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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
to obtain the most current and comprehensive results.


1

Best Practices: Energy Savings Efficient energy use reduces Colorado State's total energy demand, decreases harmful  

E-Print Network (OSTI)

square foot on campus has flattened out. Students making a difference In 2004, Colorado State became one, decreases harmful emissions, and minimizes the cost of providing energy to the campus. As a result of energy conservation initiatives that have been implemented over the past 20 years, growth in the average demand per

2

Addressing Energy Demand through Demand Response: International...  

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

Addressing Energy Demand through Demand Response: International Experiences and Practices Title Addressing Energy Demand through Demand Response: International Experiences and...

3

Addressing Energy Demand through Demand Response: International...  

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

Energy Demand through Demand Response: International Experiences and Practices Title Addressing Energy Demand through Demand Response: International Experiences and Practices...

4

Addressing Energy Demand  

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

Addressing Energy Demand through Demand Response: International Experiences and Practices Bo Shen, Girish Ghatikar, Chun Chun Ni, and Junqiao Dudley Environmental Energy...

5

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network (OSTI)

Total Annual Energy Usage Peak Electric Demand Power UsageSetpoint (°C) Peak Electric Demand Power Usage Effective-Total Annual Energy Usage Peak Electric Demand Scenario

Shehabi, Arman

2010-01-01T23:59:59.000Z

6

Turkey's energy demand and supply  

SciTech Connect

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

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

2009-07-01T23:59:59.000Z

7

ENERGY DEMAND FORECAST METHODS REPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400 .......................................................................................................................................1-1 ENERGY DEMAND FORECASTING AT THE CALIFORNIA ENERGY COMMISSION: AN OVERVIEW

8

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

of integrating demand response and energy efficiencyand D. Kathan (2009), Demand Response in U.S. ElectricityFRAMEWORKS THAT PROMOTE DEMAND RESPONSE 3.1. Demand Response

Shen, Bo

2013-01-01T23:59:59.000Z

9

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network (OSTI)

DX Cooling Total Annual Energy Usage Peak Electric DemandDX Cooling Total Annual Energy Usage Scenario Supply/ ReturnDX Cooling Total Annual Energy Usage Peak Electric Demand

Shehabi, Arman

2010-01-01T23:59:59.000Z

10

CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST Demand Forecast report is the product of the efforts of many current and former California Energy Commission staff. Staff contributors to the current forecast are: Project Management and Technical Direction

11

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

12

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

13

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

energy efficiency and demand response programs and tariffs.energy efficiency and demand response program and tariffenergy efficiency and demand response programs and tariffs.

Goldman, Charles

2010-01-01T23:59:59.000Z

14

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, Electricity Demography Japan’s population, an important factor in predicting residential energy demand as well

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

15

Energy Demand Staff Scientist  

E-Print Network (OSTI)

consumption per ton steel #12;Industrial Energy EfficiencyIndustrial Energy Efficiency Policy Analysis intensity trends and policy background · Focus on Industrial Energy Efficiency · Policy analysis PrimaryEnergy(Mtce) Commercial Buildings Residential Buildings Transportation Industry China 0 500 1,000 1

Knowles, David William

16

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

17

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

18

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

19

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"

20

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

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

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

E-Print Network (OSTI)

US 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 Approach Page 1 of 25 US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier

22

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

2007 EMCS EPACT ERCOT FCM FERC FRCC demand side managementEnergy Regulatory Commission (FERC). EPAct began the processin wholesale markets, which FERC Order 888 furthered by

Shen, Bo

2013-01-01T23:59:59.000Z

23

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand The demand forecast is the combined product of the hard work and expertise of numerous California Energy previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare

24

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand.Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad

25

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Robert P. Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast

26

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

California Energy Demand Scenario Projections to 2050 RyanResearch Program California Energy Commission November 7,Chris Kavalec. California Energy Commission. CEC (2003a)

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

2008-01-01T23:59:59.000Z

27

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network (OSTI)

USA, and published in the Conference Proceedings Structure of SBEAM Floor-space forecast to 2050 Gross demandUSA, and published in the Conference Proceedings Structure of SBEAM Floor-space forecast to 2050 Gross demandUSA, and published in the Conference Proceedings Relative Importance Total off- site energy demand (

Stadler, Michael

2011-01-01T23:59:59.000Z

28

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.

29

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.

30

Demand Response | Department of Energy  

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

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

31

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

for the most natural gas usage (33% and 51% of total demanddependence in natural gas usage, and consequently, Januarygas demand exhibits a strong winter peak in residential usage

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

2008-01-01T23:59:59.000Z

32

Energy Basics: Tankless Demand Water Heaters  

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

only as needed and without the use of a storage tank. They don't produce the standby energy losses associated with storage water heaters. How Demand Water Heaters Work Demand...

33

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

and Demand Response Duke Energy is using the name “Save-a-Energy Efficiency Division. Duke Energy describes all of itsPresident, and C.E.O. Duke Energy Kateri Callahan President

Goldman, Charles

2010-01-01T23:59:59.000Z

34

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

35

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad

36

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped

37

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work and expertise of numerous, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare

38

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped

39

Residential sector: the demand for energy services  

Science Conference Proceedings (OSTI)

The purpose of this report is to project the demand for residential services, and, thereby, the demand for energy into the future. The service demands which best represent a complete breakdown of residential energy consumption is identified and estimates of the amount of energy, by fuel type, used to satisfy each service demand for an initial base year (1978) are detailed. These estimates are reported for both gross (or input) energy use and net or useful energy use, in the residential sector. The various factors which affect the consumption level for each type of energy and each identified service demand are discussed. These factors include number of households, appliance penetration, choice of fuel type, technical conversion efficiency of energy using devices, and relative energy efficiency of the building shell (extent of insulation, resistance to air infiltration, etc.). These factors are discussed relative to both the present and expected future values, for the purpose of projections. The importance of the housing stock to service demand estimation and projection and trends in housing in Illinois are discussed. How the housing stock is projected based on population and household projections is explained. The housing projections to the year 2000 are detailed. The projections of energy consumption by service demand and fuel type are contrasted with the various energy demand projections in Illinois Energy Consumption Trends: 1960 to 2000 and explains how and why the two approaches differ. (MCW)

Not Available

1981-01-01T23:59:59.000Z

40

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

dependence in natural gas usage. January typically sees theindustrial fuels usage. Natural gas demand has been risinggas demands regionally, to account for variability in energy usage

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

2008-01-01T23:59:59.000Z

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

Coordination of Energy Efficiency and Demand Response  

Science Conference Proceedings (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

42

Coordination of Energy Efficiency and Demand Response  

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

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

43

Japan's Residential Energy Demand Outlook to 2030  

E-Print Network (OSTI)

for Energy Efficiency and Renewable Energy, Planning, Analysis, and Evaluation section in the U.S. Department section in the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. #12;ppaappeerr ttoo bbeeLBNL-292E Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards

44

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

45

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

time. 4 Reducing this peak demand through DR programs meansthat a 5% reduction in peak demand would have resulted insame 5% reduction in the peak demand of the US as a whole.

Shen, Bo

2013-01-01T23:59:59.000Z

46

China End-Use Energy Demand Modeling  

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

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

47

Renewable Energy, Demand Response, Energy Efficiency, and Advanced...  

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

Renewable Energy, Demand Response, Energy Efficiency, and Advanced Energy Storage Infrastructure in UC San Diego's Microgrid Speaker(s): Byron Washom Date: August 14, 2008 -...

48

The Integration of Energy Efficiency, Renewable Energy, Demand...  

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

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

49

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity forecast is the combined product of the hard work and expertise of numerous staff members in the Demand the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast. Miguel Garcia

50

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

51

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

52

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

53

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

54

A residential energy demand system for Spain  

E-Print Network (OSTI)

Sharp price fluctuations and increasing environmental and distributional concerns, among other issues, have led to a renewed academic interest in energy demand. In this paper we estimate, for the first time in Spain, an ...

Labandeira Villot, Xavier

2005-01-01T23:59:59.000Z

55

BRYAN LOVELL Energy supply, demand and impact  

E-Print Network (OSTI)

BRYAN LOVELL Energy supply, demand and impact Now it is Britain's turn to think harder, says Brian both are true. Most predict that fossil fuels must remain a significant part of our energy supply, Britain has had a comfortable and profitable respite from anxieties about security of energy supply. Now

Cambridge, University of

56

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.

57

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.

58

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.

59

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

E-Print Network (OSTI)

step is to calculate energy service demand in each category,mainly determine the energy service demand while pricesthe energy source. In both energy service demand and energy

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

60

Transportation Energy: Supply, Demand and the Future  

E-Print Network (OSTI)

Transportation Energy: Supply, Demand and the Future http://www.uwm.edu/Dept/CUTS//2050/energy05.pdf Edward Beimborn Center for Urban Transportation Studies University of Wisconsin-Milwaukee Presentation to the District IV Conference Institute of Transportation Engineers June, 2005, updated September

Saldin, Dilano

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

Energy Demand (released in AEO2010)  

Reports and Publications (EIA)

Growth in U.S. energy use is linked to population growth through increases in demand for housing, commercial floorspace, transportation, manufacturing, and services. This affects not only the level of energy use, but also the mix of fuels and consumption by sector.

Information Center

2010-05-11T23:59:59.000Z

62

Letters: Energy demand prediction using GMDH networks  

Science Conference Proceedings (OSTI)

The electric power industry is in transition as it moves towards a competitive and deregulated environment. In this emerging market, traditional electric utilities as well as energy traders, power pools and independent system operators (ISOs) need the ... Keywords: Artificial neural networks, Energy demand, Forecasting, Group method of data handling (GMDH) networks, Self-organizing networks

Dipti Srinivasan

2008-12-01T23:59:59.000Z

63

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network (OSTI)

off- site energy demand (2030) 20% decrease to parameter 20%off-site energy demand (2030) 20% decrease to parameter 20%off-site energy demand (2030) 20% decrease to parameter 20%

Stadler, Michael

2011-01-01T23:59:59.000Z

64

EIA - Annual Energy Outlook 2009 - Energy Demand  

Gasoline and Diesel Fuel Update (EIA)

demand for renewable fuels increasing the fastestincluding E85 and biodiesel fuels for light-duty vehicles, biomass for co-firing at coal-fired electric power plants, and...

65

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

66

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)"

67

"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"

68

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"

69

Managing Energy Demand With Standards and Information  

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

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

70

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

Natural Gas Demands..xi Annual natural gas demand for each alternativeused in natural gas demand projections. 34

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

2008-01-01T23:59:59.000Z

71

Opportunities for Energy Efficiency and Demand Response in the...  

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

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

72

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

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

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

73

Energy Demands and Efficiency Strategies in Data Center Buildings  

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

Energy Demands and Efficiency Strategies in Data Center Buildings Title Energy Demands and Efficiency Strategies in Data Center Buildings Publication Type Thesis Year of...

74

South Korea-ANL Distributed Energy Resources and Demand Side...  

Open Energy Info (EERE)

Korea-ANL Distributed Energy Resources and Demand Side Management Jump to: navigation, search Name Distributed Energy Resources and Demand Side Management in South Korea Agency...

75

Modeling the residential demand for energy  

Science Conference Proceedings (OSTI)

Demand for energy is derived from the demand for services that appliances and energy together provide. This raises a number of serious econometric issues when estimating energy-demand functions: delineation of short-run and long-run household responses, specification of the price variable and in particular, the assumption that the model is recursive, or in other words, that the appliance choice equation and the energy consumption equation are uncorrelated. The dissertation utilizes a structural model of energy use whose theoretical underpinnings derive from the conditional logit model and an extension of that model to the joint-discrete/continuous case by Dubin and McFadden (1980). It uses the 1978 to 1979 National Interim Energy Comsumption Survey. Three appliance portfolio choices are analyzed; choice of water and space heating and central air-conditioning; choice of room air conditioners; and choice of clothes dryers, either as multinomial logit or binary probit choices. Results varied widely across the appliance choice considered; use of Hausman's test led to acceptance of the null hypothesis of orthogonality in some cases but not in others. Demand for electricity and natural gas tended to be price inelastic; however, estimated own-price effects differed considerably when disaggregated by appliance categories and across methods of estimation.

Kirby, S.N.

1983-01-01T23:59:59.000Z

76

Total organic carbon (TOC) and chemical oxygen demand (COD) - Monitoring of organic pollutants in wastewater.  

E-Print Network (OSTI)

?? Total organic carbon (TOC) and chemical oxygen demand (COD) are two methods used for measuring organic pollutants in wastewater. Both methods are widely used… (more)

Hodzic, Elvisa

2011-01-01T23:59:59.000Z

77

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

Minimum demand and Maximum demand incorporate assumptionslevels, or very minor Maximum demand household size, growthvehicles in Increasing Maximum demand 23 mpg truck share

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

2008-01-01T23:59:59.000Z

78

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 and brake, a lathe, a process chiller, and cooling tower pumps and fans] in two industrial plants. Demand factors for heavily loaded air compressors were found to be near 100 %, for lightly loaded centrifugal equipment (lathe, sheet metal shear and brake, and granulator) near 10 %, and for injection-molding machines near 50 %. The measured demand factors differ from those often estimated during energy surveys. Duty factors for some equipment were found to exceed 100 %, showing that some loads were on for longer periods than that indicated by plant personnel. Comparing a detailed summary of equipment rated loads to annual utility bills, when measurements are not available, can prevent over-estimation of the demand and duty factors for a plant. Raw unadjusted estimates of demand factors of 60 % or higher are often made, yet comparisons of rated loads to utility bills show that some equipment demand factors may be 50 % or less. This project tested a simple beacon alerting system, which used a blue strobe light to alert plant personnel when a preset demand limit had been reached. Tests of load shedding verified that the estimated demand savings of 50 kVA were realized (out of a total demand of almost 1200 kVA) when lighting and air conditioning loads were turned off.

Dooley, Edward Scott

2001-01-01T23:59:59.000Z

79

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":""}]}

80

Load Reduction, Demand Response and Energy Efficient Technologies and Strategies  

SciTech Connect

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

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

2008-11-19T23:59:59.000Z

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

Impact of improved building thermal efficiency on residential energy demand  

SciTech Connect

The impact of improved building shell thermal efficiency on residential energy demand is explored in a theoretical framework. The important economic literature on estimating the price elasticity of residential energy demand is reviewed. The specification of the residential energy demand model is presented. The data used are described. The empirical estimation of the residential energy demand model is described. (MHR)

Adams, R.C.; Rockwood, A.D.

1983-04-01T23:59:59.000Z

82

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":""}]}

83

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

to Building Energy Management Systems (BEMS) to begin pre-a facility using Energy Management Control Systems (EMCS) orAct of 2007 energy management control systems The Energy

Shen, Bo

2013-01-01T23:59:59.000Z

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

Comparison of Demand Response Performance with an EnergyPlus...  

