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


1

National Energy Modeling System (NEMS)  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. through 2030. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. NEMS was designed and implemented by the Energy Information Administration (EIA) of the U.S. Department of Energy (DOE). NEMS can be used to analyze the effects of existing and proposed government laws and regulations related to energy production and use; the potential impact of new and advanced energy production, conversion, and consumption technologies; the impact and cost of greenhouse gas control; the impact of increased use of renewable energy sources; and the potential savings from increased efficiency of energy use; and the impact of regulations on the use of alternative or reformulated fuels. NEMS has also been used for a number of special analyses at the request of the Administration, U.S. Congress, other offices of DOE and other government agencies, who specify the scenarios and assumptions for the analysis. Modules allow analyses to be conducted in energy topic areas such as residential demand, industrial demand, electricity market, oil and gas supply, renewable fuels, etc.

2

Price Responsiveness in the AEO2003 NEMS Residential and Commercial Buildings Sector Models  

Reports and Publications (EIA)

This paper describes the demand responses to changes in energy prices in the Annual Energy Outlook 2003 versions of the Residential and Commercial Demand Modules of the National Energy Modeling System (NEMS). It updates a similar paper completed for the Annual Energy Outlook 1999 version of the NEMS.

2003-01-01T23:59:59.000Z

3

National Energy Modeling System (NEMS) | Open Energy Information  

Open Energy Info (EERE)

National Energy Modeling System (NEMS) National Energy Modeling System (NEMS) Jump to: navigation, search Tool Summary LAUNCH TOOL Name: National Energy Modeling System (NEMS) Agency/Company /Organization: Energy Information Administration Sector: Energy Focus Area: Economic Development Phase: Develop Goals Topics: Policies/deployment programs Resource Type: Software/modeling tools User Interface: Desktop Application Website: www.eia.gov/oiaf/aeo/overview/index.html OpenEI Keyword(s): EERE tool, National Energy Modeling System, NEMS Language: English References: The National Energy Modeling System: An Overview[1] Project the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and

4

How to obtain the National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

The National Energy Modeling System (NEMS) NEMS is used by the modelers at the U. S. Energy Information Administration (EIA) who understand its structure and programming. NEMS has only been used by a few organizations outside of the EIA, because most people that requested NEMS found out that it was too difficult or rigid to use. NEMS is not typically used for state-level analysis and is poorly suited for application to other countries. However, many do obtain the model simply to use the data in its input files or to examine the source code.

2013-01-01T23:59:59.000Z

5

The National Energy Modeling System: An Overview 2000 - Overview of NEMS  

Gasoline and Diesel Fuel Update (EIA)

NEMS represents domestic energy markets by explicitly representing the economic decision making involved in the production, conversion, and consumption of energy products. Where possible, NEMS includes explicit representation of energy technologies and their characteristics. NEMS represents domestic energy markets by explicitly representing the economic decision making involved in the production, conversion, and consumption of energy products. Where possible, NEMS includes explicit representation of energy technologies and their characteristics. Since energy costs and availability and energy-consuming characteristics can vary widely across regions, considerable regional detail is included. Other details of production and consumption categories are represented to facilitate policy analysis and ensure the validity of the results. A summary of the detail provided in NEMS is shown below. Summary Table Major Assumptions Each module of NEMS embodies many assumptions and data to characterize the future production, conversion, or consumption of energy in the United States. Two major assumptions concern economic growth in the United States and world oil prices, as determined by world oil supply and demand.

6

Comparison of Bottom-Up and Top-Down Forecasts: Vision Industry Energy Forecasts with ITEMS and NEMS  

E-Print Network [OSTI]

of the Department of Energy's Office of Industrial Technologies, EIA extracted energy use infonnation from the Annual Energy Outlook (AEO) - 2000 (8) for each of the seven # The Pacific Northwest National Laboratory is operated by Battelle Memorial Institute...-6, 2000 NEMS The NEMS industrial module is the official forecasting model for EIA and thus the Department of Energy. For this reason, the energy prices and output forecasts used to drive the ITEMS model were taken from EIA's AEO 2000. Understanding...

Roop, J. M.; Dahowski, R. T

7

NEMS integrating module documentation report  

SciTech Connect (OSTI)

The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to a variety of assumptions. The assumptions encompass macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, technology characteristics, and demographics. NEMS produces a general equilibrium solution for energy supply and demand in the U.S. energy markets on an annual basis through 2015. Baseline forecasts from NEMS are published in the Annual Energy Outlook. Analyses are also prepared in response to requests by the U.S. Congress, the DOE Office of Policy, and others. NEMS was first used for forecasts presented in the Annual Energy Outlook 1994.

NONE

1997-05-01T23:59:59.000Z

8

The National Energy Modeling System: An Overview 1998 - Overview of NEMS  

Gasoline and Diesel Fuel Update (EIA)

OVERVIEW OF NEMS OVERVIEW OF NEMS blueball.gif (205 bytes) Major Assumptions blueball.gif (205 bytes) NEMS Modular Structure blueball.gif (205 bytes) Integrating Module NEMS represents domestic energy markets by explicitly representing the economic decisionmaking involved in the production, conversion, and consumption of energy products. For example, the penetration of a new or advanced technology for electricity generation is projected only if the technology is deemed to be economic when considering the cost-minimizing mix of fuels over the life of the equipment. Since energy costs and availability and energy- consuming characteristics can vary widely across regions, considerable regional detail is included. Other details of production and consumption categories are represented to

9

PRICE GOUGING | Department of Energy  

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

PRICE GOUGING PRICE GOUGING PRICE GOUGING More Documents & Publications PRICE GOUGING Department of Energy Response to Hurricane Katrina Fact Sheet Department of Energy Response to...

10

EIA Buildings Analysis of Consumer Behavior in NEMS  

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

Buildings Analysis of Consumer Buildings Analysis of Consumer Behavior in NEMS Behavioral Economics Experts Meeting July 17, 2013 | Washington, DC David Peterson Buildings Energy Consumption and Efficiency Analysis Overview Behavioral Economics Experts Meeting, Washington DC, July 17, 2013 2 * NEMS Structure * Housing/floorspace and service demand in Residential Demand Module (RDM) and Commercial Demand Module (CDM) * Market share calculation for equipment in RDM and CDM * Price responses / elasticities * Distributed generation (DG) & combined heat and power (CHP) NEMS Structure Behavioral Economics Experts Meeting, Washington DC, July 17, 2013 3 * Represents energy supply, conversion, and demand in a unified, but modular system * Detailed structural and process models in most energy sectors

11

A sensitivity analysis of the treatment of wind energy in the AEO99 version of NEMS  

E-Print Network [OSTI]

other assumptions for wind power to determine which onesused in NEMS regarding wind power to determine their impact

Osborn, Julie G.; Wood, Frances; Richey, Cooper; Sanders, Sandy; Short, Walter; Koomey, Jonathan

2001-01-01T23:59:59.000Z

12

Stephanie Price | Department of Energy  

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

Renewable Energy Laboratory Stephanie Price is a communicator at the National Renewable Energy Laboratory, which assists EERE in providing technical content for many of its...

13

energy prices | OpenEI  

Open Energy Info (EERE)

prices prices Dataset Summary Description The State Energy Data System (SEDS) is compiled by the U.S. Energy Information Administration's (EIA); it is a comprehensive database of energy statistics by state (and includes totals for the entire US). SEDS includes estimates of energy production, consumption, prices, and expenditures broken down by energy source and sector. Annual estimates are available from 1960 - 2009 for production and consumption estimates and from 1970 - 2009 for price and expenditure estimates. Source EIA Date Released June 30th, 2011 (3 years ago) Date Updated Unknown Keywords EIA Energy Consumption Energy Expenditures energy prices energy production SEDS State energy data States US Data text/csv icon Complete SEDS dataset as csv (may be too big for Excel) (csv, 40.6 MiB)

14

Multi-Factor Energy Price Models Exotic Derivatives Pricing  

E-Print Network [OSTI]

of Statistics University of Toronto c Copyright by Samuel Hikspoors 2008 #12;Multi-Factor Energy Price Models of Toronto, May 2008 Abstract The high pace at which many of the world's energy markets have gradually beenMulti-Factor Energy Price Models and Exotic Derivatives Pricing by Samuel Hikspoors A thesis

Jaimungal, Sebastian

15

Energy Prices and California's Economic  

E-Print Network [OSTI]

on Energy Prices, Renewables, Efficiency, and Economic Growth: Scenarios and Forecasts, financial support and incentives to promote energy efficiency and renewable energy and decrease the use of fossil fuels. Aligned with that plan, the state legislature recently passed the nation's boldest commitment to renewable energy

Sadoulet, Elisabeth

16

Nano-Electro-Mechanical (NEM) Relay Devices and Technology for Ultra-Low Energy Digital Integrated Circuits  

E-Print Network [OSTI]

Technology 3.1 Introduction Nano-electro-mechanical (NEM)improvements, a scaled nano-relay technology with optimizedNano-Electro-Mechanical (NEM) Relay Devices and Technology

Nathanael, Rhesa

2012-01-01T23:59:59.000Z

17

Energy prices, production  

E-Print Network [OSTI]

This paper investigates economic incentives influencing the adoption of energy saving technology by industry, namely, CHP in UK and Dutch manufacturing sectors. The empirical analysis is based on a cross sectional time series econometric model...

Bonilla, David

18

Today in Energy - Daily Prices - Prices - U.S. Energy Information  

Gasoline and Diesel Fuel Update (EIA)

December 20, 2013Daily Prices December 20, 2013Daily Prices Daily wholesale and retail prices for various energy products are shown below, including spot prices and select futures prices at national or regional levels. Prices are updated each weekday (excluding federal holidays), typically between 7:30 and 8:30 a.m. This page is meant to provide a snapshot of selected daily prices only. Prices are republished by EIA with permission as follows: Wholesale Spot Petroleum Prices from Thomson Reuters, Retail Petroleum Prices from AAA Fuel Gauge Report, Prompt-Month Energy Futures from CME Group, and Select Spot Prices from SNL Energy. Daily Prices Wholesale Spot Petroleum Prices, 12/19/13 Close Product Area Price Percent Change* Crude Oil ($/barrel) WTI 98.40 +0.8 Brent 110.78 +1.1 Louisiana Light 108.27 +4.9

19

Marginal Energy Prices- RECS97 Update  

Broader source: Energy.gov [DOE]

An updated estimation of residential marginal energy prices at the individual house level using the 1997 RECS survey data

20

Marginal Energy Prices - RECS97 Update  

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

Marginal Energy Prices - RECS97 Update Marginal Energy Prices - RECS97 Update The original estimation of residential marginal energy prices at the individual household level (as reported in the Marginal Energy Prices Report, http://www.eren.doe.gov/buildings/codes_standards/applbrf/pdfs/marginal_ energy_price.pdf) was based on household energy billing data from EIA's 1993 RECS survey. When the 1997 RECS survey data became available, LBNL updated its estimation of residential marginal energy prices at the individual household level using that data. In addition, LBNL incorporated several refinements (as described below) to the marginal price estimation method it had originally developed. Presented below are the: * RECS97-based results. * Refinements to LBNL's marginal price estimation method.

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

Marginal Energy Prices - RECS97 Update  

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

Marginal Energy Prices - RECS97 Update Marginal Energy Prices - RECS97 Update The original estimation of residential marginal energy prices at the individual household level (as reported in the Marginal Energy Prices Report, http://www.eren.doe.gov/buildings/codes_standards/applbrf/pdfs/marginal_ energy_price.pdf) was based on household energy billing data from EIA's 1993 RECS survey. When the 1997 RECS survey data became available, LBNL updated its estimation of residential marginal energy prices at the individual household level using that data. In addition, LBNL incorporated several refinements (as described below) to the marginal price estimation method it had originally developed. Presented below are the: * RECS97-based results. * Refinements to LBNL's marginal price estimation method.

22

State energy price and expenditure report 1991  

SciTech Connect (OSTI)

The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 States and the District of Columbia and in aggregate for the United States. The price and expenditure estimates are provided by energy source and economic sector and are published for the years 1970, 1975, 1980, and 1985 through 1991. Data for all years, 1970 through 1991, are available on personal computer diskettes. Documentation in Appendix A describes how the price estimates are developed, including sources of data, methods of estimation, and conversion factors applied. This report is an update of the State Energy Price and Expenditure Report 1990, published in September 1992.

Not Available

1993-09-01T23:59:59.000Z

23

Belinda Price | Department of Energy  

Office of Environmental Management (EM)

Belinda Price About Us Belinda Price - Member Belinda is a senior hydrogeologist with Alliant Corporation. She has more than 25 years experience in environmental investigation and...

24

Prices for Natural Gas | Open Energy Information  

Open Energy Info (EERE)

Prices for Natural Gas Prices for Natural Gas Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Prices for Natural Gas Agency/Company /Organization: Google Sector: Energy Focus Area: Economic Development Resource Type: Software/modeling tools User Interface: Website Website: www.google.com/publicdata/explore?ds=m49d2j928087j_ Country: United States Web Application Link: www.google.com/publicdata/explore?ds=m49d2j928087j_ Cost: Free Northern America Prices for Natural Gas Screenshot References: Public Data Explorer[1] EIA[2] Logo: Prices for Natural Gas Prices for Natural Gas Dollars per Thousand Cubic Feet and Percent in U.S. Total Represented by the Price. Overview A graphing tool that displays prices for natural gas dollars per thousand cubic feet and percent in U.S. Total represented by the price, using data

25

A SENSITIVITY ANALYSIS OF THE TREATMENT OF WIND ENERGY IN THE AEO99 VERSION OF NEMS  

E-Print Network [OSTI]

Laboratory University of California Berkeley, CA 94720 and National Renewable Energy Laboratory 1617 Cole limitations on growth in capacity; these limitations include depletion of resources, costs of rapid of the other renewable technologies, such as solar thermal and photovoltaics (PV), our findings may

26

State energy price and expenditure report 1994  

SciTech Connect (OSTI)

The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 States and the District of Columbia and in aggregate for the United States. The price and expenditure estimates developed in the State Energy Price and Expenditure Data System (SEPEDS) are provided by energy source and economic sector and are published for the years 1970 through 1994. Consumption estimates used to calculate expenditures and the documentation for those estimates are taken from the State Energy Data Report 1994, Consumption Estimates (SEDR), published in October 1996. Expenditures are calculated by multiplying the price estimates by the consumption estimates, which are adjusted to remove process fuel; intermediate petroleum products; and other consumption that has no direct fuel costs, i.e., hydroelectric, geothermal, wind, solar, and photovoltaic energy sources. Documentation is included describing the development of price estimates, data sources, and calculation methods. 316 tabs.

NONE

1997-06-01T23:59:59.000Z

27

State energy price and expenditure report 1993  

SciTech Connect (OSTI)

The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 states and the District of Columbia and in aggregate for the US. The five economic sectors used in SEPER correspond to those used in SEDR and are residential, commercial, industrial, transportation, and electric utility. Documentation in appendices describe how the price estimates are developed, provide conversion factors for measures used in the energy analysis, and include a glossary. 65 tabs.

NONE

1995-12-01T23:59:59.000Z

28

State energy price and expenditure report 1992  

SciTech Connect (OSTI)

The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 States and the District of Columbia and in aggregate for the United States. The price and expenditure estimates are provided by energy source and economic sector and are published for the years 1970, 1980, and 1985 through 1992. Data for all years, 1970 through 1992, are available on personal computer diskettes.

Not Available

1994-12-01T23:59:59.000Z

29

Price discovery in energy markets  

Science Journals Connector (OSTI)

Abstract In this study, we empirically analyze the price discovery process in the futures and spot markets for crude oil, heating oil and natural gas using daily closing prices. We use two different information share measures that are based on the methods proposed by Gonzalo and Granger (1995) and Lien and Shrestha (2014). Both measures indicate that almost all the price discovery takes place in the futures markets for the heating oil and natural gas. However, for the crude oil, the price discovery takes place both in the futures and spot markets. As a whole, our study indicates that futures markets play an important role in the price discovery process.

Keshab Shrestha

2014-01-01T23:59:59.000Z

30

Managing Energy Price Risk with Derivatives  

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

Managing Energy Price Risk with Derivatives Managing Energy Price Risk with Derivatives Speaker(s): Douglas Hale Date: September 18, 2003 - 12:00pm Location: Bldg. 90 Seminar Host/Point of Contact: Joseph Eto Energy derivatives came into being with the deregulation of the petroleum and natural gas industries in the early 1980s. Although derivatives-forwards, futures and options-have been used in American agriculture since the mid-1800's to manage price risk, they were unnecessary in regulated energy industries. Deregulation revealed that oil, gas and electricity prices are exceptionally volatile. Companies were forced to cope with the uncertainty in energy prices; they latched onto derivatives as one tool for managing that risk. Enron's collapse brought energy derivatives to public attention. Following the derivative linked

31

State energy price and expenditure report, 1995  

SciTech Connect (OSTI)

The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates individually for the 50 States and the District of Columbia and in aggregate for the US. The estimates developed in the State Energy Price and Expenditure Data System (SEPEDS) are provided by energy source and economic sector and are published for the years 1970 through 1995. Data for all years are available on a CD-ROM and via Internet. Consumption estimates used to calculate expenditures and the documentation for those estimates are taken from the State Energy Data Report 1995, Consumption Estimates (SEDR), published in December 1997. Expenditures are calculated by multiplying the price estimates by the consumption estimates, which are adjusted to remove process fuel; intermediate petroleum products; and other consumption that has no direct fuel costs, i.e., hydroelectric, geothermal, wind, solar, and photovoltaic energy sources.

NONE

1998-08-01T23:59:59.000Z

32

Overview of NEMS-H2, Version 1.0  

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

NEMS-H2, Version 1.0 NEMS-H2, Version 1.0 Frances Wood OnLocation, Inc., Energy Systems Consulting (fwood@onlocationinc.com) January 26, 2006 OnLocation, Inc., Energy Systems Consulting 2 Today's Presentation * Overview of NEMS-H2 Structure * Current Status * New Hydrogen Market Module (HMM) * Transportation Module Modifications * Preliminary Test Runs * Looking Ahead to Next Phase OnLocation, Inc., Energy Systems Consulting 3 NEMS Overview * The National Energy Modeling System (NEMS) was developed and is maintained by EIA - Annual Energy Outlook projections - Congressional as well as agency requests * NEMS has also been used extensively outside of EIA - Various National Laboratories studies - National Commission on Energy Policy - Program offices within DOE for R&D benefits estimation * Modular structure allows each sector to be represented by

33

Energy prices and the adoption of energy-saving technology  

E-Print Network [OSTI]

This paper investigates the link between factor prices, technology and factor demands. I estimate the effect of price-induced technology adoption on energy demand in the U.S. manufacturing sector, using plant data from the ...

Linn, Joshua

2006-01-01T23:59:59.000Z

34

State Energy Price System: 1982 update  

SciTech Connect (OSTI)

The State Energy Price System (STEPS) contains estimates of energy prices for ten major fuels (electricity, natural gas, metallurgical coal, steam coal, distillate, motor gasoline, diesel, kerosene/jet fuel, residual fuel, and liquefied petroleum gas), by major end-use sectors (residential, commercial, industrial, transportation, and electric utility), and by state through 1982. Both physical unit prices and prices per million Btu are included in STEPS. Major changes in STEPS data base for 1981 and 1982 are described. The most significant changes in procedures for the updates occur in the residential sector distillate series and the residential sector kerosene series. All physical unit and Btu prices are shown with three significant digits instead of with four significant digits as shown in the original documentation. Details of these and other changes are contained in this report, along with the updated data files. 31 references, 65 tables.

Imhoff, K.L.; Fang, J.M.

1984-10-01T23:59:59.000Z

35

State energy price and expenditure report 1989  

SciTech Connect (OSTI)

The State Energy Price and Expenditure Report (SEPER) presents energy price and expenditure estimates for the 50 States, the District of Columbia, and the United States. The estimates are provided by energy source (e.g., petroleum, natural gas, coal, and electricity) and by major consuming or economic sector. This report is an update of the State Energy Price and Expenditure Report 1988 published in September 1990. Changes from the last report are summarized in a section of the documentation. Energy price and expenditure estimates are published for the years 1970, 1975, 1980, and 1985 through 1989. Documentation follows the tables and describes how the price estimates are developed, including sources of data, methods of estimation, and conversion factors applied. Consumption estimates used to calculate expenditures, and the documentation for those estimates, are from the State Energy Data Report, Consumption Estimates, 1960--1989 (SEDR), published in May 1991. Expenditures are calculated by multiplying the price estimates by the consumption estimates, adjusted to remove process fuel and intermediate product consumption. All expenditures are consumer expenditures, that is, they represent estimates of money directly spent by consumers to purchase energy, generally including taxes. 11 figs., 43 tabs.

