thomas G.

1982-01-01T23:59:59.000Z

308

Impacts of Temperature Variation on Energy Demand in Buildings (released in AEO2005)  

Reports and Publications (EIA)

In the residential and commercial sectors, heating and cooling account for more than 40% of end-use energy demand. As a result, energy consumption in those sectors can vary significantly from year to year, depending on yearly average temperatures.

2005-01-01T23:59:59.000Z

309

Issues Related to the Growth of Electricity in Global Energy Demand  

Science Journals Connector (OSTI)

Since the subject of this international conference is Global Energy Demand in Transition: The New Role of Electricity ... drive the evolution of the market shares of energy sources and uses (which are different,...

Marcelo Alonso

1995-01-01T23:59:59.000Z

310

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network [OSTI]

for cooking and lighting. Biomass energy consumption willused in an economy, biomass energy consumption is certainlyby a large share of biomass energy use representing 50% of

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

311

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network [OSTI]

10. Final and Primary Energy Consumption in the Industry35 Figure 16. Primary Energy Consumption byby end users while primary energy consumption includes final

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

312

Determinants of Smart Energy Demand Management: An Exploratory Analysis  

Science Journals Connector (OSTI)

The unprecedented rise of population with increasing energy consumption has necessitated the stabilization of dwindling energy resources to secure the provision of energy. Electricity production and distribution ...

Zaheer Tariq; Sergio Cavalieri

2013-01-01T23:59:59.000Z

313

Calculating Energy and Demand Retrofit Savings for Victoria High School: Interim Report  

E-Print Network [OSTI]

ESL-TR-92/12-03 Calculating Energy and Demand Retrofit Savings For Victoria High School Yue Liu, T. Agami Reddy, S. Katipamula and David E. Claridge. Interim Report Energy Systems Laboratory Texas A&M University College Station, TX 77843 December... 1992 Calculating Energy and Demand Retrofit Savings For Victoria High School Yue Liu, T. Agami Reddy, S. Katipamula and David E. Claridge. Interim Report Energy Systems Laboratory Texas A&M University College Station, TX 77843 December 1992 Abstract...

Liu, Y.; Reddy, T. A.; Katipamula, S.; Claridge, D. E.

1992-01-01T23:59:59.000Z

314

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network [OSTI]

Efficiency in Electricity Consumption", HWWA Discussionelectricity includes electricity consumption plus thedistribution. Total electricity consumption represents 1,654

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

315

Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;  

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

4 End Uses of Fuel Consumption, 2006; 4 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Trillion Btu. Distillate Fuel Oil Coal NAICS Net Demand Residual and LPG and (excluding Coal Code(a) End Use for Electricity(b) Fuel Oil Diesel Fuel(c) Natural Gas(d) NGL(e) Coke and Breeze) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 3,335 251 129 5,512 79 1,016 Indirect Uses-Boiler Fuel 84 133 23 2,119 8 547 Conventional Boiler Use 84 71 17 1,281 8 129 CHP and/or Cogeneration Process 0 62 6 838 1 417 Direct Uses-Total Process 2,639 62 52 2,788 39 412 Process Heating 379 59 19 2,487 32 345 Process Cooling and Refrigeration

316

How Can China Lighten Up? Urbanization, Industrialization and Energy Demand Scenarios  

E-Print Network [OSTI]

21 Figure 13: Primary Energy Consumption byEffects on Industry Primary Energy Consumption, 1995-share of total primary energy consumption surged even higher

Aden, Nathaniel T.

2010-01-01T23:59:59.000Z

317

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

318

National Action Plan on Demand Response, June 2010 | Department of Energy  

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

Action Plan on Demand Response, June 2010 Action Plan on Demand Response, June 2010 National Action Plan on Demand Response, June 2010 The Federal Energy Regulatory Commission (FERC) is required to develop the National Action Plan on Demand Response (National Action Plan) as outlined in section 529 of the Energy Independence and Security Act of 2007 (EISA), entitled "Electricity Sector Demand Response." This National Action Plan is designed to meet three objectives: Identify "requirements for technical assistance to States to allow them to maximize the amount of demand response resources that can be developed and deployed." Design and identify "requirements for implementation of a national communications program that includes broad-based customer education and support."

319

Energy Upgrade California Drives Demand From Behind the Wheel  

Broader source: Energy.gov [DOE]

With a goal of "energy efficiency or bust," theCalifornia Center for Sustainable Energy (CCSE) recently completed a statewide tour of its ongoing Energy Upgrade California Roadshow. The mobile...

320

Assumptions to the Annual Energy Outlook 2000 - Electricity Market Demand  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module (EMM) represents the planning, operations, and pricing of electricity in the United States. It is composed of four primary submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. In addition, nonutility generation and supply and electricity transmission and trade are represented in the planning and dispatching submodules. Electricity Market Module (EMM) represents the planning, operations, and pricing of electricity in the United States. It is composed of four primary submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. In addition, nonutility generation and supply and electricity transmission and trade are represented in the planning and dispatching submodules. Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. The major assumptions are summarized below.

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


321

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

SciTech Connect (OSTI)

This report summarizes the Lawrence Berkeley National Laboratory's research to date in characterizing energy efficiency and open automated demand response opportunities for industrial refrigerated warehouses in California. The report describes refrigerated warehouses characteristics, energy use and demand, and control systems. It also discusses energy efficiency and open automated demand response opportunities and provides analysis results from three demand response studies. In addition, several energy efficiency, load management, and demand response case studies are provided for refrigerated warehouses. This study shows that refrigerated warehouses can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for open automated demand response (OpenADR) at little additional cost. These improved controls may prepare facilities to be more receptive to OpenADR due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.

Lekov, Alex; Thompson, Lisa; McKane, Aimee; Rockoff, Alexandra; Piette, Mary Ann

2009-05-11T23:59:59.000Z

322

The Legacy of Twenty Years of Energy Demand Management: we know more about Individual Behaviour but next to Nothing about Demand  

Science Journals Connector (OSTI)

Our intention in the paper has been to explore a new approach to the science of energy demand: one which adequately accounts for the actors ... the object of inquiry as the services which energy provides; and whi...

Harold Wilhite; Elizabeth Shove

2000-01-01T23:59:59.000Z

323

Coordination of Energy Efficiency and Demand Response: A Resource...  

Open Energy Info (EERE)

cleanenergydocumentssucaeeanddr.pdf Equivalent URI: cleanenergysolutions.orgcontentcoordination-energy-efficiency-and-de Language: English Policies:...

324

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

Estimating Total Energy Consumption and Emissions of Chinasof Chinas total energy consumption mix. However, accuratelyof Chinas total energy consumption, while others estimate

Fridley, David G.

2008-01-01T23:59:59.000Z

325

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

ABORATORY Estimating Total Energy Consumption and Emissionscomponent of Chinas total energy consumption mix. However,about 19% of Chinas total energy consumption, while others

Fridley, David G.

2008-01-01T23:59:59.000Z

326

Total and Peak Energy Consumption Minimization of Building HVAC Systems Using Model Predictive Control  

E-Print Network [OSTI]

combination of the total energy consumption and the peakalso reduces the total energy consumption of the occupancyTotal and Peak Energy Consumption Minimization of Building

Maasoumy, Mehdi; Sangiovanni-Vincentelli, Alberto

2012-01-01T23:59:59.000Z

327

Transportation Energy Futures Series: Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future  

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

DEMAND DEMAND Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future TRANSPORTATION ENERGY FUTURES SERIES: Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future A Study Sponsored by U.S. Department of Energy Office of Energy Efficiency and Renewable Energy March 2013 Prepared by CAMBRIDGE SYSTEMATICS Cambridge, MA 02140 under subcontract DGJ-1-11857-01 Technical monitoring performed by NATIONAL RENEWABLE ENERGY LABORATORY Golden, Colorado 80401-3305 managed by Alliance for Sustainable Energy, LLC for the U.S. DEPARTMENT OF ENERGY Under contract DC-A36-08GO28308 This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their

328

Pseudo Dynamic Transitional Modeling of Building Heating Energy Demand Using Artificial1 Neural Network2  

E-Print Network [OSTI]

Transitional Modeling of Building Heating Energy Demand Using Artificial1 Neural Network2 Subodh Paudel a.Lecorre@mines-nantes.fr9 Abstract10 This paper presents the building heating demand prediction model with occupancy profile Institution15 building and compared its results with static and other pseudo dynamic neural network models

Paris-Sud XI, Université de

329

Agent-based coordination techniques for matching supply and demand in energy networks  

Science Journals Connector (OSTI)

There is a lot of effort directed toward realizing the power network of the future. The future power network is expected to depend on a large number of renewable energy resources connected directly to the low and medium voltage power network. Demand ... Keywords: Supply and demand matching, market and non-market algorithms, multi-agent systems

Rashad Badawy; Benjamin Hirsch; Sahin Albayrak

2010-12-01T23:59:59.000Z

330

SmartHG: Energy Demand Aware Open Services for Smart Grid Intelligent Automation  

E-Print Network [OSTI]

SmartHG: Energy Demand Aware Open Services for Smart Grid Intelligent Automation Enrico Tronci- ing, energy storage (e.g., batteries or plug-in hybrid electric vehicles) and energy production (e economically viable Intelligent Automation Services (IASs), which gather real-time data about energy usage from

Tronci, Enrico

331

Coordination of Energy Efficiency and Demand Response: A Resource of the  

Open Energy Info (EERE)

Coordination of Energy Efficiency and Demand Response: A Resource of the Coordination of Energy Efficiency and Demand Response: A Resource of the National Action Plan for Energy Efficiency Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Coordination of Energy Efficiency and Demand Response: A Resource of the National Action Plan for Energy Efficiency Focus Area: Energy Efficiency Topics: Policy, Deployment, & Program Impact Website: www.epa.gov/cleanenergy/documents/suca/ee_and_dr.pdf Equivalent URI: cleanenergysolutions.org/content/coordination-energy-efficiency-and-de Language: English Policies: "Regulations,Deployment Programs" is not in the list of possible values (Deployment Programs, Financial Incentives, Regulations) for this property. DeploymentPrograms: Retrofits Regulations: Energy Standards

332

Long Term Options for Energy Supply and Demand Side Management  

Science Journals Connector (OSTI)

A great deal has been said and written about future energy options and the need for responsibility and caution in protecting the worlds natural environment. Clearly, energy policies and environmental policies...

Tom Morron; Fred Denny

1993-01-01T23:59:59.000Z

333

Integration of solar thermal energy into processes with heat demand  

Science Journals Connector (OSTI)

An integration of solar thermal energy can reduce the utility cost and the environmental impact. A proper integration of solar thermal energy is required in order to achieve ... objective of this study is to maxi...

Andreja Nemet; Zdravko Kravanja

2012-06-01T23:59:59.000Z

334

Harmony Search Algorithm for Transport Energy Demand Modeling  

Science Journals Connector (OSTI)

The transport sector is one of the major consumers of energy production throughout the world. Thus, the estimation of medium and long-term energy consumption based on socio-economic and transport related indic...

Halim Ceylan; Huseyin Ceylan

2009-01-01T23:59:59.000Z

335

Aerodynamic Improvements and Associated Energy Demand Reduction of Trains  

Science Journals Connector (OSTI)

The importance for developing energy efficient rail vehicles is increasing with rising energy prices and the vital necessity to reduce the CO2production to slow down the climate change. This study shows a compari...

Alexander Orellano; Stefan Sperling

2009-01-01T23:59:59.000Z

336

Energy in Europe: Demand, Forecast, Control and Supply  

Science Journals Connector (OSTI)

Adequate and reasonably-priced energy supplies are fundamental to the functioning of the economy and to the stability of the society of all countries. Energy questions, therefore, have become of steadily incre...

H.-F. Wagner

1981-01-01T23:59:59.000Z

337

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network [OSTI]

data center floor. Waste heat from the chiller refrigerantParameters Floor Area UPS Waste Heat Data Center LightsLoad Lights Fans UPS Waste Heat DX Cooling Total Annual

Shehabi, Arman

2010-01-01T23:59:59.000Z

338

Intelligent demand side energy management system for autonomous polygeneration microgrids  

Science Journals Connector (OSTI)

Autonomous polygeneration microgrids is a novel approach in addressing the needs of remote areas. These needs can include power, fuel for transportation in the form of hydrogen, potable water through desalination and space heating and cooling. This approach has been investigated technically and economically and has proved viable. Further research has taken place in the supervisory management of this topology using computational intelligence techniques like fuzzy logic, which has optimized the concept minimizing the sizes of the installed components. The optimal design of the system can meet, though, only the design principles and needs. In reality experience has shown that most autonomous power systems operate out of specifications very shortly after installation or after a couple of years new needs arise and it is not possible economic wise for the people to extend it. In these cases the microgrid would struggle to cover the increased needs and in the end fail, causing blackouts. A solution to this is partial load shedding in an intelligent manner. This paper presents a multi agent system for intelligent demand side management of the polygeneration microgrid topology which also includes grey prediction algorithms for better management. This approach can also be used for designing the optimal polygeneration microgrid for a given amount of an investment. The results show that the proposed intelligent demand side management system can address its design principles successfully and guaranty the most effective operation even in conditions near and over the limits of the design specification of the autonomous polygeneration microgrid.

George Kyriakarakos; Dimitrios D. Piromalis; Anastasios I. Dounis; Konstantinos G. Arvanitis; George Papadakis

2013-01-01T23:59:59.000Z

339

Scenario Prediction of Energy Demand and Development Status of Renewable Energy in Dunstan Area of Chongming Island  

Science Journals Connector (OSTI)

Based on the data of GDP and population during the period 20032008, the energy demand in 2020 for industrial and residential energy in Dunstan area of Chongming Island was ... research material, the development ...