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

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

86

Building Energy Software Tools Directory: Energy Demand Modeling  

NLE Websites -- All DOE Office Websites (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

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

8.4 Demand Response Integration . . . . . . . . . . .for each day type for the demand response study - moderatefor each day type for the demand response study - moderate

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

88

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

89

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

is determined by the market energy price offered by themay be paid the spot market energy price. (e.g. PJM SRM, UKor the wholesale market price for energy. By codifying the

Shen, Bo

2013-01-01T23:59:59.000Z

90

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

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

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

91

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

rate California electricity consumption (GWh) Over two-thirds of total electricity demand is concentrated in the residential andrate N/A PG&E SMUD SCE LADWP SDGE BGP Other All CA 2005 IEPR Residential electricity

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

2008-01-01T23:59:59.000Z

92

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

93

Coordination of Energy Efficiency and Demand Response  

NLE Websites -- All DOE Office Websites (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

94

Univariate Modeling and Forecasting of Monthly Energy Demand Time Series  

E-Print Network (OSTI)

in this report. #12;i ABSTRACT These electricity demand forms and instructions ask load-serving entities and Instructions for Electricity Demand Forecasts. California Energy Commission, Electricity Supply Analysis.................................................................................................................................7 Form 1 Historic and Forecast Electricity Demand

Abdel-Aal, Radwan E.

95

Driving Demand for Home Energy Improvements  

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

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

96

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

E-Print Network (OSTI)

Energy Outlook -A Projection up to 2030 under EnvironmentalEnergy Demand Outlook to 2030 Considering Energy EfficiencyEnergy Demand Outlook to 2030 Considering Energy Efficiency

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

97

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

E-Print Network (OSTI)

Japan Long-Term Energy Outlook -A Projection up to 2030Residential Energy Demand Outlook to 2030 Considering EnergyResidential Energy Demand Outlook to 2030 Considering Energy

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

98

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

residential electricity consumption, the flattening of the demand curves (except Maximum demand) reflects decreasing population growth ratesresidential electricity demand are described in Table 11. For simplicity, end use-specific UEC and saturation rates

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

2008-01-01T23:59:59.000Z

99

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

percent of 2008 summer peak demand (FERC, 2008). Moreover,138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).non-coincident summer peak demand by 157 GW” by 2030, or 14–

Goldman, Charles

2010-01-01T23:59:59.000Z

100

Tankless Demand Water Heaters | Department of Energy  

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

Demand Water Heaters Tankless Demand Water Heaters August 19, 2013 - 2:57pm Addthis Illustration of an electric demand water heater. At the top of the image, the heating unit is...

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

EIA - Annual Energy Outlook 2009 - Electricity Demand  

Gasoline and Diesel Fuel Update (EIA)

data Rate of Electricity Demand Growth Slows, Following the Historical Trend Electricity demand fluctuates in the short term in response to business cycles, weather conditions,...

102

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

29 5.6. Peak and hourly demand43 6.6. Peak and seasonal demandthe average percent of peak demand) significantly impact the

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

2008-01-01T23:59:59.000Z

103

Energy Efficiency Funds and Demand Response Programs - National Overview  

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

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

104

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network (OSTI)

Heat DX Cooling Total Annual Energy Usage Peak Electricifier DX Cooling Total Annual Energy Usage Scenario Supply/ifier DX Cooling Total Annual Energy Usage Peak Electric

Shehabi, Arman

2010-01-01T23:59:59.000Z

105

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

106

Residential Demand Module of the National Energy Modeling ...  

U.S. Energy Information Administration (EIA)

Residential Demand Module of the National Energy Modeling System: Model Documentation 2013 November 2013 Independent Statistics & Analysis ...

107

Residual Fuel Demand - U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

In the 1986 to 1991 period, residual fuel oil demand declined only slightly both in absolute and as a percent of total product demand. While not shown, residual fuel ...

108

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

109

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

Open Energy Info (EERE)

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:...

110

Chapter 3 Demand-Side Resources | Department of Energy  

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

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

111

Examining Synergies between Energy Management and Demand Response...  

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

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

112

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

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

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

113

Energy Efficiency/Demand Response/Smart Grid/Distribution ...  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration Independent Statistics & Analysis www.eia.gov Energy Efficiency/Demand Response/Smart Grid/Distribution ...

114

Assumptions to the Annual Energy Outlook 1999 - Industrial Demand...  

Gasoline and Diesel Fuel Update (EIA)

industrial.gif (5205 bytes) The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing...

115

Solar in Demand | Department of Energy  

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

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...

116

Demand Response - Policy | Department of Energy  

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

over the last 11 years when interest in demand response increased. Demand response is an electricity tariff or program established to motivate changes in electric use by end-use...

117

Propane Demand by Sector - Energy Information Administration  

U.S. Energy Information Administration (EIA)

In order to understand markets you also have to look at supply and demand. First, demand or who uses propane. For the most part, the major components of propane ...

118

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":""}]}

119

Reducing Energy Demand in Buildings Through State Energy Codes  

NLE Websites -- All DOE Office Websites (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:

120

Reducing Energy Demand in Buildings Through State Energy Codes  

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

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:

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

Residential Energy Demand Reduction Analysis and Monitoring Platform - REDRAMP  

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

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

122

Building Energy Software Tools Directory: Demand Response Quick Assessment  

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

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

123

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

In Maximum demand, year 2050 electricity consumption reachesefficiency, year 2050 electricity consumption is 357 TWh,capita electricity consumption increases from 7,421 kWh/year

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

2008-01-01T23:59:59.000Z

124

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

Science Conference Proceedings (OSTI)

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

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

2011-07-01T23:59:59.000Z

125

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

126

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

127

Solar total energy project Shenandoah  

DOE Green Energy (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

128

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":""}]}

129

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.

130

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)

131

Forecasts of intercity passenger demand and energy use through 2000  

SciTech Connect

The development of national travel demand and energy-use forecasts for automobile and common-carrier intercity travel through the year 2000. The forecasts are driven by the POINTS (Passenger Oriented Intercity Network Travel Simulation) model, a model direct-demand model which accounts for competition among modes and destinations. Developed and used to model SMSA-to-SMSA business and nonbusiness travel, POINTS is an improvement over earlier direct demand models because it includes an explicit representation of cities' relative accessibilities and a utility maximizing behavorial multimodal travel function. Within POINTS, pathbuilding algorithms are used to determine city-pair travel times and costs by mode, including intramodal transfer times. Other input data include projections of SMSA population, public and private sector employment, and hotel and other retail receipts. Outputs include forecasts of SMSA-to-SMSA person trips and person-miles of travel by mode. For the national forecasts, these are expanded to represent all intercity travel (trips greater than 100 miles, one way) for two fuel-price cases. Under both cases rising fuel prices, accompanied by substantial reductions in model-energy intensities, result in moderate growth in total intercity passenger travel. Total intercity passenger travel is predicted to grow at approximately one percent per year, slightly fster than population growth, while air travel grows almost twice as fast as population. The net effect of moderate travel growth and substantial reduction in model energy intensities is a reduction of approximately 50 percent in fuel consumption by the intercity passenger travel market.

Kaplan, M.P.; Vyas, A.D.; Millar, M.; Gur, Y.

1982-01-01T23:59:59.000Z

132

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

Open Energy Info (EERE)

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:...

133

Residential Energy Demand Reduction Analysis and Monitoring Platform...  

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

Dramatic Peak Residential Demand Reduction in the Desert Southwest Yahia Baghzouz Center for Energy Research University of Nevada, Las Vegas Golden, CO Overview * Project...

134

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

Open Energy Info (EERE)

Side Management Website Jump to: navigation, search Name Network-Driven Demand Side Management Website Abstract This task of the International Energy Agency is a broad,...

135

1995 Demand-Side Managment - Energy Information Administration  

U.S. Energy Information Administration (EIA)

and more detailed data on energy savings, peak load reductions and costs attributable to DSM. Target Audience ... Profile: U.S. Electric Utility Demand-Side

136

Commercial Demand Module of the National Energy Modeling System ...  

U.S. Energy Information Administration (EIA)

Commercial Demand Module of the National Energy Modeling System: Model Documentation 2012 November 2012 . Independent Statistics & Analysis . www.eia.gov

137

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

138

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

Scale Renewable Energy Integration . . . . . . . . . . .Impacts of Renewable Energy Supply . . . . . . . . . . . . .1.3 Coupling Renewable Energy with Deferrable

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

139

Solar in Demand | Department of Energy  

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

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

140

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

Regulatory Commission [FERC] (2008). Assessment of DemandRegulatory Commission [FERC] (2009). A National AssessmentEIS EMCS EMS EPA ESCO ESPC FERC GE HVAC ISO ISO-NE kW kWh MW

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.


141

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

function of real-time electricity prices (left) and windinflexible) demand and real-time prices. The case study inas a special case. The real-time price process is modeled as

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

142

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

143

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

144

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

Figure 16 Annual peak electricity demand by sector. Tableincludes an hourly electricity demand (i.e. power) profileof aggregating sectoral electricity demands into a statewide

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

2008-01-01T23:59:59.000Z

145

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

Table 22. Agricultural natural gas demand by planning area.23. “Other” sector natural gas demand by planning area.Projections Monthly natural gas demands are depicted in

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

2008-01-01T23:59:59.000Z

146

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

147

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].

148

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.

149

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,

150

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

151

Assessment of Residential Energy Management Systems for Demand Response Applications  

Science Conference Proceedings (OSTI)

This Technical Update provides a description of what a residential energy management system comprises, with a focus on demand response applications. It includes findings from a survey of residential energy management system technology vendors; system pricing and availability; an overview of technology components and features; customer load monitoring and control capabilities; utility demand response control functions; communications protocols and technologies supported; and options for demand response si...

2009-12-22T23:59:59.000Z

152

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

same or better levels of energy services. ” This definitionSenior Vice President, Energy Services and Technology NewNational Association of Energy Service Companies Chuck Gray

Goldman, Charles

2010-01-01T23:59:59.000Z

153

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

to managing their energy usage. Greater customer willingnessto managing their energy usage. And greater customera net reduction in energy usage. 5 With sufficient advance

Goldman, Charles

2010-01-01T23:59:59.000Z

154

Regulation Services with Demand Response - Energy Innovation ...  

Biomass and Biofuels; Building Energy Efficiency; Electricity Transmission; Energy Analysis; Energy Storage; Geothermal; Hydrogen and Fuel Cell; ... (i.e. target ...

155

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

achieving all cost-effective energy efficiency by 2025. Thisinvestment in cost-effective energy efficiency. Coordinationto achieve all cost-effective energy efficiency by 2025. 1

Goldman, Charles

2010-01-01T23:59:59.000Z

156

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

control system energy management system U.S. Environmentalbuilding energy management systems (EMS) can deliversystem; EMS = energy management system; ISO = independent

Goldman, Charles

2010-01-01T23:59:59.000Z

157

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&E’s Integrated Energy Audit, a program for businesses

Goldman, Charles

2010-01-01T23:59:59.000Z

158

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

what if wholesale market energy prices remain low or if CPPwith high prices in the real-time energy market. Nationalmarket prices and reliability circumstances, even though energy

Goldman, Charles

2010-01-01T23:59:59.000Z

159

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

forecasting for wind energy: Temperature dependence andlarge amounts of wind energy with a small electric system.Large scale integration of wind energy in the european power

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

160

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

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

"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"

162

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST forecast is the combined product of the hard work and expertise of numerous staff members in the Demand prepared the residential sector forecast. Mohsen Abrishami prepared the commercial sector forecast. Lynn

163

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

Director, Energy and Environmental Policy American ForestEnergy Efficiency Partnerships Roger Cooper Executive Vice President, Policy and Planning American

Goldman, Charles

2010-01-01T23:59:59.000Z

164

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

State Energy Research & Development Authority offers incentivesState Energy Research and Development Authority (NYSERDA) Existing Facilities Program offers incentives

Goldman, Charles

2010-01-01T23:59:59.000Z

165

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

E-Print Network (OSTI)

Energy. “Benefits of Demand Response in Electricity MarketsEnergy Efficiency and Demand Response?7 3.1.Demand Response in Commercial

Piette, Mary Ann; Kiliccote, Sila

2006-01-01T23:59:59.000Z

166

A Successful Case Study of Small Business Energy Efficiency and Demand Response with Communicating Thermostats  

E-Print Network (OSTI)

to everyone at the Demand Response Research Center, theEnergy Efficiency and Demand Response with CommunicatingEnergy Efficiency and Demand Response with Communicating

Herter, Karen

2010-01-01T23:59:59.000Z

167

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

E-Print Network (OSTI)

Energy  Efficiency and Demand Response in the California 1   4.0   Energy Efficiency and Demand Response 5   4.2.   Demand Response 

Olsen, Daniel

2012-01-01T23:59:59.000Z

168

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

169

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

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

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...

170

Strategies for reducing energy demand in the materials sector  

E-Print Network (OSTI)

This research answers a key question - can the materials sector reduce its energy demand by 50% by 2050? Five primary materials of steel, cement, aluminum, paper, and plastic, contribute to 50% or more of the final energy ...

Sahni, Sahil

2013-01-01T23:59:59.000Z

171

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

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

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

172

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

new technology and systems integration tools. Energy controland systems that support integration and coordination of energyand systems integration represent key building blocks for enabling greater coordination of energy

Goldman, Charles

2010-01-01T23:59:59.000Z

173

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

174

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

175

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

Optimal Control of Distributed Energy Resources and DemandRenewable Energy, former Distributed Energy Program of theOptimal Control of Distributed Energy Resources and Demand

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

176

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

by Sector Residential Peak Demand (MW) Commercial IndustrialTable 16. Non-coincident peak demand by sector. growth Avg.IEPR Projected non-coincident peak demand (MW) 3.1.2. Hourly

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

2008-01-01T23:59:59.000Z

177

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.

178

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022  

E-Print Network (OSTI)

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA or adequacy of the information in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast forecast. Bryan Alcorn and Mehrzad Soltani Nia prepared the industrial forecast. Miguel Garcia- Cerrutti

179

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

180

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

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

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

182

2009 Total Energy Production by State | Department of Energy  

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

09 Total Energy Production by State 2009 Total Energy Production by State 2009 Total Energy Production by State Click on a state for more information. Addthis Browse By Topic...

183

Estimating disaggregated price elasticities in industrial energy demand  

Science Conference Proceedings (OSTI)

Econometric energy models are used to evaluate past policy experiences, assess the impact of future policies and forecast energy demand. This paper estimates an industrial energy demand model for the province of Ontario using a linear-logit specification for fuel type equations which are embedded in an aggregate energy demand equation. Short-term, long-term, own- and cross-price elasticities are estimated for electricity, natural gas, oil and coal. Own- and cross-price elasticities are disaggregated to show that overall price elasticities and the energy-constant price elasticities when aggregate energy use is held unchanged. These disaggregations suggest that a substantial part of energy conservation comes from the higher aggregate price of energy and not from interfuel substitution. 13 refs., 2 tabs.

Elkhafif, M.A.T. (Ontario Ministry of Energy, Toronto (Canada))

1992-01-01T23:59:59.000Z

184

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

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

Housing Units (millions) Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Census Division Total South...

185

Total Energy | U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

What's New in Total Energy. Monthly Energy Review September 25, 2013. Monthly Energy Review August 27, 2013. Monthly Energy Review July 26, 2013.

186

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

E-Print Network (OSTI)

L ABORATORY Japan’s Residential Energy Demand Outlook tol i f o r n i a Japan’s Residential Energy Demand Outlook toParticularly in Japan’s residential sector, where energy

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

187

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

188

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.

189

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.

190

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

191

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

192

Industrial Demand Module 1999, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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.

T. Crawford Honeycutt

1999-01-01T23:59:59.000Z

193

Industrial Demand Module 2005, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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.

T. C. Honeycutt

2005-05-01T23:59:59.000Z

194

Industrial Demand Module 2006, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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.

T. C. Honeycutt

2006-07-01T23:59:59.000Z

195

Industrial Demand Module 2009, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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.

T. C. Honeycutt

2009-05-20T23:59:59.000Z

196

Industrial Demand Module 2003, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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.