Not Available

1991-09-30T23:59:59.000Z

36

Marginal Energy Price Report - July 1999  

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

J:\marginal\FinalDraftReport7-29-99.wpd J:\marginal\FinalDraftReport7-29-99.wpd DRAFT Marginal Energy Prices Report July 1999 U.S. Department of Energy Assistant Secretary, Energy Efficiency & Renewable Energy Office of Codes and Standards Washington, DC 20585 ii J:\marginal\FinalDraftReport7-29-99.wpd This document was prepared for the Department of Energy by staff members of the Lawrence Berkeley National Laboratory (LBNL) iii J:\marginal\FinalDraftReport7-29-99.wpd MARGINAL ENERGY PRICES Final Report Page Outline i Executive Summary 1 I. Background 2 II. Methods 4 III. Analysis and Results - Commercial 6 IV. Analysis and Results - Residential 12 V. Residential Heating Oil and Propane 19 VI. Taxes 22 Appendices Appendix 1. Tariffs Used in the Commercial Analysis 26

37

Marginal Energy Price Report - July 1999  

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

J:\marginal\FinalDraftReport7-29-99.wpd J:\marginal\FinalDraftReport7-29-99.wpd DRAFT Marginal Energy Prices Report July 1999 U.S. Department of Energy Assistant Secretary, Energy Efficiency & Renewable Energy Office of Codes and Standards Washington, DC 20585 ii J:\marginal\FinalDraftReport7-29-99.wpd This document was prepared for the Department of Energy by staff members of the Lawrence Berkeley National Laboratory (LBNL) iii J:\marginal\FinalDraftReport7-29-99.wpd MARGINAL ENERGY PRICES Final Report Page Outline i Executive Summary 1 I. Background 2 II. Methods 4 III. Analysis and Results - Commercial 6 IV. Analysis and Results - Residential 12 V. Residential Heating Oil and Propane 19 VI. Taxes 22 Appendices Appendix 1. Tariffs Used in the Commercial Analysis 26

38

State Energy Data System Price  

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

Appendix C provides metric and other physical conversion factors for measures used in energy analyses. Appendix D summarizes the changes in SEDS content made since the last...

39

Energy & Financial Markets: What Drives Crude Oil Prices? - Energy  

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

& Financial Markets - U.S. Energy Information Administration (EIA) & Financial Markets - U.S. Energy Information Administration (EIA) U.S. Energy Information Administration - EIA - Independent Statistics and Analysis Sources & Uses Petroleum & Other Liquids Crude oil, gasoline, heating oil, diesel, propane, and other liquids including biofuels and natural gas liquids. Natural Gas Exploration and reserves, storage, imports and exports, production, prices, sales. Electricity Sales, revenue and prices, power plants, fuel use, stocks, generation, trade, demand & emissions. Consumption & Efficiency Energy use in homes, commercial buildings, manufacturing, and transportation. Coal Reserves, production, prices, employ- ment and productivity, distribution, stocks, imports and exports. Renewable & Alternative Fuels

40

Appendix E: Other NEMS-MP results for the base case and scenarios.  

SciTech Connect (OSTI)

The NEMS-MP model generates numerous results for each run of a scenario. (This model is the integrated National Energy Modeling System [NEMS] version used for the Multi-Path Transportation Futures Study [MP].) This appendix examines additional findings beyond the primary results reported in the Multi-Path Transportation Futures Study: Vehicle Characterization and Scenario Analyses (Reference 1). These additional results are provided in order to help further illuminate some of the primary results. Specifically discussed in this appendix are: (1) Energy use results for light vehicles (LVs), including details about the underlying total vehicle miles traveled (VMT), the average vehicle fuel economy, and the volumes of the different fuels used; (2) Resource fuels and their use in the production of ethanol, hydrogen (H{sub 2}), and electricity; (3) Ethanol use in the scenarios (i.e., the ethanol consumption in E85 vs. other blends, the percent of travel by flex fuel vehicles on E85, etc.); (4) Relative availability of E85 and H2 stations; (5) Fuel prices; (6) Vehicle prices; and (7) Consumer savings. These results are discussed as follows: (1) The three scenarios (Mixed, (P)HEV & Ethanol, and H2 Success) when assuming vehicle prices developed through literature review; (2) The three scenarios with vehicle prices that incorporate the achievement of the U.S. Department of Energy (DOE) program vehicle cost goals; (3) The three scenarios with 'literature review' vehicle prices, plus vehicle subsidies; and (4) The three scenarios with 'program goals' vehicle prices, plus vehicle subsidies. The four versions or cases of each scenario are referred to as: Literature Review No Subsidies, Program Goals No Subsidies, Literature Review with Subsidies, and Program Goals with Subsidies. Two additional points must be made here. First, none of the results presented for LVs in this section include Class 2B trucks. Results for this class are included occasionally in Reference 1. They represent a small, though noticeable, segment of the 'LV plus 2B' market (e.g., a little more than 3% of today's energy use in that market). We generally do not include them in this discussion, simply because it requires additional effort to combine the NEMS-MP results for them with the results for the other LVs. (Where there is an exception, we will indicate so.) Second, where reference is made to E85, the ethanol content is actually 74%. The Energy Information Administration (EIA) assumes that, to address cold-starting issues, the percent of ethanol in E85 will vary seasonally. The EIA uses an annual average ethanol content of 74% in its forecasts. That assumption is maintained in the NEMS-MP scenario runs.

Plotkin, S. E.; Singh, M. K.; Energy Systems

2009-12-03T23:59:59.000Z

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

Table E6. Transportation Sector Energy Price Estimates, 2012  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

E6. Transportation Sector Energy Price Estimates, 2012 (Dollars per Million Btu) State Primary Energy Retail Electricity Total Energy Coal Natural Gas Petroleum Total Aviation...

42

Estimating Marginal Residential Energy Prices in the Analysis of Proposed  

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

Marginal Residential Energy Prices in the Analysis of Proposed Marginal Residential Energy Prices in the Analysis of Proposed Appliance Energy Efficiency Standards Title Estimating Marginal Residential Energy Prices in the Analysis of Proposed Appliance Energy Efficiency Standards Publication Type Report LBNL Report Number LBNL-44230 Year of Publication 2000 Authors Chaitkin, Stuart, James E. McMahon, Camilla Dunham Whitehead, Robert D. Van Buskirk, and James D. Lutz Document Number LBNL-44230 Date Published March 1 Publisher Lawrence Berkeley National Laboratory City Berkeley Abstract Use of marginal energy prices, instead of average energy prices, represents a theoretically valuable and challenging refinement to the usual life-cycle cost analysis conducted for proposed appliance energy efficiency standards. LBNL developed a method to estimate marginal residential energy prices using a regression analysis based on a nationally representative sample of actual consumer energy bills. Based on the 1997 Residential Energy Consumption Survey (RECS), national mean marginal electricity prices were estimated to be 2.5% less than average electricity prices in the summer and 10.0% less than average prices in the non-summer months. For natural gas, marginal prices were 4.4% less than average prices in the winter and 15.3% less than average prices in the non-winter months.

43

EIA - International Energy Outlook 2007-Low World Oil Price Projections  

Gasoline and Diesel Fuel Update (EIA)

Low World Oil Price Case Projections (1990-2030) Low World Oil Price Case Projections (1990-2030) International Energy Outlook 2007 Low World Oil Price Projections Tables (1990-2030) Formats Table Data Titles (1 to 12 complete) Low World Oil Price Projections Tables. Need help, contact the National Energy Information Center at 202-586-8800. Low World Oil Price Projections Tables. Need help, contact the National Energy Information Center at 202-586-8800. Table E1 World Total Energy Consumption by Region, Low World Oil Price Case Table E1. World Total Energy Consumption by Region. Need help, contact the National Energy Information Center at 202-586-8800. Table E2 World Total Energy Consumption by Region and Fuel, Low World Oil Price Case Table E2. World Total Energy Consumption by Region and Fuel. Need help, contact the National Energy Information Center at 202-586-8800.

44

NEMS Freight Transportation Module Improvement Study  

Reports and Publications (EIA)

The U.S. Energy Information Administration (EIA) contracted with IHS Global, Inc. (IHS) to analyze the relationship between the value of industrial output, physical output, and freight movement in the United States for use in updating analytic assumptions and modeling structure within the National Energy Modeling System (NEMS) freight transportation module, including forecasting methodologies and processes to identify possible alternative approaches that would improve multi-modal freight flow and fuel consumption estimation.

2015-01-01T23:59:59.000Z

45

Modelling spot and forward prices for energy companies  

E-Print Network [OSTI]

Modelling spot and forward prices for energy companies Dafydd Steele MSc Stochastics and Financial forward and spot prices for energy com- panies. The two main ways of modelling power prices are stochastic markets (coal, gas and power). The fundamental model is a mixed-integer programming stack model

Bhulai, Sandjai

46

Quality Guidelines for Energy System Studies: Fuel Pricing  

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

11212 National Energy Technology Laboratory Office of Program Performance and Benefits 2 Fuel Prices for Selected Feedstocks in NETL Studies Quality Guidelines for Energy System...

47

EIA - Annual Energy Outlook 2008 (Early Release)- Energy Prices Section  

Gasoline and Diesel Fuel Update (EIA)

Prices Prices Annual Energy Outlook 2008 (Early Release) Energy Prices EIA has raised the reference case path for world oil prices in AEO2008 (although the upward adjustment is smaller than the last major adjustment, introduced in AEO2006). In developing its current oil price outlook, EIA explicitly considered four factors: (1) expected growth in world liquids consumption; (2) the outlook for conventional oil production in countries outside the Organization of the Petroleum Exporting Countries (non-OPEC producers); (3) growth in unconventional liquids production; and (4) OPEC behavior. Global economic growth has been strong over the past few years, despite high oil prices; and it now appears that, in the mid-term, the cost of non-OPEC conventional oil and unconventional liquids will be higher than previously assumed. As a result, in the AEO2008 reference case, OPEC and non-OPEC production volumes and total world liquids production are similar to those in the AEO2007 reference case, but the oil prices are higher.4

48

BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation | Department  

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

BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation The Brattle Group was retained by Baltimore Gas & Electric Company (BGE) in December 2006 to assist in the design of a dynamic pricing pilot program to develop assessments of the likely impact of a variety of dynamic pricing programs on BGE residential customer load shapes. The residential pilot program, Smart Energy Pricing (SEP) Pilot, was subsequently approved by the Maryland Public Service Commission and successfully implemented in the summer of 2008. This report presents the results from the impact evaluation of the BGE's SEP Pilot in the summer of 2008. BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation More Documents & Publications

49

BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation | Department  

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

BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation The Brattle Group was retained by Baltimore Gas & Electric Company (BGE) in December 2006 to assist in the design of a dynamic pricing pilot program to develop assessments of the likely impact of a variety of dynamic pricing programs on BGE residential customer load shapes. The residential pilot program, Smart Energy Pricing (SEP) Pilot, was subsequently approved by the Maryland Public Service Commission and successfully implemented in the summer of 2008. This report presents the results from the impact evaluation of the BGE's SEP Pilot in the summer of 2008. BGE's Smart Energy Pricing Pilot Summer 2008 Impact Evaluation More Documents & Publications

50

Energy Spot Price Models and Spread Options Pricing Samuel Hikspoors and Sebastian Jaimungal a  

E-Print Network [OSTI]

). The world wide energy commodities markets have created a need for a deeper quan- titative understandingEnergy Spot Price Models and Spread Options Pricing Samuel Hikspoors and Sebastian Jaimungal a a Department of Statistics and Mathematical Finance Program, University of Toronto, 100 St. George Street

Jaimungal, Sebastian

51

Definition: Variable Peak Pricing | Open Energy Information  

Open Energy Info (EERE)

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

52

CHARTER, Price-Anderson Act Task Force | Department of Energy  

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

CHARTER, Price-Anderson Act Task Force CHARTER, Price-Anderson Act Task Force CHARTER, Price-Anderson Act Task Force This charter establishes the responsibilities of the Price-Anderson Act Task Force (Task Force). The Secretary of Energy has approved formation of this Task Force to review the need for the continuation or modification of the Price-Anderson Act, section 170 of the Atomic Energy Act of 1954, as amended (AEA), and to prepare a detailed report for submission to Congress as required by section 170p. of the AEA by August 1, 1998. CHARTER, Price-Anderson Act Task Force More Documents & Publications MEMORANDUM FOR THE SECRETARY Report to Congress on the Price-Anderson Act Appendix A. Notice of Inquiry: Preparation of Report to Congress on Price-Anderson Act. 62 Federal Register 68,272 (December 31, 1997)

53

Optimal Control of Residential Energy Storage Under Price Fluctuations  

E-Print Network [OSTI]

Optimal Control of Residential Energy Storage Under Price Fluctuations Peter van de ven Department habits. We formulate the problem of minimizing the cost of energy storage purchases subject to both user- gramming, energy storage, threshold policy. I. INTRODUCTION Wholesale energy prices exhibit significant

54

DOE Energy Technology Prices and Trends | Open Energy Information  

Open Energy Info (EERE)

DOE Energy Technology Prices and Trends DOE Energy Technology Prices and Trends Jump to: navigation, search Tool Summary LAUNCH TOOL Name: DOE Energy Technology Prices and Trends Agency/Company /Organization: United States Department of Energy Sector: Energy Focus Area: Renewable Energy, Non-renewable Energy Phase: Determine Baseline Topics: Market analysis, Technology characterizations Resource Type: Software/modeling tools User Interface: Website Website: energy.gov/prices-trends Country: United States Cost: Free Northern America Coordinates: 37.09024°, -95.712891° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.09024,"lon":-95.712891,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

55

Sustainably Priced Energy Enterprise Development (SPEED) Goals | Department  

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

Sustainably Priced Energy Enterprise Development (SPEED) Goals Sustainably Priced Energy Enterprise Development (SPEED) Goals Sustainably Priced Energy Enterprise Development (SPEED) Goals < Back Eligibility Investor-Owned Utility Municipal Utility Rural Electric Cooperative Savings Category Bioenergy Alternative Fuel Vehicles Hydrogen & Fuel Cells Buying & Making Electricity Water Solar Heating & Cooling Water Heating Wind Program Info State Vermont Program Type Renewables Portfolio Standard Provider Vermont Public Service Board Vermont's Sustainably Priced Energy Enterprise Development (SPEED) Program was created by legislation in 2005 to promote renewable energy development. The SPEED program itself is not a renewable portfolio goal or standard. However, if the Vermont Public Service Board (PSB) determines that the

56

DOE Gasoline Price Watch Website and Hotline | Department of Energy  

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

Gasoline Price Watch Website and Hotline Gasoline Price Watch Website and Hotline DOE Gasoline Price Watch Website and Hotline April 20, 2006 - 12:26pm Addthis WASHINGTON, DC - Secretary of Energy Samuel W. Bodman today is reminding consumers about the Department of Energy's (DOE) gasoline price reporting system. Consumers can report activity at local gasoline filling stations that they believe may constitute "gouging" or "price fixing" by visiting gaswatch.energy.gov/. "There are many legitimate factors influencing the price consumers are paying at the pump, including growing demand, the high price of crude oil, the lingering effects of last summer's hurricanes on our refining sector and the regular transition of fuel blends as we head into the summer," said Secretary Bodman. "And while the majority of local merchants are fair and

57

Energy Information Administration (EIA) - High World Oil Price Case  

Gasoline and Diesel Fuel Update (EIA)

High World Oil Price Case Projections Tables (1990-2030) High World Oil Price Case Projections Tables (1990-2030) International Energy Outlook 2007 High World Oil Price Case Projections Tables (1990-2030) Formats Data Table Titles (1 to 12 complete) High World Oil Price Case Projections Tables. Need help, contact the National Energy Information Center at 202-586-8800. High World Oil Price Case Tables. Need help, contact the National Energy Information Center at 202-586-8800. Table D1 World Total Primary Energy Consumption by Region Table D1. World Total Primary Energy Consumption by Region. Need help, contact the National Energy Information Center at 202-586-8800. Table D2 World Total Energy Consumption by Region and Fuel Table D2. World total Energy Consumption by Region and Fuel. Need help, contact the National Energy Information Center at 202-586-8800.

58

Public Comment re Price-Anderson Act | Department of Energy  

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

Comment re Price-Anderson Act Comment re Price-Anderson Act Public Comment re Price-Anderson Act Preparation of Report to Congress on Price-Anderson Act. The Price Anderson Act should be eliminated. The Price Anderson Act assumes that the encouragement and growth of the commercial nuclear industry is in the public interest. It is not. Rational evaluation of the commercial nuclear industry forces the conclusion that the Price Anderson Act simply shields the commercial nuclear industry from costs that it would otherwise, in a fair market setting, be forced to internalize and pay. Price Anderson amounts to corporate welfare that has already caused a massive disruption of energy markets, and the abusiveness enabled by this welfare system threatens to dislodge society from its ecological as

59

Definition: Critical Peak Pricing | Open Energy Information  

Open Energy Info (EERE)

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

60

Increased energy prices: energy savings and equity aspects. Final report  

SciTech Connect (OSTI)

A mathematical model has been developed which approximates the reduction in a household's total energy consumption in response to higher energy prices and different rebate schemes. This model is based on the assumption that energy consumption is a function of a household's real income, prices of different commodities and energy intensities. The amount of energy saved and the change in real expenditure of a household has been calculated for four tax rates; 50%, 100%, 224% and 400%, and five rebate schemes; one regressive, two progressive, one income distribution preserving and the flat per capita rebate. The results indicate that, for a given tax rate, the choice of rebate scheme does not significantly affect the amount of energy conserved by the households. However, the effect of different rebate schemes on a household's real expenditure could be dramatically different.

Herendeen, R.A.

1983-06-01T23:59:59.000Z

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

Definition: Dynamic Pricing Program | Open Energy Information  

Open Energy Info (EERE)

Pricing Program Pricing Program Jump to: navigation, search Dictionary.png Dynamic Pricing Program Dynamic pricing refers to the family of rates that offer customers time-varying electricity prices on a day-ahead or real-time basis.[1] Related Terms electricity generation References ↑ https://www.smartgrid.gov/category/technology/dynamic_pricing_program [[C LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ategory: Smart Grid Definitionssmart grid,smart grid, |Template:BASEPAGENAME]]smart grid,smart grid, Retrieved from "http://en.openei.org/w/index.php?title=Definition:Dynamic_Pricing_Program&oldid=502620" Category: Definitions What links here Related changes Special pages Printable version Permanent link Browse properties 429 Throttled (bot load)

62

State energy price system. Volume I: overview and technical documentation  

SciTech Connect (OSTI)

This study utilizes existing data sources and previous analyses of state-level energy prices to develop consistent state-level energy prices series by fuel type and by end-use sector. The fuels are electricity, natural gas, coal, distillate fuel oil, motor gasoline, diesel, kerosene, jet fuel, residual fuel, and liquefied petroleum gas. The end-use sectors are residential, commercial, industrial, transportation, and electric utility. Based upon an evaluation of existing data sources, recommendations were formulated on the feasible approaches for developing a consistent state energy price series. The data series were compiled based upon the approaches approved after a formal EIA review. Detailed documentation was provided, including annual updating procedures. Recommendations were formulated for future improvements in the collection of data or in data processing. Generally, the geographical coverage includes the 50 states and the District of Columbia. Information on state-level energy use was generally taken from the State Energy Data System (SEDS). Corresponding average US prices are also developed using volumes reported in SEDS. To the extent possible, the prices developed are quantity weighted average retail prices. Both a Btu price series and a physical unit price series are developed for each fuel. The period covered by the data series is 1970 through 1980 for most fuels, though prices for electricity and natural gas extend back to 1960. (PSB)

Fang, J.M.; Nieves, L.A.; Sherman, K.L.; Hood, L.J.

1982-06-01T23:59:59.000Z

63

Energy prices and energy intensity in China : a structural decomposition analysis and econometric study  

E-Print Network [OSTI]

Since the start of its economic reforms in 1978, China's energy prices relative to other prices have increased. At the same time, its energy intensity, i.e., physical energy consumption per unit of Gross Domestic Product ...

Shi, Xiaoyu, M.C.P. Massachusetts Institute of Technology

2005-01-01T23:59:59.000Z

64

Energy prices and energy intensity in China : a structural decomposition analysis and econometrics study  

E-Print Network [OSTI]

Since the start of its economic reforms in 1978, China's energy prices relative to other prices have increased. At the same time, its energy intensity, i.e., energy consumption per unit of Gross Domestic Product (GDP), has ...