Xuezhong Fan; Liquan Zhang

2013-01-01T23:59:59.000Z

340

Conserving Energy with On-Demand Topology Management  

E-Print Network [OSTI]

@cs.uiuc.edu Abstract-- To reduce idle-time energy consumption, nodes in ad hoc networks can switch to a power-save mode], [4]. A common approach to idle- time energy conservation is to switch to a power-save mode where of potential energy savings from proactive and reactive approaches. We show that proactive approaches save

Kravets, Robin

Note: This page contains sample records for the topic "total energy 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

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

342

1.0 Motivation............................................................................................................2 1.1Overview of Energy Supply and Demand in the 21st  

E-Print Network [OSTI]

............................................................................................................2 1.1Overview of Energy Supply and Demand in the 21st Century..........................2 1.2 UK Energy ...................................................................................24 6.6 Correlation between Wind Strength and Demand for Electricity..................24 6

343

The Impact of Hedonism on Domestic Hot Water Energy Demand for Showering ? The Case of the Schanzenfest, Hamburg  

Science Journals Connector (OSTI)

The causes of variation in energy demand for hot water in showering or bathing ... was triangulated with electric meter data to examine energy use behaviours and explore changes in hot water demand. This occurred...

Stephen Lorimer; Marianne Jang; Korinna Thielen

2013-01-01T23:59:59.000Z

344

Demand Response and Smart Metering Policy Actions Since the Energy Policy  

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

and Smart Metering Policy Actions Since the Energy 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 Energy Policy Act of 2005: A Summary for State Officials This report represents a review of policy developments on demand response and other related areas such as smart meters and smart grid. It has been prepared by the Demand Response Coordinating Committ ee (DRCC) for the National Council on Electricity Policy (NCEP). The report focuses on State and Federal policy developments during the period from 2005 to mid-year 2008. It is an att empt to catalogue information on policy developments at both the federal and state level, both in the legislative and regulatory arenas. Demand Response and Smart Metering Policy Actions Since the Energy Policy

345

COMBINING DIVERSE DATA SOURCES FOR CEDSS, AN AGENT-BASED MODEL OF DOMESTIC ENERGY DEMAND  

E-Print Network [OSTI]

energy use covers the use of electricity, gas and oil within the home for space and water heating and electricalenergy demand. These exercises led us to focus on electrical

Gotts, Nicholas Mark; Polhill, Gary; Craig, Tony; Galan-Diaz, Carlos

2014-01-01T23:59:59.000Z

346

Transport, energy and greenhouse gases: perspectives on demand limitation. Guest editorial  

Science Journals Connector (OSTI)

The current economic recession results in reduced industrial output and energy consumption, and thus reduces freight transport activity ... , but everything indicates that growth in transport demand should re-sta...

Charles Raux; Martin E. H. Lee-Gosselin

2010-05-01T23:59:59.000Z

347

Energy Management Using Storage Batteries in Large Commercial Facilities Based on Projection of Power Demand  

Science Journals Connector (OSTI)

This study provides three methods for projection of power demand of large commercial facilities planned for construction, ... the operation algorithm of storage batteries to manage energy and minimize power costs...

Kentaro Kaji; Jing Zhang; Kenji Tanaka

2013-01-01T23:59:59.000Z

348

Fact Sheet: U.S. and China Actions Matter for Global Energy Demand, for  

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

Fact Sheet: U.S. and China Actions Matter for Global Energy Demand, Fact Sheet: U.S. and China Actions Matter for Global Energy Demand, for Global Environmental Quality, and for the Challenge of Global Climate Change Fact Sheet: U.S. and China Actions Matter for Global Energy Demand, for Global Environmental Quality, and for the Challenge of Global Climate Change December 5, 2008 - 4:58pm Addthis The U.S. is committed to working together with China to tackle current energy challenges the world faces, including cultivating sufficient investment, the development and deployment of new energy technologies, and addressing greenhouse gas emissions from producing and using energy. Our cooperation spans power generation, efficient buildings, sustainable transportation, emissions-free nuclear power, and clean fossil fuels. The U.S. and China are the world's largest energy consumers and are

349

Fact Sheet: U.S. and China Actions Matter for Global Energy Demand, for  

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

S. and China Actions Matter for Global Energy Demand, S. and China Actions Matter for Global Energy Demand, for Global Environmental Quality, and for the Challenge of Global Climate Change Fact Sheet: U.S. and China Actions Matter for Global Energy Demand, for Global Environmental Quality, and for the Challenge of Global Climate Change December 5, 2008 - 4:58pm Addthis The U.S. is committed to working together with China to tackle current energy challenges the world faces, including cultivating sufficient investment, the development and deployment of new energy technologies, and addressing greenhouse gas emissions from producing and using energy. Our cooperation spans power generation, efficient buildings, sustainable transportation, emissions-free nuclear power, and clean fossil fuels. The U.S. and China are the world's largest energy consumers and are

350

Web-based energy information systems for energy management and demand response in commercial buildings  

SciTech Connect (OSTI)

Energy Information Systems (EIS) for buildings are becoming widespread in the U.S., with more companies offering EIS products every year. As a result, customers are often overwhelmed by the quickly expanding portfolio of EIS feature and application options, which have not been clearly identified for consumers. The object of this report is to provide a technical overview of currently available EIS products. In particular, this report focuses on web-based EIS products for large commercial buildings, which allow data access and control capabilities over the Internet. EIS products combine software, data acquisition hardware, and communication systems to collect, analyze and display building information to aid commercial building energy managers, facility managers, financial managers and electric utilities in reducing energy use and costs in buildings. Data types commonly processed by EIS include energy consumption data; building characteristics; building system data, such as heating, ventilation, and air-conditioning (HVAC) and lighting data; weather data; energy price signals; and energy demand-response event information. This project involved an extensive review of research and trade literature to understand the motivation for EIS technology development. This study also gathered information on currently commercialized EIS. This review is not an exhaustive analysis of all EIS products; rather, it is a technical framework and review of current products on the market. This report summarizes key features available in today's EIS, along with a categorization framework to understand the relationship between EIS, Energy Management and Control Systems (EMCSs), and similar technologies. Four EIS types are described: Basic Energy Information Systems (Basic-EIS); Demand Response Systems (DRS); Enterprise Energy Management (EEM); and Web-based Energy Management and Control Systems (Web-EMCS). Within the context of these four categories, the following characteristics of EIS are discussed: Metering and Connectivity; Visualization and Analysis Features; Demand Response Features; and Remote Control Features. This report also describes the following technologies and the potential benefits of incorporating them into future EIS products: Benchmarking; Load Shape Analysis; Fault Detection and Diagnostics; and Savings Analysis.

Motegi, Naoya; Piette, Mary Ann; Kinney, Satkartar; Herter, Karen

2003-04-18T23:59:59.000Z

351

Total  

Gasoline and Diesel Fuel Update (EIA)

Total Total .............. 16,164,874 5,967,376 22,132,249 2,972,552 280,370 167,519 18,711,808 1993 Total .............. 16,691,139 6,034,504 22,725,642 3,103,014 413,971 226,743 18,981,915 1994 Total .............. 17,351,060 6,229,645 23,580,706 3,230,667 412,178 228,336 19,709,525 1995 Total .............. 17,282,032 6,461,596 23,743,628 3,565,023 388,392 283,739 19,506,474 1996 Total .............. 17,680,777 6,370,888 24,051,665 3,510,330 518,425 272,117 19,750,793 Alabama Total......... 570,907 11,394 582,301 22,601 27,006 1,853 530,841 Onshore ................ 209,839 11,394 221,233 22,601 16,762 1,593 180,277 State Offshore....... 209,013 0 209,013 0 10,244 260 198,509 Federal Offshore... 152,055 0 152,055 0 0 0 152,055 Alaska Total ............ 183,747 3,189,837 3,373,584 2,885,686 0 7,070 480,828 Onshore ................ 64,751 3,182,782

352

SNG Production from Coal: A Possible Solution to Energy Demand  

Science Journals Connector (OSTI)

Abstract In some areas of the world, natural gas demand cannot be fully satisfied either by domestic sources or foreign imports, while abundant coal resources are available. The conversion of coal to Substitute Natural Gas, SNG, by coal gasification and subsequent syngas methanation is one of the possible solutions to solve the problem. Foster Wheeler has developed a simple process for SNG production, named VESTA, utilizing catalysts from Clariant. The process concept has been proven by laboratory tests, and a demonstration unit will soon be completed. The VESTA process is very flexible and can handle syngas coming from several sources such as coal, biomass, petroleum coke and solid waste. In this paper our overview of the technology and its development status will be outlined.

Letizia Romano; Fabio Ruggeri; Robert Marx

2014-01-01T23:59:59.000Z

353

Matching renewable energy supply and demand in green datacenters  

Science Journals Connector (OSTI)

Abstract In this paper, we propose GreenSlot, a scheduler for parallel batch jobs in a datacenter powered by a photovoltaic solar array and the electrical grid (as a backup). GreenSlot predicts the amount of solar energy that will be available in the near future, and schedules the workload to maximize the green energy consumption while meeting the jobs deadlines. If grid energy must be used to avoid deadline violations, the scheduler selects times when it is cheap. Evaluation results show that GreenSlot can increase solar energy consumption by up to 117% and decrease energy cost by up to 39%, compared to conventional schedulers, when scheduling three scientific workloads and a data processing workload. Based on these positive results, we conclude that green datacenters and green-energy-aware scheduling can have a significant role in building a more sustainable IT ecosystem.

igo Goiri; Md E. Haque; Kien Le; Ryan Beauchea; Thu D. Nguyen; Jordi Guitart; Jordi Torres; Ricardo Bianchini

2015-01-01T23:59:59.000Z

354

Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;  

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

Next MECS will be conducted in 2010 Next MECS will be conducted in 2010 Table 5.3 End Uses of Fuel Consumption, 2006; Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity; Unit: Physical Units or Btu. Distillate Coal Fuel Oil (excluding Coal Net Demand Residual and Natural Gas(d) LPG and Coke and Breeze) NAICS for Electricity(b) Fuel Oil Diesel Fuel(c) (billion NGL(e) (million Code(a) End Use (million kWh) (million bbl) (million bbl) cu ft) (million bbl) short tons) Total United States 311 - 339 ALL MANUFACTURING INDUSTRIES TOTAL FUEL CONSUMPTION 977,338 40 22 5,357 21 46 Indirect Uses-Boiler Fuel 24,584 21 4 2,059 2 25 Conventional Boiler Use 24,584 11 3

355

Property:FlatDemandStructure | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:FlatDemandStructure Jump to: navigation, search This is a property of type Page. Pages using the property "FlatDemandStructure" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 0000827d-84d0-453d-b659-b86869323897 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 00101108-073b-4503-9cd4-01769611c26f + 00101108-073b-4503-9cd4-01769611c26f + 001361ca-50d2-49bc-b331-08755a2c7c7d + 001361ca-50d2-49bc-b331-08755a2c7c7d + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 001d1952-955c-411b-8ce4-3d146852a75e + 001d1952-955c-411b-8ce4-3d146852a75e +

356

High Electric Demand Days: Clean Energy Strategies for Improving Air Quality  

Broader source: Energy.gov [DOE]

This presentation by Art Diem of the State and Local Capacity Building Branch in the U.S. Environmental Protection Agency 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.

357

The Impact of Neighbourhood Density on the Energy Demand of Passive Houses and on Potential Energy Sources from the Waste Flows and Solar Energy.  

E-Print Network [OSTI]

??This study demonstrates how the density of a neighbourhood affects its energy demand, metabolism (energy and material flows) and its ability to produce its own (more)

Stupka, Robert

2011-01-01T23:59:59.000Z

358

Experts Meeting: Behavioral Economics as Applied to Energy Demand...  

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

modeling system of U.S. through 2040, to project the production, imports, conversion, consumption, and prices of energy - Ultimate EIA objectives include: * Enhance the...

359

Energy-Efficient Demand Provisioning in the Cloud  

Science Journals Connector (OSTI)

In this paper, we propose optimized provisioning models to guarantee minimum energy consumption of Internet and cloud services where high performance data centers are located at the...

Kantarci, Burak; Mouftah, Hussein T

360

On-Demand Energy Harvesting Techniques - A System Level Perspective.  

E-Print Network [OSTI]

??In recent years, energy harvesting has been generating great interests among researchers, scientists and engineers alike. One of the major reasons for this increased interest (more)

Ugwuogo, James

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total energy 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

UK Energy Research Centre Demand Reduction Theme, University of Oxford  

E-Print Network [OSTI]

, for 51% of total UK carbon dioxide (CO2) emissions, including carbon equivalent emissions from aircraft, significant reductions must be made in individuals' direct emissions. A policy of Personal Carbon Allowances a free, equal share of permitted emissions ­ their personal carbon allowance; · The allowance would cover

362

The impact of demand-controlled ventilation on energy use in buildings  

SciTech Connect (OSTI)

The overall objective of this work was to evaluate typical energy requirements associated with alternative ventilation control strategies. The strategies included different combinations of economizer and demand-controlled ventilation controls and energy analyses were performed for a range of typical buildings, systems, and climates. Only single zone buildings were considered, so that simultaneous heating and cooling did not exist. The energy savings associated with economizer and demand-controlled ventilation strategies were found to be very significant for both heating and cooling. In general, the greatest savings in electrical usage for cooling with the addition of demand-controlled ventilation occur in situations where the opportunities for economizer cooling are less. This is true for warm and humid climates, and for buildings that have low relative internal gains (i.e., low occupant densities). As much as 10% savings in electrical energy for cooling were possible with demand-controlled ventilation. The savings in heating energy associated with demand-controlled ventilation were generally much larger, but were strongly dependent upon the occupancy schedule. Significantly greater savings were found for buildings with highly variable occupancy schedules (e.g., stores and restaurants) as compared with office buildings. In some cases, the primary heating energy was reduced by a factor of 10 with demand-controlled ventilation as compared with fixed ventilation rates.