T. Crawford Honeycutt

2003-12-01T23:59:59.000Z

197

Industrial Demand Module 2007, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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.

T. C. Honeycutt

2007-03-21T23:59:59.000Z

198

Industrial Demand Module 2002, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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.

T. Crawford Honeycutt

2001-12-01T23:59:59.000Z

199

Industrial Demand Module 2001, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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.

T. Crawford Honeycutt

2000-12-01T23:59:59.000Z

200

Industrial Demand Module 2008, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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.

T. C. Honeycutt

2008-06-01T23:59:59.000Z

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.


201

Industrial Demand Module 2000, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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.

T. Crawford Honeycutt

2000-01-01T23:59:59.000Z

202

Industrial Demand Module 2004, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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.

T. Crawford Honeycutt

2004-02-01T23:59:59.000Z

203

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

204

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

event by paying higher real-time prices and still receivingvarying prices (e.g. , real-time prices, CPP) facilitatecorrelated with high prices in the real-time energy market.

Goldman, Charles

2010-01-01T23:59:59.000Z

205

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

E-Print Network (OSTI)

your Power. (2008). "Demand Response Programs." RetrievedS. (2008). Automated Demand Response Results from Multi-Yearusing Open Automated Demand Response, California Energy

Lekov, Alex

2009-01-01T23:59:59.000Z

206

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

E-Print Network (OSTI)

Contribution to Peak Demand?..5 3.potential to reduce peak demand in commercial buildingsbuildings’ contribution to peak demand and the use of energy

Piette, Mary Ann; Kiliccote, Sila

2006-01-01T23:59:59.000Z

207

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

E-Print Network (OSTI)

for a large portion of summer peak demand. Research resultspotential to reduce peak demand in commercial buildingsbuilding’s contribution to peak demand and the use of energy

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

2006-01-01T23:59:59.000Z

208

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network (OSTI)

lower RH upper RH UPS Waste Heat Humid- ifier DX Cooling Total Annual Energy Usage Peak Electriclower RH upper RH UPS Waste Heat Humid- ifier DX Cooling Total Annual Energy Usage Peak Electric

Shehabi, Arman

2010-01-01T23:59:59.000Z

209

Swarm intelligence approaches to estimate electricity energy demand in Turkey  

Science Conference Proceedings (OSTI)

This paper proposes two new models based on artificial bee colony (ABC) and particle swarm optimization (PSO) techniques to estimate electricity energy demand in Turkey. ABC and PSO electricity energy estimation models (ABCEE and PSOEE) are developed ... Keywords: Ant colony optimization, Artificial bee colony, Electricity energy estimation, Particle swarm optimization, Swarm intelligence

Mustafa Servet K?Ran; Eren ÖZceylan; Mesut GüNdüZ; Turan Paksoy

2012-12-01T23:59:59.000Z

210

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

E-Print Network (OSTI)

Opportunities for Energy  Efficiency and Demand Response in Agricultural/Water End?Use Energy Efficiency Program.    i 1   4.0   Energy Efficiency and Demand Response 

Olsen, Daniel

2012-01-01T23:59:59.000Z

211

Global Energy Demand, Supply, Consequences, Opportunities  

E-Print Network (OSTI)

/Joule Population-Energy Equation Power = N x (GDP/N) x (Watts/GDP) C Emission Rate = Power x (Carbon/J) #12;d HVAC Onsite Power & Heat Natural Ventilation, Indoor Environment Building Materials Appliances Thermal · Building Materials Tenants · Lease space from Developer or Property Manager · Professional firms, retailers

Knowles, David William

212

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.

213

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

214

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,

215

Energy and Emissions Long Term Outlook A Detailed Simulation of Energy Supply-Demand  

E-Print Network (OSTI)

The paper presents the results of a detailed, bottom-up modeling exercise of Mexico’s energy markets. The Energy and Power Evaluation Program (ENPEP), the Wien Automatic System Planning (WASP) and the Energy Demand Model (MODEMA) were used to develop forecasts to 2025. Primary energy supply is projected to grow from 9,313 PJ (1999) to 13,130 PJ (2025). Mexico’s crude oil production is expected to increase by 1 % annually to 8,230 PJ. As its domestic crude refining capacity becomes unable to meet the rising demand for petroleum products, imports of oil products will become increasingly important. The Mexican natural gas markets are driven by the strong demand for gas in the power generating and manufacturing industries which significantly outpaces projected domestic production. The result is a potential need for large natural gas imports that may reach approximately 46 % of total gas supplies by 2025. The long-term market outlook for Mexico’s electricity industry shows a heavy reliance on naturalgas based generating technologies. Gas-fired generation is forecast to increase 26-fold eventually accounting for over 80 % of total generation by 2025. Alternative results for a constrained-gas scenario show a substantial shift to coal-based generation and the associated effects on the natural gas market. A renewables scenario – investigates impacts of additional renewables for power generation (primarily wind plus some solar-photovoltaic). A nuclear scenario – analyzes the impacts of additional nuclear power

Juan Quintanilla Martínez; Autónoma México; Centro Mario Molina; Juan Quintanilla Martínez

2005-01-01T23:59:59.000Z

216

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

DOE Green Energy (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

217

The Economics of Energy (and Electricity) Demand  

E-Print Network (OSTI)

% electrical efficiency might be able to deliver electrical heat using half the gas of gas fired boiler with ‘90% efficiency’ (p.152-153). An electric car uses around 15 kWh per 100 km, around 5 times less than the average fossil fuel car. This implies... that there is always a wide-range of observed efficiencies in the economy, with the average efficiency of the provision of an energy service being significantly less than the efficiency of the most efficient. Current new fossil fuel cars and gas boilers are 50...

Platchkov, Laura M.; Pollitt, Michael G.

218

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.

219

Tankless or Demand-Type Water Heaters | Department of Energy  

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

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.

220

Impact of selected energy conservation technologies on baseline demands  

SciTech Connect

This study is an application of the modeling and demand projection capability existing at Brookhaven National Laboratory to specific options in energy conservation. Baseline energy demands are modified by introducing successively three sets of conservation options. The implementation of improved building standards and the use of co-generation in industry are analyzed in detail and constitute the body of this report. Two further sets of energy demands are presented that complete the view of a low energy use, ''conservation'' scenario. An introduction to the report covers the complexities in evaluating ''conservation'' in view of the ways it is inextricably linked to technology, prices, policy, and the mix of output in the economy. The term as used in this report is narrowly defined, and methodologies are suggested by which these other aspects listed can be studied in the future.

Doernberg, A

1977-09-01T23:59:59.000Z

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

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

222

United States energy supply and demand forecasts 1979-1995  

SciTech Connect

Forecasts of U.S. energy supply and demand by fuel type and economic sector, as well as historical background information, are presented. Discussion and results pertaining to the development of current and projected marginal energy costs, and their comparison with market prices, are also presented.

Walton, H.L.

1979-01-01T23:59:59.000Z

223

Linking Continuous Energy Management and Open Automated Demand Response  

Science Conference Proceedings (OSTI)

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

Piette, Mary Ann; Kiliccote, Sila; Ghatikar, Girish

2008-10-03T23:59:59.000Z

224

Opportunities for Energy Efficiency and Demand Response in the California  

NLE Websites -- All DOE Office Websites (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.

225

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

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

Division Total West Mountain Pacific Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

226

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

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

(millions) Census Division Total South Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC13.7...

227

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

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

Census Division Total Midwest Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC12.7...

228

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

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

Census Division Total Northeast Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC11.7...

229

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

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

Census Division Total South Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

230

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

Gasoline and Diesel Fuel Update (EIA)

(millions) Census Division Total West Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC14.7...

231

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.

232

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:

233

A dynamic model of industrial energy demand in Kenya  

Science Conference Proceedings (OSTI)

This paper analyses the effects of input price movements, technology changes, capacity utilization and dynamic mechanisms on energy demand structures in the Kenyan industry. This is done with the help of a variant of the second generation dynamic factor demand (econometric) model. This interrelated disequilibrium dynamic input demand econometric model is based on a long-term cost function representing production function possibilities and takes into account the asymmetry between variable inputs (electricity, other-fuels and Tabour) and quasi-fixed input (capital) by imposing restrictions on the adjustment process. Variations in capacity utilization and slow substitution process invoked by the relative input price movement justifies the nature of input demand disequilibrium. The model is estimated on two ISIS digit Kenyan industry time series data (1961 - 1988) using the Iterative Zellner generalized least square method. 31 refs., 8 tabs.

Haji, S.H.H. [Gothenburg Univ. (Sweden)

1994-12-31T23:59:59.000Z

234

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

235

Building Energy Software Tools Directory : Demand Response Quick...  

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

Demand Response Quick Assessment Tool Back to Tool Demand response quick assessment tool screenshot Demand response quick assessment tool screenshot Demand response quick...

236

What Can China Do? China's Best Alternative Outcome for Energy Efficiency and CO2 Emissions  

E-Print Network (OSTI)

Demand by Sector, CIS and AIS Total Electrcity Final EnergyDemand (TWh) Total Electrcity Final Energy Demand (TWh)

G. Fridley, David

2010-01-01T23:59:59.000Z

237

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

238

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.

239

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)

240

Cogeneration Plant is Designed for Total Energy  

E-Print Network (OSTI)

This paper describes application considerations, design criteria, design features, operating characteristics and performance of a 200 MW combined cycle cogeneration plant located at Occidental Chemical Corporation's Battleground chlorine-caustic plant at La Porte, Texas. This successful application of a total energy management concept utilizing combined cycle cogeneration in an energy intensive electrochemical manufacturing process has resulted in an efficient reliable energy supply that has significantly reduced energy cost and therefore manufacturing cost.

Howell, H. D.; Vera, R. L.

1987-09-01T23:59:59.000Z

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.


241

Total Energy - Data - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Nuclear & Uranium. Uranium fuel, nuclear reactors, generation, spent fuel. Total Energy. ... They are for public testing and comment only. We ...

242

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.

243

U.S. Energy Demand, Offshore Oil Production and  

E-Print Network (OSTI)

;Summary of Conclusions. . . The global rate of production of oil is peaking now, coal will peak in 2U.S. Energy Demand, Offshore Oil Production and BP's Macondo Well Spill Tad Patzek, Petroleum that run the U.S. Complexity, models, risks Gulf of Mexico's oil and gas production Conclusions ­ p.3/4 #12

Patzek, Tadeusz W.

244

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

245

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

forecast methods report. California Energy Commission, CEC-Chris Kavalec. California Energy Commission. CEC (2005d)Office, 5/12/2006. California Energy Advanced Energy

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

2008-01-01T23:59:59.000Z

246

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.

247

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.

248

Construction of a Demand Side Plant with Thermal Energy Storage  

E-Print Network (OSTI)

Utility managements have two primary responsibilities. They must supply reliable electric service to meet the needs of their customers at the most efficient price possible while at the same time generating the maximum rate of return possible for their shareholders. Regulator hostility towards the addition of generating capacity has made it difficult for utilities to simultaneously satisfy both the needs of their ratepayers and the needs of their shareholders. Recent advances in thermal energy storage may solve the utilities' paradox. Residential thermal energy storage promises to provide the ratepayers significantly lower electricity rates and greater comfort levels. Utilities benefit from improved load factors, peak capacity additions at low cost, improved shareholder value (ie. a better return on assets), improved reliability, and a means of satisfying growing demand without the regulatory and litigious nightmares associated with current supply side solutions. This paper discusses thermal energy storage and its potential impact on the electric utilities and introduces the demand side plant concept.

Michel, M.

1989-01-01T23:59:59.000Z

249

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:

250

Building Energy Software Tools Directory: Energy Demand Modeling  

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

and Renewable Energy EERE Home | Programs & Offices | Consumer Information Building Energy Software Tools Directory Search Search Help Building Energy Software Tools Directory...

251

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

252

U.S. Propane Demand - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Demand is higher in 1999 due to higher petrochemical demand and a strong economy. We are also seeing strong demand in the first quarter of 2000; however, ...

253

Total Economics of Energy Efficient Motors  

E-Print Network (OSTI)

Due to the large increases in cost of electrical energy in recent years, the energy savings attainable with the use of energy-efficient motors is very attractive to all motor users. But energy and electric demand charge savings tell only part of the story. Engineers responsible for the selection of motors for many varying uses must also consider many less tangible factors when deciding whether a price premium for an energy-efficient motor is justified. These important intangible factors may throw a borderline decision in favor of a premium motor; at other times these factors may dictate that the capital money could be spent more wisely in other areas. This paper will point out those factors which effect the decision of whether or not to buy a premium priced energy-efficient motor or a standard electric motor. It will also address the question of whether it is cost-effective to rewind an old motor which has failed or to replace it with a new energy-efficient motor.

Nester, A. T.

1984-01-01T23:59:59.000Z

254

STRATEGIC ENERGY INITIATIVE @ Winter 2005 Precarious energy situation demands strategic  

E-Print Network (OSTI)

energy solutions that could have a significant impact, especially in the southeastern U.S. Blowin of the oil it produced in 1970. -- Georgia Tech Strategic Energy Initiative and U.S. Dept. of Energy's Energy energy. At the U.S.Department of Energy-funded SolarThermal Test Facility on the main campus, Georgia

Sherrill, David

255

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

the entire forecast period, primarily because both weather-adjusted peak and electricity consumption were forecast. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, conservation, California Solar Initiative. #12

256

Integrating Energy Efficiency and Demand Response into Utility Resource Plans  

Science Conference Proceedings (OSTI)

This report investigates the methods in which utilities integrate their supply-side and demand-side resources to meet their generating resource requirements. The major steps in developing a resource plan are reviewed, including the alternative methods currently employed. Finally, the report presents the results of a short survey that was administered to the advisors in Energy Utilization. The results show that methods are more sophisticated than 20 years ago, but more could be accomplished in ...

2013-01-14T23:59:59.000Z

257

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?

258

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

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

Total Energy Glossary FAQS Overview Data Monthly Annual Analysis & Projections All Reports Most Requested Annual Monthly Projections U.S. States EIA's latest Short-Term...

259

Residential Energy Consumption Survey Results: Total Energy Consumptio...  

Open Energy Info (EERE)

Consumption Survey Results: Total Energy Consumption, Expenditures, and Intensities (2005)

260

Fuel choice and aggregate energy demand in the commercial sector  

SciTech Connect

This report presents a fuel choice and aggregate-demand model of energy use in the commercial sector of the United States. The model structure is dynamic with short-run fuel-price responses estimated to be close to those of the residential sector. Of the three fuels analyzed, electricity consumption exhibits a greater response to its own price than either natural gas or fuel oil. In addition, electricity price increases have the largest effect on end-use energy conservation in the commercial sector. An improved commercial energy-use data base is developed which removes the residential portion of electricity and natural gas use that traditional energy-consumption data sources assign to the commercial sector. In addition, household and commercial petroleum use is differentiated on a state-by-state basis.

Cohn, S.

1978-12-01T23:59:59.000Z

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.