Shi, Xiaoyu

2006-01-01T23:59:59.000Z

65

Annual Energy Outlook 2007 - Low Price Case Tables  

Gasoline and Diesel Fuel Update (EIA)

4-2030) 4-2030) Annual Energy Outlook 2007 with Projections to 2030 MS Excel Viewer Spreadsheets are provided in Excel Low Price Case Tables (2004-2030) Table Title Formats Summary Low Price Case Tables Low Price Case Tables Table 1. Total Energy Supply and Disposition Summary Table 2. Energy Consumption by Sector and Source Table 3. Energy Prices by Sector and Source Table 4. Residential Sector Key Indicators and Consumption Table 5. Commercial Sector Indicators and Consumption Table 6. Industrial Sector Key Indicators and Consumption Table 7. Transportation Sector Key Indicators and Delivered Energy Consumption Table 8. Electricity Supply, Disposition, Prices, and Emissions Table 9. Electricity Generating Capacity Table 10. Electricity Trade Table 11. Petroleum Supply and Disposition Balance

66

Annual Energy Outlook 2009 - High Price Case Tables  

Gasoline and Diesel Fuel Update (EIA)

6-2030) 6-2030) Annual Energy Outlook 2009 with Projections to 2030 XLS GIF Spreadsheets are provided in Excel High Price Case Tables (2006-2030) Table Title Formats Summary High Price Case Tables PDF GIF High Price Case Tables XLS GIF Table 1. Total Energy Supply and Disposition Summary XLS GIF Table 2. Energy Consumption by Sector and Source XLS GIF Table 3. Energy Prices by Sector and Source XLS GIF Table 4. Residential Sector Key Indicators and Consumption XLS GIF Table 5. Commercial Sector Indicators and Consumption XLS GIF Table 6. Industrial Sector Key Indicators and Consumption XLS GIF Table 7. Transportation Sector Key Indicators and Delivered Energy Consumption XLS GIF Table 8. Electricity Supply, Disposition, Prices, and Emissions XLS GIF Table 9. Electricity Generating Capacity

67

Price Elasticities for Energy Use in Buildings of the United...  

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

Price Elasticities for Energy Use in Buildings of the United States October 2014 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S....

68

Pricing Energy in a Multi-Utility Market  

Science Journals Connector (OSTI)

We present a solution to the problem of tariff design for an energy supplier (utility). The tariffs for electricity ... prices for trading electricity on a day-ahead market like the European Energy Exchange (EEX)...

Markus Franke; Andreas Kamper; Anke Eer

2007-01-01T23:59:59.000Z

69

http://www.energy.gov/media/F...Biofuels_Lower_Gas_Prices.pdf...  

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

http:www.energy.govmediaF...BiofuelsLowerGasPrices.pdf http:www.energy.govmediaF...BiofuelsLowerGasPrices.pdf http:www.energy.govmediaF...BiofuelsLowerGasPrice...

70

Lessie B. Price | Department of Energy  

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

Lessie B. Price Lessie B. Price About Us Lessie B. Price - EMAB Board Member Lessie Price has served as an elected member of the Aiken City Council for the past 24 years and was the first female to run and be elected to this post in the City's history. She has also served as Mayor Pro-Tempore of Aiken and was elected by her peers across the State of South Carolina to serve as President of the Municipal Association of South Carolina, representing 274 towns and cities in the State. In addition to her public service on the Aiken City Council, Ms. Price has 40 years experience at Savannah River Site in Human Resources, Organizational & Individual Development & Training Management. She currently serves as Manager of Government Affairs in the Public Affairs Office for URS Corporation. URS employs more than 45,000 employees in 34

71

Price County, Wisconsin: Energy Resources | Open Energy Information  

Open Energy Info (EERE)

Price County, Wisconsin: Energy Resources Price County, Wisconsin: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 45.7511666°, -90.4622144° 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":45.7511666,"lon":-90.4622144,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

72

Energy Price Indices and Discount Factors for Life-Cycle Cost...  

Office of Environmental Management (EM)

0 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2010 Report describes the 2010 edition of energy price indices and discount factors for performing...

73

An Empirical Pricing Model for Renewable Energy Source  

Science Journals Connector (OSTI)

The characteristics of the renewable energy source make itself the Chinese energy strategy and the most important way to develop the low carbon mode. Therefore, the renewable energy is the only way for China to resolve the energy clearance and sustainable ... Keywords: pricing model, renewable energy source, marginal cost analysis

Bai Xueyan

2012-05-01T23:59:59.000Z

74

The price of energy efficiency in the Spanish car market  

Science Journals Connector (OSTI)

Abstract Due to climate change, energy dependence and other energy-related issues, most developed countries are attempting to reduce fossil-fuel use in the transport sector. Accordingly, there are several instruments that have been in place for many years, such as mandatory design standards, taxes on fuels, car purchase and ownership, and energy efficiency labels. Yet it is still not clear whether consumers value energy efficiency as a characteristic of vehicles. In this paper we use the European labelling system for light vehicles, which classifies automobiles according to their relative fuel consumption levels, as a novel, alternative indicator for energy efficiency. Moreover, we use a unique database that incorporates official commercial prices along with prices obtained through mystery shopping at a selection of Spanish car retailers. We apply the hedonic price method to this database to estimate the price functions for vehicles and thereby obtain the marginal price of vehicles rated highly in terms of energy efficiency. Our results show that vehicles labelled A and B are sold at prices 3 to 5.9 percent higher than those with similar characteristics but lower energy-efficiency labels.

Ibon Galarraga; Ana Ramos; Josu Lucas; Xavier Labandeira

2014-01-01T23:59:59.000Z

75

Energy and Financial Markets Overview: Crude Oil Price Formation  

Gasoline and Diesel Fuel Update (EIA)

Richard Newell, Administrator Richard Newell, Administrator May 5, 2011 Energy and Financial Markets Overview: Crude Oil Price Formation EIA's Energy and Financial Markets Initiative 2 Richard Newell, May 5, 2011 * Collection of critical energy information to improve market transparency - improved petroleum storage capacity data - other improvements to data quality and coverage * Analysis of energy and financial market dynamics to improve understanding of what drives energy prices - internal analysis and sponsorship of external research * Outreach with other Federal agencies, experts, and the public - expert workshops - public sessions at EIA's energy conferences - solicitation of public comment on EIA's data collections

76

NEMS Freight Transportation Module Improvement Study  

Gasoline and Diesel Fuel Update (EIA)

and forecast accuracy. Challenges might include new skill development within EIA, contracting for additional commercial services, and possibly altering the manner in which NEMS...

77

Transmission Pricing of Distributed Multilateral Energy Transactions to Ensure System Security and Guide Economic Dispatch  

E-Print Network [OSTI]

Transmission Pricing of Distributed Multilateral Energy Transactions to Ensure System Security and Guide Economic Dispatch...

Ilic, Marija; Hsieh, Eric; Remanan, Prasad

2004-06-16T23:59:59.000Z

78

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect (OSTI)

The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-07-01T23:59:59.000Z

79

Designing pricing strategies for coordination of networked distributed energy resources  

E-Print Network [OSTI]

simulations. Keywords: Power systems, distributed energy resources, energy market, distributed control, gameDesigning pricing strategies for coordination of networked distributed energy resources Bahman, Urbana-Champaign, USA, basar1@illinois.edu, aledan@illinois.edu. Abstract: We study the problem

Liberzon, Daniel

80

Price Electric Coop Inc | Open Energy Information  

Open Energy Info (EERE)

Price Electric Coop Inc Price Electric Coop Inc Place Wisconsin Utility Id 15356 Utility Location Yes Ownership C NERC Location MRO NERC MRO Yes ISO MISO Yes Activity Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Commercial-Peak Alert Commercial Commercial-With Demand-Three Phase Industrial Commercial-Without Demand-Single Phase Commercial Commercial-Without Demand-Three Phase Commercial Dual Fuel Commercial Lighting 100 Watt Outdoor Light Lighting Lighting 250 Watt Street Light Lighting Residential, Seasonal, and Farm Residential Average Rates Residential: $0.1650/kWh

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

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously derived supply curves, initial price paths and international regional supply and demand levels into NEMS. These quantities are not modeled directly in NEMS because NEMS is not an international model. Previous versions of the IEM adjusted these quantities after reading in initial values. In an attempt to more closely integrate the AEO2007 with the IEO2006 and the STEO some functionality was removed from the IEM. More analyst time was devoted to analyzing price relationships between marker crude oils and refined products. A new exogenous oil supply model, Generate World Oil Balances (GWOB), was also developed to incorporate actual investment occurring in the international oil market through 2015

82

Public comment on Price-Anderson Act | Department of Energy  

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

Public comment on Price-Anderson Act Public comment on Price-Anderson Act Public comment on Price-Anderson Act COMMENTS by OHM REMEDIATION SERVICES CORP on 62 CFR 68272, Re: Department of Energy, Office of General Counsel; Preparation of Report to Congress on Price-Anderson Act. OHM Remediation Services Corp. ("OHM") is a diversified services firm for government and private sector clients and provides a broad range of outsourced services including environmental remediation and project, program and construction management services. OHM is submitting comments, questions and requests for clarification to the DOE because the continued viability of the Act is crucial to OHM's core business. However, the Act needs to be modified to reflect the current state of the nuclear industry which currently has a stronger focus on decommissioning and

83

Public comment on Price-Anderson Act | Department of Energy  

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

Public comment on Price-Anderson Act Public comment on Price-Anderson Act Public comment on Price-Anderson Act COMMENTS by OHM REMEDIATION SERVICES CORP on 62 CFR 68272, Re: Department of Energy, Office of General Counsel; Preparation of Report to Congress on Price-Anderson Act. OHM Remediation Services Corp. ("OHM") is a diversified services firm for government and private sector clients and provides a broad range of outsourced services including environmental remediation and project, program and construction management services. OHM is submitting comments, questions and requests for clarification to the DOE because the continued viability of the Act is crucial to OHM's core business. However, the Act needs to be modified to reflect the current state of the nuclear industry which currently has a stronger focus on decommissioning and

84

Energy Prices and the Expansion of World Trade  

E-Print Network [OSTI]

The oil shocks of the 1970s coincided with a number of economic disturbances. However, it has been difficult to develop models where oil shocks have a quantitatively important impact on the economy. In this paper, I show that the disturbances in transportation caused by the oil shocks can significantly affect the economy. I argue that changes in energy prices were responsible for a worldwide slowdown in the growth of trade and may help explain the apparent change in the price-trade elasticity. While tariffs have fallen steadily since 1970, trade growth slowed in the mid-1970s and has grown rapidly since the mid-1980s. In a standard trade model, this pattern implies that the price-import elasticity increased sharply in the mid-1980s. In this paper, I argue that the oil crises of the 1970s led to higher transportation costs. In 1986 energy prices fell to their pre-crisis level, reducing transportation costs and by extension trade barriers. I present a trade model with an energy using transportation sector. In model simulations, I show that total trade costs (transportation cost plus tariffs) are constant from 1974 to 1982. Once transportation costs are accounted for, the price-import elasticity no longer needs to radically change. I also show that trade expansion since 1960 is 50 percent higher in a standard trade model that includes a transportation sector compared to one that does not.

Benjamin Bridgman

2008-01-01T23:59:59.000Z

85

Price Municipal Corporation | Open Energy Information  

Open Energy Info (EERE)

Municipal Corporation Municipal Corporation Jump to: navigation, search Name Price Municipal Corporation Place Utah Utility Id 14198 Utility Location Yes Ownership M NERC Location WECC NERC WECC Yes Activity Distribution Yes Activity Buying Distribution Yes References EIA Form EIA-861 Final Data File for 2010 - File1_a[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Utility Rate Schedules Grid-background.png Electrical substation delivery discount Commercial General Service- Large Industrial General service-small Industrial Residential Residential Security area lighting-250 watts and up Lighting Security area lighting-Less than 250 watts Lighting Special service-Non profit charitable organization Commercial

86

EIA-Assumptions to the Annual Energy Outlook - International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2007 International Energy Module The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously derived supply curves, initial price paths and international regional supply and demand levels into NEMS. These quantities are not modeled directly in NEMS because NEMS is not an international model. Previous versions of the IEM adjusted these quantities after reading in initial values. In an attempt to more closely integrate the AEO2007 with the IEO2006 and the STEO some functionality was removed from the IEM. More analyst time was devoted to analyzing price relationships between marker crude oils and refined products. A new exogenous oil supply model, Generate World Oil Balances (GWOB), was also developed to incorporate actual investment occurring in the international oil market through 2015 and resource assumptions through 2030. The GWOB model provides annual country level oil production detail for eight conventional and unconventional oils.

87

Effect of Energy Efficiency Standards on Natural Gas Prices  

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

Energy Efficiency Standards on Natural Gas Prices Energy Efficiency Standards on Natural Gas Prices Title Effect of Energy Efficiency Standards on Natural Gas Prices Publication Type Report LBNL Report Number LBNL-4994E Year of Publication 2011 Authors Carnall, Michael, Larry L. Dale, and Alexander B. Lekov Subsidiary Authors Energy Analysis Department Document Number LBNL-4994E Pagination 37 Date Published July 1 Publisher Lawrence Berkeley National Laboratory City Berkeley ISBN Number LBNL-4994E Abstract Requiring home appliances to meet fuel efficiency standards can reduce the fuel usage, fuel price, and the life-cycle cost of these appliances (Meyers 2005). Although this seems to be an unambiguous benefit to society, it is sometimes asserted, among other things, that the reduction in consumers' expenditures is obtained at the cost of reductions in the profit of fuel producers and owners of mineral rights and is thus a transfer from one sector of the economy to another, rather than a net benefit to society as a whole (Wiser 2005). In an attempt to resolve this question, we estimate the magnitude of the effects of a standard on the primary sectors affected by the standard and determine how much of the benefits are transfers from other sectors.

88

Subject: Cost and Price Analysis | Department of Energy  

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

Subject: Cost and Price Analysis Subject: Cost and Price Analysis Subject: Cost and Price Analysis More Documents & Publications Acquisition Letter 2009-03 Acquisition...

89

Less platinum means lower prices for autos | Department of Energy  

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

Less platinum means lower prices for autos Less platinum means lower prices for autos Less platinum means lower prices for autos January 21, 2010 - 3:29pm Addthis Joshua DeLung You might wear a platinum wedding band, but tucked away in the guts of a car probably isn't where Americans prefer this pricey, precious metallic element to be. Luckily, researchers at 3M's Fuel Cell Component's Program in St. Paul, Minnesota have us covered. 3M has developed technology that will reduce the amount of platinum necessary in a fuel cell system by using nano-catalyst particles that actually make surface atoms more efficient at producing energy. Platinum is needed in fuel cells because no other metals are even close to being as effective at speeding up chemical reactions to make power. 3M is among a handful of fuel cell system suppliers in the U.S., and these advancements

90

Impacts of high energy prices on long-term energy-economic scenarios for Germany  

E-Print Network [OSTI]

Impacts of high energy prices on long-term energy-economic scenarios for Germany Volker Krey1 , Dag and Technology Evaluation (IEF-STE), 52425 Jülich, Germany 2) DIW Berlin, Königin-Luise-Str. 5, 14195 Berlin, Germany 3) ?ko-Institut, Novalisstr. 10, 10115 Berlin, Germany Abstract Prices of oil and other fossil

91

EIA: High Oil Prices, GHG Controls Would Help Clean Energy Grow...  

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

EIA: High Oil Prices, GHG Controls Would Help Clean Energy Grow EIA: High Oil Prices, GHG Controls Would Help Clean Energy Grow April 1, 2009 - 11:35am Addthis The growth of...

92

Automakers' Short-Run Responses to Changing Gasoline Prices and the Implications for Energy Policy  

E-Print Network [OSTI]

Automakers' Short-Run Responses to Changing Gasoline Prices and the Implications for Energy Policy as if consumers respond to gasoline prices. We estimate a selection-corrected regression equation and exploit operating costs between vehicles. Keywords: automobile prices, gasoline prices, environmental policy JEL

Edwards, Paul N.

93

The National Energy Modeling System: An Overview 2000 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period through 2020. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. NEMS was designed and implemented by the Energy Information Administration (EIA) of the U.S. Department of Energy (DOE). National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period through 2020. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. NEMS was designed and implemented by the Energy Information Administration (EIA) of the U.S. Department of Energy (DOE). The National Energy Modeling System: An Overview presents an overview of the structure and methodology of NEMS and each of its components. This chapter provides a description of the design and objectives of the system, followed by a chapter on the overall modeling structure and solution algorithm. The remainder of the report summarizes the methodology and scope of the component modules of NEMS. The model descriptions are intended for readers familiar with terminology from economics, operations research, and energy modeling. More detailed model documentation reports for all the NEMS modules are also available from EIA (Appendix, “Bibliography”).

94

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.  

E-Print Network [OSTI]

contractual, energy and market-related characteristics. Alocal-level wholesale energy market price dynamics and localof the relationship between energy factor markets, leasing

Jaffee, Dwight M.; Stanton, Richard; Wallace, Nancy E.

2010-01-01T23:59:59.000Z

95

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.  

E-Print Network [OSTI]

contractual, energy and market-related characteristics. Alocal-level wholesale energy market price dynamics and localfunction of local energy-market and weather characteristics

Jaffee, Dwight; Stanton, Richard; Wallace, Nancy

2012-01-01T23:59:59.000Z

96

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.  

E-Print Network [OSTI]

contractual, energy and market-related characteristics. Afunction of local energy-market and weather characteristicslocal-level wholesale energy market price dynamics and local

Jaffee, Dwight; Stanton, Richard; Wallace, Nancy

2012-01-01T23:59:59.000Z

97

Investigation of residential central air conditioning load shapes in NEMS  

SciTech Connect (OSTI)

This memo explains what Berkeley Lab has learned about how the residential central air-conditioning (CAC) end use is represented in the National Energy Modeling System (NEMS). NEMS is an energy model maintained by the Energy Information Administration (EIA) that is routinely used in analysis of energy efficiency standards for residential appliances. As part of analyzing utility and environmental impacts related to the federal rulemaking for residential CAC, lower-than-expected peak utility results prompted Berkeley Lab to investigate the input load shapes that characterize the peaky CAC end use and the submodule that treats load demand response. Investigations enabled a through understanding of the methodology by which hourly load profiles are input to the model and how the model is structured to respond to peak demand. Notably, it was discovered that NEMS was using an October-peaking load shape to represent residential space cooling, which suppressed peak effects to levels lower than expected. An apparent scaling down of the annual load within the load-demand submodule was found, another significant suppressor of the peak impacts. EIA promptly responded to Berkeley Lab's discoveries by updating numerous load shapes for the AEO2002 version of NEMS; EIA is still studying the scaling issue. As a result of this work, it was concluded that Berkeley Lab's customary end-use decrement approach was the most defensible way for Berkeley Lab to perform the recent CAC utility impact analysis. This approach was applied in conjunction with the updated AEO2002 load shapes to perform last year's published rulemaking analysis. Berkeley Lab experimented with several alternative approaches, including modifying the CAC efficiency level, but determined that these did not sufficiently improve the robustness of the method or results to warrant their implementation. Work in this area will continue in preparation for upcoming rulemakings for the other peak coincident end uses, commercial air conditioning and distribution transformers.

Hamachi LaCommare, Kristina; Marnay, Chris; Gumerman, Etan; Chan, Peter; Rosenquist, Greg; Osborn, Julie

2002-05-01T23:59:59.000Z

98

China Lingbo Kong, Lynn Price, Ali Hasanbeigi China Energy Group  

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

Potential for reducing paper mill Potential for reducing paper mill energy use and carbon dioxide emissions through plant-wide energy audits: A case study in China Lingbo Kong, Lynn Price, Ali Hasanbeigi China Energy Group Environmental Energy Technologies Division Lawrence Berkeley National Laboratory Huanbin Liu, Jigeng Li State Key Laboratory of Pulp and Paper Engineering, South China University of Technology Reprint version of journal article published in "Applied Energy", Volume 102, February 2013 March 2013 This work was supported by the China Sustainable Energy Program of the Energy Foundation through the U.S. Department of Energy under Contract No. DE-AC02- 05CH11231. ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY

99

Analysis and Representation of Miscellaneous Electric Loads in NEMS -  

Gasoline and Diesel Fuel Update (EIA)

Analysis and Representation of Miscellaneous Electric Loads in NEMS Analysis and Representation of Miscellaneous Electric Loads in NEMS Release date: January 6, 2014 Miscellaneous Electric Loads (MELs) comprise a growing portion of delivered energy consumption in residential and commercial buildings. Recently, the growth of MELs has offset some of the efficiency gains made through technology improvements and standards in major end uses such as space conditioning, lighting, and water heating. Miscellaneous end uses, including televisions, personal computers, security systems, data center servers, and many other devices, have continued to penetrate into building-related market segments. Part of this proliferation of devices and equipment can be attributed to increased service demand for entertainment, computing, and convenience appliances.