Braun, J.E.; Brandemuehl, M.J.

1999-07-01T23:59:59.000Z

363

Property:Geothermal/TotalProjectCost | Open Energy Information  

Open Energy Info (EERE)

TotalProjectCost TotalProjectCost Jump to: navigation, search Property Name Geothermal/TotalProjectCost Property Type Number Description Total Project Cost Pages using the property "Geothermal/TotalProjectCost" Showing 25 pages using this property. (previous 25) (next 25) A A 3D-3C Reflection Seismic Survey and Data Integration to Identify the Seismic Response of Fractures and Permeable Zones Over a Known Geothermal Resource at Soda Lake, Churchill Co., NV Geothermal Project + 14,571,873 + A Demonstration System for Capturing Geothermal Energy from Mine Waters beneath Butte, MT Geothermal Project + 2,155,497 + A Geothermal District-Heating System and Alternative Energy Research Park on the NM Tech Campus Geothermal Project + 6,135,381 + A new analytic-adaptive model for EGS assessment, development and management support Geothermal Project + 1,629,670 +

364

Energy-Efficient Reliable Paths for On-Demand Routing Protocols Tamer Nadeem, Suman Banerjee, Archan Misra, Ashok Agrawala  

E-Print Network [OSTI]

1 Energy-Efficient Reliable Paths for On-Demand Routing Protocols Tamer Nadeem, Suman Banerjee within the framework of on-demand routing protocols. Computation of minimum energy reli- able paths does not work for on-demand protocols and some additional mechanisms are needed to compute energy

Banerjee, Suman

365

Transportation Energy Futures Series: Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future  

SciTech Connect (OSTI)

Freight transportation demand is projected to grow to 27.5 billion tons in 2040, and to nearly 30.2 billion tons in 2050. This report describes the current and future demand for freight transportation in terms of tons and ton-miles of commodities moved by truck, rail, water, pipeline, and air freight carriers. It outlines the economic, logistics, transportation, and policy and regulatory factors that shape freight demand, the trends and 2050 outlook for these factors, and their anticipated effect on freight demand. After describing federal policy actions that could influence future freight demand, the report then summarizes the capabilities of available analytical models for forecasting freight demand. This is one in a series of reports produced as a result of the Transportation Energy Futures project, a Department of Energy-sponsored multi-agency effort to pinpoint underexplored strategies for reducing GHGs and petroleum dependence related to transportation.

Grenzeback, L. R.; Brown, A.; Fischer, M. J.; Hutson, N.; Lamm, C. R.; Pei, Y. L.; Vimmerstedt, L.; Vyas, A. D.; Winebrake, J. J.

2013-03-01T23:59:59.000Z

366

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

367

A Unit Commitment Model with Demand Response for the Integration of Renewable Energies  

E-Print Network [OSTI]

The output of renewable energy fluctuates significantly depending on weather conditions. We develop a unit commitment model to analyze requirements of the forecast output and its error for renewable energies. Our model obtains the time series for the operational state of thermal power plants that would maximize the profits of an electric power utility by taking into account both the forecast of output its error for renewable energies and the demand response of consumers. We consider a power system consisting of thermal power plants, photovoltaic systems (PV), and wind farms and analyze the effect of the forecast error on the operation cost and reserves. We confirm that the operation cost was increases with the forecast error. The effect of a sudden decrease in wind power is also analyzed. More thermal power plants need to be operated to generate power to absorb this sudden decrease in wind power. The increase in the number of operating thermal power plants within a short period does not affect the total opera...

Ikeda, Yuichi; Kataoka, Kazuto; Ogimoto, Kazuhiko

2011-01-01T23:59:59.000Z

368

A Successful Case Study of Small Business Energy Efficiency and Demand  

Open Energy Info (EERE)

A Successful Case Study of Small Business Energy Efficiency and Demand A Successful Case Study of Small Business Energy Efficiency and Demand Response with Communicating Thermostats Jump to: navigation, search Tool Summary LAUNCH TOOL Name: A Successful Case Study of Small Business Energy Efficiency and Demand Response with Communicating Thermostats Focus Area: Energy Efficiency Topics: Socio-Economic Website: drrc.lbl.gov/sites/drrc.lbl.gov/files/lbnl-2743e.pdf Equivalent URI: cleanenergysolutions.org/content/successful-case-study-small-business- Language: English Policies: Financial Incentives This report presents the results of a pilot study of 78 small commercial customers in the Sacramento Municipal Utility District. Participants were given a participation incentive and provided with both help in implementing energy efficiency measures for their buildings and an array of energy

369

Drivers of rising global energy demand: The importance of spatial lag and error dependence  

Science Journals Connector (OSTI)

Abstract This paper analyzes key factors that led to rising global energy demand in recent decades. In addition to income and price elasticities traditionally examined, this research takes into account the effects of structural, demographic, technological and temperature changes on energy demand. Using newly developed panel data techniques allowing for spatial error and/or spatial lag dependence, this research finds evidence for the existence of spatial lag dependence, a positive but declining income elasticity, a negative price elasticity, and the significant effects of industry/service value added, urbanization and technical innovations on energy demand. This research has important implications for public policies that aim to encourage energy savings, develop service sector and promote energy-efficient technologies towards a sustainable energy future.

Yongfu Huang

2014-01-01T23:59:59.000Z

370

Maximizing Energy Savings Reliability in BC Hydro Industrial Demand-side Management Programs  

E-Print Network [OSTI]

saving potential, and (5) a lack of organizational awareness of an operation's energy efficiency over efficiency requirements and pursuing demand-side management (DSM) incentive programs in the large industrial to investment in energy efficiency, and (2) requiring that incentive payments be dependent on measured energy

Victoria, University of

371

A Multipath Energy-Aware On demand Source Routing Protocol for Mobile Ad-Hoc Networks  

E-Print Network [OSTI]

to re-establish broken routes. Thus, a considerable global energy gain can be achieved by minimizing. The choice of the primary route in MEA-DSR is conditioned by two factors: 1) the residual energy of nodesA Multipath Energy-Aware On demand Source Routing Protocol for Mobile Ad-Hoc Networks S. Chettibi

Boyer, Edmond

372

DEMAND SIDE ENERGY MANAGEMENT AND CONSERVATION PROGRAM Measurement and Verification Program  

E-Print Network [OSTI]

DEMAND SIDE ENERGY MANAGEMENT AND CONSERVATION PROGRAM Measurement and Verification Program 4. Operating hours per room usage category ii. Pre-retrofit energy measurements for sampled fixtures iii. Post-retrofit energy measurements for sampled fixtures iv. Summary savings report b. For each of the items above, the M

Hofmann, Hans A.

373

Behavioral Economics Applied to Energy Demand Analysis: A Foundation  

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

the U.S., to project the production, imports, conversion, consumption, and prices of energy over a long-term (30-year) forecast horizon, subject to assumptions on macroeconomic...

374

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

What's New in Monthly Energy Review What's New in Monthly Energy Review December 2013 PDF | previous editions Release Date: December 24, 2013 Next Update: January 28, 2014 Listed below are changes in Monthly Energy Review content. Only months with changes beyond the standard updates are shown. CONTENT CHANGES + EXPAND ALL Changes in 2013 December 2013 Release Electricity statistics have been revised in coordination with EIA's Electric Power Annual 2012. Revisions affect data series in Energy Overview, Energy Consumption, Petroleum, Natural Gas, Coal, Electricity, Nuclear Energy, Energy Prices, Renewable Energy, and Environment. Final 2012 heat content values for electricity (Table A6) have also been incorporated. October 2013 Release Excel and CSV files now include pre-1973 data for all series except for Section 12. The Excel files now have two worksheets, one for monthly data and one for annual data.

375

Electricity Demand-Side Management for an Energy Efficient Future in China: Technology Options and Policy Priorities  

E-Print Network [OSTI]

Electricity Demand-Side Management for an Energy Efficient Future in China: Technology Options sensitive impacts on electricity demand growth by different demand-side management (DSM) scenarios countries. The research showed that demand side management strategies could result in significant reduction

de Weck, Olivier L.

376

Methodology for Analyzing Energy and Demand Savings From Energy Services Performance Contract Using Short-Term Data  

E-Print Network [OSTI]

METHODOLOGY FOR ANALYZING ENERGY AND DEMAND SAVINGS FROM ENERGY SERVICES PERFORMANCE CONTRACT USING SHORT-TERM DATA Zi Liu, Jeff Haberl, Soolyeon Cho Energy Systems Laboratory Texas A&M University System College Station, TX 77843 Bobby... Contract, and includes the methodology developed to calculate the electricity and demand use savings based on different data sources including hourly data from permanently installed logger, hourly data from portable loggers, and weekly manual readings...

Liu, Z.; Haberl, J. S.; Cho, S.; Lynn, B.; Cook, M.

2006-01-01T23:59:59.000Z

377

Total............................................................  

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

Total................................................................... Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546

378

Demand Control Utilizing Energy Management Systems - Report of Field Tests  

E-Print Network [OSTI]

) -- 11.00 DUTY CYCLE (X) -- 1.6 ENERGY USE (KWH) --- - 23.55 ENERGY USE .(%) p- .17 Pattie grill Soup kettle East fryer West fryer Steam booster Outside lights Dishwasher booster Oven Center ~/C(prim) East A/C(prim) Center A.../C(sec) East A/C(sec) Base load MAXIMUM, MINIMUM, AND AVERAGE DURATIONS - - -- ON DURATION OFF DURATION MAXIMUM 0:49 AVERAGE 0:18 Pattie grill Soup kettle East fryer West fryer Steam booster Outside lights Dishwasher booster Oven Center A...

Russell, B. D.; Heller, R. P.; Perry, L. W.

1984-01-01T23:59:59.000Z

379

A Simulation Platform to Demonstrate Active Demand-Side Management by Incorporating Heuristic Optimization for Home Energy Management.  

E-Print Network [OSTI]

??Demand-Side Management (DSM) can be defined as the implementation of policies and measures to control, regulate, and reduce energy consumption. This document introduces home energy (more)

Gudi, Nikhil

2010-01-01T23:59:59.000Z

380

Total...................  

Gasoline and Diesel Fuel Update (EIA)

4,690,065 52,331,397 2,802,751 4,409,699 7,526,898 209,616 1993 Total................... 4,956,445 52,535,411 2,861,569 4,464,906 7,981,433 209,666 1994 Total................... 4,847,702 53,392,557 2,895,013 4,533,905 8,167,033 202,940 1995 Total................... 4,850,318 54,322,179 3,031,077 4,636,500 8,579,585 209,398 1996 Total................... 5,241,414 55,263,673 3,158,244 4,720,227 8,870,422 206,049 Alabama ...................... 56,522 766,322 29,000 62,064 201,414 2,512 Alaska.......................... 16,179 81,348 27,315 12,732 75,616 202 Arizona ........................ 27,709 689,597 28,987 49,693 26,979 534 Arkansas ..................... 46,289 539,952 31,006 67,293 141,300 1,488 California ..................... 473,310 8,969,308 235,068 408,294 693,539 36,613 Colorado...................... 110,924 1,147,743

Note: This page contains sample records for the topic "total energy 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

National Fuel Cell and Hydrogen Energy Overview: Total Energy USA 2012  

Broader source: Energy.gov [DOE]

Presentation by Sunita Satyapal at the Total Energy USA 2012 meeting in Houston, Texas, on November 27, 2012.

382

Energy Demand in China (Carbon Cycle 2.0)  

ScienceCinema (OSTI)

Lynn Price, LBNL scientist, speaks at the Carbon Cycle 2.0 kick-off symposium Feb. 2, 2010. We emit more carbon into the atmosphere than natural processes are able to remove - an imbalance with negative consequences. Carbon Cycle 2.0 is a Berkeley Lab initiative to provide the science needed to restore this balance by integrating the Labs diverse research activities and delivering creative solutions toward a carbon-neutral energy future. http://carboncycle2.lbl.gov/

Price, Lynn

2011-06-08T23:59:59.000Z

383

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Superseded -- see MER for key annual tables Superseded -- see MER for key annual tables Annual Energy Review archives for data year: 2011 2010 2009 2008 all archives Go CONTENT CHANGES + EXPAND ALL Changes in Annual Energy Review 2011 Annual Energy Review 2011 Release: September 27, 2012 1. Energy Consumption, Expenditures, and Emissions Indicators Estimates (Table 1.5) has been modified to include columns for Gross Output and Energy Expenditures as Share of Gross Output and remove Greenhouse Gas Emissions per Real Dollar of Gross Domestic Product. 2. Sales of Fossil Fuels Produced on Federal and American Indian Lands (Table 1.14) was previously titled "Fossil Fuel Production on Federally Administered Lands." It has been redesigned and now provides data on sales of fossil fuels from Federal and American Indian lands for fiscal years 2003 through 2011.