261

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

262

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

263

Energy packet networks: smart electricity storage to meet surges in demand  

Science Conference Proceedings (OSTI)

When renewable energy is used either as a primary source, or as a back-up source to meet excess demand, energy storage becomes very useful. Simple examples of energy storage units include electric car batteries and uninterruptible power supplies. More ... Keywords: energy packet networks, network control of energy flow, on-demand energy dispatching, smart grid, store and forward energy, storing renewable energy

Erol Gelenbe

2012-03-01T23:59:59.000Z

264

Advanced Control Technologies and Strategies Linking Demand Response and Energy Efficiency  

E-Print Network (OSTI)

demand shifting are thermal energy storage systems, whichlockout, pre-cooling, thermal energy storage, cooling loadlockout • Pre-cooling • Thermal energy storage • Cooling

Kiliccote, Sila; Piette, Mary Ann

2005-01-01T23:59:59.000Z

265

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

Solution Procedure for SDP Energy Prices We use electricityLondon for assistance with energy price modeling. Siddiquiof DER under uncertain energy prices with demand response

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

266

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

minimization Monthly peak demand management Daily time-of-Some tariff designs have peak demand charges that apply tothat may result in a peak demand that occurs in one month to

Piette, Mary Ann

2009-01-01T23:59:59.000Z

267

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

Dryer WH - Clothes Washer Clothes Washer WH - DishwasherDishwasher Water Heating Figure 7 Breakdown of residentialUEC Water Heating (WH) Dishwasher Advanced Energy Pathways -

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

2008-01-01T23:59:59.000Z

268

EIA - 2010 International Energy Outlook - World Energy Demand...  

Gasoline and Diesel Fuel Update (EIA)

about energy security and greenhouse gas emissions support the development of new nuclear generating capacity. World average capacity utilization rates have continued to rise...

269

Industrial Demand Module 1998, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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 ofthe 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 supportof its models (Public Law 94-385, section 57.b2). 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.

T. Crawford Honeycutt

1998-01-01T23:59:59.000Z

270

ENERGY DEMAND AND CONSERVATION IN KENYA: INITIAL APPRAISAL  

E-Print Network (OSTI)

of Statistics d) Nairobi, Kenya. See also Estimates ofDEMAND AND CONSERVATION IN KENYA: INITIAL APPRAISAL LeeDemand and Conservation in Kenya: Initial Appraisal Lee

Schipper, Lee

2013-01-01T23:59:59.000Z

271

Electric grid planners: demand response and energy efficiency to ...  

U.S. Energy Information Administration (EIA)

Source: Form EIA-411, Coordinated Bulk Power Demand and Supply Report Note: All data are reported for time of summer peak, rather than overall demand.

272

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

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

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

273

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

274

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.

275

Projecting household energy consumption within a conditional demand framework  

SciTech Connect

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

276

Projecting household energy consumption within a conditional demand framework  

Science Conference Proceedings (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

277

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

278

Japan's Long-term Energy Demand and Supply Scenario to 2050 ...  

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

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

279

EIA Data: Total International Primary Energy Consumption

This...  

Open Energy Info (EERE)

EIA Data: Total International Primary Energy Consumption

This table lists total primary energy consumption by country and region in Quadrillion Btu.  Figures in this table...

280

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST  

E-Print Network (OSTI)

Policy Report, over the entire forecast period, primarily because both weather-adjusted peak and commercial sectors. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, California Solar Initiative. #12;ii #12

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

Dynamic Controls for Energy Efficiency and Demand Response: Framework Concepts and a New Construction Study Case in New York  

E-Print Network (OSTI)

of Fully Automated Demand Response in Large Facilities.for Energy Efficiency and Demand Response”, Proceedings ofAuthority (NYSERDA), the Demand Response Research Center (

Kiliccote, Sila; Piette, Mary Ann; Watson, David S.; Hughes, Glenn

2006-01-01T23:59:59.000Z

282

Commercial applications of solar total energy systems. Volume 4. Appendices. Final report. [Solar Total Energy System Evaluation Program (STESEP) code  

DOE Green Energy (OSTI)

A methodology has been developed by Atomics International under contract to the Department of Energy to define the applicability of solar total energy systems (STES) to the commercial sector (e.g., retail stores, shopping centers, offices, etc.) in the United States. Candidate STES concepts were selected to provide on-site power generation capability, as well as thermal energy for both heating and cooling applications. Each concept was evaluated on the basis of its cost effectiveness (i.e., as compared to other concepts) and its ability to ultimately penetrate and capture a significant segment of this market, thereby resulting in a saving of fossil fuel resources. This volume contains the appendices. Topics include deterministic insolation model computer code; building energy usage data; computer simulation programs for building energy demand analysis; model buildings for STES evaluation; Solar Total Energy System Evaluation Program (STESEP) computer code; transient simulation of STES concept; solar data tape analysis; program listings and sample output for use with TRNSYS; transient simulation, and financial parameters sensitivities. (WHK)

Boobar, M.G.; McFarland, B.L.; Nalbandian, S.J.; Willcox, W.W.; French, E.P.; Smith, K.E.

1978-07-01T23:59:59.000Z

283

Advanced Control Technologies and Strategies Linking Demand Response and Energy Efficiency  

E-Print Network (OSTI)

Electrical Peak Demands in Commercial Buildings” Center for Analysis and Dissemination of Demonstrated Energy Technologies (CADDET), IEA/OECD Analyses

Kiliccote, Sila; Piette, Mary Ann

2005-01-01T23:59:59.000Z

284

Solar Total Energy Project final test report  

DOE Green Energy (OSTI)

The Solar Total Energy Project (STEP), a cooperative effort between the United States Department of Energy (DOE) and Georgia Power Company (GPC) located at Shenandoah, Georgia, has undergone several design modifications based on experience from previous operations and test programs. The experiences encountered were discussed in detail in the Solar Total Energy Project Summary Report'' completed in 1987 for DOE. Most of the proposed changes discussed in this report were installed and tested in 1987 as part of two 15-day test programs (SNL Contract No. 06-3049). However, several of the suggested changes were not completed before 1988. These plant modifications include a new distributed control system for the balance of plant (BOP), a fiber a optical communications ring for the field control system, and new control configuration reflecting the new operational procedures caused by the plant modifications. These modifications were tested during a non-consecutive day test, and a 60-day field test conducted during the autumn of 1989. These test were partially funded by SNL under Contract No. 42-4859, dated June 22, 1989. Results of these tests and preliminary analysis are presented in this test summary report. 9 refs., 19 figs., 7 tabs.

Nelson, R.F.; Abney, L.O.; Towner, M.L. (Georgia Power Co., Shenandoah, GA (USA))

1990-09-01T23:59:59.000Z

285

Comfort-aware home energy management under market-based demand-response  

Science Conference Proceedings (OSTI)

To regulate energy consumption and enable Demand-Response programs, effective demand-side management at home is key and an integral part of the future Smart Grid. In essence, the home energy management is a mix between discrete appliance scheduling problem ... Keywords: demand-response, energy management, smart grid

Jin Xiao, Jian Li, Raouf Boutaba, James Won-Ki Hong

2012-10-01T23:59:59.000Z

286

Analysis of photovoltaic total energy systems for single family residential applications  

DOE Green Energy (OSTI)

The performance and cost-effectiveness of three photovoltaic total energy system concepts designed to meet the thermal and electrical demands of a typical single family house are compared. The three photovoltaic total energy system concepts considered are: (1) All-photovoltaic systems. Passively air-cooled photovoltaic panels provide electricity to meet both electrical and thermal demands. (2) Separate-panel systems. Solar thermal panels provide thermal energy, while passively air-cooled photovoltaic panels serve the purely electric demand. (3) Combined thermal/electric panel systems. Water-cooled photovoltaic panels provide both thermal energy (transported by cooling water) and electrical energy to meet the separate thermal and electrical demands. Additional passively air-cooled photovoltaic panels are added, as required, to meet the electrical demand. The thermal demand is assumed to consist of the energy required for domestic hot water and space heating, while the electrical demand includes the energy required for baseload power (lights, appliances, etc.) plus air conditioning. An analysis procedure has been developed that permits definition of the panel area, electrical and/or thermal storage capacity, and utility backup energy level that, in combination, provide the lowest annual energy cost to the homeowner for each system concept for specified assumptions about costs and system operations. The procedure appears capable of being used to approximately any size system using solar collectors, as well as in any application where the thermal and/or electrical demand is being provided by solar energy, with utility or other conventional backup. This procedure has been used to provide results for homes located in Phoenix, Arizona, and Madison, Wisconsin, and to evaluate the effects of array and backup power costs and the desirability of selling excess electrical energy back to the utility. (WHK)

Chobotov, V.; Siegel, B.

1978-08-01T23:59:59.000Z

287

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":""}]}

288

Total Energy - Analysis & Projections - U.S. Energy Information...  

Annual Energy Outlook 2012 (EIA)

Current & Selected Reports Most Requested Annual Monthly Projections U.S. States Search within Total Energy Search By: Go Pick a date range: From: To: Go Search All Reports &...

289

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

SciTech Connect

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

290

Total energy cycle emissions and energy use of electric vehicles  

DOE Green Energy (OSTI)

The purpose of this project is to provide estimates of changes in life cycle energy use and emissions that would occur with the introduction of EVs. The topics covered include a synopsis of the methodology used in the project, stages in the EV and conventional vehicle energy cycles, characterization of EVs by type and driving cycle, load analysis and capacity of the electric utility, analysis of the materials used for vehicle and battery, description of the total energy cycle analysis model, energy cycle primary energy resource consumption, greenhouse gas emissions, energy cycle emissions, and conclusions.

Singh, M.

1997-12-31T23:59:59.000Z

291

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

Open Energy Info (EERE)

Website http:www-pub.iaea.orgMTCDp References MAED 21 "MAED model evaluates future energy demand based on medium- to long-term scenarios of socio-economic,...

292

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

293

Chapter 3: Demand-Side Resources | Department of Energy  

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

spent 14.7 billion on DSM programs between 1989 and 1999, an average of 1.3 billion per year. Chapter 3: Demand-Side Resources More Documents & Publications Chapter 3 Demand-Side...

294

AEO2011: Total Energy Supply, Disposition, and Price Summary...  

Open Energy Info (EERE)

Total Energy Supply, Disposition, and Price Summary This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report...

295

Table US1. Total Energy Consumption, Expenditures, and Intensities ...  

U.S. Energy Information Administration (EIA)

Part 1: Housing Unit Characteristics and Energy Usage Indicators Energy Consumption 2 Energy Expenditures 2 Total U.S. (quadrillion Btu) Per Household (Dollars) Per

296

Annual Energy Outlook with Projections to 2025-Figure 5. Total...  

Gasoline and Diesel Fuel Update (EIA)

5. Total energy production and consumption, 1970-2025 (quadrillion Btu). For more detailed information, contact the National Energy Information Center at (202) 586-8800. Energy...

297

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

298

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.

299

Proceedings of the Chinese-American symposium on energy markets and the future of energy demand  

SciTech Connect

The Symposium was organized by the Energy Research Institute of the State Economic Commission of China, and the Lawrence Berkeley Laboratory and Johns Hopkins University from the United States. It was held at the Johns Hopkins University Nanjing Center in late June 1988. It was attended by about 15 Chinese and an equal number of US experts on various topics related to energy demand and supply. Each presenter is one of the best observers of the energy situation in their field. A Chinese and US speaker presented papers on each topic. In all, about 30 papers were presented over a period of two and one half days. Each paper was translated into English and Chinese. The Chinese papers provide an excellent overview of the emerging energy demand and supply situation in China and the obstacles the Chinese planners face in managing the expected increase in demand for energy. These are matched by papers that discuss the energy situation in the US and worldwide, and the implications of the changes in the world energy situation on both countries. The papers in Part 1 provide historical background and discuss future directions. The papers in Part 2 focus on the historical development of energy planning and policy in each country and the methodologies and tools used for projecting energy demand and supply. The papers in Part 3 examine the pattern of energy demand, the forces driving demand, and opportunities for energy conservation in each of the major sectors in China and the US. The papers in Part 4 deal with the outlook for global and Pacific region energy markets and the development of the oil and natural gas sector in China.

Meyers, S. (ed.)

1988-11-01T23:59:59.000Z

300

China's Energy and Carbon Emissions Outlook to 2050  

E-Print Network (OSTI)

rail and road electrification. Total Electrcity Final EnergyDemand (TWh) Total Electrcity Final Energy Demand (TWh)

Zhou, Nan

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.


301

Demand Response - Policy: More Information | Department of Energy  

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

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

302

Map Data: Total Production | Department of Energy  

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

Total Production Map Data: Total Production totalprod2009final.csv More Documents & Publications Map Data: Renewable Production Map Data: State Consumption...

303

Total energy cycle energy use and emissions of electric vehicles.  

SciTech Connect

A total energy cycle analysis (TECA) of electric vehicles (EV) was recently completed. The EV energy cycle includes production and transport of fuels used in power plants to generate electricity, electricity generation, EV operation, and vehicle and battery manufacture. This paper summarizes the key assumptions and results of the EVTECA. The total energy requirements of EVS me estimated to be 24-35% lower than those of the conventional, gasoline-fueled vehicles they replace, while the reductions in total oil use are even greater: 55-85%. Greenhouse gases (GHG) are 24-37% lower with EVs. EVs reduce total emissions of several criteria air pollutants (VOC, CO, and NO{sub x}) but increase total emissions of others (SO{sub x}, TSP, and lead) over the total energy cycle. Regional emissions are generally reduced with EVs, except possibly SO{sub x}. The limitations of the EVTECA are discussed, and its results are compared with those of other evaluations of EVs. In general, many of the results (particularly the oil use, GHG, VOC, CO, SO{sub x}, and lead results) of the analysis are consistent with those of other evaluations.

Singh, M. K.

1999-04-29T23:59:59.000Z

304

Optimal Technology Investment and Operation in Zero-Net-Energy Buildings with Demand Response  

E-Print Network (OSTI)

and achieve demand response. For example, on a hot August after- noon during the energy crisis, high demand-in trans- former used for everything from cell phones to computers could be up to 50 percent more efficient

305

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 Åkerlind, Ingrid Gudrun

2013-01-01T23:59:59.000Z

306

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

and Demand Response under Uncertainty • F P t : wholesale natural gasdemand response and DER under uncertain electricity and natural gasand Demand Response under Uncertainty Energy Price Models We assume that the logarithms of the deseasonalized electricity and natural gas

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

307

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

308

Demand Side Energy Saving though Proper Construction Practices and Materials Selection  

E-Print Network (OSTI)

Energy consumed during the construction of buildings and structures, including the embodied energy of the concrete and other construction materials, represent a considerable percentage that may reach 40% of the total energy consumed during the whole service life of the structure. Reducing energy consumed in the construction practices along with reducing the embodied energy of concrete and building materials, therefore, are of major importance. Reducing concrete's embodied energy represents one of the major green features of buildings and an important tool to improve sustainability, save resources for coming generations and reduce greenhouse gas emissions. In this paper, different methods to reduce concrete's embodied energy are discussed and their effect on demand side energy are assessed. Using local materials, pozzolanic blended cements, fillers, along with specifying 56 days strength in design are discussed and assessed. Proper mix design, quality control and proper architectural design also affect and reduce embodied energy. Improving durability, regular maintenance and scheduled repair are essential to increase the expected service life of buildings and hence reduce overall resources consumption and reduce energy. These effects are discussed and quantified. Construction practices also consume considerable amount of energy. The effect of transporting, conveying, pouring, finishing and curing concrete on energy consumption are also discussed.

El-Hawary, M.

2010-01-01T23:59:59.000Z

309

U.S. Regional Energy Demand Forecasts Using NEMS and GIS  

E-Print Network (OSTI)

LBNL-57955 U.S. Regional Energy Demand Forecasts Using NEMS and GIS Jesse A. Cohen, Jennifer L Efficiency and Renewable Energy, Office of Planning, Budget, and Analysis of the U.S. Department of Energy-57955 U.S. Regional Energy Demand Forecasts Using NEMS and GIS Prepared for the Office of Planning

310

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

311

demand response - U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

EIA Survey Forms › Facebook Twitter ... demand response June 14, 2012 California's electric power market faces challenges heading into summer. March 24, ...