100

The Price-Independent Trend in Energy Efficiency in Canada and the Potential Influence of Non-Price Policies  

E-Print Network [OSTI]

Index (AEEI) measures the rate at which energy per unit of output (E/GDP) changes over time, with energy, suggesting that energy intensity will decline by .7% per year. At this rate, Canada will not achieve its 2010The Price-Independent Trend in Energy Efficiency in Canada and the Potential Influence of Non

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

The impact of energy prices on the volatility of ethanol prices and the role of gasoline emissions  

Science Journals Connector (OSTI)

Abstract The contribution of Renewable Energy Resources is vital for a country?s economic growth by providing high efficiency in energy, as well as an effective tool for the confrontation of climate change. In particular, concerning the EU, an increase in the consumption of Renewable Energy Resources as a proportion of the total energy consumption by its member states was set as an objective until 2020. Ethanol has been widely used as a substitute to conventional energy like gasoline and oil. The present paper surveys the role of alternative energy prices and gas emissions in the formation of the ethanol prices. The results of the empirical survey confirmed the existence of a sole relationship among the variables employed. According to the results obtained, an increase in the volume of emissions or in gasoline prices results in an increase in ethanol prices while the opposite is confirmed in the case of crude oil. ?he elasticity of ethanol prices to the increase of the emissions is another result worth mentioning, indicative of the significant role of the emissions in the formation of ethanol prices.

E. Zafeiriou; G. Arabatzis; S. Tampakis; K. Soutsas

2014-01-01T23:59:59.000Z

102

Microsoft PowerPoint - Arseneau_EIA_ShortTermDriversofEnergyPrices.ppt [Compatibility Mode]  

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

SHORT-TERM ENERGY PRICES: SHORT-TERM ENERGY PRICES: WHAT DRIVERS MATTER MOST? DAVID M. ARSENEAU FEDERAL RESERVE BOARD U.S. Energy Information Administration & Johns Hopkins University - SAIS FEDERAL RESERVE BOARD Johns Hopkins University SAIS 2010 Energy Conference Washington, D.C., U.S.A. A il 6 2010 April 6, 2010 BROAD COMMODITY PRICES SINCE 2000 Short-term Energy Prices: What Drivers Matters Most? BROAD COMMODITY PRICES SINCE 2000 April 6, 2010 Seminar: 2010 EIA/SAIS Energy Conference 2 A (GROSSLY OVERSIMPLIFIED) FRAMEWORK Short-term Energy Prices: What Drivers Matters Most? A (GROSSLY OVERSIMPLIFIED) FRAMEWORK ...  Two candidate explanations:  "Fundamentals"  Fundamentals  Trend price movements appear broadly interpretable through lens of fundamental market developments...

103

NREL: News - Solar Energy Prices See Double-digit Declines in...  

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

714 Solar Energy Prices See Double-digit Declines in 2013; Trend Expected to Continue PV pricing to drop another 3 - 12 percent in 2014 October 20, 2014 Distributed solar...

104

Energy and Financial Markets Overview: Crude Oil Price Formation  

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

John Maples John Maples 2011 EIA Energy Conference April 26, 2011 Transportation and the Environment Light-duty vehicle combined Corporate Average Fuel Economy Standards (CAFE) in three cases, 2005-2035 2 0 20 40 60 80 2005 2010 2015 2020 2025 2030 2035 miles per gallon Source: EIA, Annual Energy Outlook 2011 CAFE6 CAFE3 Reference John Maples, April 26, 2011 Light-duty vehicle delivered energy consumption and total transportation carbon dioxide emissions, 2005-2035 3 0 5 10 15 20 2005 2010 2015 2020 2025 2030 2035 Reference CAFE3 CAFE6 quadrillion Btu 0 500 1000 1500 2000 2500 2005 2010 2015 2020 2025 2030 2035 million metric tons carbon dioxide equivalent Source: EIA, Annual Energy Outlook 2011 John Maples, April 26, 2011 Distribution of new light-duty vehicle sales by price, 2010 and 2025 (2009$) 4 Source: EIA, Annual Energy Outlook 2011

105

Energy policies in a macroeconomic model: an analysis of energy taxes when oil prices decline  

Science Journals Connector (OSTI)

Economic planners and policy-makers have been acquainted, in the last fifteen years, with unanticipated oil price increases. The energy economics literature is abundant ... rules that would mitigate the negative ...

P. Capros; P. Karadeloglou; G. Mentzas

1992-01-01T23:59:59.000Z

106

A Probability Theory Based Price Determination Framework for Utility Companies in an Oligopolistic Energy Market  

E-Print Network [OSTI]

Energy Market Tiansong Cui, Yanzhi Wang, Xue Lin, Shahin Nazarian, and Massoud Pedram University to determine the energy price for utility companies in an oligopolistic energy market. At the beginning of each non-cooperative utility companies that offer time-of-use dependent energy prices to energy consumers

Pedram, Massoud

107

Greenhouse Gas Initiatives - Analysis of McCain-Lieberman Bill S.280 The ClimateStewardship and Innovation Act of 2007 Using the National Energy Modeling System  

E-Print Network [OSTI]

assumptions to SAIC-NEMS. Some key technical, societal and political uncertainties include: (1) the number of new nuclear generation builds, (2) availability of renewable generation (bio-power and wind power), (3) the technological development...) Installed Electric Generating Capacity, (3) Produced Electric Energy, (4) Prices of CO 2 Offsets and Permits (5) Natural Gas Prices, (6) Electricity Prices, and (7) Other Energy Prices. While the study ran seven scenarios for each focus area, two...

Ellsworth, C.

2008-01-01T23:59:59.000Z

108

EIA-Annual Energy Outlook 2010 - Low Oil PriceTables  

Gasoline and Diesel Fuel Update (EIA)

Oil Price Tables (2007-2035) Oil Price Tables (2007-2035) Annual Energy Outlook 2010 Main Low Oil Price Tables (2007- 2035) Table Title Formats Summary Low Oil Price Case Tables PDF Gif Year-by-Year Low Oil Price Case Tables Excel Gif Table 1. Total Energy Supply and Disposition Summary Excel Gif Table 2. Energy Consumption by Sector and Source Excel Gif Table 3. Energy Prices by Sector and Source Excel Gif Table 4. Residential Sector Key Indicators and Consumption Excel Gif Table 5. Commercial Sector Indicators and Consumption Excel Gif Table 6. Industrial Sector Key Indicators and Consumption Excel Gif Table 7. Transportation Sector Key Indicators and Delivered Energy Consumption Excel Gif Table 8. Electricity Supply, Disposition, Prices, and Emissions Excel Gif Table 9. Electricity Generating Capacity

109

The National Energy Modeling System: An Overview 1998 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

INTRODUCTION INTRODUCTION blueball.gif (205 bytes) Purpose of NEMS blueball.gif (205 bytes) Representations of Energy Market blueball.gif (205 bytes) Technology Representation blueball.gif (205 bytes) External Availability The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period through 2020. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. NEMS was designed and implemented by the Energy Information Administration (EIA) of the U.S.

110

Renewable Energy Price-Stability Benefits in Utility Green Power Programs  

SciTech Connect (OSTI)

This paper examines utility experiences when offering the fixed-price benefits of renewable energy in green pricing programs, including the methods utilized and the impact on program participation. It focuses primarily on utility green pricing programs in states that have not undergone electric industry restructuring.

Bird, L. A.; Cory, K. S.; Swezey, B. G.

2008-08-01T23:59:59.000Z

111

U.S. Regional Demand Forecasts Using NEMS and GIS  

E-Print Network [OSTI]

Forecasts Using NEMS and GIS National Climatic Data Center.with Changing Boundaries." Use of GIS to Understand Socio-Forecasts Using NEMS and GIS Appendix A. Map Results Gallery

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-01-01T23:59:59.000Z

112

The informational content of oil and natural gas prices in energy fund performance  

Science Journals Connector (OSTI)

This paper explores whether the informational content of oil and gas prices has an impact on energy mutual fund returns. We first re-visit the relationship between oil and gas prices and energy index returns; our findings confirm that better energy index performance is associated with oil and gas price increases. Using the Fama and MacBeth (1973) two-stage regressions, we find that the information contained in oil and gas prices also plays a significant role in explaining energy mutual fund returns, making these an alternative investment to direct energy stock investments.

Viet Do; Tram Vu

2012-01-01T23:59:59.000Z

113

Integrated NEMS and optoelectronics for sensor applications.  

SciTech Connect (OSTI)

This work utilized advanced engineering in several fields to find solutions to the challenges presented by the integration of MEMS/NEMS with optoelectronics to realize a compact sensor system, comprised of a microfabricated sensor, VCSEL, and photodiode. By utilizing microfabrication techniques in the realization of the MEMS/NEMS component, the VCSEL and the photodiode, the system would be small in size and require less power than a macro-sized component. The work focused on two technologies, accelerometers and microphones, leveraged from other LDRD programs. The first technology was the nano-g accelerometer using a nanophotonic motion detection system (67023). This accelerometer had measured sensitivity of approximately 10 nano-g. The Integrated NEMS and optoelectronics LDRD supported the nano-g accelerometer LDRD by providing advanced designs for the accelerometers, packaging, and a detection scheme to encapsulate the accelerometer, furthering the testing capabilities beyond bench-top tests. A fully packaged and tested die was never realized, but significant packaging issues were addressed and many resolved. The second technology supported by this work was the ultrasensitive directional microphone arrays for military operations in urban terrain and future combat systems (93518). This application utilized a diffraction-based sensing technique with different optical component placement and a different detection scheme from the nano-g accelerometer. The Integrated NEMS LDRD supported the microphone array LDRD by providing custom designs, VCSELs, and measurement techniques to accelerometers that were fabricated from the same operational principles as the microphones, but contain proof masses for acceleration transduction. These devices were packaged at the end of the work.

Czaplewski, David A.; Serkland, Darwin Keith; Olsson, Roy H., III; Bogart, Gregory R. (Symphony Acoustics, Rio Rancho, NM); Krishnamoorthy, Uma; Warren, Mial E.; Carr, Dustin Wade (Symphony Acoustics, Rio Rancho, NM); Okandan, Murat; Peterson, Kenneth Allen

2008-01-01T23:59:59.000Z

114

Dynamic spillovers among major energy and cereal commodity prices  

Science Journals Connector (OSTI)

Abstract Over the past decade, the sharp increases in the prices of oil and agricultural commodities have raised serious concerns about the heightened volatility of these markets and the possible negative interactions between them. This article deals with the dynamic return and volatility spillovers across international energy and cereal commodity markets. It also examines the impacts of three types of OPEC news announcements on the volatility spillovers and persistence in these markets. For this purpose, we make use of the VAR-BEKK-GARCH and VAR-DCC-GARCH models for the daily spot prices of eight major commodities including WTI oil, Europe Brent oil, gasoline, heating oil, barley, corn, sorghum, and wheat. Our results provide evidence of significant linkages between these energy and cereal markets. Moreover, the OPEC news announcements are found to exert influence on the oil markets as well as on the oilcereal relationships. Finally, we show that the persistence of volatility decreases (increases) for the crude oil and heating oil (gasoline) returns after accounting for the OPEC announcements in these multivariate GARCH models. However, the results are more mixed for the cereal markets. Overall, our results can be used to improve the risk-adjusted performance by having more diversified portfolios and also serve to hedge the oil risk more effectively.

Walid Mensi; Shawkat Hammoudeh; Duc Khuong Nguyen; Seong-Min Yoon

2014-01-01T23:59:59.000Z

115

Annual Energy Outlook 2009 with Projections to 2030  

SciTech Connect (OSTI)

The Annual Energy Outlook 2009 (AEO2009), prepared by the Energy Information Administration (EIA), presents long-term projections of energy supply, demand, and prices through 2030, based on results from EIAs National Energy Modeling System (NEMS). EIA published an early release version of the AEO2009 reference case in December 2008.

None

2009-03-01T23:59:59.000Z

116

Energy Price Indices and Discount Factors for Life-Cycle Cost...  

Office of Environmental Management (EM)

Analysis-2013 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis-2013 Handbook describes the annual supplements to the NIST Handbook 135 and NBS Special...

117

Relationship Between Wind Generation and Balancing Energy Market Prices in ERCOT: 2007-2009  

SciTech Connect (OSTI)

This paper attempts to measure the average marginal effects of wind generation on the balancing-energy market price in ERCOT with the help of econometric analysis.

Nicholson, E.; Rogers, J.; Porter, K.

2010-11-01T23:59:59.000Z

118

Price Elasticities for Energy Use in Buildings of the United States  

Reports and Publications (EIA)

Energy demand tends to be responsive to changes in energy prices, a concept in economics known as price elasticity. Generally, an increase in a fuel price causes users to use less of that fuel or switch to a different fuel. The extent to which each of these changes takes place is of high importance to stakeholders in the energy sector and especially in energy planning. The purpose of this analysis is to determine fuel-price elasticities in stationary structures, particularly in the residential and commercial sectors.

2014-01-01T23:59:59.000Z

119

Quantifying the value that energy efficiency and renewable energy provide as a hedge against volatile natural gas prices  

SciTech Connect (OSTI)

Advocates of energy efficiency and renewable energy have long argued that such technologies can mitigate fuel price risk within a resource portfolio. Such arguments--made with renewed vigor in the wake of unprecedented natural gas price volatility during the winter of 2000/2001--have mostly been qualitative in nature, however, with few attempts to actually quantify the price stability benefit that these sources provide. In evaluating this benefit, it is important to recognize that alternative price hedging instruments are available--in particular, gas-based financial derivatives (futures and swaps) and physical, fixed-price gas contracts. Whether energy efficiency and renewable energy can provide price stability at lower cost than these alternative means is therefore a key question for resource acquisition planners. In this paper we evaluate the cost of hedging gas price risk through financial hedging instruments. To do this, we compare the price of a 10-year natural gas swap (i.e., what it costs to lock in prices over the next 10 years) to a 10-year natural gas price forecast (i.e., what the market is expecting spot natural gas prices to be over the next 10 years). We find that over the past two years natural gas users have had to pay a premium as high as $0.76/mmBtu (0.53/242/kWh at an aggressive 7,000 Btu/kWh heat rate) over expected spot prices to lock in natural gas prices for the next 10 years. This incremental cost to hedge gas price risk exposure is potentially large enough - particularly if incorporated by policymakers and regulators into decision-making practices - to tip the scales away from new investments in variable-price, natural gas-fired generation and in favor of fixed-price investments in energy efficiency and renewable energy.

Bolinger, Mark; Wiser, Ryan; Bachrach, Devra; Golove, William

2002-05-15T23:59:59.000Z

120

The Effects of Energy Prices on Groundwater Extraction in Agriculture in the High Plains Aquifer*  

E-Print Network [OSTI]

in the High Plains Aquifer. Dumler et al. (2009) estimate that the energy cost of extracting irrigation water1 The Effects of Energy Prices on Groundwater Extraction in Agriculture in the High Plains-752-0824 Abstract In this article we examine the effects of energy prices on groundwater extraction using

Lin, C.-Y. Cynthia

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

The impact of oil prices on income and energy  

Science Journals Connector (OSTI)

The major determinant of real income growth in Korea is real oil prices, followed by money supply, exchange rates, ... longer horizon, the effects of exchange rates, oil prices, government spending, and money sup...

Young U. Glasure; Aie-Rie Lee

2002-05-01T23:59:59.000Z

122

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

Open Energy Info (EERE)

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

123

Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis- 2010  

Broader source: Energy.gov [DOE]

Report describes the 2010 edition of energy price indices and discount factors for performing life-cycle cost analyses of energy and water conservation and renewable energy projects in federal facilities.

124

China energy issues : energy intensity, coal liquefaction, and carbon pricing  

E-Print Network [OSTI]

In my dissertation I explore three independent, but related, topics on China's energy issues. First, I examine the drivers for provincial energy-intensity trends in China, and finds that technology innovation is the key ...

Wu, Ning, Ph. D. Massachusetts Institute of Technology

2011-01-01T23:59:59.000Z

125

Definition: Time-of-use Pricing | Open Energy Information  

Open Energy Info (EERE)

of-use Pricing of-use Pricing Jump to: navigation, search Dictionary.png Time-of-use Pricing Time-of-use pricing (TOU) typically applies to usage over broad blocks of hours (e.g., on-peak=6 hours for summer weekday afternoon; off-peak= all other hours in the summer months) where the price for each period is predetermined and constant.[1] Related Terms smart grid References ↑ https://www.smartgrid.gov/category/technology/time_of_use_pricing [[C LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ategory: Smart Grid Definitionsoff-peak, |Template:BASEPAGENAME]]off-peak, Retrieved from "http://en.openei.org/w/index.php?title=Definition:Time-of-use_Pricing&oldid=502494" Category: Definitions What links here Related changes Special pages Printable version

126

Regional variations in US residential sector fuel prices: implications for development of building energy performance standards  

SciTech Connect (OSTI)

The Notice of Proposed Rulemaking for Energy Performance Standards for New Buildings presented life-cycle-cost based energy budgets for single-family detached residences. These energy budgets varied with regional climatic conditions but were all based on projections of national average prices for gas, oil and electricity. The Notice of Proposed Rulemaking indicated that further analysis of the appropriateness of various price measures for use in setting the Standards was under way. This part of that ongoing analysis addresses the availability of fuel price projections, the variation in fuel prices and escalation rates across the US and the effects of aggregating city price data to the state, Region, or national level. The study only provides a portion of the information required to identify the best price aggregation level for developing of the standards. The research addresses some of the economic efficiency considerations necessary for design of a standard that affects heterogeneous regions. The first section discusses the effects of price variation among and within regions on the efficiency of resource allocation when a standard is imposed. Some evidence of the extreme variability in fuel prices across the US is presented. In the second section, time series, cross-sectional fuel price data are statistically analyzed to determine the similarity in mean fuel prices and price escalation rates when the data are treated at increasing levels of aggregation. The findings of this analysis are reported in the third section, while the appendices contain price distributions details. The last section reports the availability of price projections and discusses some EIA projections compared with actual prices.

Nieves, L.A.; Tawil, J.J.; Secrest, T.J.

1981-03-01T23:59:59.000Z

127

Clean Fuel Advanced Technology Public Education Campaign: Billboards According to the U.S. Department of Energy's July 2013 alternative fuel price report, the price of propane  

E-Print Network [OSTI]

.S. Department of Energy's July 2013 alternative fuel price report, the price of propane (LPG) in North Carolina.S. Department of Energy and U.S. Environmental Protection Agency, gas mileage decreases rapidly above 50 MPH fuel, regardless of vehicle type. · According to the U.S. Department of Energy (and based on North

128

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

Science Journals Connector (OSTI)

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

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

2003-11-01T23:59:59.000Z

129

DRAFT DO NOT QUOTE Energy Prices and Energy Intensity in China: A Structural Decomposition Analysis and Econometrics Study  

E-Print Network [OSTI]

Since the start of its economic reforms in 1978, China's energy prices relative to other prices have increased. At the same time, its energy intensity, i.e., energy consumption per unit of Gross Domestic Product (GDP), has declined dramatically, by about 70%, in spite of increases in energy consumption. Is this just a coincidence? Or does a systematic relationship exist between energy prices and energy intensity? In this study, we examine whether and how Chinas energy price changes affect its energy intensity trend during 1980-2002 at a macro level. We conduct the research by using two complementary economic models: the input-output-based structural decomposition analysis (SDA) and econometric regression models and by using a decomposition method of own-price elasticity of energy intensity. Findings include a negative own-price elasticity of energy intensity, a price-inducement effect on energyefficiency improvement, and a greater sensitivity (in terms of the reaction of energy intensity towards changes in energy prices) of the industry sector, compared to the overall economy. Analysts can use these results as a starting point for China's energy and carbon

Xiaoyu Shi; Karen R. Polenske; Xiaoyu Shi; Karen R. Polenske

2005-01-01T23:59:59.000Z

130

Reply Comments of Energy Contractors Price-Anderson Group to DOE Notice of  

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

Reply Comments of Energy Contractors Price-Anderson Group to DOE Reply Comments of Energy Contractors Price-Anderson Group to DOE Notice of Inquiry Reply Comments of Energy Contractors Price-Anderson Group to DOE Notice of Inquiry Reply comments by the ad hoc Energy Contractors Price-Anderson Group (the "Group") in response to various comments submitted to the U.S. Department of Energy on its Federal Register "Notice of Inquiry concerning preparation of report to Congress on the Price-Anderson Act" of December 31, 1997. 62 Fed.Reg. 68272. The Group is comprised of comprised of Bechtel National, Inc., BNFL, Inc., BWX Technologies, Inc., Duke Engineering & Services, Inc., Fluor Corporation, Johnson Controls World Services Corporation, Newport News Shipbuilding and Dry Dock Company, Nuclear Fuel Services,

131

Public comment re Price-Anderson Act | Department of Energy  

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

comment re Price-Anderson Act comment re Price-Anderson Act Public comment re Price-Anderson Act Notice of Inquiry Concerning Preparation of Report to Congress on the Price-Anderson Act 62 Federal Register 250. Universities Research Association, Inc. (URA) is a nonprofit corporation consisting of 87 member research universities located in the United States, Canada, Japan, and Italy.This Association strongly supports the continuation of the provisions of the Price-Anderson Act for DOE contractors and suppliers, including the exemption of Fermilab, among other named DOE national laboratories, from the payment of civil penalties under that Act. It is our experience at Fermilab that a few subcontractors/suppliers expect Price-Anderson protection and will not contract with the Laboratory without it.