384

Life-Cycle Energy Demand of Computational Logic:From High-Performance 32nm CPU to Ultra-Low-Power 130nm MCU  

E-Print Network [OSTI]

Boyd et al. : Life-cycle energy demand and global warmingLife-Cycle Energy Demand of Computational Logic: From High-to assess the life-cycle energy demand of its products for

Bol, David; Boyd, Sarah; Dornfeld, David

2011-01-01T23:59:59.000Z

385

Life-Cycle Energy Demand of Computational Logic: From High-Performance 32nm CPU to Ultra-Low-Power 130nm MCU  

E-Print Network [OSTI]

Boyd et al. : Life-cycle energy demand and global warmingLife-Cycle Energy Demand of Computational Logic: From High-to assess the life-cycle energy demand of its products for

Bol, David; Boyd, Sarah; Dornfeld, David

2011-01-01T23:59:59.000Z

386

Optimal energy management of a micro-grid with renewable energy resources and demand response  

Science Journals Connector (OSTI)

With the introduction of smart energy grids and extensive penetration of renewable energy resources in distribution networks Micro-Grids (MGs) which are comprised of various alternative energy resources and Advanced Metering Infrastructure (AMI) systems for better implementation of DR programs are effectively employed. The design and development of Smart Energy Management Systems (SEMSs) for MGs are interesting and attractive research problems. In this paper a new SEMS architecture is presented to solve the multi-objective operation management and scheduling problem in a typical MG while considering different energy resource technologies Plug-in Hybrid Electric Vehicles (PHEVs) and DR programs. The energy management problem is formulated as a constrained mixed integer nonlinear multi-objective optimization problem in which the MG's total operating cost and net emissions must be minimized simultaneously. Three different optimization algorithms are used to solve the above mentioned problem and their outputs (Pareto optimal solutions) for the same problem are compared and analyzed.

M. Parvizimosaed; F. Farmani; A. Anvari-Moghaddam

2013-01-01T23:59:59.000Z

387

The impact of demand-controlled and economizer ventilation strategies on energy use in buildings  

SciTech Connect (OSTI)

The overall objective of this work was to evaluate typical energy requirements associated with alternative ventilation control strategies for constant-air-volume (CAV) systems in commercial buildings. The strategies included different combinations of economizer and demand-controlled ventilation, and energy analyses were performed for four typical building types, eight alternative ventilation systems, and twenty US climates. Only single-zone buildings were considered so that simultaneous heating and cooling did not exist. The energy savings associated with economizer and demand-controlled ventilation strategies were found to be very significant for both heating and cooling. In general, the greatest savings in electrical usage for cooling with the addition of demand-controlled ventilation occur in situations where the opportunities for economizer cooling are less. This is true for warm and humid climates and for buildings that have relatively low internal gains (i.e., low occupant densities). As much as 20% savings in electrical energy for cooling were possible with demand-controlled ventilation. The savings in heating energy associated with demand-controlled ventilation were generally much larger but were strongly dependent upon the building type and occupancy schedule. Significantly greater savings were found for buildings with highly variable occupancy schedules and large internal gains (i.e., restaurants) as compared with office buildings. In some cases, the primary heating energy was virtually eliminated by demand-controlled ventilation as compared with fixed ventilation rates. For both heating and cooling, the savings associated with demand-controlled ventilation are dependent on the fixed minimum ventilation rate of the base case at design conditions.

Brandemuehl, M.J.; Braun, J.E.

1999-07-01T23:59:59.000Z

388

Advanced Control Technologies and Strategies Linking DemandResponse and Energy Efficiency  

SciTech Connect (OSTI)

This paper presents a preliminary framework to describe how advanced controls can support multiple modes of operations including both energy efficiency and demand response (DR). A general description of DR, its benefits, and nationwide status is outlined. The role of energy management and control systems for DR is described. Building systems such as HVAC and lighting that utilize control technologies and strategies for energy efficiency are mapped on to DR and demand shedding strategies are developed. Past research projects are presented to provide a context for the current projects. The economic case for implementing DR from a building owner perspective is also explored.

Kiliccote, Sila; Piette, Mary Ann

2005-09-02T23:59:59.000Z

389

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Primary Energy Consumption by Source and Sector, 2011 (Quadrillion Btu) Primary Energy Consumption by Source and Sector, 2011 (Quadrillion Btu) Primary Energy Consumption by Source and Sector diagram image Footnotes: 1 Does not include biofuels that have been blended with petroleum-biofuels are included in "Renewable Energy." 2 Excludes supplemental gaseous fuels. 3 Includes less than 0.1 quadrillion Btu of coal coke net exports. 4 Conventional hydroelectric power, geothermal, solar/PV, wind, and biomass. 5 Includes industrial combined-heat-and-power (CHP) and industrial electricity-only plants. 6 Includes commercial combined-heat-and-power (CHP) and commercial electricity-only plants. 7 Electricity-only and combined-heat-and-power (CHP) plants whose primary business is to sell electricity, or electricity and heat, to the public.

390

Energy Demand Forecast for South East Asia Region: An Econometric Approach with Relation to the Energy Per Capita Curve  

Science Journals Connector (OSTI)

Based on the causality analysis completed for the ASEAN region, macroeconomic factors have a strong relation with increasing the power demand. The bi-directional relationship from energy causing the increase of e...

Nuki Agya Utama; Keiichi N. Ishihara; Tetsuo Tezuka

2013-01-01T23:59:59.000Z

391

Autonomous Demand Side Management Based on Game-Theoretic Energy Consumption  

E-Print Network [OSTI]

Autonomous Demand Side Management Based on Game-Theoretic Energy Consumption Scheduling consumption scheduling game, where the players are the users and their strategies are the daily schedules is achieved at the Nash equilibrium of the formulated energy consumption scheduling game. The proposed

Mohsenian-Rad, Hamed

392

THE CHALLENGES AND OPPORTUNITIES TO MEET THE WORKFORCE DEMAND IN THE ELECTRIC POWER AND ENERGY PROFESSION  

E-Print Network [OSTI]

, but also has become the backbone for our economic development. The world has witnessed electric power1 THE CHALLENGES AND OPPORTUNITIES TO MEET THE WORKFORCE DEMAND IN THE ELECTRIC POWER AND ENERGY and supply in the world in general, and in the US, in particular. The electric power and energy industry

393

Modeling, Estimation, and Control in Energy Systems: Batteries & Demand Response  

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

Modeling, Modeling, Estimation, and Control in Energy Systems: Batteries & Demand Response Scott Moura Assistant Professor Civl & Environmental Engineering University of California, Berkeley EETD | LBNL Scott Moura | UC Berkeley Control, Batts, DR December 4, 2013 | Slide 1 Source: Vaclav Smil Estimates from Energy Transitions Scott Moura | UC Berkeley Control, Batts, DR December 4, 2013 | Slide 2 Energy Initiatives Denmark 50% wind penetration by 2025 Brazil uses 86% renewables China's aggressive energy/carbon intensity reduction EV Everywhere SunShot Green Button Zero emissions vehicle (ZEV) 33% renewables by 2020 Go Solar California Scott Moura | UC Berkeley Control, Batts, DR December 4, 2013 | Slide 3 Energy Systems of Interest Energy storage Smart Grids (e.g., batteries) (e.g., demand response) Scott Moura | UC Berkeley Control, Batts, DR December 4, 2013 | Slide 4 Energy

394

Analysis of the impacts of building energy efficiency policies and technical improvements on China's future energy demand  

Science Journals Connector (OSTI)

In this paper, the LEAP (Long-range Energy Alternatives Planning system) 2000 model and scenario analysis were utilised to study the impact of implementing building energy efficiency policies and promoting related technical improvements on China's future building energy demand up to 2020. In the coming 20 years, China's building energy consumption is expected to increase and will be the main contributor to the growth in China's future energy demand. Without the rational induction of energy efficiency and environmental policies, China's building energy consumption may reach 860 Mtce in 2020 from 197 Mtce in 2000. On the other hand, China possesses huge energy saving potential in the building area. With the enforcement and adoption of related building energy efficiency policies and technical improvement measures, energy consumption in the building sector might decrease to 480 Mtce by 2020; and the energy saving potential might reach 380 Mtce.

Kang Yanbing; Wei Qingpeng

2005-01-01T23:59:59.000Z

395

Potential Energy Total electric potential energy, U, of a system of  

E-Print Network [OSTI]

Potential Energy Total electric potential energy, U, of a system of charges is obtained from of work done by the field, W*= -W. Bring q1 from , W *= 0 since no electric F yet #12;Potential Energy Total electric potential energy, U, of a system of charges is obtained from the work done by an external

Bertulani, Carlos A. - Department of Physics and Astronomy, Texas A&M University

396

Total...........................................................  

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

Q Q Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005

397

Total...................................................................  

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

Single-Family Units Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) At Home Behavior Home Used for Business

398

Total...........................................................  

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

Q Q Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions)

399

Regional Differences in the Price-Elasticity of Demand for Energy  

SciTech Connect (OSTI)

At the request of the National Renewable Energy Laboratory (NREL), the RAND Corporation examined the relationship between energy demand and energy prices with the focus on whether the relationships between demand and price differ if these are examined at different levels of data resolution. In this case, RAND compares national, regional, state, and electric utility levels of data resolution. This study is intended as a first step in helping NREL understand the impact that spatial disaggregation of data can have on estimating the impacts of their programs. This report should be useful to analysts in NREL and other national laboratories, as well as to policy nationals at the national level. It may help them understand the complex relationships between demand and price and how these might vary across different locations in the United States.

Bernstein, M. A.; Griffin, J.

2006-02-01T23:59:59.000Z

400

Demand-side management and European environmental and energy goals: An optimal complementary approach  

Science Journals Connector (OSTI)

Abstract Demand side management (DSM) in electricity markets could improve energy efficiency and achieve environmental targets through controlled consumption. For the past 10 years or so DSM programmes have registered significant results. However, detailed analysis of its real impact as observed by a large number of pilot studies suggests that such programmes need to be fine-tuned to suit clearly identified conditions. This study aims to provide recommendations for the instruments to be used to prompt demand response with a view to maximizing energy and environmental efficiencies of various countries. The present study suggests that different DSM models should be deployed depending on the specific generation mix in any given country. Beside the natural benefits from cross-borders infrastructures, DSM improves the flexibility and reliability of the energy system, absorbing some shock on generation mix. We show efficiency increases with demand response but at a decreasing rate. So, according to rebound and report effects, simple DSM tools could be preferred.

Claire Bergaentzl; Cdric Clastres; Haikel Khalfallah

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total energy 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

Demand Response and Smart Metering Policy Actions Since the Energy Policy  

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 Page Edit with form History Facebook icon Twitter icon » Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials Focus Area: Energy Efficiency, - Utility Topics: Socio-Economic Website: www.demandresponsesmartgrid.org/Resources/Documents/Final_NCEP_Report_ Equivalent URI: cleanenergysolutions.org/content/demand-response-and-smart-metering-po Language: English Policies: Regulations

402

Electrical power distribution control methods, electrical energy demand monitoring methods, and power management devices  

DOE Patents [OSTI]

Electrical power distribution control methods, electrical energy demand monitoring methods, and power management devices are described. In one aspect, an electrical power distribution control method includes providing electrical energy from an electrical power distribution system, applying the electrical energy to a load, providing a plurality of different values for a threshold at a plurality of moments in time and corresponding to an electrical characteristic of the electrical energy, and adjusting an amount of the electrical energy applied to the load responsive to an electrical characteristic of the electrical energy triggering one of the values of the threshold at the respective moment in time.

Chassin, David P. (Pasco, WA); Donnelly, Matthew K. (Kennewick, WA); Dagle, Jeffery E. (Richland, WA)

2006-12-12T23:59:59.000Z

403

Process efficiency in polymer extrusion: Correlation between the energy demand and melt thermal stability  

Science Journals Connector (OSTI)

Abstract Thermal stability is of major importance in polymer extrusion, where product quality is dependent upon the level of melt homogeneity achieved by the extruder screw. Extrusion is an energy intensive process and optimisation of process energy usage while maintaining melt stability is necessary in order to produce good quality product at low unit cost. Optimisation of process energy usage is timely as world energy prices have increased rapidly over the last few years. In the first part of this study, a general discussion was made on the efficiency of an extruder. Then, an attempt was made to explore correlations between melt thermal stability and energy demand in polymer extrusion under different process settings and screw geometries. A commodity grade of polystyrene was extruded using a highly instrumented single screw extruder, equipped with energy consumption and melt temperature field measurement. Moreover, the melt viscosity of the experimental material was observed by using an off-line rheometer. Results showed that specific energy demand of the extruder (i.e. energy for processing of unit mass of polymer) decreased with increasing throughput whilst fluctuation in energy demand also reduced. However, the relationship between melt temperature and extruder throughput was found to be complex, with temperature varying with radial position across the melt flow. Moreover, the melt thermal stability deteriorated as throughput was increased, meaning that a greater efficiency was achieved at the detriment of melt consistency. Extruder screw design also had a significant effect on the relationship between energy consumption and melt consistency. Overall, the relationship between the process energy demand and thermal stability seemed to be negatively correlated and also it was shown to be highly complex in nature. Moreover, the level of process understanding achieved here can help to inform selection of equipment and setting of operating conditions to optimise both energy and thermal efficiencies in parallel.

Chamil Abeykoon; Adrian L. Kelly; Javier Vera-Sorroche; Elaine C. Brown; Phil D. Coates; Jing Deng; Kang Li; Eileen Harkin-Jones; Mark Price

2014-01-01T23:59:59.000Z

404

Total..........................................................................  

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

7.1 7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1 2.8 2.4 2,500 to 2,999..................................................... 10.3 3.7 1.8 2.8 2.1 3,000 to 3,499..................................................... 6.7 2.0 1.4 1.7 1.6 3,500 to 3,999..................................................... 5.2 1.6 0.8 1.5 1.4 4,000 or More.....................................................

405

Total..........................................................................  

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

0.7 0.7 21.7 6.9 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.6 Q Q 500 to 999........................................................... 23.8 9.0 4.2 1.5 3.2 1,000 to 1,499..................................................... 20.8 8.6 4.7 1.5 2.5 1,500 to 1,999..................................................... 15.4 6.0 2.9 1.2 1.9 2,000 to 2,499..................................................... 12.2 4.1 2.1 0.7 1.3 2,500 to 2,999..................................................... 10.3 3.0 1.8 0.5 0.7 3,000 to 3,499..................................................... 6.7 2.1 1.2 0.5 0.4 3,500 to 3,999..................................................... 5.2 1.5 0.8 0.3 0.4 4,000 or More.....................................................