312

EU-15 Gasoline & Distillate Demand - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

The European refining system is not well matched to its demand slate. Unlike the United States, Europe produces more gasoline than it can use, which ...

313

Tankless Demand Water Heater Basics | Department of Energy  

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

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

314

Tankless Demand Water Heater Basics | Department of Energy  

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

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

315

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"

316

Univariate modeling and forecasting of monthly energy demand time series using abductive and neural networks  

Science Conference Proceedings (OSTI)

Neural networks have been widely used for short-term, and to a lesser degree medium and long-term, demand forecasting. In the majority of cases for the latter two applications, multivariate modeling was adopted, where the demand time series is related ... Keywords: Abductive networks, Energy demand, Medium-term load forecasting, Neural networks, Time series forecasting, Univariate time series analysis

R. E. Abdel-Aal

2008-05-01T23:59:59.000Z

317

Survey and Forecast of Marketplace Supply and Demand for Energy-Efficient Lighting Products  

Science Conference Proceedings (OSTI)

Utility incentive programs have placed significant demands on the suppliers of certain types of energy-efficient lighting products--particularly compact fluorescent lamps and electronic ballasts. Two major federal programs may soon place even greater demands on the lighting industry. This report assesses the program-induced demand for efficient lighting products and their likely near-term supply.

1992-12-01T23:59:59.000Z

318

Solar total energy systems (STES) simulation program user's guide  

DOE Green Energy (OSTI)

A computer program which simulates the operations of a STES facility and evaluates its annualized costs and energy displacement is described. The program contains a dynamic model which simulates the interaction of the insolation and electrical and thermal demands on an hourly basis. The program is flexible enough to allow thousands of different configurations to be simulated under a wide variety of conditions. Moreover, with this program, the sizes of the STES components can be adjusted to maximize the return on invested capital or the savings in fossil fuels. The program can also be used to simulate conventional fossil fuel Total Energy (TE) systems and solar thermal energy systems for comparison with STES. The program is written in Fortran for the FTN compiler on The Aerospace Corporation's CDC 7600 computer. It consists of 9 routines and approximately 1300 cards, including comments. A description of the program, its inputs and its outputs are presented. Examples of program input and otput as well as a sample deck structure are provided. A source listing appears in the appendix.

Timmer, B.R.

1979-01-04T23:59:59.000Z

319

LBNL/PUB-5482 Energy Efficiency Options for the New England Demand  

E-Print Network (OSTI)

LBNL/PUB-5482 Energy Efficiency Options for the New England Demand Response Initiative (NEDRI://eetd.lbl.gov/EA/EMP/ The work described in this study was funded by the Assistance Secretary of Energy Efficiency and Renewable00098 #12;Energy Efficiency Options for the New England Demand Response Initiative (NEDRI) ­ Framing

320

energy: Supply, Demand, and impacts CooRDinATinG LeAD AUThoR  

E-Print Network (OSTI)

240 chapter 12 energy: Supply, Demand, and impacts CooRDinATinG LeAD AUThoR Vincent C. Tidwell;energy: supply, demand, and impacts 241 · Delivery of electricity may become more vulnerable) in 2009, equal to 222 million BTUs per person (EIA 2010). Any change or disruption to the supply of energy

Kammen, Daniel M.

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

Large-Scale Integration of Deferrable Demand and Renewable Energy Sources  

E-Print Network (OSTI)

1 Large-Scale Integration of Deferrable Demand and Renewable Energy Sources Anthony Papavasiliou model for assessing the impacts of the large-scale integration of renewable energy sources. In order to accurately assess the impacts of renewable energy integration and demand response integration

Oren, Shmuel S.

322

Retail Demand Response in Southwest Power Pool | Department of Energy  

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

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.

323

Tankless or Demand-Type Water Heaters | Department of Energy  

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

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...

324

Chapter 3: Demand-Side Resources | Department of Energy  

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

spent 14.7 billion on DSM programs between 1989 and 1999, an average of 1.3 billion per year. Chapter 3: Demand-Side Resources More Documents & Publications Draft Chapter 3:...

325

Annual World Oil Demand Growth - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Following relatively small increases of 1.3 million barrels per day in 1999 and 0.8 million barrels per day in 2000, EIA is estimating world demand may grow by 1.5 ...

326

The Window Market in Texas: Opportunities for Energy Savings and Demand Reduction  

E-Print Network (OSTI)

The use of high performance windows represents a promising opportunity to reduce energy consumption and summer electrical demand in homes and commercial buildings in Texas and neighboring states. While low-e glass coatings and other energy efficiency features have become standard features in windows in states with building energy codes, their sales in the Texas market remain limited. This paper presents findings from a pilot energy efficiency program sponsored by American Electric Power Company (AEP). The Texas Window Initiative (TWI) has conducted over 160 on-site training sessions for hardware store sales personnel and builders across the AEP service areas in Texas over the past two years. Companion promotional activities have also been completed. The past one and a half years have witnessed a very significant increase in the market penetration of energy efficient windows in the AEP service area; from about 2.5% of total window sales in early 2000 to roughly 25% (according to preliminary data) by the end of 2001.1 Some of this increase is attributable to TWI's activities, although other factors may be responsible for a portion of this increase as well. The market for windows in Texas is described. TWI's approach to promoting energy efficient windows is reviewed. Initial impact estimates from TWI's activities are presented. The technical potential for energy savings and utility peak demand reduction from the installation of energy efficient windows in Texas is presented. The paper also provides some speculation on how the window market might be impacted by the adoption of building energy codes in Texas.

Zarnikau, J.; Campbell, L.

2002-01-01T23:59:59.000Z

327

A Total Energy & Water Quality Management System  

Science Conference Proceedings (OSTI)

This report develops a generic model for an energy and water quality management system for the water community, and defines standard specifications for software applications required to minimize energy costs within the constraints of water quality and operation goals.

1999-09-30T23:59:59.000Z

328

Solar total energy systems final technical summary report. Volume I. Solar total energy systems market penetration  

SciTech Connect

The results of the market penetration analysis of Solar Total Energy Systems (STES) for the industrial sector are described. Performance data derived for STES commercial applications are included. The energy use and price forecasts used in the analysis are summarized. The STES Applications Model (SAM), has been used to develop data on STES development potential by state and industry as a function of time from 1985 through 2015. A second computer code, the Market Penetration Model (MPM), has been completed and used to develop forecasts of STES market penetration and national energy displacement by fuel type. This model was also used to generate sensitivity factors for incentives, and variations in assumptions of cost of STES competing fuel. Results for the STES performance analysis for commercial applications are presented. (MHR)

Bush, L.R.; Munjal, P.K.

1978-03-31T23:59:59.000Z

329

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.

330

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

331

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

332

Achieving Total Employee Engagement in Energy Efficiency  

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

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

333

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

Previous papers have discussed definitions of energyThis paper provides a framework linking continuous energyThe paper presents a framework about when energy is used,

Piette, Mary Ann

2009-01-01T23:59:59.000Z

334

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network (OSTI)

tech. selection Net energy consumption Service tech. cost &equip. selection Net energy consumption Service tech. cost &tech. selection Net energy consumption Service tech. cost &

Stadler, Michael

2011-01-01T23:59:59.000Z

335

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

and equity”, 2005, the Energy and Resources Institute (Tables Figures Figure 1. India Primary Energy Supply by fuel7 Figure 2. Final and Primary Energy (including biomass) by

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

336

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

Commercial Building Energy Consumption Survey” (CBECS),7 Figure 3. Energy Consumption in the Agriculture Sector (13 Figure 6. Energy Consumption in the Service

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

337

Industrial Sector Energy Demand: Revisions for Non-Energy-Intensive Manufacturing (released in AEO2007)  

Reports and Publications (EIA)

For the industrial sector, EIAs analysis and projection efforts generally have focused on the energy-intensive industriesfood, bulk chemicals, refining, glass, cement, steel, and aluminumwhere energy cost averages 4.8 percent of annual operating cost. Detailed process flows and energy intensity indicators have been developed for narrowly defined industry groups in the energy-intensive manufacturing sector. The non-energy-intensive manufacturing industries, where energy cost averages 1.9 percent of annual operating cost, previously have received somewhat less attention, however. In AEO2006, energy demand projections were provided for two broadly aggregated industry groups in the non-energy-intensive manufacturing sector: metal-based durables and other non-energy-intensive. In the AEO2006 projections, the two groups accounted for more than 50 percent of the projected increase in industrial natural gas consumption from 2004 to 2030.

Information Center

2007-03-11T23:59:59.000Z

338

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 +

339

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":""}]}

340

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

optimized relative to the energy services begin delivered.energy is used, levels of services by energy using systems,energy efficiency and advances in controls and service level

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.


341

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

Science Conference Proceedings (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

342

Modelling the Energy Demand of Households in a Combined  

E-Print Network (OSTI)

. Emissions from passenger transport, households'electricity and heat consumption are growing rapidly despite demand analysis for electricity (e.g. Larsen and Nesbakken, 2004; Holtedahl and Joutz, 2004; Hondroyiannis, 2004) and passenger cars (Meyer et al., 2007). Some recent studies cover the whole residential

Steininger, Karl W.

343

Economic development and the structure of the demand for commerial energy  

E-Print Network (OSTI)

To deepen the understanding of the relation between economic 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 ...

Judson, Ruth A.

344

Economic development and the structure of the demand for commerial energy  

E-Print Network (OSTI)

To deepen understanding of the relation between economic 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 ...

Judson, Ruth A.; Schmalensee, Richard.; Stoker, Thomas M.

345

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

346

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":""}]}

347

ENERGY DEMAND AND CONSERVATION IN KENYA: INITIAL APPRAISAL  

E-Print Network (OSTI)

bound up in steel, paper, and other energy intensive goods.and residential energy use in the paper by McGranahan 1 eton energy use and the economy can be found in the paper by

Schipper, Lee

2013-01-01T23:59:59.000Z

348

Commercial applications of solar total energy systems. Final report. Volume 2. Technical  

SciTech Connect

The overall objective of this program was to assess the feasibility of using solar energy to provide a significant fraction of the energy needs of commercial buildings that have energy demands greater than 200 kWe. This volume of the final report discusses the approach employed to develop: (1) STES concept configurations and component data, (2) commercial buildings application data, and (3) computer simulation programs for evaluating various STES concept-commercial buildings applications. Various solar thermal and photovoltaic solar total energy systems (STES) configurations were considered. Concurrently, data on commercial buildings (e.g., categories, energy demand, demographic population, etc.) were developed and used to define six model building configurations which could be used as representative commercial buildings within six various regions (12 specific sites) of the United States. The six configurations included four building types (a low rise office building, a large retail store, a medium-size shopping center and a large shopping center) typifying current building designs. The remaining two configurations used the large shopping center model except that the energy demand was changed to reflect future building designs. The STESEP Computer Code was developed for a quick evaluation method for tradeoffs related to (1) cascading of thermal power conversion systems, (2) determination of optimum collector sizes and operating conditions (make or buy decisions for auxiliary energy), and (3) comparison of solar total energy concepts in various parts of the country and in various types of commercial buildings to assess their future economic potential for various economic scenarios. (WHK)

Boobar, M.G.; McFarland, B.L.; Nalbandian, S.J.; Willcox, W.W.; French, E.P.; Smith, K.E.

1978-07-01T23:59:59.000Z

349

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

Price, 2008 “Sectoral Trends in Global Energy Use and Greenhouse GasTrends in Global Energy Use and Greenhouse Gas Emissions (Price

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

350

Future world energy demand driven by trends in developing ...  

U.S. Energy Information Administration (EIA)

EIA's International Energy Outlook 2013 (IEO2013) projects that growth in world energy use largely comes from countries outside of the Organization ...

351

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

gas oil nuclear hydro Energy output Own Uses Transmissiongas oil nuclear hydro Energy output Own Uses Transmissionenergy equivalence of electricity generated from hydro or

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

352

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.

353

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

E-Print Network (OSTI)

equipment. Since electricity demand, is projected to exhibitfrom 44% in 2006. In electricity demand, its usage in plugRuns, Average Value) Electricity Demand Power/Electricity

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

354

Control and Optimization Meet the Smart Power Grid - Scheduling of Power Demands for Optimal Energy Management  

E-Print Network (OSTI)

The smart power grid aims at harnessing information and communication technologies to enhance reliability and enforce sensible use of energy. Its realization is geared by the fundamental goal of effective management of demand load. In this work, we envision a scenario with real-time communication between the operator and consumers. The grid operator controller receives requests for power demands from consumers, with different power requirement, duration, and a deadline by which it is to be completed. The objective is to devise a power demand task scheduling policy that minimizes the grid operational cost over a time horizon. The operational cost is a convex function of instantaneous power consumption and reflects the fact that each additional unit of power needed to serve demands is more expensive as demand load increases.First, we study the off-line demand scheduling problem, where parameters are fixed and known. Next, we devise a stochastic model for the case when demands are generated continually and sched...

Koutsopoulos, Iordanis

2010-01-01T23:59:59.000Z

355

2009 Total Energy Production by State | Department of Energy  

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

Per Person Solar Energy Potential Solar Energy Potential Renewable Energy Production By State Renewable Energy Production By State 2009 Energy Consumption Per Person...

356

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

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

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."

357

"Table 17. Total Delivered Residential Energy Consumption, Projected...  

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

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,...

358

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

Open Energy Info (EERE)

Facebook icon Twitter icon Correlation Of Surface Heat Loss And Total Energy Production For Geothermal Systems Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home...

359

Atomic total energies: Atomic Ref.Data Elec Struc Cal  

Science Conference Proceedings (OSTI)

... These tables contain the atomic total energies and orbital eigenvalues, for the ground electronic configuration of the elements H ... Definition of format ...

360

Atomic total energies: Atomic Ref. Data Elec. Struc. Cal.  

Science Conference Proceedings (OSTI)

... These tables contain the atomic total energies and orbital eigenvalues, for the ground electronic configuration of the elements H ... Definition of format ...

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

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

362

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

Science Conference Proceedings (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

363

Energy dependence of the total photoproduction cross section at HERA  

E-Print Network (OSTI)

The energy dependence of the total photon-proton cross-section is determined from data collected with the ZEUS detector at HERA with two different proton beam energies.

Aharon Levy

2008-07-01T23:59:59.000Z

364

The Total Energy Norm in a Quasigeostrophic Model  

Science Conference Proceedings (OSTI)

Total energy E as the sum of kinetic and available potential energies is considered here for quasigeostrophic (QG) dynamics. The discrete expression for E is derived for the QG model formulation of Marshall and Molteni. While E is conserved by ...

Martin Ehrendorfer

2000-10-01T23:59:59.000Z

365

2012 End-Use Energy Efficiency and Demand Response, EPRI Program 170: Summary of Deliverables  

Science Conference Proceedings (OSTI)

The EPRI research program on End-Use Energy Efficiency and Demand Response (Program 170) is focused on the assessment, testing, and demonstration of energy-efficient and intelligent end-use devices, as well as analytical studies of the economic, environmental, and behavioral aspects of energy efficiency and demand response. The 2012 reports, tools and resources produced in this program are available to employees of funding companies, and can be accessed by clicking on the product number link listed after ..