132

Public Comment re Price-Anderson Act | Department of Energy  

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

Comment re Price-Anderson Act Comment re Price-Anderson Act Public Comment re Price-Anderson Act Comments for modification of the Price-Anderson Act Notice of Inquiry(NOI) by the Board of Mineral County Commissioners. The provisions covered by the current Act should, at the very least, be maintained. We are concerned that if the DOE Price-Anderson indemnification is not continued, we will not have the proper protection should a severe accident occur when spent nuclear fuel is transported through our community on its way to Yucca Mountain. The maintaining of the DOE PriceAnderson indemnification becomes even more important with the privatization of the OC RWM transportation program. DOE cannot expect private contractors, and in particular carriers, to be able to afford adequate coverage from a private insurer.

133

Stochastic Modeling and Analysis of Energy Commodity Spot Price Processes.  

E-Print Network [OSTI]

??Supply and demand in the World oil market are balanced through responses to price movement with considerable complexity in the evolution of underlying supply-demand expectation (more)

Otunuga, Olusegun Michael

2014-01-01T23:59:59.000Z

134

Report to Congress on the Price-Anderson Act | Department of Energy  

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

Report to Congress on the Price-Anderson Act Report to Congress on the Price-Anderson Act Report to Congress on the Price-Anderson Act The Price-Anderson Amendments Act of 1988 (1988 Amendments) directed both the Department of Energy (DOE) and the Nuclear Regulatory Commission (NRC) to file reports with Congress containing their respective recommendations for continuation, repeal or modification of the Price-Anderson Act. This report fulfills the statutory requirement in Atomic Energy Act § 170.p. by focusing on those provisions of the Price- Anderson Act under which DOE indemnifies its contractors and other persons for legal liability arising from a nuclear incident or precautionary evacuation caused by activities under a contract with DOE (the DOE indemnification). It also examines the related provisions in § 234A of the

135

EIA: High Oil Prices, GHG Controls Would Help Clean Energy Grow  

Broader source: Energy.gov [DOE]

The growth of renewable energy and renewable fuels in the United States will be significantly greater under scenarios involving high oil prices and stricter controls on greenhouse gas (GHG) emissions, according to DOE's Energy Information Administration (EIA).

136

Cost-effective retrofitting of Swedish residential buildings: effects of energy price developments and discount rates  

Science Journals Connector (OSTI)

This paper investigates how the cost-effectiveness of different energy-saving measures (ESMs) in buildings is dependent upon energy prices and discount rates. A bottom-up ... different ESMs for Swedish residentia...

rika Mata; Angela Sasic Kalagasidis; Filip Johnsson

2014-08-01T23:59:59.000Z

137

The long-run evolution of energy prices  

E-Print Network [OSTI]

I examine the long-run behavior of oil, coal, and natural gas prices, using up to 127 years of data, and address the following questions: What does over a century of data tell us about the stochastic dynamics of price ...

Pindyck, Robert S.

1999-01-01T23:59:59.000Z

138

Industrial Attitudes to Petroleum Prices: Policies and Energy Efficiency  

E-Print Network [OSTI]

Beginning in 2001, the US began to see sharp increases and volatility in what had been historically low natural gas prices. The traditional response to events such as this had been to switch fuels when possible and negotiate more attractive price...

Shipley, A. M.; Langer, T.; Black, S.

2007-01-01T23:59:59.000Z

139

EIA - The National Energy Modeling System: An Overview 2003-Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction The National Energy Modeling System: An Overview 2003 Introduction The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of U.S. energy markets for the midterm period through 2025. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. NEMS was designed and implemented by the Energy Information Administration (EIA) of the U.S. Department of Energy (DOE). The National Energy Modeling System: An Overview 2003 presents an overview of the structure and methodology of NEMS and each of its components. This chapter provides a description of the design and objectives of the system, followed by a chapter on the overall modeling structure and solution algorithm. The remainder of the report summarizes the methodology and scope of the component modules of NEMS. The model descriptions are intended for readers familiar with terminology from economics, operations research, and energy modeling. More detailed model documentation reports for all the NEMS modules are also available from EIA (Appendix, “Bibliography”).

140

Embedding renewable energy pricing policies in day-ahead electricity market clearing  

Science Journals Connector (OSTI)

Abstract Since the 90s various policies have been applied for supporting the development of Renewable Energy Sources (RES), including quota or amount-based systems and price-based systems (feed-in tariffs or FiT). In both cases, there is a political stress when there is a need to increase the renewable uplift charge rates (out-of-market mechanism), in order to finance the RES projects. This issue is resolved by adopting a novel market framework, in which the demand entities clearing price entails the whole cost they are willing to pay for their participation in the energy market, including energy prices, reserve prices and the RES uplift price. A Mixed Complementarity Problem is utilized for clearing the market, in which the demand clearing prices are implicitly defined by mixing the explicit prices for energy, reserves and the RES uplift. The model retains the consistency of the supply (energy and reserves) and demand cleared quantities with the respective bids and the clearing prices, and attains a significant decrease of the payments through the relevant uplift accounts. The efficiency of the proposed model is demonstrated on a 24-h day-ahead market simulation using the IEEE RTS-96, defining endogenously the RES uplift under a system-wide FiT and a Green Certificate mechanism.

Andreas G. Vlachos; Pandelis N. Biskas

2014-01-01T23:59:59.000Z

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

Wheat and corn prices and energy markets: spillover effects  

Science Journals Connector (OSTI)

This paper investigates volatility spillover across crude oil market and wheat and corn markets. The corn commodity is taken here to assess the impact of change in demand for biofuel on wheat market. Results of multivariate GARCH model show evidence of corn price volatility transmission to wheat market. Our results indicate that while shocks (unexpected news) in crude oil market have significant impact on volatility in wheat and corn markets, the effect of crude oil price changes on wheat and corn prices is insignificant. The impulse response analysis also indicates shocks in oil markets have permanent effect on wheat and corn price changes. This reveals the influence of future crude oil markets on global food price volatility. Also indicated that fertilisers markets influenced by own-shocks and shocks in oil markets. Thus, shocks in crude oil markets have direct and indirect effects (via fertilisers markets) on food commodity markets.

Ibrahim A. Onour; Bruno S. Sergi

2012-01-01T23:59:59.000Z

142

London Congestion Pricing: Implications for Other Cities | Open Energy  

Open Energy Info (EERE)

London Congestion Pricing: Implications for Other Cities London Congestion Pricing: Implications for Other Cities Jump to: navigation, search Tool Summary LAUNCH TOOL Name: London Congestion Pricing: Implications for Other Cities Agency/Company /Organization: Victoria Transport Policy Institute Focus Area: Standards - Incentives - Policies - Regulations Topics: Best Practices Website: www.vtpi.org/london.pdf Congestion charging has reduced traffic congestion, improved bus and taxi service, and generated substantial revenues. There is now support to expand the program to other parts of London and other cities in the United Kingdom. This is the first congestion pricing program in a major European city, and its success suggests that congestion pricing may become more politically feasible elsewhere. How to Use This Tool

143

Understanding Crude Oil Prices  

E-Print Network [OSTI]

2004. OPECs Optimal Crude Oil Price, Energy Policy 32(2),percent change in real oil price. Figure 3. Price of crude023 Understanding Crude Oil Prices James D. Hamilton June

Hamilton, James Douglas

2008-01-01T23:59:59.000Z

144

Understanding Crude Oil Prices  

E-Print Network [OSTI]

2004. OPECs Optimal Crude Oil Price, Energy Policy 32(2),percent change in real oil price. Figure 3. Price of crudein predicting quarterly real oil price change. variable real

Hamilton, James Douglas

2008-01-01T23:59:59.000Z

145

The National Energy Modeling System: An overview  

SciTech Connect (OSTI)

The National Energy Modeling System (NEMS) is a computer-based, energy-economy modeling system of US energy markets for the midterm period of 1990 to 2010. NEMS projects the production, imports, conversion, consumption, and prices of energy, subject to assumptions on macroeconomic and financial factors, world energy markets, resource availability and costs, behavioral and technological choice criteria, cost and performance characteristics of energy technologies, and demographics. This report presents an overview of the structure and methodology of NEMS and each of its components. The first chapter provides a description of the design and objectives of the system. The second chapter describes the modeling structure. The remainder of the report summarizes the methodology and scope of the component modules of NEMS. The model descriptions are intended for readers familiar with terminology from economics, operations research, and energy modeling. Additional background on the development of the system is provided in Appendix A of this report, which describes the EIA modeling systems that preceded NEMS. More detailed model documentation reports for all the NEMS modules are also available from EIA.

Not Available

1994-05-01T23:59:59.000Z

146

Long-term policies needed to address energy use and price volatility  

SciTech Connect (OSTI)

This paper reports on the gasoline price spike after the Exxon Valdez oil spill and the home heating fuel price increases last winter, which make the third sharp increase in the price of petroleum products that US citizens have experienced in the past 18 months. Although the United States is in a better position to deal with these price increases than in the 1970s because of increased energy efficiency and the existence of the Strategic Petroleum Reserve (SPR), concerns remain about recent trends showing increasing oil consumption, increased reliance on imports from the Persian Gulf, and the SPR's role in reducing the impact of these incidents.

Not Available

1990-09-01T23:59:59.000Z

147

Easing the natural gas crisis: Reducing natural gas prices through increased deployment of renewable energy and energy efficiency  

SciTech Connect (OSTI)

Heightened natural gas prices have emerged as a key energy-policy challenge for at least the early part of the 21st century. With the recent run-up in gas prices and the expected continuation of volatile and high prices in the near future, a growing number of voices are calling for increased diversification of energy supplies. Proponents of renewable energy and energy efficiency identify these clean energy sources as an important part of the solution. Increased deployment of renewable energy (RE) and energy efficiency (EE) can hedge natural gas price risk in more than one way, but this paper touches on just one potential benefit: displacement of gas-fired electricity generation, which reduces natural gas demand and thus puts downward pressure on gas prices. Many recent modeling studies of increased RE and EE deployment have demonstrated that this ''secondary'' effect of lowering natural gas prices could be significant; as a result, this effect is increasingly cited as justification for policies promoting RE and EE. This paper summarizes recent studies that have evaluated the gas-price-reduction effect of RE and EE deployment, analyzes the results of these studies in light of economic theory and other research, reviews the reasonableness of the effect as portrayed in modeling studies, and develops a simple tool that can be used to evaluate the impact of RE and EE on gas prices without relying on a complex national energy model. Key findings are summarized.

Wiser, Ryan; Bolinger, Mark; St. Clair, Matt

2004-12-21T23:59:59.000Z

148

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

Open Energy Info (EERE)

Total Energy Supply, Disposition, and Price Summary Total Energy Supply, Disposition, and Price Summary Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion Btu and the U.S. Dollar. The data is broken down into production, imports, exports, consumption and price. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption disposition energy exports imports Supply 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 Comment Temporal and Spatial Coverage

149

Table 7.5 Average Prices of Selected Purchased Energy Sources, 2002  

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

5 Average Prices of Selected Purchased Energy Sources, 2002;" 5 Average Prices of Selected Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Million Btu." " ",," "," ",," "," ","RSE" "Economic",,"Residual","Distillate","Natural ","LPG and",,"Row" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","Factors" ,"Total United States"

150

Table N8.2. Average Prices of Purchased Energy Sources, 1998  

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

2. Average Prices of Purchased Energy Sources, 1998;" 2. Average Prices of Purchased Energy Sources, 1998;" " Level: National and Regional Data; " " Row: NAICS Codes; Column: All Energy Sources Collected;" " Unit: U.S. Dollars per Million Btu." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Selected","Wood and Other","Biomass","Components" ,,,,,,,"Coal Components",,,"Coke",,"Electricity","Components",,,,,,,,,,,,,"Natural Gas","Components",,"Steam","Components" ,,,,,,,,,,,,,,"Total",,,,,,,,,,,,,,,,,,,,,,,"Wood Residues" " "," "," ",,,,,"Bituminous",,,,,,"Electricity","Diesel Fuel",,,,,,"Motor",,,,,,,"Natural Gas",,,"Steam",,,," ",,,"and","Wood-Related",," ",," "

151

Table 7.1 Average Prices of Purchased Energy Sources, 2002  

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

Average Prices of Purchased Energy Sources, 2002;" Average Prices of Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes;" " Column: All Energy Sources Collected;" " Unit: U.S. Dollars per Physical Units." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Selected Wood and Other Biomass Components" ,,,,,,"Coal Components",,,"Coke",,,"Electricity Components",,,,,,,,,,,,,,"Natural Gas Components",,,"Steam Components" ,,,,,,,,,,,,,,"Total",,,,,,,,,,,,,,,,,,,,,,,"Wood Residues" " "," "," ",,,,,"Bituminous",,,,,,"Electricity","Diesel Fuel",,,,,,"Motor",,,,,,,"Natural Gas",,,"Steam",,,," ",,,"and","Wood-Related",," ",," "

152

Table 7.2 Average Prices of Purchased Energy Sources, 2002  

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

2 Average Prices of Purchased Energy Sources, 2002;" 2 Average Prices of Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: NAICS Codes; " " Column: All Energy Sources Collected;" " Unit: U.S. Dollars per Million Btu." ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,"Selected Wood and Other Biomass Components" ,,,,,,"Coal Components",,,"Coke",,,"Electricity Components",,,,,,,,,,,,,,"Natural Gas Components",,,"Steam Components" ,,,,,,,,,,,,,,"Total",,,,,,,,,,,,,,,,,,,,,,,"Wood Residues" " "," "," ",,,,,"Bituminous",,,,,,"Electricity","Diesel Fuel",,,,,,"Motor",,,,,,,"Natural Gas",,,"Steam",,,," ",,,"and","Wood-Related",," ",," "

153

Table 7.4 Average Prices of Selected Purchased Energy Sources, 2002  

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

4 Average Prices of Selected Purchased Energy Sources, 2002;" 4 Average Prices of Selected Purchased Energy Sources, 2002;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Physical Units." " ",," "," ",," "," " ,,"Residual","Distillate","Natural ","LPG and",,"RSE" "Economic","Electricity","Fuel Oil","Fuel Oil(b)","Gas(c)","NGL(d)","Coal","Row" "Characteristic(a)","(kWh)","(gallons)","(gallons)","(1000 cu ft)","(gallons)","(short tons)","Factors"

154

"Table E8.1. Average Prices of Selected Purchased Energy Sources, 1998;"  

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

1. Average Prices of Selected Purchased Energy Sources, 1998;" 1. Average Prices of Selected Purchased Energy Sources, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Physical Units." " ",," "," ",," "," " ,,"Residual","Distillate",,"LPG and",,"RSE" "Economic","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","Row" "Characteristic(a)","(kWh)","(gallons)","(gallons)","(1000 cu ft)","(gallons)","(short tons)","Factors"

155

"Table E8.2. Average Prices of Selected Purchased Energy Sources, 1998;"  

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

2. Average Prices of Selected Purchased Energy Sources, 1998;" 2. Average Prices of Selected Purchased Energy Sources, 1998;" " Level: National and Regional Data; " " Row: Values of Shipments and Employment Sizes;" " Column: Energy Sources;" " Unit: U.S. Dollars per Million Btu." " ",," "," ",," "," ","RSE" "Economic",,"Residual","Distillate",,"LPG and",,"Row" "Characteristic(a)","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","NGL(d)","Coal","Factors" ,"Total United States"

156

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 International Energy Module The NEMS International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, the NEMS IEM computes oil prices, provides a supply curve of world crude-like liquids, generates a worldwide oil supply- demand balance with regional detail, and computes quantities of crude oil and light and heavy petroleum products imported into the United States by export region. Changes in the oil price (WTI), which is defined as the price of light, low-sulfur crude oil delivered to Cushing, Oklahoma in

157

Energy Price Indices and Discount Factors for Life-Cycle Cost...  

Office of Environmental Management (EM)

2 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2012 Report provides tables of present-value factors for use in the life-cycle cost analysis of capital...

158

"Table A25. Average Prices of Selected Purchased Energy Sources by Census"  

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

. Average Prices of Selected Purchased Energy Sources by Census" . Average Prices of Selected Purchased Energy Sources by Census" " Region, Industry Group, and Selected Industries, 1991: Part 1" " (Estimates in Dollars per Physical Unit)" ,,,,," " " "," "," ","Residual","Distillate","Natural Gas(c)"," "," ","RSE" "SIC"," ","Electricity","Fuel Oil","Fuel Oil(b)","(1000","LPG","Coal","Row" "Code(a)","Industry Groups and Industry","(kWh)","(gallon)","(gallon)","cu ft)","(gallon)","(short ton)","Factors"

159

Lynn Price  

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

Lynn Price Lynn Price China Energy Group Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R2002 Berkeley CA 94720 Office Location: 90-2108 (510) 486-6519 LKPrice@lbl.gov Lynn Price is a Staff Scientist and Leader of the China Energy Group of the Energy Analysis and Environmental Impacts Department, Environmental Energy Technologies Division, of Lawrence Berkeley National Laboratory. Ms. Price has a MS in Environmental Science from the University of Wisconsin-Madison and has worked at LBNL since 1990. Ms. Price has been a member of the Intergovernmental Panel on Climate Change, which won the Nobel Peace Prize in 2007, since 1994 and was an author on the industrial sector chapter of IPCC's Fourth Assessment Report on Mitigation of Climate Change. Since 1999, Ms. Price has provided technical assistance to the Energy

160

The Facts on Gas Prices: Infographic | Department of Energy  

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

The Facts on Gas Prices: Infographic The Facts on Gas Prices: Infographic The Facts on Gas Prices: Infographic March 13, 2012 - 4:19pm Addthis Domestic oil production has climbed every year since President Obama took office, and our dependence on foreign oil is at its lowest level since the 1990s. | Graphic courtesy of the White House Domestic oil production has climbed every year since President Obama took office, and our dependence on foreign oil is at its lowest level since the 1990s. | Graphic courtesy of the White House Matt Compton Deputy Director of Online Content for the Office of Digital Strategy at the White House. This article is cross posted from the White House. Here are the facts: The United States produced more than 2 billion barrels

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

Public comment re Price Anderson Act extension | Department of Energy  

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

Public comment re Price Anderson Act extension Public comment re Price Anderson Act extension Public comment re Price Anderson Act extension Recently I learned of interpretations of the University's comments submitted on January 30, 1998, that I think bear some clarification. One of our comments suggested an alternative for DOE if the civil fine exemption were to be eliminated. That comment was not an endorsement for eliminating the exemption; rather it is a means for partially mitigating the adverse consequences to the production of science were the exemption eliminated. The University has never believed that the risk of financial incentives or penalties is the most appropriate means of motivating non-profit organizations to either perform better or avoid inappropriate actions. Consequently we do not embrace the imposition of criminal or civil fines

162

The Facts on Gas Prices: Infographic | Department of Energy  

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

The Facts on Gas Prices: Infographic The Facts on Gas Prices: Infographic The Facts on Gas Prices: Infographic March 13, 2012 - 4:19pm Addthis Domestic oil production has climbed every year since President Obama took office, and our dependence on foreign oil is at its lowest level since the 1990s. | Graphic courtesy of the White House Domestic oil production has climbed every year since President Obama took office, and our dependence on foreign oil is at its lowest level since the 1990s. | Graphic courtesy of the White House Matt Compton Deputy Director of Online Content for the Office of Digital Strategy at the White House. This article is cross posted from the White House. Here are the facts: The United States produced more than 2 billion barrels

163

Energy Factors, Leasing Structure and the Market Price of Office Buildings  

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

Energy Factors, Leasing Structure and the Market Price of Office Buildings Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S. Speaker(s): Nancy Wallace Date: June 15, 2011 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Paul Mathew The talk will cover the results from an empirical paper that analyzes the relationship between energy factor markets, leasing structures and the transaction prices of office buildings in the {U.S.} We employ a large sample of 15,133 office building transactions that occurred between 2001 and 2010. In addition to building characteristics, we also include information on the operating expenses, the net operating income, and the market capitalization rates at sale to estimate an asset pricing model for commercial office real estate assets. A further set of important controls

164

Can Deployment of Renewable Energy and Energy Efficiency Put Downward Pressure on Natural Gas Prices  

E-Print Network [OSTI]

RE and EE may also put downward pressure on coal prices, theelasticity of coal prices to altered demand conditions isthe impact of RE and EE on coal prices is probably modest

Wiser, Ryan; Bolinger, Mark

2005-01-01T23:59:59.000Z

165

Dynamic online optimization of a house heating system in a fluctuating energy price  

E-Print Network [OSTI]

Dynamic online optimization of a house heating system in a fluctuating energy price scenario University of Science and Technology (NTNU), Trondheim, Norway Abstract: We consider dynamic optimization of the energy consumption in a building with energy storage capabilities. The goal is to find optimal policies

Skogestad, Sigurd

166

The National Energy Modeling System: An Overview 2000 - Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic assessment at EIA involves several modes of analysis. The first type of analysis, used in forecasting the Annual Energy Outlook where energy prices change, uses kernel regression and response surface techniques to mimic the response of larger macroeconomic and industrial models. This mode of analysis requires a given economic baseline and then calculates the economic impacts of changing energy prices, calculated from the chosen growth path. The economic growth cases are derived from the larger core models and can reflect either high, low, or reference case growth assumptions. Analyzing economic impacts from energy price changes uses the macroeconomic activity module (MAM) within NEMS and provides a subset of the macroeconomic variables available in the larger core models. The composition of the subset is determined by the other energy modules in NEMS, as they use various macroeconomic concepts as assumptions to their particular energy model.