406

Total..........................................................................  

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

25.6 25.6 40.7 24.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.9 1.0 500 to 999........................................................... 23.8 4.6 3.9 9.0 6.3 1,000 to 1,499..................................................... 20.8 2.8 4.4 8.6 5.0 1,500 to 1,999..................................................... 15.4 1.9 3.5 6.0 4.0 2,000 to 2,499..................................................... 12.2 2.3 3.2 4.1 2.6 2,500 to 2,999..................................................... 10.3 2.2 2.7 3.0 2.4 3,000 to 3,499..................................................... 6.7 1.6 2.1 2.1 0.9 3,500 to 3,999..................................................... 5.2 1.1 1.7 1.5 0.9 4,000 or More.....................................................

407

Total..........................................................................  

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

4.2 4.2 7.6 16.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 1.0 0.2 0.8 500 to 999........................................................... 23.8 6.3 1.4 4.9 1,000 to 1,499..................................................... 20.8 5.0 1.6 3.4 1,500 to 1,999..................................................... 15.4 4.0 1.4 2.6 2,000 to 2,499..................................................... 12.2 2.6 0.9 1.7 2,500 to 2,999..................................................... 10.3 2.4 0.9 1.4 3,000 to 3,499..................................................... 6.7 0.9 0.3 0.6 3,500 to 3,999..................................................... 5.2 0.9 0.4 0.5 4,000 or More.....................................................

408

Total.........................................................................  

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

Floorspace (Square Feet) Floorspace (Square Feet) Total Floorspace 2 Fewer than 500.................................................. 3.2 Q 0.8 0.9 0.8 0.5 500 to 999.......................................................... 23.8 1.5 5.4 5.5 6.1 5.3 1,000 to 1,499.................................................... 20.8 1.4 4.0 5.2 5.0 5.2 1,500 to 1,999.................................................... 15.4 1.4 3.1 3.5 3.6 3.8 2,000 to 2,499.................................................... 12.2 1.4 3.2 3.0 2.3 2.3 2,500 to 2,999.................................................... 10.3 1.5 2.3 2.7 2.1 1.7 3,000 to 3,499.................................................... 6.7 1.0 2.0 1.7 1.0 1.0 3,500 to 3,999.................................................... 5.2 0.8 1.5 1.5 0.7 0.7 4,000 or More.....................................................

409

Total..........................................................................  

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

. . 111.1 20.6 15.1 5.5 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.4 500 to 999........................................................... 23.8 4.6 3.6 1.1 1,000 to 1,499..................................................... 20.8 2.8 2.2 0.6 1,500 to 1,999..................................................... 15.4 1.9 1.4 0.5 2,000 to 2,499..................................................... 12.2 2.3 1.7 0.5 2,500 to 2,999..................................................... 10.3 2.2 1.7 0.6 3,000 to 3,499..................................................... 6.7 1.6 1.0 0.6 3,500 to 3,999..................................................... 5.2 1.1 0.9 0.3 4,000 or More.....................................................

410

Total..........................................................................  

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

7.1 7.1 7.0 8.0 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.4 Q Q 0.5 500 to 999........................................................... 23.8 2.5 1.5 2.1 3.7 1,000 to 1,499..................................................... 20.8 1.1 2.0 1.5 2.5 1,500 to 1,999..................................................... 15.4 0.5 1.2 1.2 1.9 2,000 to 2,499..................................................... 12.2 0.7 0.5 0.8 1.4 2,500 to 2,999..................................................... 10.3 0.5 0.5 0.4 1.1 3,000 to 3,499..................................................... 6.7 0.3 Q 0.4 0.3 3,500 to 3,999..................................................... 5.2 Q Q Q Q 4,000 or More.....................................................

411

Total..........................................................  

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

.. .. 111.1 24.5 1,090 902 341 872 780 441 Total Floorspace (Square Feet) Fewer than 500...................................... 3.1 2.3 403 360 165 366 348 93 500 to 999.............................................. 22.2 14.4 763 660 277 730 646 303 1,000 to 1,499........................................ 19.1 5.8 1,223 1,130 496 1,187 1,086 696 1,500 to 1,999........................................ 14.4 1.0 1,700 1,422 412 1,698 1,544 1,348 2,000 to 2,499........................................ 12.7 0.4 2,139 1,598 Q Q Q Q 2,500 to 2,999........................................ 10.1 Q Q Q Q Q Q Q 3,000 or More......................................... 29.6 0.3 Q Q Q Q Q Q Heated Floorspace (Square Feet) None...................................................... 3.6 1.8 1,048 0 Q 827 0 407 Fewer than 500......................................

412

Total...................................................................  

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

2,033 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546 3,500 to 3,999................................................. 5.2 3,549 2,509 1,508

413

Cooling energy demand evaluation by means of regression models obtained from dynamic simulations  

E-Print Network [OSTI]

of energy and CO2 emitter in the EU and is the major energy consumer of the EU's total final energy consumption and CO2 emissions. Buildings account for 40­45% of energy consumption in Europe and China (and estimation of the energy consumption is very difficult. So, we need precise and easy to use support tools

Paris-Sud XI, Université de

414

Total...........................................................  

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

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................... 3.2 1.9 0.9 Q Q Q 1.3 2.3 500 to 999........................................... 23.8 10.5 7.3 3.3 1.4 1.2 6.6 12.9 1,000 to 1,499..................................... 20.8 5.8 7.0 3.8 2.2 2.0 3.9 8.9 1,500 to 1,999..................................... 15.4 3.1 4.2 3.4 2.0 2.7 1.9 5.0 2,000 to 2,499..................................... 12.2 1.7 2.7 2.9 1.8 3.2 1.1 2.8 2,500 to 2,999..................................... 10.3 1.2 2.2 2.3 1.7 2.9 0.6 2.0 3,000 to 3,499..................................... 6.7 0.9 1.4 1.5 1.0 1.9 0.4 1.4 3,500 to 3,999..................................... 5.2 0.8 1.2 1.0 0.8 1.5 0.4 1.3 4,000 or More...................................... 13.3 0.9 1.9 2.2 2.0 6.4 0.6 1.9 Heated Floorspace

415

Total...........................................................  

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

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500.................................... 3.2 0.7 Q 0.3 0.3 0.7 0.6 0.3 Q 500 to 999........................................... 23.8 2.7 1.4 2.2 2.8 5.5 5.1 3.0 1.1 1,000 to 1,499..................................... 20.8 2.3 1.4 2.4 2.5 3.5 3.5 3.6 1.6 1,500 to 1,999..................................... 15.4 1.8 1.4 2.2 2.0 2.4 2.4 2.1 1.2 2,000 to 2,499..................................... 12.2 1.4 0.9 1.8 1.4 2.2 2.1 1.6 0.8 2,500 to 2,999..................................... 10.3 1.6 0.9 1.1 1.1 1.5 1.5 1.7 0.8 3,000 to 3,499..................................... 6.7 1.0 0.5 0.8 0.8 1.2 0.8 0.9 0.8 3,500 to 3,999..................................... 5.2 1.1 0.3 0.7 0.7 0.4 0.5 1.0 0.5 4,000 or More...................................... 13.3

416

Total................................................  

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

.. .. 111.1 86.6 2,522 1,970 1,310 1,812 1,475 821 1,055 944 554 Total Floorspace (Square Feet) Fewer than 500............................. 3.2 0.9 261 336 162 Q Q Q 334 260 Q 500 to 999.................................... 23.8 9.4 670 683 320 705 666 274 811 721 363 1,000 to 1,499.............................. 20.8 15.0 1,121 1,083 622 1,129 1,052 535 1,228 1,090 676 1,500 to 1,999.............................. 15.4 14.4 1,574 1,450 945 1,628 1,327 629 1,712 1,489 808 2,000 to 2,499.............................. 12.2 11.9 2,039 1,731 1,055 2,143 1,813 1,152 Q Q Q 2,500 to 2,999.............................. 10.3 10.1 2,519 2,004 1,357 2,492 2,103 1,096 Q Q Q 3,000 or 3,499.............................. 6.7 6.6 3,014 2,175 1,438 3,047 2,079 1,108 N N N 3,500 to 3,999.............................. 5.2 5.1 3,549 2,505 1,518 Q Q Q N N N 4,000 or More...............................

417

Estimating the energy consumption and power demand of small power equipment in office buildings  

Science Journals Connector (OSTI)

Abstract Small power is a substantial energy end-use in office buildings in its own right, but also significantly contributes to internal heat gains. Technological advancements have allowed for higher efficiency computers, yet current working practices are demanding more out of digital equipment. Designers often rely on benchmarks to inform predictions of small power consumption, power demand and internal gains. These are often out of date and fail to account for the variability in equipment speciation and usage patterns in different offices. This paper details two models for estimating small power consumption in office buildings, alongside typical power demand profiles. The first model relies solely on the random sampling of monitored data, and the second relies on a bottom-up approach to establish likely power demand and operational energy use. Both models were tested through a blind validation demonstrating a good correlation between metered data and monthly predictions of energy consumption. Prediction ranges for power demand profiles were also observed to be representative of metered data with minor exceptions. When compared to current practices, which often rely solely on the use of benchmarks, both proposed methods provide an improved approach to predicting the operational performance of small power equipment in offices.

A.C. Menezes; A. Cripps; R.A. Buswell; J. Wright; D. Bouchlaghem

2014-01-01T23:59:59.000Z

418

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Electricity Flow, (Quadrillion Btu) Electricity Flow, (Quadrillion Btu) Electricity Flow diagram image Footnotes: 1 Blast furnace gas, propane gas, and other manufactured and waste gases derived from fossil fuels. 2 Batteries, chemicals, hydrogen, pitch, purchased steam, sulfur, miscellaneous technologies, and non-renewable waste (municipal solid waste from non-biogenic sources, and tire-derived fuels). 3 Data collection frame differences and nonsampling error. Derived for the diagram by subtracting the "T & D Losses" estimate from "T & D Losses and Unaccounted for" derived from Table 8.1. 4 Electric energy used in the operation of power plants. 5 Transmission and distribution losses (electricity losses that occur between the point of generation and delivery to the customer) are estimated

419

Total Energy - Data - U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Flow, (Million Barrels per Day) Petroleum Flow, (Million Barrels per Day) Petroleum Energy Flow diagram image Footnotes: 1 Unfinished oils, hydrogen/oxygenates/renewables/other hydrocarbons, and motor gasoline and aviation gasoline blending components. 2 Renewable fuels and oxygenate plant net production (0.972), net imports (1.164) and adjustments (0.122) minus stock change (0.019) and product supplied (0.001). 3 Finished petroleum products, liquefied petroleum gases, and pentanes plus. 4 Natural gas plant liquids. 5 Field production (2.183) and renewable fuels and oxygenate plant net production (-.019) minus refinery and blender net imputs (0.489). 6 Production minus refinery input. (s)= Less than 0.005. Notes: * Data are preliminary. * Values are derived from source data prior to rounding for publication.

420

Japan's Long-term Energy Demand and Supply Scenario to 2050 - Estimation for the Potential of Massive CO2 Mitigation  

E-Print Network [OSTI]

to cut primary energy demand per GDP ( T P E S / G D P ) inhowever, primary energy supply per GDP decelerated a declineattention to primary energy supply per GDP, per capita GDP

Komiyama, Ryoichi

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total energy 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

DEMAND SIDE ENERGY MANAGEMENT AND CONSERVATION PROGRAM Measurement and Verification Program  

E-Print Network [OSTI]

DEMAND SIDE ENERGY MANAGEMENT AND CONSERVATION PROGRAM Measurement and Verification Program 4) - Measure toilet and urinal flush volumes a. Units: gallon per flush (gpf) b. Measured by flushing fixture) - Measure faucet and showerhead flow rates a. Units: gallons per minute (gpm) b. Measured using a micro weir

Hofmann, Hans A.

422

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

423

Economic Development and the Structure of the Demand for Commercial Energy Ruth A. Judson, Richard Schmalensee and Thomas M. Stoker*  

E-Print Network [OSTI]

development and energy demand, this study estimates the Engel curves that relate per-capita energy consumption in major economic sectors to per- capita GDP. Panel data covering up to 123 nations are employedEconomic Development and the Structure of the Demand for Commercial Energy Ruth A. Judson, Richard

424

Effect of tree-shading on energy demand of two similar buildings  

Science Journals Connector (OSTI)

Abstract This study investigates the effect of tree-shading on energy demand in two similar buildings. Outdoor and indoor air temperature was measured simultaneously for a period of 6 months. Five different base temperatures ranging from 20C to 25C were chosen and used to calculate cooling degree-days. Degree-day and cooling/warming rate methods were used to estimate cooling energy requirements for the two buildings. Indoor and outdoor cooling degree days were observed to be more for the un-shaded buildings compared to the tree-shaded one. Indoor warming and cooling rate show that the un-shaded building warms earlier and faster than the tree-shaded. Results indicate that tree-shading can save up to 34,500 NGN (US$218) on energy costs. The study shows the role of greening in reducing energy demand in buildings.

Ahmed Adedoyin Balogun; Tobi Eniolu Morakinyo; Olumuyiwa Bayode Adegun

2014-01-01T23:59:59.000Z

425

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

18 Figure 6 Primary Energy Consumption by End-Use in24 Figure 7 Primary Energy Consumption by Fuel in Commercialbased on total primary energy consumption (source energy),

Fridley, David G.