2013-05-22T23:59:59.000Z

366

Assessment of Commercial Building Automation and Energy Management Systems for Demand Response Applications  

Science Conference Proceedings (OSTI)

This Technical Update is an overview of commercial building automation and energy management systems with a focus on their capabilities (current and future), especially in support of demand response (DR). The report includes background on commercial building automation and energy management systems; a discussion of demand response applications in commercial buildings, including building loads and control strategies; and a review of suppliers’ building automation and energy management systems to support d...

2009-12-14T23:59:59.000Z

367

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

E-Print Network (OSTI)

Electricity and Natural Gas Demand in Japanese ResidentialWater Heating Natural Gas Demand Mtoe Actual Projection Mtoe

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

368

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

water (3%). Finally oil is a source of energy for theOil Diesel Oil LPG Electricity Source: CEA, 2006; MOSPI,countries, oil remains an important source of energy for

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

369

Commercial Demand Module of the National Energy Modeling ...  

U.S. Energy Information Administration (EIA)

Commercial Buildings Energy Consumption Survey ... space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The market segment ...

370

ENERGY DEMAND AND CONSERVATION IN KENYA: INITIAL APPRAISAL  

E-Print Network (OSTI)

plants, at what energy intensity? hotel in a given year? toenergy use for key kinds of buildings; major tals. hotels~

Schipper, Lee

2013-01-01T23:59:59.000Z

371

Total Energy - Data - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

... Quarterly Coal Report › Monthly Energy Review › Residential Energy ... Solar › Energy in Brief. What's ... They are for public testing and comment ...

372

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

U.S. Energy Information Administration (EIA)

... Quarterly Coal Report › Monthly Energy Review › Residential Energy Consumption ... Solar › Energy in ... testing but not to operate at full power.

373

Energy demand and conservation in Kenya: initial appraisal  

SciTech Connect

Ongoing research into the use and conservation of energy in Kenya is reported briefly. A partial accounting of energy use in Kenya is presented, and evidence that some energy conservation has been taking place is discussed. A fuller accounting for all commercial energy flows is both possible and desirable. The work presented should serve as a basis for further data collection and analysis in Kenya, and can be used as a model for similar efforts in other countries. The author intends to continue much of this energy accounting in Kenya in the latter half of 1980.

Schipper, L.

1980-03-01T23:59:59.000Z

374

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

Science Conference Proceedings (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

375

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

E-Print Network (OSTI)

1 THE CHALLENGES AND OPPORTUNITIES TO MEET THE WORKFORCE DEMAND IN THE ELECTRIC POWER AND ENERGY PROFESSION Wanda Reder, S & C Electric Company, 6601 North Ridge Blvd., Chicago, IL 60626- 3997, USA Vahid, Iowa State University ABSTRACT There is a tremendous imbalance between engineering workforce demand

376

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

NLE Websites -- All DOE Office Websites (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

377

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

378

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

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

methods associated with the modeling of changing energy markets for purposes of public information and policy analysis. - EIA uses the NEMS tool, a computer-based,...

379

Demand-Side Management and Energy Efficiency Revisited  

E-Print Network (OSTI)

of electricity consumption reported by utility n in year telectricity consumption due to energy e?ciency DSM expenditures across utilities and years

Auffhammer, Maximilian; Blumstein, Carl; Fowlie, Meredith

2007-01-01T23:59:59.000Z

380

Determining energy requirement for future water supply and demand alternatives.  

E-Print Network (OSTI)

??Water and energy are two inextricably linked resources. Each has the potential to limit the development of the other. There is a substantial body of… (more)

Larsen, Sara Gaye

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.


381

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand...  

Annual Energy Outlook 2012 (EIA)

household.gif (5637 bytes) The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and...

382

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 +

383

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

384

Proposed Design for a Coupled Ground-Source Heat Pump/Energy Recovery Ventilator System to Reduce Building Energy Demand.  

E-Print Network (OSTI)

??The work presented in this thesis focuses on reducing the energy demand of a residential building by using a coupled ground-source heat pump/energy recovery ventilation… (more)

McDaniel, Matthew Lee

2011-01-01T23:59:59.000Z

385

Discussion Paper Prepared for: Deploying Demand Side Energy Technologies workshop  

E-Print Network (OSTI)

The IEA study Energy Technology Perspectives 2006 (ETP 2006) demonstrates how energy technologies can contribute to a stabilization of CO2 emissions at today’s level by 2050. The results of the scenario analysis showed that no fundamental technology breakthroughs are needed. Technologies that are available today or that are under development today will

Cecilia Tam; Dolf Gielen

2007-01-01T23:59:59.000Z

386

Demand Response and Smart Metering Policy Actions Since the Energy Policy  

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

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

387

Saving Energy and Enabling Auto-Demand Response in Existing Buildings...  

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

Saving Energy and Enabling Auto-Demand Response in Existing Buildings and Plants Using Non-Invasive Retrofit Technologies Speaker(s): Harry Sim Date: April 7, 2011 - 12:00pm...

388

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

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

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

389

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

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

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

390

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

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

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

391

India Energy Outlook: End Use Demand in India to 2020  

SciTech Connect

Integrated economic models have been used to project both baseline and mitigation greenhouse gas emissions scenarios at the country and the global level. Results of these scenarios are typically presented at the sectoral level such as industry, transport, and buildings without further disaggregation. Recently, a keen interest has emerged on constructing bottom up scenarios where technical energy saving potentials can be displayed in detail (IEA, 2006b; IPCC, 2007; McKinsey, 2007). Analysts interested in particular technologies and policies, require detailed information to understand specific mitigation options in relation to business-as-usual trends. However, the limit of information available for developing countries often poses a problem. In this report, we have focus on analyzing energy use in India in greater detail. Results shown for the residential and transport sectors are taken from a previous report (de la Rue du Can, 2008). A complete picture of energy use with disaggregated levels is drawn to understand how energy is used in India and to offer the possibility to put in perspective the different sources of end use energy consumption. For each sector, drivers of energy and technology are indentified. Trends are then analyzed and used to project future growth. Results of this report provide valuable inputs to the elaboration of realistic energy efficiency scenarios.

de la Rue du Can, Stephane; McNeil, Michael; Sathaye, Jayant

2009-03-30T23:59:59.000Z

392

An overview of energy supply and demand in China  

DOE Green Energy (OSTI)

Although China is a poor country, with much of its population still farming for basic subsistence in rural villages, China is rich in energy resources. With the world's largest hydropower potential, and ranking third behind the US and USSR in coal reserves, China is in a better position than many other developing countries when planning for its future energy development and self-sufficiency. China is now the third largest producer and consumer of commercial energy, but its huge populace dilutes this impressive aggregate performance into a per capita figure which is an order of magnitude below the rich industrialized nations. Despite this fact, it is still important to recognize that China's energy system is still one of the largest in the world. A system this size allows risk taking and can capture economies of scale. The Chinese have maintained rapid growth in energy production for several decades. In order to continue and fully utilize its abundant resources however, China must successfully confront development challenges in many areas. For example, the geographic distribution of consumption centers poorly matches the distribution of resources, which makes transportation a vital but often weak link in the energy system. Another example -- capital -- is scarce relative to labor, causing obsolete and inefficiently installed technology to be operated well beyond what would be considered its useful life in the West. Major improvements in industrial processes, buildings, and other energy-using equipment and practices are necessary if China's energy efficiency is to continue to improve. Chinese energy planners have been reluctant to invest in environmental quality at the expense of more tangible production quotas.

Liu, F.; Davis, W.B.; Levine, M.D.

1992-05-01T23:59:59.000Z

393

An overview of energy supply and demand in China  

DOE Green Energy (OSTI)

Although China is a poor country, with much of its population still farming for basic subsistence in rural villages, China is rich in energy resources. With the world`s largest hydropower potential, and ranking third behind the US and USSR in coal reserves, China is in a better position than many other developing countries when planning for its future energy development and self-sufficiency. China is now the third largest producer and consumer of commercial energy, but its huge populace dilutes this impressive aggregate performance into a per capita figure which is an order of magnitude below the rich industrialized nations. Despite this fact, it is still important to recognize that China`s energy system is still one of the largest in the world. A system this size allows risk taking and can capture economies of scale. The Chinese have maintained rapid growth in energy production for several decades. In order to continue and fully utilize its abundant resources however, China must successfully confront development challenges in many areas. For example, the geographic distribution of consumption centers poorly matches the distribution of resources, which makes transportation a vital but often weak link in the energy system. Another example -- capital -- is scarce relative to labor, causing obsolete and inefficiently installed technology to be operated well beyond what would be considered its useful life in the West. Major improvements in industrial processes, buildings, and other energy-using equipment and practices are necessary if China`s energy efficiency is to continue to improve. Chinese energy planners have been reluctant to invest in environmental quality at the expense of more tangible production quotas.

Liu, F.; Davis, W.B.; Levine, M.D.

1992-05-01T23:59:59.000Z

394

Correlations between industrial demands (direct and total) for communications and transportation in the US economy 1947-1997  

E-Print Network (OSTI)

information and communications technology on transportation.information and communication technologies (ICT), and travelcommunications and transportation using Almost Ideal Demand System modeling: 1984-2002. Transportation Planning and Technology

Lee, Taihyeong; Mokhtarian, Patricia L

2008-01-01T23:59:59.000Z

395

EIA - Annual Energy Outlook 2009 - Natural Gas Demand  

Annual Energy Outlook 2012 (EIA)

at 202-586-8800. figure data Figure 72. Liquids production from gasification and oil shale, 2007-2030 (thousand barrels per day). Need help, contact the National Energy...

396

Power Sector Reforms in India: Demand Side and Renewable Energy...  

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

with EETD scientists on cooperative research? Get a job in EETD? Make my home more energy-efficient? Find a source within EETD for a news story I'm writing, shooting, or...

397

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

Past Trend and Future Outlook",LBNL forthcoming. de la Rue2006. “Building up India: Outlook for India’s real estate”,2006a. “World Energy Outlook”, IEA/OECD, Paris, France.

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

398

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network (OSTI)

trends in the iron and steel industry” Energy Policy 30 (user is the iron and steel industry representing almost halfTable 9). The Indian steel industry is slowly shifting from

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

399

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

U.S. Energy Information Administration (EIA)

Maps. Maps by energy source and topic, ... Solar › Energy in Brief. ... U.S. Department of Energy USA.gov FedStats. Stay Connected

400

Total Energy - Analysis & Projections - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Financial market analysis and financial data for major energy companies. ... is the U.S. Energy Information Administration's primary report of recent energy statistics.

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

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

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

Homes Million U.S. Housing Units Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.7...

402

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

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

Homes Million U.S. Housing Units Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC4.7...

403

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

Annual Energy Outlook 2012 (EIA)

Self-Reported) City Town Suburbs Rural Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC8.7...

404

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

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

East North Central West North Central Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

405

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

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

Heating Characteristics Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC5.4 Space Heating...

406

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

U.S. Energy Information Administration (EIA)

Short-Term Energy Outlook › Annual Energy Outlook › Energy Disruptions › International Energy Outlook ... A B C D E F G H I J K L M N O P Q R S T U V ...

407

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

E-Print Network (OSTI)

pricing and consumption data in South Korea. Index Terms--smart grid, demand-response, energy management I-based pricing. In peak capping, each home is allocated an energy quota. In market-based pricing, the price-term viable way of regulating energy consumptions. We work with day-ahead market pricing in this paper

Boutaba, Raouf

408

2009 Total Energy Production by State | Department of Energy  

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

Sandy Alternative Fueling Station Locator Alternative Fueling Station Locator Energy Department National Labs and Minority Serving Institutions Energy Department National...

409

Total Energy - Analysis & Projections - U.S. Energy ...  

U.S. Energy Information Administration (EIA)

Released: July 25, 2013. This report presents international energy projections through 2040, ... 2012. A report of historical annual energy ...

410

Total Energy - Analysis & Projections - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Energy Information Administration - EIA ... Financial market analysis and financial data for major energy companies. Environment. Greenhouse gas data, ...

411

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

412

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

413

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

414

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

SciTech Connect

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

415

Retrofitting Existing Buildings for Demand Response & Energy Efficiency  

E-Print Network (OSTI)

heating or cooling load, and enables existing Building Management Systems to control fan speed) · Lighting ­ 20% (solution: Adura ALPS partnership) · Plug loads, data centers ­ remainder (solution: WTR partnership) · Plug loads, data centers ­ remainder (solution: WTR, WBM) Source: US Energy Information

California at Los Angeles, University of

416

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

417

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

E-Print Network (OSTI)

Estimating Total Energy Consumption and Emissions of China’sof China’s total energy consumption mix. However, accuratelyof China’s total energy consumption, while others estimate

Fridley, David G.

2008-01-01T23:59:59.000Z

418

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

SciTech Connect

Commercial buildings account for a large portion of summer peak demand. Research results show that there is significant potential to reduce peak demand in commercial buildings through advanced control technologies and strategies. However, a better understanding of commercial building's contribution to peak demand and the use of energy management and control systems is required to develop this demand response resource to its full potential. This paper discusses recent research results and new opportunities for advanced building control systems to provide demand response (DR) to improve electricity markets and reduce electric grid problems. The main focus of this paper is the role of new and existing control systems for HVAC and lighting in commercial buildings. A demand-side management framework from building operations perspective with three main features: daily energy efficiency, daily peak load management and event driven, dynamic demand response is presented. A general description of DR, its benefits, and nationwide potential in commercial buildings is outlined. Case studies involving energy management and control systems and DR savings opportunities are presented. The paper also describes results from three years of research in California to automate DR in buildings. Case study results and research on advanced buildings systems in New York are also presented.

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

2006-01-17T23:59:59.000Z

419

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

SciTech Connect

Commercial buildings account for a large portion of summer peak demand. Research results show that there is significant potential to reduce peak demand in commercial buildings through advanced control technologies and strategies. However, a better understanding of commercial building's contribution to peak demand and the use of energy management and control systems is required to develop this demand response resource to its full potential. This paper discusses recent research results and new opportunities for advanced building control systems to provide demand response (DR) to improve electricity markets and reduce electric grid problems. The main focus of this paper is the role of new and existing control systems for HVAC and lighting in commercial buildings. A demand-side management framework from building operations perspective with three main features: daily energy efficiency, daily peak load management and event driven, dynamic demand response is presented. A general description of DR, its benefits, and nationwide potential in commercial buildings is outlined. Case studies involving energy management and control systems and DR savings opportunities are presented. The paper also describes results from three years of research in California to automate DR in buildings. Case study results and research on advanced buildings systems in New York are also presented.

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

2006-01-17T23:59:59.000Z

420

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

E-Print Network (OSTI)

This paper presents preliminary results of a study of electrical energy conservation and peak demand reduction potential for the building sector in Texas. Starting from 1980 building stocks and energy use characteristics, technical conservation potentials were calculated relative to frozen energy efficiency stock growth over the 1980-2000 period. The application of conservation supply methodology to Texas utilities is outlined, and then the energy use and peak demand savings, and their associated costs, are calculated using a prototypical building technique. Representative results are presented, for residential and commercial building types, as conservation supply curves for several end use categories; complete results of the study are presented in Ref. 1.