167

Energy price prediction multi-step ahead using hybrid model in the Brazilian market  

Science Journals Connector (OSTI)

Abstract This paper proposes a new hybrid approach for short-term energy price prediction. This approach combines auto-regressive integrated moving average (ARIMA) and neural network (NN) models in a cascaded structure and uses explanatory variables. A two step procedure is applied. In the first step, the selected explanatory variables are predicted. In the second one, the energy prices are forecasted by using the explanatory variables prediction. Further, the proposed model considers a multi-step ahead price prediction (12 weeks-ahead) and is applied to Brazilian market, which adopts a cost-based centralized dispatch with unique characteristics of price behavior. The results show good ability to predict spikes and satisfactory accuracy according to error measures and tail loss test when compared with traditional techniques. Thus, the model can be an attractive tool to mitigate risks in purchasing power.

Jos C. Reston Filho; Carolina de M. Affonso; Roberto C.L. de Oliveira

2014-01-01T23:59:59.000Z

168

Market dynamics and price stability: the case of the global energy market  

Science Journals Connector (OSTI)

In the present century, the potential for growth in the world demand for energy is enormous due to growing industrialisation, economic advancement and population growth far and wide. However, there is hardly any consensus on strategies to encourage smooth supplies and sustainable prices in the energy markets. This paper examines the current market conditions of the energy market and the mechanism used by OPEC for pricing. Lessons from past years are used to design policies aimed at creating a win-win situation for energy producers and consumers.

Quhafah Mahasneh

2003-01-01T23:59:59.000Z

169

Fact #766: February 11, 2013 Electricity Prices are More Stable...  

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

6: February 11, 2013 Electricity Prices are More Stable than Gasoline Prices Fact 766: February 11, 2013 Electricity Prices are More Stable than Gasoline Prices All energy prices...

170

An Analysis of the Effects of Residential Photovoltaic Energy Systems on Home Sales Prices in California  

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

Energy Markets and Policy Group * Energy Analysis Department Energy Markets and Policy Group * Energy Analysis Department An Analysis of the Effects of Residential Photovoltaic Energy Systems on Home Sales Prices in California Ben Hoen, Peter Cappers, Mark Thayer, Ryan Wiser Lawrence Berkeley National Laboratory LBNL Webinar June 9 th , 2011 This work was supported by the Office of Energy Efficiency and Renewable Energy (Solar Energy Technologies Program) of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, by the National Renewable Energy Laboratory under Contract No. DEK-8883050, and by the Clean Energy States Alliance.

171

DOE Cites Battelle Energy Alliance, LLC for Price-Anderson Violations |  

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

Cites Battelle Energy Alliance, LLC for Price-Anderson Cites Battelle Energy Alliance, LLC for Price-Anderson Violations DOE Cites Battelle Energy Alliance, LLC for Price-Anderson Violations December 3, 2007 - 4:44pm Addthis WASHINGTON, DC - The U.S. Department of Energy (DOE) today notified Battelle Energy Alliance, LLC (BEA) that it will fine the company $123,750 for violations of the Department's nuclear safety requirements. BEA is the DOE Idaho Operations Office prime contractor for the operation of the Neutron Radiography (NRAD) reactor. The Neutron Radiography Reactor is used to non-destructively examine irradiated materials; the imaging technique utilizes thermal neutrons and is used for quality control purposes in industries which require precision machining. The Preliminary Notice of Violation (PNOV) issued today cited a series of

172

Overview of NEMS-H2, Version 1.0  

Broader source: Energy.gov [DOE]

Presentation on Overview of NEMS-H2, Version 1.0 given by Frances Wood of OnLocation during the DOE Hydrogen Transition Analysis Workshop on January 26, 2006.

173

Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Outlook Outlook 2010 Restrospective Review July 2011 www.eia.gov U.S. Depa rtment of Energy W ashington, DC 20585 This page inTenTionally lefT blank 3 U.S. Energy Information Administration | Annual Energy Outlook Retrospective Review While the integrated nature of NEMS may result in some feedback that slightly modifies the initial assumptions about world oil price and the macroeconomic growth environment, these feedbacks tend to be relatively small, so that the initial assumptions for world oil price and the macroeconomic growth environment largely determine the overall projection environ- ment. To the extent that this general environment deviates from the initial assumptions, the NEMS projection results will also deviate. Table 2 provides a summary of the percentage of years in

174

Multi-Path Transportation Futures Study: Vehicle Characterization and Scenario Analyses - Appendix E: Other NEMS-MP Results for the Base Case and Scenarios  

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

Appendix E: Other NEMS-MP Results Appendix E: Other NEMS-MP Results for the Base Case and Scenarios Energy Systems Division Availability of This Report This report is available, at no cost, at http://www.osti.gov/bridge. It is also available on paper to the U.S. Department of Energy and its contractors, for a processing fee, from: U.S. Department of Energy Office of Scientific and Technical Information P.O. Box 62

175

Representing Energy Price Variability in Long-and Medium-term Hydropower Optimization  

E-Print Network [OSTI]

, 2002). The output of each hydropower plant is usually small relative to the overall energy market1 Representing Energy Price Variability in Long- and Medium- term Hydropower Optimization Marcelo A Department of Civil and Environmental Engineering, University of California, Davis, USA Journal of Water

Pasternack, Gregory B.

176

Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis- 2012  

Broader source: Energy.gov [DOE]

Report provides tables of present-value factors for use in the life-cycle cost analysis of capital investment projects for federal facilities. It also provides energy price indices based on the U.S. Department of Energy (DOE) forecasts from 2012 to 2042.

177

Integrating Dynamic Pricing of Electricity into Energy Aware Scheduling for HPC Systems  

E-Print Network [OSTI]

- ure that the size of these jobs affects their energy efficiency or not. We hypothesizeIntegrating Dynamic Pricing of Electricity into Energy Aware Scheduling for HPC Systems Xu Yang aimed at reducing en- ergy consumption in HPC environments. In this paper we propose a job power aware

Sun, Xian-He

178

Understanding Crude Oil Prices  

E-Print Network [OSTI]

2004. OPECs Optimal Crude Oil Price, Energy Policy 32(2),023 Understanding Crude Oil Prices James D. Hamilton Junedirectly. Understanding Crude Oil Prices* James D. Hamilton

Hamilton, James Douglas

2008-01-01T23:59:59.000Z

179

DOE Cites Battelle Energy Alliance, LLC for Price-Anderson Violations |  

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

Price-Anderson Price-Anderson Violations DOE Cites Battelle Energy Alliance, LLC for Price-Anderson Violations December 3, 2007 - 4:44pm Addthis WASHINGTON, DC - The U.S. Department of Energy (DOE) today notified Battelle Energy Alliance, LLC (BEA) that it will fine the company $123,750 for violations of the Department's nuclear safety requirements. BEA is the DOE Idaho Operations Office prime contractor for the operation of the Neutron Radiography (NRAD) reactor. The Neutron Radiography Reactor is used to non-destructively examine irradiated materials; the imaging technique utilizes thermal neutrons and is used for quality control purposes in industries which require precision machining. The Preliminary Notice of Violation (PNOV) issued today cited a series of violations that occurred on August 20, 2006 during the restart and

180

Regional Differences in the Price-Elasticity of Demand for Energy  

SciTech Connect (OSTI)

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

Bernstein, M. A.; Griffin, J.

2006-02-01T23:59:59.000Z

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

Session 4: "Short-Term Energy Prices - What Drivers Matter Most?"  

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

4: "Short-Term Energy Prices - What Drivers Matter Most?" 4: "Short-Term Energy Prices - What Drivers Matter Most?" Speakers: Howard K. Gruenspecht, EIA David M. Arseneau, Federal Reserve Board Guy F. Caruso, Center for Strategic and International Studies Christopher Ellsworth, Federal Energy Regulatory Commission Edward L. Morse, Credit Suisse Securities [Note: Recorders did not pick up introduction of panel (see biographies for details on the panelists) or introduction of session.] Howard: And this presentation could not be more timely, given current developments in oil and natural gas markets and the start of the traditional summer driving season. In discussions of rapidly rising oil prices leading to a peak of $147 per barrel in the summer of 2008, the factors that were traditionally the focus of EIA's

182

Model documentation, Coal Market Module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives and the conceptual and methodological approach used in the development of the National Energy Modeling System`s (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 1998 (AEO98). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM`s two submodules. These are the Coal Production Submodule (CPS) and the Coal Distribution Submodule (CDS). CMM provides annual forecasts of prices, production, and consumption of coal for NEMS. In general, the CDS integrates the supply inputs from the CPS to satisfy demands for coal from exogenous demand models. The international area of the CDS forecasts annual world coal trade flows from major supply to major demand regions and provides annual forecasts of US coal exports for input to NEMS. Specifically, the CDS receives minemouth prices produced by the CPS, demand and other exogenous inputs from other NEMS components, and provides delivered coal prices and quantities to the NEMS economic sectors and regions.

NONE

1998-01-01T23:59:59.000Z

183

EIA - The National Energy Modeling System: An Overview 2003  

Gasoline and Diesel Fuel Update (EIA)

The National Energy Modeling System: An Overview 2003 This report provides a summary description of the NEMS which was used to generate the projections of energy production, demand, imports, and prices through the year 2025 for the Annual Energy Outlook 2003. Preface Introduction Overview of NEMS Carbon Dioxide and Methane Emissions Macroeconomic Activity Module International Energy Module Residential Demand Module Commercial Demand Module Industrial Demand Module Transportation Demand Module Electricity Market Module Renewable Fuels Module Oil and Gas Supply Module Natural Gas Transmission and Distribution Module Petroleum Market Module Coal Market Module Bibliography Download the Report NEMS: An Overview 2003 Cover. Need help, contact the National Energy Information Center at 202-586-8800.

184

Renewable Energy RFPs: Solicitation Response and Wind Contract Prices  

E-Print Network [OSTI]

solicitations in the Midwest (Xcel, Great River Energy, andRE RE RE RE RE RE Utility Xcel (MN) Great River Energy MG&E/Electric Puget Sound Energy Xcel/PSCo NorthWestern NCPA (CA)

Wiser, Ryan; Bolinger, Mark

2005-01-01T23:59:59.000Z

185

"Table A25 Average Prices of Selected Purchased Energy Sources by Census"  

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

Average Prices of Selected Purchased Energy Sources by Census" Average Prices of Selected Purchased Energy Sources by Census" " Region, Industry Group, and Selected Industries, 1991: Part 2" " (Estimates in Dollars per Million Btu)" ,,,,,,,,"RSE" "SIC"," "," ","Residual","Distillate"," "," "," ","Row" "Code(a)","Industry Groups and Industry","Electricity","Fuel Oil","Fuel Oil(b)","Natural Gas(c)","LPG","Coal","Factors" ,,"Total United States" ,"RSE Column Factors:",0.7,0.8,1,2.8,1,0.7 20,"Food and Kindred Products",15.789,2.854,6.064,2.697,7.596,1.433,4.5

186

Testing residential energy pricing in the Krakow, Poland, municipal district heat system  

SciTech Connect (OSTI)

While understanding of the operation of the price and rebate mechanism may be imperfect in the United States, in Poland most of the necessary infrastructure simply does not exist. Of all the former Soviet-bloc countries, Poland has moved the quickest to a market economy; however, the stresses have been and continue to be significant, particularly on the pensioned. The energy sector of the economy is still centrally planned while the legal framework for a transition to a regulated market is created. Some utilities have made more rapid progress than others in the transition. This paper describes the first year of an experiment involving design, implementation, and analysis of a pilot pricing, conservation, and heating system control experiment in 264 apartments in four buildings. The results--and experience in the United States--will be used to guide the pricing decisions of the municipal district heat utility and the conservation and air quality strategies of the Krakow development authority. Development of a price incentive strategy involved considerations of public policy toward fixed-income occupants and ownership of energy metering. Thermostats were installed to permit occupant control, and building-level conservation and control techniques were implemented. Physical constraints required the use of German ``cost allocator`` metering technology at the apartment level. Final subsidy or ``pseudo-pricing`` design included-building-level incentives as well as apartment performance inducements. Results include insights on communication and cultural impacts and guidance for future testing as well as energy conservation effectiveness values.

Wisnewski, R.; Reeves, G. [George Reeves Associates, Inc., Lake Hopatcong, NJ (United States); Markiewicz, J. [Fundacja na Rzecz Efektywnego Wykorzystania Energii w Krakowie, Krakow (Poland)

1995-08-01T23:59:59.000Z

187

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

SciTech Connect (OSTI)

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

NONE

1997-01-01T23:59:59.000Z

188

Prices & Trends  

Broader source: Energy.gov [DOE]

The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment. Learn about EIA and Energy Department organizations that track energy prices and trends.

189

Effect of oil prices on returns to alternative energy investments.  

E-Print Network [OSTI]

??This paper presents the role of alternative energy technologies in displacing fossil fuels as the world's primary energy source. To that end, a CAPM-GARCH multi-factor (more)

Schmitz, Anthony

2009-01-01T23:59:59.000Z

190

Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2010  

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

5 5 (Rev. 5/10) Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2010 Annual Supplement to Amy S. Rushing NIST Handbook 135 and Joshua D. Kneifel NBS Special Publication 709 Barbara C. Lippiatt U.S. DEPARTMENT OF COMMERCE Technology Administration National Institute of Standards and Technology Prepared for United States Department of Energy Federal Energy Management Program April 2005 May 2010 ENERGY PRICE INDICES AND DISCOUNT FACTORS FOR LIFE-CYCLE COST ANALYSIS Annual Supplement to NIST Handbook 135 and NBS Special Publication 709 April 1, 2010 to March 31, 2011 Data for the Federal Methodology for Life-Cycle Cost Analysis, Title 10, CFR, Part 436, Subpart A; and for the Energy Conservation Mandatory Performance Standards for New Federal Residential Buildings,

191

Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2011  

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

April 2005 April 2005 NISTIR 85-3273-26 (Rev. 9/11) Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2011 Annual Supplement to Amy S. Rushing NIST Handbook 135 and Joshua D. Kneifel NBS Special Publication 709 Barbara C. Lippiatt U.S. DEPARTMENT OF COMMERCE Technology Administration National Institute of Standards and Technology Prepared for United States Department of Energy Federal Energy Management Program September 2011 NISTIR 85-3273-26 ENERGY PRICE INDICES AND DISCOUNT FACTORS FOR LIFE-CYCLE COST ANALYSIS Annual Supplement to NIST Handbook 135 and NBS Special Publication 709 April 1, 2011 to March 31, 2012 Data for the Federal Methodology for Life-Cycle Cost Analysis, Title 10, CFR, Part 436, Subpart A; and for the Energy Conservation Mandatory Performance Standards for New Federal Residential Buildings,

192

Modeling of CO2 Reduction Impacts on Energy Prices with Modelica Philip Machanick1  

E-Print Network [OSTI]

, Peter Fritzson1,2 1 School ITEE, University of Queensland, Australia 2 PELAB, Department of ComputerModeling of CO2 Reduction Impacts on Energy Prices with Modelica Philip Machanick1 , Ariel Liebman1 at the ap- propriate rate. In this paper we present a Modelica model which explores the trade

Machanick, Philip

193

Renewable Energy RFPs: Solicitation Response and Wind ContractPrices  

SciTech Connect (OSTI)

As input into renewable energy policy discussions in Illinois, we have been asked to provide information on the results of recent, competitive solicitations for renewable energy, with a focus on wind power. In particular, this memorandum includes two pieces of information: (1) Publicly available data on the strength of response to recent renewable energy solicitations; and (2) Wind power purchase costs as revealed through actual power purchase agreements with electric utilities.

Wiser, Ryan; Bolinger, Mark

2005-04-18T23:59:59.000Z

194

Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis-2013  

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

8 8 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2013 Annual Supplement to NIST Handbook 135 and NBS Special Publication 709 Amy S. Rushing Joshua D. Kneifel Barbara C. Lippiatt http://dx.doi.org/10.6028/NIST.IR.85-3273-28 U.S. DEPARTMENT OF COMMERCE Technology Administration National Institute of Standards and Technology Prepared for United States Department of Energy Federal Energy Management Program April 2005 NISTIR 85-3273-28 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2013 Annual Supplement to NIST Handbook 135 and NBS Special Publication 709 Amy S. Rushing Joshua D. Kneifel Barbara C. Lippiatt Applied Economics Office Engineering Laboratory http://dx.doi.org/10.6028/NIST.IR.85-3273-28

195

Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2012  

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

7 7 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2012 Annual Supplement to NIST Handbook 135 and NBS Special Publication 709 Amy S. Rushing Joshua D. Kneifel Barbara C. Lippiatt http://dx.doi.org/10.6028/NIST.IR.85-3273-27 U.S. DEPARTMENT OF COMMERCE Technology Administration National Institute of Standards and Technology Prepared for United States Department of Energy Federal Energy Management Program April 2005 NISTIR 85-3273-27 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2012 Annual Supplement to NIST Handbook 135 and NBS Special Publication 709 Amy S. Rushing Joshua D. Kneifel Barbara C. Lippiatt Applied Economics Office Engineering Laboratory http://dx.doi.org/10.6028/NIST.IR.85-3273-27

196

EIA - The National Energy Modeling System: An Overview 2003 - Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface The National Energy Modeling System: An Overview 2003 Preface The National Energy Modeling System: An Overview 2003 provides a summary description of the National Energy Modeling System (NEMS), which was used to generate the forecasts of energy production, demand, imports, and prices through the year 2025 for the Annual Energy Outlook 2003 (AEO2003), (DOE/EIA-0383(2003)), released in January 2003. AEO2003 presents national forecasts of energy markets for five primary cases—a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The Overview presents a brief description of the methodology and scope of each of the component modules of NEMS. The model documentation reports listed in the appendix of this document provide further details.

197

A Survey of Utility Experience with Real Time Pricing  

E-Print Network [OSTI]

with Real Time Pricing Xcel Energy (Public Service Companywith Real Time Pricing Xcel Energy, MDC (MinnesotaUtilities Division). 2001. Xcel Energys Real-Time Pricing

Barbose, Galen; Goldman, Charles; Neenan, Bernie

2004-01-01T23:59:59.000Z

198

Prices and Price Setting.  

E-Print Network [OSTI]

??abstractThis thesis studies price data and tries to unravel the underlying economic processes of why firms have chosen these prices. It focuses on three aspects (more)

R.P. Faber (Riemer)

2010-01-01T23:59:59.000Z

199

What Is Price Volatility  

Gasoline and Diesel Fuel Update (EIA)

What Is Price Volatility? What Is Price Volatility? The term "price volatility" is used to describe price fluctuations of a commodity. Volatility is measured by the day-to-day percentage difference in the price of the commodity. The degree of variation, not the level of prices, defines a volatile market. Since price is a function of supply and demand, it follows that volatility is a result of the underlying supply and demand characteristics of the market. Therefore, high levels of volatility reflect extraordinary characteristics of supply and/or demand. Prices of basic energy (natural gas, electricity, heating oil) are generally more volatile than prices of other commodities. One reason that energy prices are so volatile is that many consumers are extremely limited in their ability to substitute other fuels when the price, of natural gas

200

Time of Use Energy Pricing Memo December 17, 2013  

E-Print Network [OSTI]

. Unfortunately in Minnesota, Xcel Energy, the largest investor owned utility in the state, only offers time the implementation responsibility in the hands of utilities rather than through blunt government mandates that force Utilities Commission 121 7th Place East, Suite 350 Saint Paul, MN 55101-2147 Governor Dayton and Public

Kammen, Daniel M.