2008-01-01T23:59:59.000Z

426

Deployment of Behind-The-Meter Energy Storage for Demand Charge Reduction  

SciTech Connect (OSTI)

This study investigates how economically motivated customers will use energy storage for demand charge reduction, as well as how this changes in the presence of on-site photovoltaic power generation, to investigate the possible effects of incentivizing increased quantities of behind-the-meter storage. It finds that small, short-duration batteries are most cost effective regardless of solar power levels, serving to reduce short load spikes on the order of 2.5% of peak demand. While profitable to the customer, such action is unlikely to adequately benefit the utility as may be desired, thus highlighting the need for modified utility rate structures or properly structured incentives.

Neubauer, J.; Simpson, M.

2015-01-01T23:59:59.000Z

427

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)

428

Kitchen Table Strategy: Home Inspectors Driving Demand for Home Energy Upgrades  

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

20/2012 20/2012 1 Benjamin Gromicko, InterNACHI "Kitchen Table" Strategy: Home Inspectors Driving Demand for Home Energy Upgrades 3/20/2012 2 Benjamin Gromicko, InterNACHI "Although the home performance industry's delivery of comprehensive energy and comfort improvements has been growing across the country, it continues to struggle in creating consumer attention and demand. Our industry's delivery timing is off. We are not yet engaging the homeowner at their sweet spot of making improvements -- right after they purchase a home! This is when they move most aggressively with all sorts of home improvement projects -- and, unfortunately, seldom with any concerns of energy use. I strongly believe the home inspection industry is in a prime position to educate new homeowners on the long-term

429

Model documentation report: Industrial sector demand module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects. The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2015) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMS system, the Industrial Model receives fuel prices, employment data, and the value of industrial output. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types.

NONE

1997-01-01T23:59:59.000Z

430

Demand Responsive and Energy Efficient Control Technologies and Strategies in Commercial Buildings  

E-Print Network [OSTI]

perspective, a demand-side management framework with threethe integration of DR in demand-side management activitiesdevelopments. The demand-side management (DSM) framework

Piette, Mary Ann; Kiliccote, Sila

2006-01-01T23:59:59.000Z

431

Advanced Controls and Communications for Demand Response and Energy Efficiency in Commercial Buildings  

E-Print Network [OSTI]

buildings. A demand-side management framework from buildingthe integration of DR in demand-side management activitiesdevelopments. The demand-side management (DSM) framework

Kiliccote, Sila; Piette, Mary Ann; Hansen, David

2006-01-01T23:59:59.000Z

432

Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas, and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.

NONE

1998-01-01T23:59:59.000Z

433

Environmental and Resource Economics Household Energy Demand in Urban China: Accounting for regional prices and rapid  

E-Print Network [OSTI]

growth, China's energy consumption is rising at one of the fastest rates in the world, almost 8% per year over the period 2000-2010. Residential energy consumption has grown even faster than the national total . Although household energy consumption per capita is still low compared to the developed countries

434

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

435

Creating balanced energy market structures: equal valuation of supply and demand side initiatives  

Science Journals Connector (OSTI)

Now in its fifth year, the Bordeaux Energy Colloquium was originally created to bring together the voices of various industry constituents to engage in a series of dialogues regarding the creation of a competitive energy marketplace. Each year, Colloquium members consider key variables within various contexts and evaluate their effect on the global transition trend from regulation to competition in energy markets. Fall-2005 Colloquium members agreed that the fundamental imbalance between how supply and demand options are valued is a key stumbling block in the proper functioning of energy markets. Working under the auspices of the Bordeaux Energy Colloquium, 2005 members created a call for action paper that attempts to identify important points of leverage that can be used to further unleash the potential of energy systems in favour of new lines of development.

Kimberly E. Samaha; Thomas L. Welch; John A. Anderson; Thomas R. Casten; Cody Graves

2007-01-01T23:59:59.000Z

436

Closing Data Gaps for LCA of Food Products: Estimating the Energy Demand of Food Processing  

Science Journals Connector (OSTI)

Closing Data Gaps for LCA of Food Products: Estimating the Energy Demand of Food Processing ... To quantify the environmental impacts arising from food production, environmental assessment tools such as life cycle assessment (LCA) should be applied. ... Most of the published LCAs on food are assessing primary agricultural products, e.g., refs 4 and 5, whereas the number of studies available on processed food is lower, e.g., refs 6?8. ...

Neus Sanjun; Franziska Stoessel; Stefanie Hellweg

2013-12-17T23:59:59.000Z

437

Impacts of urban location and climate change upon energy demand of office buildings in Vienna, Austria  

Science Journals Connector (OSTI)

Abstract Urban heat island effects are already known for decades to result in increased urban outdoor temperatures as compared to the surrounding countryside. At the same time, recent years have witnessed growing concern about climate change's impact upon office buildings' performance in regard to indoor thermal comfort and the energy consumption needed to safeguard this comfort. Thus, it has to be expected that buildings in urban areas are especially effected by increased outdoor temperatures and the effects these may cause for indoor thermal comfort. A vicious circle of raising outdoor temperatures and consequently increasing CO2 emissions associated with raising energy demands for cooling during summer heat waves is anticipated in this respect. This paper builds upon regionally downscaled weather data from future climate scenarios and applies these to dynamic thermal simulation of four sample office buildings in Vienna, Austria, at urban locations ranging from central business district to green outskirts of the city. Values of both heating and cooling demands under current and future conditions are calculated: while heating demands slightly diminish, cooling requirements generally rise significantly. Distinct differences in energy performance of buildings from different periods of construction can be observed. The impact of location within the city is considerable.

Tania Berger; Christof Amann; Herbert Formayer; Azra Korjenic; Bernhard Pospichal; Christoph Neururer; Roman Smutny

2014-01-01T23:59:59.000Z

438

The Excitation Energy Dependence of the Total Kinetic Energy Release in 235U(n,f)  

E-Print Network [OSTI]

The total kinetic energy release in the neutron induced fission of $^{235}$U was measured (using white spectrum neutrons from LANSCE) for neutron energies from E$_{n}$ = 3.2 to 50 MeV. In this energy range the average post-neutron total kinetic energy release drops from 167.4 $\\pm$ 0.7 to 162.1 $\\pm$ 0.8 MeV, exhibiting a local dip near the second chance fission threshold. The values and the slope of the TKE vs. E$_{n}$ agree with previous measurements but do disagree (in magnitude) with systematics. The variances of the TKE distributions are larger than expected and apart from structure near the second chance fission threshold, are invariant for the neutron energy range from 11 to 50 MeV. We also report the dependence of the total excitation energy in fission, TXE, on neutron energy.

R. Yanez; L. Yao; J. King; W. Loveland; F. Tovesson; N. Fotiades

2014-03-18T23:59:59.000Z

439

The Impact of Energy Efficiency and Demand Response Programs on the U.S. Electricity Market  

SciTech Connect (OSTI)

This study analyzes the impact of the energy efficiency (EE) and demand response (DR) programs on the grid and the consequent level of production. Changes in demand caused by EE and DR programs affect not only the dispatch of existing plants and new generation technologies, the retirements of old plants, and the finances of the market. To find the new equilibrium in the market, we use the Oak Ridge Competitive Electricity Dispatch Model (ORCED) developed to simulate the operations and costs of regional power markets depending on various factors including fuel prices, initial mix of generation capacity, and customer response to electricity prices. In ORCED, over 19,000 plant units in the nation are aggregated into up to 200 plant groups per region. Then, ORCED dispatches the power plant groups in each region to meet the electricity demands for a given year up to 2035. In our analysis, we show various demand, supply, and dispatch patterns affected by EE and DR programs across regions.

Baek, Young Sun [ORNL; Hadley, Stanton W [ORNL

2012-01-01T23:59:59.000Z

440

Design Considerations for an On-Demand Minimum Energy Routing Protocol for a Wireless Ad Hoc Network  

E-Print Network [OSTI]

at Boulder Boulder, CO-80309 Abstract--A minimum energy routing protocol reduces the energy con- sumption the energy consumption of a wireless ad hoc network. Past research has focused on energy savings schemes1 Design Considerations for an On-Demand Minimum Energy Routing Protocol for a Wireless Ad Hoc

Brown, Timothy X.

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


441

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

were used to calculate the energy mix in manufacturing,of Chinas total energy consumption mix. However, accuratelyof Chinas total energy consumption mix. However, accurately

Fridley, David G.

2008-01-01T23:59:59.000Z

442

Envelope-related energy demand: A design indicator of energy performance for residential buildings in early design stages  

Science Journals Connector (OSTI)

The architectural design variables which most influence the energy performance of a building are the envelope materials, shape and window areas. As these start to be defined in the early design stages, designers require simple tools to obtain information about the energy performance of the building for the design variations being considered at this phase. The shape factor is one of those tools, but it fails to correlate with energy demand in the presence of important solar gains. This paper presents a new design indicator of energy performance for residential buildings, the Envelope-Related Energy Demand (ERED), which aims to overcome the shortcomings of the shape factor while maintaining a reasonable simplicity of use. The inputs to ERED are areas of envelope elements (floor, walls, roofs and windows), U-values of envelope materials, solar heat gain coefficients (SHGC) of windows and site related parameters, concerning temperature and solar irradiation. ERED was validated against detailed simulation results of 8000 hypothetical residential buildings, varying in envelope shape, window areas and materials. Results show that there is a strong correlation between ERED and simulated energy demand. These results confirm the adequacy of ERED to assist design decisions in early stages of the design process.

Vasco Granadeiro; Joo R. Correia; Vtor M.S. Leal; Jos P. Duarte

2013-01-01T23:59:59.000Z

443

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

Science Journals Connector (OSTI)

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

P. Finn; M. OConnell; C. Fitzpatrick

2013-01-01T23:59:59.000Z

444

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

445

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

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

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

446

Model documentation report: Residential sector demand module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document providing a detailed description for energy analysts, other users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

NONE

1995-03-01T23:59:59.000Z

447

"Table A15. Selected Energy Operating Ratios for Total Energy Consumption for"  

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

Selected Energy Operating Ratios for Total Energy Consumption for" Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region and Economic" " Characteristics of the Establishment, 1991" ,,,"Consumption","Major" " "," ","Consumption","per Dollar","Byproducts(b)","Fuel Oil(c)"," " " ","Consumption","per Dollar","of Value","as a Percent","as a Percent","RSE" " ","per Employee","of Value Added","of Shipments","of Consumption","of Natural Gas","Row" "Economic Characteristics(a)","(million Btu)","(thousand Btu)","(thousand Btu)","(percent)","(percent)","Factors"

448

"Table A45. Selected Energy Operating Ratios for Total Energy Consumption"  

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

5. Selected Energy Operating Ratios for Total Energy Consumption" 5. Selected Energy Operating Ratios for Total Energy Consumption" " for Heat, Power, and Electricity Generation by Industry Group," " Selected Industries, and Value of Shipment Categories, 1994" ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent","as a Percent","RSE" "SIC",,"per Employee","of Value Added","of Shipments","of Consumption","of Natural Gas","Row" "Code(a)","Economic Characteristics(b)","(million Btu)","(thousand Btu)","(thousand Btu)","(percents)","(percents)","Factors"

449

"Table A46. Selected Energy Operating Ratios for Total Energy Consumption"  

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

Selected Energy Operating Ratios for Total Energy Consumption" Selected Energy Operating Ratios for Total Energy Consumption" " for Heat, Power, and Electricity Generation by Industry Group," " Selected Industries, and Employment Size Categories, 1994" ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent","as a Percent","RSE" "SIC",,"per Employee","of Value Added","of Shipments","of Consumption","of Natural Gas","Row" "Code(a)","Economic Characteristics(b)","(million Btu)","(thousand Btu)","(thousand Btu)","(percents)","(percents)","Factors"

450

"Table A48. Selected Energy Operating Ratios for Total Energy Consumption for"  

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

8. Selected Energy Operating Ratios for Total Energy Consumption for" 8. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region, Census Division, and Economic" " Characteristics of the Establishment, 1994" ,,,"Consumption","Major" " "," ","Consumption","per Dollar","Byproducts(b)","Fuel Oil(c)"," " " ","Consumption","per Dollar","of Value","as a Percent","as a Percent","RSE" " ","per Employee","of Value Added","of Shipments","of Consumption","of Natural Gas","Row"

451

"Table A8. Selected Energy Operating Ratios for Total Energy Consumption for"  

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

A8. Selected Energy Operating Ratios for Total Energy Consumption for" A8. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region, Industry Group, and" " Selected Industries, 1991" ,,,,,"Major" ,,,,"Consumption","Byproducts(b)" ,,,"Consumption","per Dollar","as a","Fuel Oil(c) as" ,,"Consumption","per Dollar","of Value","Percent of","a Percent of","RSE" "SIC"," ","per Employee","of Value Added","of Shipments","Consumsption","Natural Gas","Row" "Code(a)","Industry Groups and Industry","(million Btu)","(thousand Btu)","(thousand Btu)","(PERCENT)","(percent)","Factors"

452

"Table A51. Selected Energy Operating Ratios for Total Energy Consumption for"  

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

1. Selected Energy Operating Ratios for Total Energy Consumption for" 1. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region and Economic" " Characteristics of the Establishment, 1991 " ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent","as a Percent","RSE" "SIC",,"per Employee","of Value Added","of Shipments","of Consumption","of Natural Gas","Row" "Code(a)","Economic Characteristics(b)","(million Btu)","(thousand Btu)","(thousand Btu)","(percent)","(percent)","Factors"

453

"Table A47. Selected Energy Operating Ratios for Total Energy Consumption for"  