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

1985-01-01T23:59:59.000Z

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 Responsive and Energy Efficient Control Technologies andStrategies in Commercial Buildings  

SciTech Connect

Commercial buildings account for a large portion of summer peak electric demand. Research results show that there is significant potential to reduce peak demand in commercial buildings through advanced control technologies and strategies. However, a better understanding of commercial buildings contribution to peak demand and the use of energy management and control systems is required to develop this demand response resource to its full potential. The main objectives of the study were: (1) To evaluate the size of contributions of peak demand commercial buildings in the U.S.; (2) To understand how commercial building control systems support energy efficiency and DR; and (3) To disseminate the results to the building owners, facility managers and building controls industry. In order to estimate the commercial buildings contribution to peak demand, two sources of data are used: (1) Commercial Building Energy Consumption Survey (CBECS) and (2) National Energy Modeling System (NEMS). These two sources indicate that commercial buildings noncoincidental peak demand is about 330GW. The project then focused on technologies and strategies that deliver energy efficiency and also target 5-10% of this peak. Based on a building operations perspective, a demand-side management framework with three main features: (1) daily energy efficiency, (2) daily peak load management and (3) dynamic, event-driven DR are outlined. A general description of DR, its benefits, and nationwide DR potential in commercial buildings are presented. Case studies involving these technologies and strategies are described. The findings of this project are shared with building owners, building controls industry, researchers and government entities through a webcast and their input is requested. Their input is presented in the appendix section of this report.

Piette, Mary Ann; Kiliccote, Sila

2006-09-01T23:59:59.000Z

422

The asymmetric effects of changes in price and income on energy and oil demandEnergy Journal 23(1  

E-Print Network (OSTI)

This paper estimates the effects on energy and oil demand of changes in income and oil prices, for 96 of the world’s largest countries, in per-capita terms. We examine three important issues: the asymmetric effects on demand of increases and decreases in oil prices; the asymmetric effects on demand of increases and decreases in income; and the different speeds of demand adjustment to changes in price and in income. Its main conclusions are the following: (1) OECD demand responds much more to increases in oil prices than to decreases; ignoring this asymmetric price response will bias downward the estimated response to income changes; (2) demand’s response to income decreases in many Non-OECD countries is not necessarily symmetric to its response to income increases; ignoring this asymmetric income response will bias the estimated response to income changes; (3) the speed of demand adjustment is faster to changes in income than to changes in price; ignoring this difference will bias upward the estimated response to income changes. Using correctly specified equations for energy and oil demand, the long-run response in demand for income growth is about 1.0 for Non-OECD Oil Exporters, Income Growers and perhaps all Non-OECD countries, and about 0.55 for OECD countries. These estimates for developing countries are significantly higher than current estimates used by the US Department of Energy. Our estimates for the OECD countries are also higher than those estimated recently by Schmalensee-Stoker-Judson (1998) and Holtz-Eakin and Selden (1995), who ignore the (asymmetric) effects of prices on demand. Higher responses to income changes, of course, will increase projections of energy and oil demand, and of carbon dioxide emissions.

Dermot Gately; Hillard G. Huntington; Dermot Gately; Hillard G. Huntington; Joyce Dargay; Lawrence Goulder; Mary Riddel; Shane Streifel

2002-01-01T23:59:59.000Z

423

Potential For Energy, Peak Demand, and Water Savings in California Tomato Processing Facilities  

E-Print Network (OSTI)

Tomato processing is a major component of California's food industry. Tomato processing is extremely energy intensive, with the processing season coinciding with the local electrical utility peak period. Significant savings are possible in the electrical energy, peak demand, natural gas consumption, and water consumption of facilities. The electrical and natural gas energy usage and efficiency measures will be presented for a sample of California tomato plants. A typical end-use distribution of electrical energy in these plants will be shown. Results from potential electrical efficiency, demand response, and natural gas efficiency measures that have applications in tomato processing facilities will be presented. Additionally, water conservation measures and the associated savings will be presented. It is shown that an estimated electrical energy savings of 12.5%, electrical demand reduction of 17.2%, natural gas savings of 6.0%, and a fresh water usage reduction of 15.6% are achievable on a facility-wide basis.

Trueblood, A. J.; Wu, Y. Y.; Ganji, A. R.

2013-01-01T23:59:59.000Z

424

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

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

60,000 to 79,999 80,000 or More Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

425

Table 21. Total Energy Related Carbon Dioxide Emissions, Projected...  

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

Total Energy Related Carbon Dioxide Emissions, Projected vs. Actual Projected (million metric tons) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008...

426

AEO2011:Total Energy Supply, Disposition, and Price Summary ...  

Open Energy Info (EERE)

AEO2011:Total Energy Supply, Disposition, and Price Summary

427

2009 Total Energy Production by State | Department of Energy  

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

Non-powered Dams U.S. Hydropower Potential from Existing Non-powered Dams Creating an Energy Innovation Ecosystem Creating an Energy Innovation Ecosystem Sunshot Rooftop Solar...

428

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

SciTech Connect

In this analysis, the authors projected Japan's energy demand/supply and energy-related CO{sub 2} emissions to 2050. Their analysis of various scenarios indicated that Japan's CO{sub 2} emissions in 2050 could be potentially reduced by 26-58% from the current level (FY 2005). These results suggest that Japan could set a CO{sub 2} emission reduction target for 2050 at between 30% and 60%. In order to reduce CO{sub 2} emissions by 60% in 2050 from the present level, Japan will have to strongly promote energy conservation at the same pace as an annual rate of 1.9% after the oil crises (to cut primary energy demand per GDP (TPES/GDP) in 2050 by 60% from 2005) and expand the share of non-fossil energy sources in total primary energy supply in 2050 to 50% (to reduce CO{sub 2} emissions per primary energy demand (CO{sub 2}/TPES) in 2050 by 40% from 2005). Concerning power generation mix in 2050, nuclear power will account for 60%, solar and other renewable energy sources for 20%, hydro power for 10% and fossil-fired generation for 10%, indicating substantial shift away from fossil fuel in electric power supply. Among the mitigation measures in the case of reducing CO{sub 2} emissions by 60% in 2050, energy conservation will make the greatest contribution to the emission reduction, being followed by solar power, nuclear power and other renewable energy sources. In order to realize this massive CO{sub 2} abatement, however, Japan will have to overcome technological and economic challenges including the large-scale deployment of nuclear power and renewable technologies.

Komiyama, Ryoichi; Marnay, Chris; Stadler, Michael; Lai, Judy; Borgeson, Sam; Coffey, Brian; Azevedo, Ines Lima

2009-09-01T23:59:59.000Z

429

Identification of Changes Needed in Supermarket Design for Energy Demand Reduction  

E-Print Network (OSTI)

Supermarkets use 3 percent of UK energy. To satisfy building regulations supermarket buildings are modeled in considerable detail. Lighting, occupancy, and small electrical energy impacts are included in this modeling. However, refrigeration energy is not, as it is classified as process energy rather than building related. Refrigeration energy, which can be very significant, is therefore currently unregulated and as a result, heat transfers related to refrigeration cabinets are typically not incorporated in modeling of the building at design stage. This paper explores the comparative energy demands of supermarket stores modeled, using a simple first order dynamic model, executed on Excel, and optimized firstly with, and secondly without, the cooling effect of refrigeration cabinets included in the model. A recently built supermarket is modeled. Results suggest that the energy demand of a new store could be reduced by 15 to 25 percent by improvement of the building envelope design with process energy included in the modeling.

Hill, F.; Edwards, R.; Levermore, G.

2012-01-01T23:59:59.000Z

430

Total Prompt Energy Release in the Neutron-Induced Fission  

E-Print Network (OSTI)

This study addresses, for the first time, the total prompt energy release and its components for the fission of 235 U, 238 U, and 239 Pu as a function of the kinetic energy of the neutron inducing the fission. The components are extracted from experimental measurements, where they exist, together with model-dependent calculation, interpolation, and extrapolation. While the components display clear dependencies upon the incident neutron energy, their sums display only weak, yet definite, energy dependencies. Also addressed is the total prompt energy deposition in fission for the same three systems. Results are presented in equation form. New measurements are recommended as a consequence of this study. Key words: Energy release and energy deposition in neutron-induced fission,

D. G. Madland

2006-01-01T23:59:59.000Z

431

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

SciTech Connect

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 reference document provides a detailed description for energy analysts, other users, and the public. The NEMS Residential Sector Demand Module is currently used for mid-term forecasting purposes and energy policy analysis over the forecast horizon of 1993 through 2020. The model generates forecasts of energy demand for the residential sector by service, fuel, and Census Division. Policy impacts resulting from new technologies, market incentives, and regulatory changes can be estimated using the module. 26 refs., 6 figs., 5 tabs.

NONE

1998-01-01T23:59:59.000Z

432

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

433

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 percent 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.

Information Center

2005-04-01T23:59:59.000Z

434

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 +

435

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

436

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.

437

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

NLE Websites -- All DOE Office Websites (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

438

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

U.S. Energy Information Administration (EIA)

Comprehensive data summaries, comparisons, analysis, and projections integrated across all energy sources. Highlights This Week in Petroleum ... Wind › Geothermal

439

Tracking Progress Last updated 5/8/2013 Statewide Energy Demand 1  

E-Print Network (OSTI)

Electricity consumption grew at a rate of about 1.5 percent from 1990 to 2000, 1 percent from 2000 to 2008. Net peak is total electricity demand at peak on the customer side, plus utility transmission,884 2022* 74,049 70,946 66,916 Note: Historical values are shaded. *Weather-normalized: a weather

440

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

Annual Energy Outlook 2012 (EIA)

Usage Indicators by U.S. Census Region, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators U.S. Census Region Northeast Midwest South West Energy Information...

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

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

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

U.S. Housing Units Home Electronics Usage Indicators Table HC10.12 Home Electronics Usage Indicators by U.S. Census Region, 2005 Housing Units (millions) Energy Information...

442

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

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

U.S. Housing Units Home Electronics Usage Indicators Table HC8.12 Home Electronics Usage Indicators by UrbanRural Location, 2005 Housing Units (millions) Energy Information...

443

Correlations between industrial demands (direct and total) for communications and transportation in the US economy 1947-1997  

E-Print Network (OSTI)

inputs is high, does its requirement for communicationcommodity is high, does its requirement for the other typeTjt ) is high, does its total requirement for communications

Lee, Taihyeong; Mokhtarian, Patricia L

2008-01-01T23:59:59.000Z

444

Regional Differences in the Price-Elasticity of Demand for Energy  

DOE Green Energy (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

445

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

446

Consensus forecast of U. S. energy supply and demand to the year 2000  

DOE Green Energy (OSTI)

Methods used in forecasting energy supply and demand are described, and recent forecasts are reviewed briefly. Forecasts to the year 2000 are displayed in tables and graphs and are used to prepare consensus forecasts for each form of fuel and energy supply. Fuel demand and energy use by consuming sector are tabulated for 1972 and 1975 for the various fuel forms. The distribution of energy consumption by use sector, as projected for the years 1985 and 2000 in the ERDA-48 planning report (Scenario V), is normalized to match the consensus energy supply forecasts. The results are tabulated listing future demand for each fuel and energy form by each major energy-use category. Recent estimates of U.S. energy resources are also reviewed briefly and are presented in tables for each fuel and energy form. The outlook for fossil fuel resources to the year 2040, as developed by the Institute for Energy Analysis at the Oak Ridge Associated Universities, is also presented.

Lane, J.A.

1976-02-01T23:59:59.000Z

447

Transportation Demand This  

Annual Energy Outlook 2012 (EIA)

69 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 Transportation Demand Module The NEMS Transportation Demand Module estimates...

448

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

U.S. Energy Information Administration (EIA)

Financial market analysis and financial data for major energy companies. Environment. Greenhouse gas data, voluntary report- ing, electric power plant emissions.

449

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

SciTech Connect

In this study, we measured and documented summertime air-conditioning (a/c) daily energy savings and demand reduction from a reflective roof membrane retrofit on a large retail store in Austin, Texas. The original black rubber membrane was replaced with white thermoplastic resulting in a decrease in the average maximum roof surface temperature from 168 degrees F (76 degrees C) to 126 degrees F (52 degrees C). This building, with 100,000ft2 (9300m2) of roof area, yielded 3.6Wh/ft2 (39Wh/m2) in a/c average daily energy savings and 0.35W/ft2 (3.8W/m2) in average reduced demand. Total a/c annual abated energy and demand expenditures were estimated to be $7200 or $0.072/ft2 ($0.77/m2). Based on cost data provided by the building manager, the payback is instantaneous with negligible incremental combined labor and material costs. The estimated present value of future abated expenditures ranged from $62,000 to $71,000 over the baseline 13-year service life of the roof membrane.

Konopacki, Steven J.; Akbari, Hashem

2001-06-25T23:59:59.000Z

450

Energy Demand: Limits on the Response to Higher Energy Prices in the End-Use Sectors (released in AEO2007)  

Reports and Publications (EIA)

Energy consumption in the end-use demand sectorsresidential, commercial, industrial, and transportationgenerally shows only limited change when energy prices increase. Several factors that limit the sensitivity of end-use energy demand to price signals are common across the end-use sectors. For example, because energy generally is consumed in long-lived capital equipment, short-run consumer responses to changes in energy prices are limited to reductions in the use of energy services or, in a few cases, fuel switching; and because energy services affect such critical lifestyle areas as personal comfort, medical services, and travel, end-use consumers often are willing to absorb price increases rather than cut back on energy use, especially when they are uncertain whether price increases will be long-lasting. Manufacturers, on the other hand, often are able to pass along higher energy costs, especially in cases where energy inputs are a relatively minor component of production costs. In economic terms, short-run energy demand typically is inelastic, and long-run energy demand is less inelastic or moderately elastic at best.

Information Center

2007-03-11T23:59:59.000Z

451

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

452

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)

2011-12-06T23:59:59.000Z

453

Utilization of Energy Efficiency and Demand Response as Resources for Transmission and Distribution Planning  

Science Conference Proceedings (OSTI)

EPRI began its Energy Efficiency Initiative in early 2007. Initiative research, which covers numerous topics associated with energy efficiency and demand management, is categorized into three areas: analytics, infrastructure, and devices. The project described in this report details the Initiative’s analytics element, which deals with methods and tools for analyzing aspects of the use of energy efficiency as supply resource, including measurement and verification, inclusion in generation planning, emissi...

2008-02-05T23:59:59.000Z

454

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

follows: • EDemand t : electricity demand during day t (incost of reducing electricity demand (in $/MWh e ) • HRDCost:maximum fraction of electricity demand to be met by demand

Siddiqui, Afzal

2010-01-01T23:59:59.000Z

455

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.

456

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)

457

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

458

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

459

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.

460

Hawaii Energy Strategy: Program guide. [Contains special sections on analytical energy forecasting, renewable energy resource assessment, demand-side energy management, energy vulnerability assessment, and energy strategy integration  

SciTech Connect

The Hawaii Energy Strategy program, or HES, is a set of seven projects which will produce an integrated energy strategy for the State of Hawaii. It will include a comprehensive energy vulnerability assessment with recommended courses of action to decrease Hawaii's energy vulnerability and to better prepare for an effective response to any energy emergency or supply disruption. The seven projects are designed to increase understanding of Hawaii's energy situation and to produce recommendations to achieve the State energy objectives of: Dependable, efficient, and economical state-wide energy systems capable of supporting the needs of the people, and increased energy self-sufficiency. The seven projects under the Hawaii Energy Strategy program include: Project 1: Develop Analytical Energy Forecasting Model for the State of Hawaii. Project 2: Fossil Energy Review and Analysis. Project 3: Renewable Energy Resource Assessment and Development Program. Project 4: Demand-Side Management Program. Project 5: Transportation Energy Strategy. Project 6: Energy Vulnerability Assessment Report and Contingency Planning. Project 7: Energy Strategy Integration and Evaluation System.