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

Exchange rate effect on carbon credit price via energy markets  

Science Journals Connector (OSTI)

Abstract This paper examines the impact of currency exchange rates on the carbon market. We scrutinize this effect through the European Union Emission Trading Scheme (EU-ETS), which primarily uses two substitutable fossil energy inputs for the generation of electricity: coal and natural gas. The European coal market is directly driven by global coal markets that are denominated in USD, whereas, natural gas is mainly imported from Russia and is denominated in Euros. The impulse response functions of a Structural Vector Autoregression (SVAR) model demonstratethat a shock in the Euro/USD exchange rate can be transmitted through the channel of energy substitution between coal and natural gas, and influence on the carbon credit market.

Jongmin Yu; Mindy L. Mallory

2014-01-01T23:59:59.000Z

202

Assessment and Suggestions to Improve the Commercial Building Module of EIA-NEMS  

E-Print Network [OSTI]

use from the base case divided by the total change in lighting electricity use from the base case. VI LIST OF FIGURES Figure 1. Impact of lighting energy reduction on heating and cooling energy use in the large office building Figure 2. Impact...-South-Central) for the Commercial Sector Demand Module of NEMS. Units are in MBtu/sq.ft./year. E = Electricity NG = Natural Gas O = Other LA This was usually done by metering consumption before and after the retrofit and then analyzing the data to account for weather and changes...

O'Neal, D. L.; Reddy, T. A.; Sucher, B.

1996-01-01T23:59:59.000Z

203

An Analysis of the Effects of Residential Photovoltaic Energy Systems on Home Sales Prices in California  

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

4476E 4476E An Analysis of the Effects of Residential Photovoltaic Energy Systems on Home Sales Prices in California Ben Hoen, Ryan Wiser, Peter Cappers and Mark Thayer Environmental Energy Technologies Division April 2011 Download from http://eetd.lbl.gov/ea/emp/reports/lbnl-4476e.pdf This work was supported by the Office of Energy Efficiency and Renewable Energy (Solar Energy Technologies Program) of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, by the National Renewable Energy Laboratory under Contract No. DEK-8883050, and by the Clean Energy States Alliance. ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Disclaimer This document was prepared as an account of work sponsored by the United States Government.

204

The National Energy Modeling System: An Ocerview 2000 - Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface The National Energy Modeling System: An Overview provides a summary description of the National Energy Modeling System (NEMS), which was used to generate the forecasts of energy production, demand, imports, and prices through the year 2020 for the Annual Energy Outlook 2000 (AEO2000), (DOE/EIA-0383(2000)), released in November 1999. AEO2000 presents national forecasts of energy markets for five cases—a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The Overview presents a brief description of the methodology and scope of each of the component modules of NEMS. The model documentation reports listed in the appendix of this document provide further details.

205

Scenarios for Benefits Analysis of Energy Research, Development,Demonstration and Deployment  

SciTech Connect (OSTI)

For at least the last decade, evaluation of the benefits of research, development, demonstration, and deployment (RD3) by the U.S. Department of Energy has been conducted using deterministic forecasts that unrealistically presume we can precisely foresee our future 10, 25,or even 50 years hence. This effort tries, in a modest way, to begin a process of recognition that the reality of our energy future is rather one rife with uncertainty. The National Energy Modeling System (NEMS) is used by the Department of Energy's Office of Energy Efficiency and Renewable Energy (EE) and Fossil Energy (FE) for their RD3 benefits evaluation. In order to begin scoping out the uncertainty in these deterministic forecasts, EE and FE designed two futures that differ significantly from the basic NEMS forecast. A High Fuel Price Scenario and a Carbon Cap Scenario were envisioned to forecast alternative futures and the associated benefits. Ernest Orlando Lawrence Berkeley National Laboratory (LBNL) implemented these scenarios into its version of NEMS,NEMS-LBNL, in late 2004, and the Energy Information Agency created six scenarios for FE in early 2005. The creation and implementation of the EE-FE scenarios are explained in this report. Both a Carbon Cap Scenario and a High Fuel Price Scenarios were implemented into the NEMS-LBNL. EIA subsequently modeled similar scenarios using NEMS. While the EIA and LBNL implementations were in some ways rather different, their forecasts do not significantly diverge. Compared to the Reference Scenario, the High Fuel Price Scenario reduces energy consumption by 4 percent in 2025, while in the EIA fuel price scenario (known as Scenario 4) reduction from its corresponding reference scenario (known as Scenario 0) in 2025 is marginal. Nonetheless, the 4 percent demand reduction does not lead to other cascading effects that would significantly differentiate the two scenarios. The LBNL and EIA carbon scenarios were mostly identical. The only major difference was that LBNL started working with the AEO 2004NEMS code and EIA was using AEO 2005 NEMS code. Unlike the High Price Scenario the Carbon Cap scenario gives a radically different forecast than the Reference Scenario. NEMS-LBNL proved that it can handle these alternative scenarios. However, results are price inelastic (for both oil and natural gas prices) within the price range evaluated. Perhaps even higher price paths would lead to a distinctly different forecast than the Reference Scenario. On the other hand, the Carbon Cap Scenario behaves more like an alternative future. The future in the Carbon Cap Scenario has higher electricity prices, reduced driving, more renewable capacity, and reduced energy consumption. The next step for this work is to evaluate the EE benefits under each of the three scenarios. Comparing those three sets of predicted benefits will indicate how much uncertainty is inherent within this sort of deterministic forecasting.

Gumerman, Etan; Marnay, Chris

2005-09-07T23:59:59.000Z

206

Strategic Pricing and Resource Allocation: Framework and Applications  

E-Print Network [OSTI]

varying wireless network capacities, electricity prices,electricity price, avail- able renewable energy supply, wireless

Ren, Shaolei

2012-01-01T23:59:59.000Z

207

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 23 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 International Energy Module The NEMS International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, the NEMS IEM computes world oil prices, provides a supply curve of world crude-like liquids, generates a worldwide oil supply- demand balance with regional detail, and computes quantities of crude oil and light and heavy petroleum products imported into

208

Energy futures prices and commodity index investment: New evidence from firm-level position data  

Science Journals Connector (OSTI)

Abstract This study brings fresh data to the highly-charged debate about the price impact of long-only index investment in energy futures markets. We use high frequency daily position data for NYMEX crude oil, heating oil, RBOB gasoline, and natural gas that are available from a representative large commodity index fund (the Fund) from February 13, 2007 through May 30, 2012. Simple correlation tests, difference-in-means tests, and Granger causality tests generally fail to reject the null hypothesis that changes in Fund positions are unrelated to subsequent returns in all four energy futures markets. We also fail to find any evidence that Fund positions are related to price movements in the WTI crude oil futures market using Singleton's (2014) long-horizon regression specification. Our results suggest Singleton's original finding of significant impacts and high levels of predictability may be simply an artifact of the method used to impute crude oil positions of index investors in a particular sample period. Overall, the empirical tests in this study fail to find compelling evidence of predictive links between commodity index investment and changes in energy futures prices.

Dwight R. Sanders; Scott H. Irwin

2014-01-01T23:59:59.000Z

209

All-nanophotonic NEMS biosensor on a chip  

E-Print Network [OSTI]

Integrated chemical and biological sensors give advantages in cost, size and weight reduction and open new prospects for parallel monitoring and analysis. Biosensors based on nanoelectromechanical systems (NEMS) are the most attractive candidates for the integrated platform. However, actuation and transduction techniques (e.g. electrostatic, magnetomotive, thermal or piezoelectric) limit their operation to laboratory conditions. All-optical approach gives the possibility to overcome this problem, nevertheless, the existing schemes are either fundamentally macroscopic or excessively complicated and expensive in mass production. Here we propose a novel scheme of extremely compact NEMS biosensor monolithically integrated on a chip with all-nanophotonic transduction and actuation. It consists of the photonic waveguide and the nanobeam cantilever placed above the waveguide, both fabricated in the same CMOS-compatible process. Being in the near field of the strongly confined photonic mode, cantilever is efficiently...

Fedyanin, Dmitry Yu

2014-01-01T23:59:59.000Z

210

Assumptions to the Annual Energy Outlook 2002 - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2002, DOE/EIA- M068(2002) January 2002. 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

211

Assumptions to the Annual Energy Outlook 2001 - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2001, DOE/EIA- M068(2001) January 2001. 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

212

Distributed Energy Consumption Control via Real-TimePricing Feedback in Smart Grid  

E-Print Network [OSTI]

provider publishes the electricity price p(l k ), and thethe announcement of electricity price [5]. Recently, game3. The role of the electricity price is similar to the lever

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

2014-01-01T23:59:59.000Z

213

Table 7.2 Average Prices of Purchased Energy Sources, 2010;  

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

Table 7.2 Average Prices of Purchased Energy Sources, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: All Energy Sources Collected; Unit: U.S. Dollars per Million Btu. Selected Wood and Other Biomass Components Coal Components Coke Electricity Components Natural Gas Components Steam Components Total Wood Residues Bituminous Electricity Diesel Fuel Motor Natural Gas Steam and Wood-Related and Electricity from Sources and Gasoline Pulping Liquor Natural Gas from Sources Steam from Sources Waste Gases Waste Oils Industrial Wood Byproducts and NAICS Coal Subbituminous Coal Petroleum Electricity from Local Other than Distillate Diesel Distillate Residual Blast Coke Oven (excluding or LPG and Natural Gas from Local

214

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

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

case tables Appendix B Economic growth cases comparisons tables Appendix C Oil price cases comparisons tables Appendix D Results from side cases tables Appendix E: NEMS...

215

Residential propane price  

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

propane price decrease The average retail price for propane is 2.37 per gallon, down 1.3 cents from last week, based on the residential heating fuel survey by the U.S. Energy...

216

Residential propane price  

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

propane price decreases The average retail price for propane is 2.35 per gallon, down 1.1 cents from last week, based on the residential heating fuel survey by the U.S. Energy...

217

Residential propane price  

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

propane price decreases The average retail price for propane is 2.36 per gallon, down 1 cent from last week, based on the residential heating fuel survey by the U.S. Energy...

218

Residential propane prices increase  

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

propane prices increase The average retail price for propane rose to 2.40 per gallon, up 1.1 cents from a week ago, based on the residential heating fuel survey by the U.S. Energy...

219

Residential propane prices available  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

propane prices available The average retail price for propane is 2.30 per gallon, based on the U.S. Energy Information Administration's weekly residential heating fuel survey....

220

Residential propane prices stable  

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

propane prices stable The average retail price for propane is 2.37 per gallon. That's down 4-tenths of a penny from a week ago, based on the U.S. Energy Information...

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

EIA - Assumptions to the Annual Energy Outlook 2008 - International Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2008 International Energy Module The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously global and U.S.A. petroleum liquids supply and demand curves (1 curve per year; 2008-2030; approximated, isoelastic fit to previous NEMS results). These quantities are not modeled directly in NEMS. Previous versions of the IEM adjusted these quantities after reading in initial values. In an attempt to more closely integrate the AEO2008 with IEO2007 and the STEO some functionality was removed from IEM while a new algorithm was implemented. Based on the difference between U.S. total petroleum liquids production (consumption) and the expected U.S. total liquids production (consumption) at the current WTI price, curves for global petroleum liquids consumption (production) were adjusted for each year. According to previous operations, a new WTI price path was generated. An exogenous oil supply module, Generate World Oil Balances (GWOB), was also used in IEM to provide annual regional (country) level production detail for conventional and unconventional liquids.

222

Assessing the impact of changes in the electricity price structure on dairy farm energy costs  

Science Journals Connector (OSTI)

Abstract This study aims to provide information on the changes in electricity consumption and costs on dairy farms, through the simulation of various electricity tariffs that may exist in the future and how these tariffs interact with changes in farm management (i.e. shifting the milking operation to an earlier or later time of the day). A previously developed model capable of simulating electricity consumption and costs on dairy farms (MECD) was used to simulate five different electricity tariffs (Flat, Day&Night, Time of Use Tariff 1 (TOU1), TOU2 and Real Time Pricing (RTP)) on three representative Irish dairy farms: a small farm (SF), a medium farm (MF) and a large farm (LF). The Flat tariff consisted of one electricity price for all time periods, the Day&Night tariff consisted of two electricity prices, a high rate from 09:00 to 00:00h and a low rate thereafter. The TOU tariff structure was similar to that of the Day&Night tariff except that a peak price band was introduced between 17:00 and 19:00h. The RTP tariff varied dynamically according to the electricity demand on the national grid. The model used in these simulations was a mechanistic mathematical representation of the electricity consumption that simulated farm equipment under the following headings; milk cooling system, water heating system, milking machine system, lighting systems, water pump systems and the winter housing facilities. The effect of milking start time was simulated to determine the effect on electricity consumption and costs at farm level. The earliest AM milking start time and the latest PM milking start time resulted in the lowest energy consumption. The difference between the lowest and highest electricity consumption within a farm was 7% for SF, 5% for MF and 5% for LF. This difference was accounted for by the variation in the milk cooling system coefficient of performance. The greatest scope to reduce total annual electricity costs by adjusting milking start times was on TOU2 (39%, 34% and 33% of total annual electricity costs on the SF, MF and LF) and the least scope for reductions using this method was on the Flat tariff (7%, 5% and 7% of total annual electricity costs). The potential for reduction of annual electricity consumption and related costs per litre of milk produced by adjusting milking times was higher for the LF than the SF or MF across all electricity tariffs. It is anticipated that these results and the use of the MECD will help support the decision-making process at farm level around increasing energy efficiency and electricity cost forecasts in future electricity pricing tariff structures.

J. Upton; M. Murphy; L. Shalloo; P.W.G. Groot Koerkamp; I.J.M. De Boer

2015-01-01T23:59:59.000Z

223

An Analysis of the Effects of Residential Photovoltaic Energy Systems on Home Sales Prices in California  

SciTech Connect (OSTI)

An increasing number of homes in the U.S. have sold with photovoltaic (PV) energy systems installed at the time of sale, yet relatively little research exists that estimates the marginal impacts of those PV systems on home sale prices. A clearer understanding of these possible impacts might influence the decisions of homeowners considering the installation of a PV system, homebuyers considering the purchase of a home with PV already installed, and new home builders considering including PV as an optional or standard product on their homes. This research analyzes a large dataset of California homes that sold from 2000 through mid-2009 with PV installed. It finds strong evidence that homes with PV systems sold for a premium over comparable homes without PV systems during this time frame. Estimates for this premium expressed in dollars per watt of installed PV range, on average, from roughly $4 to $5.5/watt across a large number of hedonic and repeat sales model specifications and robustness tests. When expressed as a ratio of the sales price premium of PV to estimated annual energy cost savings associated with PV, an average ratio of 14:1 to 19:1 can be calculated; these results are consistent with those of the more-extensive existing literature on the impact of energy efficiency on sales prices. When the data are split among new and existing homes, however, PV system premiums are markedly affected. New homes with PV show premiums of $2.3-2.6/watt, while existing homes with PV show premiums of more than $6/watt. Reasons for this discrepancy are suggested, yet further research is warranted. A number of other areas where future research would be useful are also highlighted.

Hoen, Ben; Cappers, Peter; Wiser, Ryan; Thayer, Mark

2011-04-19T23:59:59.000Z

224

Gas Prices: Frequently Asked Questions  

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

Prices: Frequently Asked Questions Prices: Frequently Asked Questions What determines the price of gasoline? Energy Information Administration What's going on with gasoline prices? Factors Affecting Gasoline Prices This Week in Petroleum (updated weekly) Gasoline Price Pass-through Oil Market Basics Primer on Gasoline Sources and Markets What's up (and down) with gasoline prices? Illustration showing component costs of gasoline What are the average national and regional gasoline prices? Energy Information Administration Gasoline and Diesel Fuel Update (updated weekly) This Week in Petroleum (updated weekly) California Energy Commission California Gasoline & Gasoline Prices What is the outlook for gasoline prices? Energy Information Administration Short-Term Energy Outlook Why are gasoline prices so different from one state (or region) to another?

225

Table 7.4 Average Prices of Selected Purchased Energy Sources, 2010;  

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

4 Average Prices of Selected Purchased Energy Sources, 2010; 4 Average Prices of Selected Purchased Energy Sources, 2010; Level: National and Regional Data; Row: Values of Shipments and Employment Sizes; Column: Energy Sources; Unit: U.S. Dollars per Physical Units. Residual Distillate LPG and Economic Electricity Fuel Oil Fuel Oil(b) Natural Gas(c) NGL(d) Coal Characteristic(a) (kWh) (gallons) (gallons) (1000 cu ft) (gallons) (short tons) Total United States Value of Shipments and Receipts (million dollars) Under 20 0.093 1.55 2.58 6.64 1.80 78.29 20-49 0.075 1.66 2.45 6.44 1.80 80.13 50-99 0.070 1.64 1.79 6.04 2.19 68.10 100-249 0.061 1.62 2.38 5.51 1.69 100.69 250-499 0.056 1.69 2.41 5.54 1.59 92.51 500 and Over 0.054 1.54 2.35 5.08 1.15 96.25 Total

226

Table 7.1 Average Prices of Purchased Energy Sources, 2010  

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

Average Prices of Purchased Energy Sources, 2010; Average Prices of Purchased Energy Sources, 2010; Level: National and Regional Data; Row: NAICS Codes; Column: All Energy Sources Collected; Unit: U.S. Dollars per Physical Units. Coal NAICS TOTAL Acetylene Breeze Total Anthracite Code(a) Subsector and Industry (million Btu) (cu ft) (short tons) (short tons) (short tons) Total United States 311 Food 9.12 0.26 0.00 53.43 90.85 3112 Grain and Oilseed Milling 6.30 0.29 0.00 51.34 50.47 311221 Wet Corn Milling 4.87 0.48 0.00 47.74 50.47 31131 Sugar Manufacturing 5.02 0.31 0.00 53.34 236.66 3114 Fruit and Vegetable Preserving and Specialty Foods 9.78 0.27 0.00 90.59 0.00 3115 Dairy Products 11.21 0.10 0.00 103.12 0.00 3116 Animal Slaughtering and Processing

227

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

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases Table E1. Summary of the AEO2011 cases Reference Baseline economic growth (2.7 percent per year from 2009 through 2035), world oil price, and technology assumptions. Complete projection tables in Appendix A. World light, sweet crude oil prices rise to about $125 per barrel by 2035 in year 2009 dollars. Assumes RFS target to be met as soon as possible. Fully integrated Low Economic Growth Real GDP grows at an average annual rate of 2.1 percent from 2009 to 2035. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B. Fully integrated High Economic Growth Real GDP grows at an average annual rate of 3.2 percent from 2009 to 2035. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B. Fully integrated

228

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

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases Table E1. Summary of the AEO2012 cases Reference Baseline economic growth (2.5 percent per year from 2010 through 2035), oil price, and technology assumptions. Complete projection tables in Appendix A. Light, sweet crude oil prices rise to about $145 per barrel (2010 dollars) in 2035. Assumes RFS target to be met as soon as possible. Low Economic Growth Real GDP grows at an average annual rate of 2.0 percent from 2010 to 2035. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B.. High Economic Growth Real GDP grows at an average annual rate of 3.0 percent from 2010 to 2035. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B.

229

Annual Energy Outlook 2000  

Gasoline and Diesel Fuel Update (EIA)

Homepage Homepage Preface The Annual Energy Outlook 2000 (AEO2000) presents midterm forecasts of energy supply, demand, and prices through 2020 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA’s National Energy Modeling System (NEMS). The report begins with an “Overview” summarizing the AEO2000 reference case. The next section, “Legislation and Regulations,” describes the assumptions made with regard to laws that affect energy markets and discusses evolving legislative and regulatory issues. “Issues in Focus” discusses current energy issues—appliance standards, gasoline and diesel fuel standards, natural gas industry expansion, competitive electricity pricing, renewable portfolio standards, and carbon emissions. It is followed by the analysis of energy market trends.

230

WEEK'S PRICE CHANGES  

Science Journals Connector (OSTI)

Stauffer reduces prices on a high energy fuel raw materialboron trichloride. ... In 100-pound cylinders the chemical's price was dropped from $3.99 to $1.70 a pound, and in ton cylinders it is now priced at $1.25 a pound. ...

1957-07-29T23:59:59.000Z

231

Value seeking, price sensitive, or green? Analyzing preference heterogeneity among residential energy consumers in Denmark  

Science Journals Connector (OSTI)

Abstract This study examines the heterogeneous consumer preference for electricity products in the residential electricity retailing market. Based on consumers trade-off decision making, we identified three distinct consumer segments: the value seeking consumers (53%), the price sensitive consumers (25%), and the green consumers (22%). We concluded that consumers are willing to pay extra for the increasing share of renewable energy. Consumer socio-demographic characteristics had also influence on their choices for electricity products. The findings of this study can help explain how different consumer segment can be affected by the change of electricity product attributes. Thus, it provides insightful knowledge on how to differentiate electricity products so as to satisfy specific consumer segments needs. Finally, the findings of this study have implications for energy policy makers (regulators) on consumers preference for electricity products assuming that consumers should make a choice among various products.