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

7. Selected Energy Operating Ratios for Total Energy Consumption for" 7. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region, Census Division, Industry Group, and" " Selected Industries, 1994" ,,,,,"Major" ,,,,"Consumption","Byproducts(b)" ,,,"Consumption","per Dollar","as a","Fuel Oil(c) as" ,,"Consumption","per Dollar","of Value","Percent of","a Percent of","RSE" "SIC"," ","per Employee","of Value Added","of Shipments","Consumption","Natural Gas","Row" "Code(a)","Industry Group and Industry","(million Btu)","(thousand Btu)","(thousand Btu)","(percents)","(percents)","Factors"

454

"Table A50. Selected Energy Operating Ratios for Total Energy Consumption for"  

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

0. Selected Energy Operating Ratios for Total Energy Consumption for" 0. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Industry Group," " Selected Industries, and Economic Characteristics of the" " Establishment, 1991 (Continued)" ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent of","as a Percent","RSE" "SIC",,"per Employee","of Value Added","of Shipments","of Consumption","of Natural Gas","Row" "Code(a)","Economic Characteristics(b)","(million Btu)","(thousand Btu)","(thousand Btu)","(Percent)","(percent)","Factors"

455

Patterns of residential energy demand by type of household: white, black, Hispanic, and low- and nonlow-income  

SciTech Connect (OSTI)

This report compares patterns of residential energy use by white, black, Hispanic, low-income, and nonlow-income households. The observed downward trend in residential energy demand over the period of this study can be attributed primarily to changes in space-heating energy demand. Demand for space-heating energy has experienced a greater decline than energy demand for other end uses for two reasons: (1) it is the largest end use of residential energy, causing public attention to focus on it and on strategies for conserving it; and (2) space-heating expenditures are large relative to other residential energy expenditures. The price elasticity of demand is thus greater, due to the income effect. The relative demand for space-heating energy, when controlled for the effect of climate, declined significantly over the 1978-1982 period for all fuels studied. Income classes do not differ significantly. In contrast, black households were found to use more energy for space heating than white households were found to use, although those observed differences are statistically significant only for houses heated with natural gas. As expected, the average expenditure for space-heating energy increased significantly for dwellings heated by natural gas and fuel oil. No statistically significant increases were found in electricity expenditures for space heating. Electric space heat is, in general, confined to milder regions of the country, where space heating is relatively less essential. As a consequence, we would expect the electricity demand for space heating to be more price-elastic than the demand for other fuels.

Klein, Y.; Anderson, J.; Kaganove, J.; Throgmorton, J.

1984-10-01T23:59:59.000Z

456

The influence of shading control strategies on the visual comfort and energy demand of office buildings  

Science Journals Connector (OSTI)

Abstract A lighting control strategy using daylighting is important to reduce energy consumption, and to provide occupants with visual comfort. The objective of this research is to evaluate visual comfort and building energy demand, and suggest lighting and shading control strategies for visual comfort and building energy savings. This research intends to achieve visual comfort and energy savings in an office building, by means of visual environmental control, and focuses on a quantitative criterion (illuminance), and a qualitative criterion (glare index) in daylighting. We used HDR images captured in real scene and simulation (DIVA-for-Rhino) for glare evaluation. The measured data from the mock-up room and the scale model were compared, to validate the simulation tool. Vertical eye illuminance (Ev) is recommended for the glare index, in place of the DGI or DGP. To prevent disturbing glare and to secure maximum daylight, control strategies of lighting and shading are suggested, related to the Ev value. In addition, the EnergyPlus program was used for calculation of the annual energy consumption. Building energy consumption is presented according to three building orientations, and 10 control strategies of lighting and shading. If there is no need to consider glare, a blind slat angle of 0 or dynamic shading is better in winter, regardless of the building orientation. In summer, a blind slat angle of 30 (static angle) or dynamic shading is suitable for an energy efficient and anti-glare control strategy.

Gyeong Yun; Kap Chun Yoon; Kang Soo Kim

2014-01-01T23:59:59.000Z

457

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

458

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

459

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

460

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

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


461

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

462

Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. This report serves three purposes. First, it is a reference document providing a detailed description for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, section 57(b)(1)). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

NONE

1995-02-01T23:59:59.000Z

463

Economic development and the structure of the demand for commercial energy  

SciTech Connect (OSTI)

To deepen understanding of the relation between economic development and energy demand, this study estimates the relations between per-capita GDP and per-capita energy consumption in major economic sectors. Panel data covering up to 123 nations are employed, and measurement problems are treated both in dataset construction and in estimation. Time and country fixed effects are assumed, and flexible forms for income effects are employed. There are substantial differences among sectors in the structure of country, time, and income effects. In particular, the household sector's share of aggregate energy consumption tends to fall with income, the share of transportation tends to rise, and the share of industry follows an inverse-U pattern.

Judson, R.A.; Schmalensee, R.; Stoker, T.M.

1999-07-01T23:59:59.000Z

464

Model documentation report: Commercial sector demand module of the national energy modeling system  

SciTech Connect (OSTI)

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. This document serves three purposes. First, it is a reference document providing a detailed description for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

NONE

1994-08-01T23:59:59.000Z

465

The energy required to produce materials: constraints on energy-intensity improvements, parameters of demand  

Science Journals Connector (OSTI)

...processes. Data for iron energy intensity are adapted...are adapted from Choate Green-[16]. Production...15 Smil, V . 2008 Energy in nature and society...Choate, WT , and JAS Green. 2003 US energy requirements for aluminum...

2013-01-01T23:59:59.000Z

466

The Impact of Building Energy Standards on Energy Use and Demand  

Science Journals Connector (OSTI)

Although energy requirements, and the associated energy costs, have always been of some concern to building designers energy criteria are a relatively new addition to building standards. It took the formation ...

J. W. Jones

1988-01-01T23:59:59.000Z

467

Optimal Participation of DR Aggregators in Day-Ahead Energy and Demand Response Exchange Markets  

Science Journals Connector (OSTI)

Aggregating the Demand Response (DR) is approved as an effective ... transmission system operator, distributors, and retailers in Demand Response eXchange (DRX) market, in addition to...

Ehsan Heydarian-Forushani

2014-01-01T23:59:59.000Z

468

The High Energy Demand of Neuronal Cells Caused by Passive Leak Currents is Not a Waste of Energy  

Science Journals Connector (OSTI)

It is estimated that maintenance of the resting potential of neurons consumes between 15% (in gray matter) and 44% (in fully myelinated white matter) of the brains total energy budget [1...]. This poses the in...

Nikolaus Berndt; Hermann-Georg Holzhtter

2013-11-01T23:59:59.000Z

469

A comparative analysis of energy demand and expenditures by minority and majority households within the context of a conditional demand system  

SciTech Connect (OSTI)

Analysis and evaluation of the impact that programs and policies have on energy consumption and expenditures are confounded by many intervening variables. A clear understanding of how these variables influence energy consumption patterns should be grounded in a rigorously developed framework. In this regard much is documented in the literature. However, an analysis of the comparative relationship between energy demand and variables which influence it among different socioeconomic groups has not been thoroughly explored with any theoretical rigor. It is proposed that differences in patterns of energy use between black, Hispanic, and majority households (where the household head is neither black nor Hispanic) are due to both structural and distribution differences. It is felt that the structural dissimilarities are primarily due to the dynamic nature in which energy consumption patterns evolve, with differences in changing housing patterns playing a significant role. For minorities, this implies a potential difference in the effect of policy and programs on economic welfare when compared to majority households.To test this hypothesis, separate conditional demand systems are estimated for majority, black, and Hispanic households. With the use of separate variance/covariance matrices, various parameter groups are tested for statistically significant differences.

Poyer, D.A.

1992-08-01T23:59:59.000Z

470

A comparative analysis of energy demand and expenditures by minority and majority households within the context of a conditional demand system  

SciTech Connect (OSTI)

Analysis and evaluation of the impact that programs and policies have on energy consumption and expenditures are confounded by many intervening variables. A clear understanding of how these variables influence energy consumption patterns should be grounded in a rigorously developed framework. In this regard much is documented in the literature. However, an analysis of the comparative relationship between energy demand and variables which influence it among different socioeconomic groups has not been thoroughly explored with any theoretical rigor. It is proposed that differences in patterns of energy use between black, Hispanic, and majority households (where the household head is neither black nor Hispanic) are due to both structural and distribution differences. It is felt that the structural dissimilarities are primarily due to the dynamic nature in which energy consumption patterns evolve, with differences in changing housing patterns playing a significant role. For minorities, this implies a potential difference in the effect of policy and programs on economic welfare when compared to majority households.To test this hypothesis, separate conditional demand systems are estimated for majority, black, and Hispanic households. With the use of separate variance/covariance matrices, various parameter groups are tested for statistically significant differences.

Poyer, D.A.

1992-01-01T23:59:59.000Z

471

Renewable generation and demand response integration in micro-grids: development of a new energy management and control system  

Science Journals Connector (OSTI)

The aim of this research resides in the development of an energy management and control system to control a micro-grid based on the use of renewable generation and demand resources to introduce the application of...

Carlos lvarez-Bel; Guillermo Escriv-Escriv; Manuel Alczar-Ortega

2013-11-01T23:59:59.000Z

472

Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings  

E-Print Network [OSTI]

of Central Government Buildings. Available at: http://Energy Commission, PIER Building End-Use Energy Efficiencythe total lifecycle of a building such as petroleum and

Fridley, David G.

2008-01-01T23:59:59.000Z

473

The carbon footprint and non-renewable energy demand of algae-derived biodiesel  

Science Journals Connector (OSTI)

Abstract We determine the environmental impact of different biodiesel production strategies from algae feedstock in terms of greenhouse gas (GHG) emissions and non-renewable energy consumption, we then benchmark the results against those of conventional and synthetic diesel obtained from fossil resources. The algae cultivation in open pond raceways and the transesterification process for the conversion of algae oil into biodiesel constitute the common elements among all considered scenarios. Anaerobic digestion and hydrothermal gasification are considered for the conversion of the residues from the wet oil extraction route; while integrated gasificationheat and power generation and gasificationFischerTropsch processes are considered for the conversion of the residues from the dry oil extraction route. The GHG emissions per unit energy of the biodiesel are calculated as follows: 41g e-CO2/MJb for hydrothermal gasification, 86g e-CO2/MJb for anaerobic digestion, 109g e-CO2/MJb for gasificationpower generation, and 124g e-CO2/MJb for gasificationFischerTropsch. As expected, non-renewable energy consumptions are closely correlated to the GHG values. Also, using the High Dimensional Model Representation (HDMR) method, a global sensitivity analysis over the entire space of input parameters is performed to rank them with respect to their influence on key sustainability metrics. Considering reasonable ranges over which each parameter can vary, the most influential input parameters for the wet extraction route include extractor energy demand and methane yield generated from anaerobic digestion or hydrothermal gasification of the oil extracted-algae. The dominant process input parameters for the dry extraction route include algae oil content, dryer energy demand, and algae annual productivity. The results imply that algal biodiesel production from a dried feedstock may only prove sustainable if a low carbon solution such as solar drying is implemented to help reducing the water content of the feedstock.

Pooya Azadi; George Brownbridge; Sebastian Mosbach; Andrew Smallbone; Amit Bhave; Oliver Inderwildi; Markus Kraft

2014-01-01T23:59:59.000Z

474

An Adaptive Tree Code for Computing Total Potential Energy in Classical Molecular Systems  

E-Print Network [OSTI]

An Adaptive Tree Code for Computing Total Potential Energy in Classical Molecular Systems Zhong, 2000 Abstract A tree code algorithm is presented for rapid computation of the total potential energy are presented for a variety of systems. Keywords: adaptive tree code; total potential energy; nonbonded

Duan, Zhong-Hui

475

THE USE OF TRUST REGIONS IN KOHN-SHAM TOTAL ENERGY MINIMIZATION  

E-Print Network [OSTI]

-consistent and the Kohn-Sham (KS) total energy function associated with the system reaches the global minimum. It has longTHE USE OF TRUST REGIONS IN KOHN-SHAM TOTAL ENERGY MINIMIZATION CHAO YANG , JUAN C. MEZA , AND LIN system, is viewed in this paper as an optimization procedure that minimizes the Kohn- Sham total energy

Geddes, Cameron Guy Robinson

476

The relationship between energy intensity and income levels: Forecasting long term energy demand in Asian emerging countries  

SciTech Connect (OSTI)

This paper analyzes long-term trends in energy intensity for ten Asian emerging countries to test for a non-monotonic relationship between energy intensity and income in the author's sample. Energy demand functions are estimated during 1973--1990 using a quadratic function of log income. The long-run coefficient on squared income is found to be negative and significant, indicating a change in trend of energy intensity. The estimates are then used to evaluate a medium-term forecast of energy demand in the Asian countries, using both a log-linear and a quadratic model. It is found that in medium to high income countries the quadratic model performs better than the log-linear, with an average error of 9% against 43% in 1995. For the region as a whole, the quadratic model appears more adequate with a forecast error of 16% against 28% in 1995. These results are consistent with a process of dematerialization, which occurs as a result of a reduction of resource use per unit of GDP once an economy passes some threshold level of GDP per capita.

Galli, R. (Birkbeck Coll., London (United Kingdom) Univ. della Svizzera Italiana, Lugano (Switzerland). Facolta di Scienze Economiche)

1998-01-01T23:59:59.000Z

477

Remote area wind energy harvesting for low-power autonomous sensors Abstract--A growing demand for deployment of autonomous  

E-Print Network [OSTI]

Remote area wind energy harvesting for low-power autonomous sensors Abstract--A growing demand wind energy harvesting is presented, with a focus on an anemometer-based solution. By utilizing for localized, independent energy harvesting capabilities for each node. In this paper, a method of remote area

478

Impact of Constraints in Energy Imports and Energy Production of Final Domestic Demand  

Science Journals Connector (OSTI)

Several events of the past ten years have clearly demonstrated how important the problem of energy dependency has become. In the case of Switzerland, this problem is crucial since all types of primary energy e...