1992-09-01T23:59:59.000Z

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.


461

The Use of Trust Regions in Kohn-Sham Total Energy Minimization  

E-Print Network (OSTI)

of the KS total energy optimization problem, which has beenthe original total energy minimization problem is. Secondly,the KS total energy minimiza- tion problem as min E total (

Yang, Chao; Meza, Juan C.; Wang, Lin-wang

2006-01-01T23:59:59.000Z

462

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.....................................................

463

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.....................................................

464

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.....................................................

465

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.....................................................

466

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.....................................................

467

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.....................................................

468

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.....................................................

469

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......................................

470

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

471

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

472

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

473

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...............................

474

Survey and forecast of marketplace supply and demand for energy- efficient lighting products  

SciTech Connect

The rapid growth in demand for energy-efficient lighting products has led to supply shortages for certain products. To understand the near-term (1- to 5-year) market for energy-efficient lighting products, a selected set of utilities and lighting product manufacturers were surveyed in early 1991. Two major U. S. government programs, EPA's Green Lights and DOE's Federal Relighting Initiative, were also examined to assess their effect on product demand. Lighting product manufacturers predicted significant growth through 1995. Lamp manufacturers indicated that compact fluorescent lamp shipments tripled between 1988 and 1991, and predicted that shipments would again triple, rising from 25 million units in 1991 to 72 million units in 1995. Ballast manufacturers predicted that demand for power-factorcorrected ballasts (both magnetic and electronic) would grow from 59.4 million units in 1991 to 71.1 million units in 1995. Electronic ballasts were predicted to grow from 11% of ballast demand in 1991 to 40% in 1995. Manufacturers projected that electronic ballast supply shortages would continue until late 1992. Lamp and ballast producers indicated that they had difficulty in determining what additional supply requirements might result due to demand created by utility programs. Using forecasts from 27 surveyed utilities and assumptions regarding the growth of U. S. utility lighting DSM programs, low, median, and high forecasts were developed for utility expenditures for lighting incentives through 1994. The projected median figure for 1992 was $316 million, while for 1994, the projected median figure was $547 million. The allocation of incentive dollars to various products and the number of units needed to meet utility-stimulated demand were also projected. To provide a better connection between future supply and demand, a common database is needed that captures detailed DSM program information including incentive dollars and unit-volume mix by product type.

Gough, A. (Lighting Research Inst., New York, NY (United States)); Blevins, R. (Plexus Research, Inc., Donegal, PA (United States))

1992-12-01T23:59:59.000Z

475

Water flows, energy demand, and market analysis of the informal water sector in Kisumu, Kenya  

E-Print Network (OSTI)

Analysis Water flows, energy demand, and market analysis of the informal water sector in Kisumu Available online xxxx Keywords: Informal water sector Water flows Developing countries Water market analysis to cope with popu- lation growth. Informal water businesses fulfill unmet water supply needs, yet little

Elimelech, Menachem

476

Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty  

E-Print Network (OSTI)

than relying on central-station electricity generation and purchase of natural gas for heating and DER under uncertain electricity and natural gas prices · Section 5 summarizes the findings Control of Distributed Energy Resources and Demand Response under Uncertainty 3 · FPt: wholesale natural

477

Barriers to reducing energy demand in existing building stock -a perspective based on  

E-Print Network (OSTI)

Barriers to reducing energy demand in existing building stock - a perspective based on observation incentives for replacing the worst boilers, installing insulation funding for businesses and charities to push incentives, offer advice, develop new interventions building regs that apply to new boilers

Carletta, Jean

478

Assessment of Achievable Potential from Energy Efficiency and Demand Response Programs in the U.S. (2010 - 2030)  

Science Conference Proceedings (OSTI)

This report documents the results of an exhaustive study to assess the achievable potential for electricity energy savings and peak demand reduction from energy efficiency and demand response programs through 2030. This achievable potential represents an estimated range of savings attainable through programs that encourage adoption of energy-efficient technologies, taking into consideration technical, economic, and market constraints.

2009-01-14T23:59:59.000Z

479

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

E-Print Network (OSTI)

A load research project by the Florida Power Corporation (FPC) is monitoring 200 residences in Central Florida, collecting detailed end-use load data. The monitoring is being performed to better estimate the impact of FPC's load control program, as well as obtain improved appliance energy consumption indexes and load profiles. A portion of the monitoring measures water heater energy use and demand in each home on a 15-minute basis.

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

2000-01-01T23:59:59.000Z

480

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

E-Print Network (OSTI)

download EMCS download Sub-metering Real-time Connectivityof diagnostic testing, sub-metering, and performancecoincident demand at sub-metering S Compare to historical

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

2003-01-01T23:59:59.000Z

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

Energy Demand and Emissions in Building in China: Scenarios and Policy Options  

E-Print Network (OSTI)

Recent rapid growth of energy use in China exerts great pressure on the energy supply and environment. This study provides scenarios of future energy development in buildings, including urban residential, rural residential and service sectors (not including transport), taking into account the most up-to-date data and recent policy discussions that will affect future economic, population, and energy supply trends. To understand the role of policy options including technology options and countermeasures, two scenarios were defined, which represent the range of plausible futures for energy development in buildings. This is also part of an energy and emission scenario study for the IPAC (Integrated Policy Assessment Model for China) modeling team. The results from quantitative analysis show that energy demand in buildings in China could increase quickly, as high as 666 million in 2030. However, policies and technologies could contribute a lot to energy demand savings, which could be 28% energy savings compared with the baseline scenario. There is still space for further energy savings if more advanced technologies could be fully diffused.

Kejun, J.; Xiulian, H.

2006-01-01T23:59:59.000Z

482

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

483

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.

484

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

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

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

485

Worldwide transportation/energy demand, 1975-2000. Revised Variflex model projections  

SciTech Connect

The salient features of the transportation-energy relationships that characterize the world of 1975 are reviewed, and worldwide (34 countries) long-range transportation demand by mode to the year 2000 is reviewed. A worldwide model is used to estimate future energy demand for transportation. Projections made by the forecasting model indicate that in the year 2000, every region will be more dependent on petroleum for the transportation sector than it was in 1975. This report is intended to highlight certain trends and to suggest areas for further investigation. Forecast methodology and model output are described in detail in the appendices. The report is one of a series addressing transportation energy consumption; it supplants and replaces an earlier version published in October 1978 (ORNL/Sub-78/13536/1).

Ayres, R.U.; Ayres, L.W.

1980-03-01T23:59:59.000Z

486

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

E-Print Network (OSTI)

As part of the LoanSTAR program, Victoria High School in Victoria, Texas underwent two retrofits: a) an absorption chiller was changed to an electric vapor compression chiller, and b) an EMCS system was installed after about 5 months in the post retrofit period. Moreover, retrofit savings calculation was complex since pre-retrofit data consisted of only monthly utility data while hourly monitored data are available for the post-retrofit period. This report describes the method in which we have performed retrofit energy and demand savings in Victoria High School. A previous report described the procedure adopted when no pre-retrofit data are available. We have only used Unnormalized Utility Bills Comparison ,or the Level-0 approach to determine electricity (energy and demand) and gas energy savings for VHS.

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

1992-01-01T23:59:59.000Z

487

Optimal Technology Investment and Operation in Zero-Net-Energy Buildings with Demand Response  

Science Conference Proceedings (OSTI)

The US Department of Energy has launched the Zero-Net-Energy (ZNE) Commercial Building Initiative (CBI) in order to develop commercial buildings that produce as much energy as they use. Its objective is to make these buildings marketable by 2025 such that they minimize their energy use through cutting-edge energy-efficient technologies and meet their remaining energy needs through on-site renewable energy generation. We examine how such buildings may be implemented within the context of a cost- or carbon-minimizing microgrid that is able to adopt and operate various technologies, such as photovoltaic (PV) on-site generation, heat exchangers, solar thermal collectors, absorption chillers, and passive / demand-response technologies. We use a mixed-integer linear program (MILP) that has a multi-criteria objective function: the minimization of a weighted average of the building's annual energy costs and carbon / CO2 emissions. The MILP's constraints ensure energy balance and capacity limits. In addition, constraining the building's energy consumed to equal its energy exports enables us to explore how energy sales and demand-response measures may enable compliance with the CBI. Using a nursing home in northern California and New York with existing tariff rates and technology data, we find that a ZNE building requires ample PV capacity installed to ensure electricity sales during the day. This is complemented by investment in energy-efficient combined heat and power equipment, while occasional demand response shaves energy consumption. A large amount of storage is also adopted, which may be impractical. Nevertheless, it shows the nature of the solutions and costs necessary to achieve ZNE. For comparison, we analyze a nursing home facility in New York to examine the effects of a flatter tariff structure and different load profiles. It has trouble reaching ZNE status and its load reductions as well as efficiency measures need to be more effective than those in the CA case. Finally, we illustrate that the multi-criteria frontier that considers costs and carbon emissions in the presence of demand response dominates the one without it.

Stadler , Michael; Siddiqui, Afzal; Marnay, Chris; ,, Hirohisa Aki; Lai, Judy

2009-05-26T23:59:59.000Z

488

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)

489

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

E-Print Network (OSTI)

New challenges of Japanese energy efficiency program by Topto 2030 Considering Energy Efficiency Standards “Top-Runnerof Energy for Energy Efficiency and Renewable Energy,

Komiyama, Ryoichi

2008-01-01T23:59:59.000Z

490

Advanced Control Technologies and Strategies Linking Demand Response and Energy Efficiency  

E-Print Network (OSTI)

Fully Automated Demand Response Tests in Large Facilities”.also provided through the Demand Response Research Center (of Fully Automated Demand Response in Large Facilities”

Kiliccote, Sila; Piette, Mary Ann

2005-01-01T23:59:59.000Z

491

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

E-Print Network (OSTI)

of Fully Automated Demand Response in Large Facilities”NYSERDA) and the Demand Response Research Center (LLC “Working Group 2 Demand Response Program Evaluation –

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

2006-01-01T23:59:59.000Z

492

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

Science Conference Proceedings (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

493

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

SciTech Connect

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 requirements of the Energy Information Administration (EIA) to provide adequate documentation in support of its model. 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

1998-01-01T23:59:59.000Z

494

Program Strategies and Results for California’s Energy Efficiency and Demand Response Markets  

E-Print Network (OSTI)

Global Energy Partners provides a review of California’s 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), is presented along with special efforts being made in support of industrial end users. The interrelationship between the CEC and the California Public Utility Commission (CPUC) with regard to advancing demand side programs is highlighted. The specific cost recovery mechanisms put in place by the CPUC is discussed, including California’s experience with revenue decoupling, public purpose funds, and avoided cost calculations. Next, the role as energy efficiency (EE) and demand response (DR) program implementer played by each of the state Investor Owned Utilities (IOUs) is outlined. Each utility is responsible for serving major end use market segments with target programs designed to provide unique value. Within the industrial sector, there is special attention paid to the needs of the various sub-markets such as oil refining, agriculture, food processing, water and wastewater, manufacturing, and others. A review is presented of how EE and DR measures are selected, how incentive values are determined, which customers are eligible for programs, and how programs are evaluated to gage effectiveness. Lastly, mechanisms used by the IOU’s to deliver industrial EE and DR incentive programs are discussed. This includes a review of “core” programs administered by the utilities as well as subcontracted programs administered by “third party” implementers and “local government partners”. Global Energy Partners will offer specific examples of program experience in the oil & gas, agriculture, and food processing sectors, and will also highlight program success within the emerging “automated” demand response market.

Ehrhard, R.; Hamilton, G.

2008-01-01T23:59:59.000Z

495

Stirling total energy systems study. Final report, May 15, 1976--June 13, 1977  

SciTech Connect

The application of Stirling cycle prime movers to total energy power generation systems was investigated. Electrical, heating, and cooling demand profiles for a typical residential complex, hospital, and office building were studied, and alternative Stirling total energy systems were conceptualized for each site. These were analyzed in detail and contrasted with purchased-power systems for these sites to determine fuel-energy savings and investment attractiveness. The residential complex and hospital would be excellent candidates for total energy systems, and prime movers in the 1000 kW output range would be required. Stirling engines with so large an output have not been built to date, although there would be no fundamental technical barrier to prevent this. However, careful consideration must be given to the following technological decision areas before arriving at a final design, if its potential is to be realized: engine configuration, hotside heat exchange interface, engine control system, internal gas seals, and advanced coal combustion technology. The principal advantage of a Stirling prime mover in this application, in view of national concern over present and future dependence on oil, is that it could utilize low-grade liquid fuels and coal.

Lehrfeld, D.

1977-08-01T23:59:59.000Z

496

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

E-Print Network (OSTI)

all the test days and maximum demand savings for the bestin Table 4. Average Maximum Demand Demand Savings SavingsTable 4. Average and maximum demand savings results from

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

2006-01-01T23:59:59.000Z

497

Total Primary Energy Use in the U.S. by Sector, 1998 (chart)  

U.S. Energy Information Administration (EIA)

Home > Energy Users > Energy Efficiency Page > Figure 1. Total Primary Energy Use by Sector [Trends in Building-Related Energy and ...

498

Assessment of Achievable Potential from Energy Efficiency and Demand Response Programs for the Tennessee Valley Authority  

Science Conference Proceedings (OSTI)

This report documents the results of a study to assess the achievable potential for electricity energy savings and peak demand reductions for the Tennessee Valley Authority (TVA) for 2010-2030. The approach involved applying the methodology and technology data developed for the Electric Power Research Institute (EPRI) National Study on the same subject (product number 1016987), adapted to the specific market sector characteristics of the Tennessee Valley. The efficient technologies and measures considere...

2010-03-24T23:59:59.000Z

499

Policy implications of the GRI Baseline Projection of US Energy Supply and Demand to 2010; 1991  

Science Conference Proceedings (OSTI)

The 1991 edition of the GRI Baseline Projection of U.S. Energy Supply and Demand is summarized. Three broad implications for the future of the natural gas industry are highlighted: the impact of the Middle East turmoil on the expected price of crude oil and the potentional for increased interfuel price competition between natural gas and petroleum in the mid-1990s if world oil prices return to lower levels.

Not Available

1990-12-01T23:59:59.000Z

500

ORNL Residential Reference House Energy Demand model (ORNL-RRHED). Volume 4. Case studies  

Science Conference Proceedings (OSTI)

This report describes the use and structure of the ORNL Residential Reference House Energy Demand Model (RRHED). RRHED is a computer-based engineering-economic end-use simulation model which forecasts energy demand based on a detailed evaluation of how households use energy for particular appliances. The report is organized into four volumes. The first volume provides an overview of the modeling approach and gives a short summary of the material presented in the other three volumes. The second volume is a user reference guide which provides the details necessary for users of the model to run the code and make changes to fit their particular application. Volume 3 presents the basic theoretical rationale for the RRHED model structure. The last volume reports on the application of the model to the analysis of two different kinds of issues: one is the examination of conservation policy impacts and the other is the forecasting of electricity demand in a need for power assessment. The report has two major objectives. The first is to provide a reader with little background in end-use modeling with an introduction to how the RRHED model works. The second is to provide the details needed by a user of the model to understand not only the theory behind the model specification, but also the structure of the code. This information will allow for the modification of subroutines to fit particular applications.

Hamblin, D.M.; Thomas, B. Jr.; Maddigan, R.J.; Forman, C.W. Jr.; Bibo, L.J.; McKeehan, K.M.

1986-02-01T23:59:59.000Z