Gabrielle Antille; Bernadette Laplanche

1985-01-01T23:59:59.000Z

479

World population and energy demand growth: the potential role of fusion energy in an efficient world  

Science Journals Connector (OSTI)

...growth: the potential role of fusion energy in an efficient world...fossil-replacement value in 2050. Fusion energy can, then, have a role...2) the deployment of all types of energy source to meet the...nuclear power, both fission and fusion, can play a very important...

1999-01-01T23:59:59.000Z

480

World population and energy demand growth: the potential role of fusion energy in an efficient world  

Science Journals Connector (OSTI)

...substantial amounts of nuclear and solar energy to meet their long-term needs...substantial amounts of nuclear and solar energy to meet their long-term needs...use must be made of nuclear and solar energies. Both sources have the advantage...

1999-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "total energy 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

Bottom-Up Energy Analysis System - Methodology and Results  

E-Print Network [OSTI]

country energy coverage will total 77% of global demand. Thetotal energy demand in 2005[6], the countries covered account for 62% of global

McNeil, Michael A.

2013-01-01T23:59:59.000Z

482

Advanced Demand Responsive Lighting  

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

483

Total China Investment Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Total China Investment Co Ltd Total China Investment Co Ltd Jump to: navigation, search Name Total (China) Investment Co. Ltd. Place Beijing, China Zip 100004 Product Total has been present in China for about 30 years through its activities of Exploration & Production, Gas & Power, Refining & Marketing, and Chemicals. Coordinates 39.90601°, 116.387909° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.90601,"lon":116.387909,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

484

The energy required to produce materials: constraints on energy-intensity improvements, parameters of demand  

Science Journals Connector (OSTI)

...data for embodied energy comes from Ashby-[10], for material prices for metals from the...10]. Plastic prices are for year 2011...2009. Figure 7. Energy intensity e versus...Natl Acad. Sci. USA 107, 20 905-20...an environmental history of the twentieth-century...

2013-01-01T23:59:59.000Z

485

Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building  

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

4E 4E Comparison of Demand Response Performance with an EnergyPlus Model in a Low Energy Campus Building J.H. Dudley, D. Black, M. Apte, M.A. Piette Lawrence Berkeley National Laboratory P. Berkeley University of California, Berkeley May 2010 Presented at the 2010 ACEEE Summer Study on Energy Efficiency in Buildings, Pacific Grove, CA, August 15-20, 2010, and published in the Proceedings DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information,

486

Energy, cost and carbondioxide optimization in regional energy systems with periodic and stochastic demand fluctuations  

Science Journals Connector (OSTI)

The new linear, stochastic optimization model ECCO...has been developed as a computerized planning tool for case studies on integrated energy management involving heat recovery by heat exchanger ... each of which...

Helmuth-M. Groscurth; Reiner Kmmel

1992-01-01T23:59:59.000Z

487

Influence of Tangent Pinch Points on the Energy Demand of Batch Distillations: Development of a Conceptual Model for Binary Mixtures  

Science Journals Connector (OSTI)

Influence of Tangent Pinch Points on the Energy Demand of Batch Distillations: Development of a Conceptual Model for Binary Mixtures ... The algorithm requires the evaluation of a series of points (x0,f0), (x1,f1), ..., (xn,fn), and it demands the smallest number of function evaluations in comparison with other methods as a consequence of using the information from previous iterations to generate greater order estimations of the inverse function (lineal, quadratic, etc.). ...

Karina Andrea Torres; Jose? Espinosa

2011-04-08T23:59:59.000Z

488

Abstract --Due to the potentially large number of Distributed Energy Resources (DERs) demand response, distributed  

E-Print Network [OSTI]

to accurately estimate the transients caused by demand response is especially important to analyze the stability of the system under different demand response strategies, where dynamics on time scales of seconds to minutes demand response. The aggregated model efficiently includes statistical information of the population

Zhang, Wei

489

Property:Building/TotalFloorArea | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:Building/TotalFloorArea Jump to: navigation, search This is a property of type Number. Total floor area (BRA), m2 Pages using the property "Building/TotalFloorArea" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 19,657 + Sweden Building 05K0002 + 7,160 + Sweden Building 05K0003 + 4,855 + Sweden Building 05K0004 + 25,650 + Sweden Building 05K0005 + 2,260 + Sweden Building 05K0006 + 13,048 + Sweden Building 05K0007 + 24,155 + Sweden Building 05K0008 + 7,800 + Sweden Building 05K0009 + 34,755 + Sweden Building 05K0010 + 437 + Sweden Building 05K0011 + 15,310 + Sweden Building 05K0012 + 22,565 + Sweden Building 05K0013 + 19,551 +

490

Property:RenewableFuelStandard/Total | Open Energy Information  

Open Energy Info (EERE)

Total Total Jump to: navigation, search This is a property of type Number. Pages using the property "RenewableFuelStandard/Total" Showing 15 pages using this property. R Renewable Fuel Standard Schedule + 13.95 + Renewable Fuel Standard Schedule + 26 + Renewable Fuel Standard Schedule + 15.2 + Renewable Fuel Standard Schedule + 28 + Renewable Fuel Standard Schedule + 16.55 + Renewable Fuel Standard Schedule + 30 + Renewable Fuel Standard Schedule + 18.15 + Renewable Fuel Standard Schedule + 9 + Renewable Fuel Standard Schedule + 33 + Renewable Fuel Standard Schedule + 20.5 + Renewable Fuel Standard Schedule + 11.1 + Renewable Fuel Standard Schedule + 36 + Renewable Fuel Standard Schedule + 22.25 + Renewable Fuel Standard Schedule + 12.95 + Renewable Fuel Standard Schedule + 24 +

491

Implications of maximizing China's technical potential for residential end-use energy efficiency: A 2030 outlook from the bottom-up  

E-Print Network [OSTI]

4 3. Basis for Residential Energy Demandand the subsequent energy demand and CO 2 emissionsa smaller share of total energy demand followed by space

Khanna, Nina

2014-01-01T23:59:59.000Z

492

"Table A28. Total Expenditures for Purchased Energy Sources by Census Region"  

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

Total Expenditures for Purchased Energy Sources by Census Region" Total Expenditures for Purchased Energy Sources by Census Region" " and Economic Characteristics of the Establishment, 1991" " (Estimates in Million Dollars)" " "," "," "," ",," "," "," "," "," ","RSE" " "," "," ","Residual","Distillate","Natural"," "," ","Coke"," ","Row" "Economic Characteristics(a)","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors"

493

Property:Building/FloorAreaTotal | Open Energy Information  

Open Energy Info (EERE)

FloorAreaTotal FloorAreaTotal Jump to: navigation, search This is a property of type Number. Total Pages using the property "Building/FloorAreaTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 19,657 + Sweden Building 05K0002 + 7,160 + Sweden Building 05K0003 + 4,454 + Sweden Building 05K0004 + 25,650 + Sweden Building 05K0005 + 2,260 + Sweden Building 05K0006 + 14,348 + Sweden Building 05K0007 + 24,155 + Sweden Building 05K0008 + 7,800 + Sweden Building 05K0009 + 34,755 + Sweden Building 05K0010 + 437 + Sweden Building 05K0011 + 15,300 + Sweden Building 05K0012 + 22,565 + Sweden Building 05K0013 + 19,551 + Sweden Building 05K0014 + 1,338.3 + Sweden Building 05K0015 + 1,550 + Sweden Building 05K0016 + 2,546 +

494

Property:Building/SPElectrtyUsePercTotal | Open Energy Information  

Open Energy Info (EERE)

SPElectrtyUsePercTotal SPElectrtyUsePercTotal Jump to: navigation, search This is a property of type String. Total Pages using the property "Building/SPElectrtyUsePercTotal" Showing 25 pages using this property. (previous 25) (next 25) S Sweden Building 05K0001 + 100.0 + Sweden Building 05K0002 + 100.0 + Sweden Building 05K0003 + 100.0 + Sweden Building 05K0004 + 100.0 + Sweden Building 05K0005 + 100.0 + Sweden Building 05K0006 + 100.0 + Sweden Building 05K0007 + 100.0 + Sweden Building 05K0008 + 100.0 + Sweden Building 05K0009 + 100.0 + Sweden Building 05K0010 + 100.0 + Sweden Building 05K0011 + 100.0 + Sweden Building 05K0012 + 100.0 + Sweden Building 05K0013 + 100.0 + Sweden Building 05K0014 + 100.0 + Sweden Building 05K0015 + 100.0 + Sweden Building 05K0016 + 100.0 +

495

The worldwide demand for green energy systems is evident. In this context, wind energy converters will play a paramount role. Extending the service life of a  

E-Print Network [OSTI]

acquisition units and a computer installed in the wind energy converter, is designed to continuously collect measurement data from the wind energy converter. As shown in Fig. 1, six three- dimensional accelerometersABSTRACT The worldwide demand for green energy systems is evident. In this context, wind energy

Stanford University

496

AEO2011: Total Energy Supply, Disposition, and Price Summary | OpenEI  

Open Energy Info (EERE)

Total Energy Supply, Disposition, and Price Summary Total Energy Supply, Disposition, and Price Summary Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion BTUs, and quantifies the energy prices using U.S. dollars. The data is broken down into total production, imports, exports, consumption, and prices for energy types. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption EIA export import production reference case total energy Data application/vnd.ms-excel icon AEO2011: Total Energy Supply, Disposition, and Price Summary - Reference Case (xls, 112.8 KiB) Quality Metrics

497

IEP - Water-Energy Interface: Total Maximum Daily Load Page  

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

Total Maximum Daily Loads (TMDLs) Total Maximum Daily Loads (TMDLs) The overall goal of the Clean Water Act is to "restore and maintain the chemical, physical, and biological integrity of the Nation’s waters." In 1999, EPA proposed changes to Section 303(d), to establish Total Maximum Daily Loads (TMDLs) for watersheds that do not meet this goal. The TMDL is the highest amount of a given pollutant that is permissible in that body of water over a given period of time. TMDLs include both waste load allocation (WLA) for point sources and load allocations for non-point sources. In Appalachia, acid mine drainage (AMD) is the single most damaging non-point source. There is also particular concern of the atmospheric deposition of airborne sulfur, nitrogen, and mercury compounds. States are currently in the process of developing comprehensive lists of impaired waters and establishing TMDLs for those waters. EPA has recently proposed a final rule that will require states to develop TMDLs and implement plans for improving water quality within the next 10 years. Under the new rule, TMDL credits could be traded within a watershed.

498

"Table A36. Total Expenditures for Purchased Energy Sources by Census Region,"  

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

6. Total Expenditures for Purchased Energy Sources by Census Region," 6. Total Expenditures for Purchased Energy Sources by Census Region," " Census Division, Industry Group, and Selected Industries, 1994" " (Estimates in Million Dollars)" ,,,,,,,,,,,"RSE" "SIC"," "," "," ","Residual","Distillate ","Natural"," "," ","Coke"," ","Row" "Code(a)","Industry Group and Industry","Total","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","LPG","Coal","and Breeze","Other(d)","Factors" ,,"Total United States"

499

Energy Efficiency and Demand Response: How do we make the most out of using less energy?  

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

Vermont ♦ Maine ♦ New Mexico ♦ California ♦ Illinois ♦ Oregon ♦ Washington Making the Most of Responsive Electricity Customers Mid-America Regulatory Conference June 8, 2010 Richard Sedano About the Regulatory Assistance Project  RAP is a non-profit organization providing technical and educational assistance to government officials on energy and environmental issues. RAP Principals all have extensive utility regulatory experience. - Richard Sedano was commissioner of the Vermont Department of Public Service from 1991-2001 and is an engineer.  Funded by foundations and the US Department Of Energy. We have worked in nearly every state and many nations.  Also provides educational assistance to stakeholders, utilities, advocates. 2 Context

500

Optimization of Ventilation Energy Demands and Indoor Air Quality in High-Performance Homes  

SciTech Connect (OSTI)

High-performance homes require that ventilation energy demands and indoor air quality (IAQ) be simultaneously optimized. We attempted to bridge these two areas by conducting tests in a research house located in Oak Ridge, TN, that was 20 months old, energy-efficient (i.e., expected to consume 50% less energy than a house built per the 2006 IRC), tightly-built (i.e., natural ventilation rate ~0.02 h-1), unoccupied, and unfurnished. We identified air pollutants of concern in the test home that could generally serve as indicators of IAQ, and conduced field experiments and computer simulations to determine the effectiveness and energy required by various techniques that lessened the concentration of these contaminants. Formaldehyde was selected as the main pollutant of concern among the contaminants that were sampled in the initial survey because it was the only compound that showed concentrations that were greater than the recommended exposure levels. Field data indicate that concentrations were higher during the summer primarily because emissions from sources rise with increases in temperature. Furthermore, supply ventilation and gas-phase filtration were effective means to reduce formaldehyde concentrations; however, exhaust ventilation had minimal influence on this pollutant. Results from simulations suggest that formaldehyde concentrations obtained while ventilating per ASHRAE 62.2-2010 could be decreased by about 20% from May through September through three strategies: 1) increasing ASHRAE supply ventilation by a factor of two, 2) reducing the thermostat setpoint from 76 to 74 F, or 3) running a gas-phase filtration system while decreasing supply ventilation per ASHRAE by half. In the mixed-humid climate of Oak Ridge, these strategies caused increases in electricity cost of ~$5 to ~$15/month depending on outdoor conditions.

Hun, Diana E [ORNL; Jackson, Mark C [University of Texas at Austin; Shrestha, Som S [ORNL

2014-01-01T23:59:59.000Z