Yingkui Yang; Hans Stubbe Solgaard; Wolfgang Haider

2015-01-01T23:59:59.000Z

232

The impact of rising energy prices on household energy consumption and expenditure patterns: The Persian Gulf crisis as a case example  

SciTech Connect (OSTI)

The Iraqi invasion of Kuwait and the subsequent war between Iraq and an international alliance led by the United States triggered immediate increases in world oil prices. Increases in world petroleum prices and in US petroleum imports resulted in higher petroleum prices for US customers. In this report, the effects of the Persian Gulf War and its aftermath are used to demonstrate the potential impacts of petroleum price changes on majority, black, and Hispanic households, as well as on poor and nonpoor households. The analysis is done by using the Minority Energy Assessment Model developed by Argonne National Laboratory for the US Department of Energy (DOE). The differential impacts of these price increases and fluctuations on poor and minority households raise significant issues for a variety of government agencies, including DOE. Although the Persian Gulf crisis is now over and world oil prices have returned to their prewar levels, the differential impacts of rising energy prices on poor and minority households as a result of any future crisis in the world oil market remains a significant long-term issue.

Henderson, L.J. (Baltimore Univ., MD (United States)); Poyer, D.A.; Teotia, A.P.S. (Argonne National Lab., IL (United States). Energy Systems Div.)

1992-09-01T23:59:59.000Z

233

Essays on price dynamics, discovery, and dynamic threshold effects among energy spot markets in North America  

E-Print Network [OSTI]

stylized facts concerning electricity prices: high volatility, mean-reversion, seasonality, and frequent extreme jumps in prices (Huisman and Mahieu, 2003). See Bunn (2004) for more studies concerning modeling electricity prices. De Vany and Walls (1999... or five trading days) convergence with respect to external shocks. Jerko, Mjelde, and Bessler (2004) using directed graphs to examine the contemporaneous causal flows 9 among spot markets suggested electricity price information flows...

Park, Haesun

2005-11-01T23:59:59.000Z

234

The Influence of a CO2 Pricing Scheme on Distributed Energy Resources in California's Commercial Buildings  

E-Print Network [OSTI]

2 pricing scheme or a feed-in tariff (FiT), and show theira CO 2 pricing scheme and a feed-in-tariff for DER and CHPCO 2 pricing scheme or feed-in tariff (FiT). Only 30.3 MW of

Stadler, Michael

2010-01-01T23:59:59.000Z

235

An Analysis of the Effects of Photovoltaic Energy Systems on Residential Selling Prices in California.  

SciTech Connect (OSTI)

An increasing number of homes with existing photovoltaic (PV) energy systems have sold in the U.S., yet relatively little research exists that estimates the marginal impacts of those PV systems on the sales price. A clearer understanding of these effects might influence the decisions of homeowners, home buyers and PV home builders. This research analyzes a large dataset of California homes that sold from 2000 through mid-2009 with PV installed. Across a large number of hedonic and repeat sales model specifications and robustness tests, the analysis finds strong evidence that homes with PV systems sold for a premium over comparable homes without. The effects range, on average, from approximately $3.9 to $6.4 per installed watt (DC), with most models coalescing near $5.5/watt, which corresponds to a premium of approximately $17,000 for a 3,100 watt system. The research also shows that, as PV systems age, the premium enjoyed at the time of home sale decreases. Additionally, existing homes with PV systems are found to have commanded a larger sales price premium than new homes with similarly sized PV systems. Reasons for this discrepancy are suggested, yet further research is warranted in this area as well as a number of other areas that are highlighted.

Cappers, Peter; Wiser, Ryan; Thayer, Mark; Hoen, Ben

2011-04-12T23:59:59.000Z

236

Average Commercial Price  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 1231 Reserves...

237

Gasoline Prices at Historical Lows  

Gasoline and Diesel Fuel Update (EIA)

0 0 Notes: Before looking at El Paso gasoline prices, let’s take a minute to look at the U.S. average price for context. Gasoline prices this year, adjusted for inflation, are the lowest ever. Back in March, before prices began to rise ahead of the traditional high-demand season, the U.S. average retail price fell to $1.00 per gallon. Prices rose an average of 7.5 cents, less than the typical seasonal runup, to peak in early June. Since then, prices have fallen back to $1.013. Given recent declines in crude oil and wholesale gasoline prices, we expect retail prices to continue to ease over at least the next few weeks. Since their sharp runup during the energy crises of the 1970’s, gasoline prices have actually been non-inflationary. Adjusting the historical prices by the Consumer Price Index, we can see that today’s

238

Do Photovoltaic Energy Systems Effect Residential Selling Prices? Results from a California Statewide Investigation.  

SciTech Connect (OSTI)

An increasing number of homes in the U.S. have sold with photovoltaic (PV) energy systems installed at the time of sale, yet relatively little research exists that provides estimates of the marginal impacts of those PV systems on home sale prices. This research analyzes a large dataset of California homes that sold from 2000 through mid-2009 with PV installed. We find strong evidence that homes with PV systems sold for a premium over comparable homes without PV systems during this time frame. Estimates for this premium expressed in dollars per watt of installed PV range, from roughly $4 to $6.4/watt across the full dataset, to approximately $2.3/watt for new homes, to more than $6/watt for existing homes. A number of ideas for further research are suggested.

Hoen, Ben; Cappers, Pete; Wiser, Ryan; Thayer, Mark

2011-04-12T23:59:59.000Z

239

Annual energy outlook 1997 with projections to 2015  

SciTech Connect (OSTI)

The Annual Energy Outlook 1997 (AEO97) presents midterm forecasts of energy supply, demand, and prices through 2015 prepared by the Energy Information Administration (EIA). These projections are based on results of EIA`s National Energy Modeling System (NEMS). This report begins with a summary of the reference case, followed by a discussion of the legislative assumptions and evolving legislative and regulatory issues. ``Issues in Focus`` discusses emerging energy issues and other topics of particular interest. It is followed by the analysis of energy market trends. The analysis in AEO97 focuses primarily on a reference case and four other cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. Forecast tables for these cases are provided in Appendixes A through C. Appendixes D and E present summaries of the reference case forecasts in units of oil equivalence and household energy expenditures. Twenty-three other cases explore the impacts of varying key assumptions in NEMS--generally, technology penetration, with the major results shown in Appendix F. Appendix G briefly describes NEMS and the major AEO97 assumptions, with a summary table. 114 figs., 22 tabs.

NONE

1996-12-01T23:59:59.000Z

240

Table ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States  

Gasoline and Diesel Fuel Update (EIA)

ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States ET1. Primary Energy, Electricity, and Total Energy Price and Expenditure Estimates, Selected Years, 1970-2011, United States Year Primary Energy Electric Power Sector h,j Retail Electricity Total Energy g,h,i Coal Coal Coke Natural Gas a Petroleum Nuclear Fuel Biomass Total g,h,i,j Coking Coal Steam Coal Total Exports Imports Distillate Fuel Oil Jet Fuel b LPG c Motor Gasoline d Residual Fuel Oil Other e Total Wood and Waste f,g Prices in Dollars per Million Btu 1970 0.45 0.36 0.38 1.27 0.93 0.59 1.16 0.73 1.43 2.85 0.42 1.38 1.71 0.18 1.29 1.08 0.32 4.98 1.65 1975 1.65 0.90 1.03 2.37 3.47 1.18 2.60 2.05 2.96 4.65 1.93 2.94 3.35 0.24 1.50 2.19 0.97 8.61 3.33 1980 2.10 1.38 1.46 2.54 3.19 2.86 6.70 6.36 5.64 9.84 3.88 7.04 7.40 0.43 2.26 4.57 1.77 13.95 6.89 1985 2.03 1.67 1.69 2.76 2.99 4.61 7.22 5.91 6.63 9.01 4.30 R 7.62 R 7.64 0.71 2.47 4.93 1.91 19.05

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

Demand side management of industrial electricity consumption: Promoting the use of renewable energy through real-time pricing  

Science Journals Connector (OSTI)

Abstract As the installed capacity of wind generation in Ireland continues to increase towards an overall goal of 40% of electricity from renewable sources by 2020, it is inevitable that the frequency of wind curtailment occurrences will increase. Using this otherwise discarded energy by strategically increasing demand at times that would otherwise require curtailment has the potential to reduce the installed capacity of wind required to meet the national 2020 target. Considering two industrial electricity consumers, this study analyses the potential for the implementation of price based demand response by an industrial consumer to increase their proportional use of wind generated electricity by shifting their demand towards times of low prices. Results indicate that while curtailing during peak price times has little or no benefit in terms of wind energy consumption, demand shifting towards low price times is likely to increase a consumers consumption of wind generation by approximately 5.8% for every 10% saved on the consumers average unit price of electricity.

Paddy Finn; Colin Fitzpatrick

2014-01-01T23:59:59.000Z

242

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,

243

The Value of Renewable Energy as a Hedge Against Fuel Price Risk: Analytic Contributions from Economic and Finance Theory  

E-Print Network [OSTI]

2003. Accounting for Fuel Price Risk: Using Forward Natural2006. Accounting for Fuel Price Risk When Comparingdraft). Analyzing Fuel Price Risks Under Competitive

Bolinger, Mark A

2009-01-01T23:59:59.000Z

244

Energy tax price tag for CPI: $1. 2 billion, jobs, and production  

SciTech Connect (OSTI)

If President Clinton's proposed energy tax had been fully in place last year, it would have cost the US chemical industry an additional $1.2 billion and 9,900 jobs, according to Chemical Manufacturers Association (CMA; Washington) estimates. It also would have driven output down 3% and prices up 5%, CMA says. Allen Lenz, CMA director/trade and economics, says the increase in production costs that would accompany the tax will not be shared by foreign competitors, cannot be neutralized with higher border taxes because of existing trade agreements, and provides another reason to move production offshore. Worse, the US chemical industry's generally impressive trade surplus declined by $2.5 billion last year, and a further drop is projected for this year. The margin of error gets thinner all the time as competition increases, Lenz says. We're not concerned only with the chemical industry, but the rest of US-based manufacturing because they taken half our output, he adds. One problem is the energy intensiveness of the chemical process industries-a CMA report says that 55% of the cost of producing ethylene glycol is energy related. And double taxation of such things as coproducts returned for credit to oil refineries could add up to $115 million/year, the report says.

Begley, R.

1993-03-03T23:59:59.000Z

245

Tariff-based analysis of commercial building electricity prices  

E-Print Network [OSTI]

4 Calculation of Electricity Prices 4.1 Averageaverage seasonal and annual electricity prices by region inbased annual average electricity price vs. annual energy

Coughlin, Katie M.; Bolduc, Chris A.; Rosenquist, Greg J.; Van Buskirk, Robert D.; McMahon, James E.

2008-01-01T23:59:59.000Z

246

Scheduling in an Energy Cost Aware Environment The energy cost aware scheduling problem (ECASP) is concerned with variable electricity tariffs, where the price of  

E-Print Network [OSTI]

Scheduling in an Energy Cost Aware Environment The energy cost aware scheduling problem (ECASP) is concerned with variable electricity tariffs, where the price of electricity changes over time depending on the demand. It is important to large scale electricity consumers in manufacturing and service industries

247

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.

248

The potential impact on socio-economic groups of rising energy prices due to the Kuwaiti crisis  

SciTech Connect (OSTI)

The Iraqi invasion of the kingdom of Kuwait on August 2, 1990, triggered immediate increases in the world price of petroleum. With US imports of petroleum and residential, commercial, and industrial consumption of petroleum products on the rise, these price increases are already evident in the US. The differential impact of these increases on poor and minority households raises significant and potentially long-term research and policy issues for various government agencies, including the US Department of Energy. The purpose of this paper is to provide a preliminary analysis of the nature and extent of the potential impact of Iraqi-induced petroleum price changes on majority, black, and Hispanic households, as well as on poor and non-poor households. As this paper is written, the US is continuing the deployment of several hundred thousand troops, aircraft, naval vessels, and other equipment to the Persian Gulf. The objectives of this deployment are to deter Iraqi invasion of Saudi Arabia and to encourage Iraqi withdrawal from Kuwait. The outcome of these initiatives, particularly the response of the government of Iraq, could stimulate additional changes in world petroleum prices and subsequent impacts on the household energy consumption and expenditure patterns of US black, Hispanic, and poor households. 8 refs., 16 figs., 5 tabs.

Henderson, L. (Baltimore Univ., MD (USA)); Poyer, D.; Teotia, A.

1990-01-01T23:59:59.000Z

249

prices | OpenEI  

Open Energy Info (EERE)

prices prices 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 12, and contains only the reference case. The dataset uses 2009 dollars per gallon. The data is broken down into crude oil prices, residential, commercial, industrial, transportation, electric power and refined petroleum product prices. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Petroleum prices Data application/vnd.ms-excel icon AEO2011: Petroleum Product Prices- Reference Case (xls, 129.9 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period 2008-2035

250

Gasoline Price Pass-through  

Gasoline and Diesel Fuel Update (EIA)

Gasoline Price Pass-through Gasoline Price Pass-through January 2003 by Michael Burdette and John Zyren* The single most visible energy statistic to American consumers is the retail price of gasoline. While the average consumer probably has a general notion that gasoline prices are related to those for crude oil, he or she likely has little idea that gasoline, like most other goods, is priced at many different levels in the marketing chain, and that changes ripple through the system as prices rise and fall. When substantial price changes occur, especially upward, there are often allegations of impropriety, even price gouging, on the part of petroleum refiners and/or marketers. In order to understand the movement of gasoline prices over time, it is necessary to examine the relationship between prices at retail and various wholesale levels.

251

The Incremental Benefits of the Nearest Neighbor Forecast of U.S. Energy Commodity Prices  

E-Print Network [OSTI]

of the prices from 33 U.S. cities.2 Crude oil data covers January 1986 to June 2010. The data are monthly. It was taken from Cushing, OK WTI3 Spot Price FOB and are expressed in dollars per barrel. Heating oil data covers the period June 1986 to June 2010..., Upstate NY, Cincinnati, Portland, Memphis, Nashville, Houston, Richmond, Seattle, Milwaukie. (Hart?s Oxy Fuel News, 2010) 3 West Texas Intermediate, also known as Texas Light Sweet. WTI is produced in Texas and South Oklahoma. Price from WTI serves...

Kudoyan, Olga

2012-02-14T23:59:59.000Z

252

Fairness and dynamic pricing: comments  

SciTech Connect (OSTI)

In ''The Ethics of Dynamic Pricing,'' Ahmad Faruqui lays out a case for improved efficiency in using dynamic prices for retail electricity tariffs and addresses various issues about the distributional effects of alternative pricing mechanisms. The principal contrast is between flat or nearly constant energy prices and time-varying prices that reflect more closely the marginal costs of energy and capacity. The related issues of fairness criteria, contracts, risk allocation, cost allocation, means testing, real-time pricing, and ethical policies of electricity market design also must be considered. (author)

Hogan, William W.

2010-07-15T23:59:59.000Z

253

Residential heating oil prices available  

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

ago, based on the U.S. Energy Information Administration's weekly residential heating fuel price survey. Heating oil prices in the New England region are at 3.48 per gallon,...

254

EIA - International Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

International Energy Outlook 2007 International Energy Outlook 2007 The International Energy Outlook 2007 (IEO2007) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2030. U.S. projections appearing in IEO2007 are consistent with those published in EIA's Annual Energy Outlook 2007 (AEO2007), which was prepared using the National Energy Modeling System (NEMS). The report is also released in print. Projection Tables Appendix A. Reference Case Appendix B. High Economic Growth Case Appendix C. Low Economic Growth Case Appendix D. High World Oil Price Case Appendix E. Low World Oil Price Case Appendix F. Reference Case Projections by End Use Appendix G. Projections of Petroleum and Other Liquids Productions in Three Cases

255

Energy dependence, oil prices and exchange rates: the Dominican economy since 1990  

Science Journals Connector (OSTI)

This paper studies the impact that oil prices have had on the floating exchange rate ... these two variables for large developed economies and oil-producing countries, always including the 1970s oil crises in the...

Diego Mndez-Carbajo

2011-04-01T23:59:59.000Z

256

Modelling power spot prices in deregulated European energy markets: a dual long memory approach  

Science Journals Connector (OSTI)

In the last decade, with deregulation and introduction of competition in power markets, prices forecasting have become a real challenge for all market participants. However, forecasting is a rather complex task since electricity prices involve many features comparably with financial ones. Electricity markets have a highly volatile nature. They are indeed a more unpredictable than that of other commodities referred to as extreme volatile. In this paper, the two most emerging European electricity markets are considered. A preliminary analysis of the time series attests to the presence of a long range dependance behaviour. Therefore, prices processes are modelled using ARFIMA-FIGARCH under Gaussian and non-Gaussian distributions. Such models are sufficiently flexible to handle the long memory phenomena often encountered in both conditional mean and conditional variance in electricity spot prices. Forecasting is subsequently performed on the basis of adequate models.

Najeh Chaâbane; Foued Saâdaoui; Saloua Benammou

2012-01-01T23:59:59.000Z

257

Renewable Energy Prices in State-Level Feed-in Tariffs: Federal Law Constraints and Possible Solutions  

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

08 08 January 2010 Renewable Energy Prices in State-Level Feed-in Tariffs: Federal Law Constraints and Possible Solutions Scott Hempling National Regulatory Research Institute Silver Spring, Maryland Carolyn Elefant The Law Offices of Carolyn Elefant Washington, D.C. Karlynn Cory National Renewable Energy Laboratory Golden, Colorado Kevin Porter Exeter Associates, Inc. Golden, Colorado National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Operated by the Alliance for Sustainable Energy, LLC Contract No. DE-AC36-08-GO28308 Technical Report NREL/TP-6A2-47408 January 2010

258

Annual Energy Outlook 2006 with Projections to 2030  

Gasoline and Diesel Fuel Update (EIA)

6 6 (AEO2006), pre- pared by the Energy Information Administration (EIA), presents long-term forecasts of energy supply, demand, and prices through 2030. The projections are based on results from EIA's National Energy Modeling System (NEMS). The report begins with an "Overview" summarizing the AEO2006 reference case and comparing it with the AEO2005 reference case. The next section, "Leg- islation and Regulations," discusses evolving legisla- tion and regulatory issues, including recently enacted legislation and regulation, such as the Energy Policy Act of 2005, and some that are proposed. "Issues in Focus" includes a discussion of the basis of EIA's sub- stantial revision of the world oil price trend used in the projections. It also examines the following topics: implications of higher oil price expectations for eco- nomic growth; differences

259

National Laboratory Dorene Price  

E-Print Network [OSTI]

Brookhaven National Laboratory Dorene Price Office of Intellectual Property and Sponsored Research: price@bnl.gov ACTIVATED ALUMINUM HYDRIDE HYDROGEN STORAGE COMPOSITIONS AND USES THEREOF Brookhaven alternatives to increase the fuel economies of vehicles as well as other applications that require an energy

260

Understanding Trends in Wind Turbine Prices Over the Past Decade  

E-Print Network [OSTI]

In comparison, the rise in coal prices has been slower andindustrial price. Finally, coal prices come from Table 4.1Fiberglass Energy Prices Diesel Coal Natural Gas Currency

Bolinger, Mark

2012-01-01T23:59:59.000Z

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

Carbon Price Drivers:Carbon Price Drivers:Carbon Price Drivers:Carbon Price Drivers: AAAAnnnn UpdatedUpdatedUpdatedUpdated Literature ReviewLiterature ReviewLiterature ReviewLiterature Review  

E-Print Network [OSTI]

, such as unexpected fluctuations in energy demand, energy prices (e.g., oil, gas, coal) and weather conditions1 Carbon Price Drivers:Carbon Price Drivers:Carbon Price Drivers:Carbon Price Drivers: AAAAnnnn the factors that shape the price of carbon, where one European Union Allowance is equal to one ton of CO2

Paris-Sud XI, Université de

262

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2006 The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2006, DOE/EIA- M068(2006). 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. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

263

Recycling Guide: Reduce, Reuse, Recycle Recycling Information Call 301-496-7990 or visit the NEMS Website at http://www.nems.nih.gov  

E-Print Network [OSTI]

Recycling Guide: Reduce, Reuse, Recycle Recycling Information ­ Call 301-496-7990 or visit the NEMS in COMMINGLED bin Rinse food/beverage containers before recycling No Pyrex or Styrofoam Printer and Copier Toner Cartridges in TONER CARTRIDGE bin Recycle packaging material in appropriate bin NIH charities

Baker, Chris I.

264

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

2 2 The commercial module forecasts consumption by fuel 13 at the Census division level using prices from the NEMS energy supply modules, and macroeconomic variables from the NEMS Macroeconomic Activity Module (MAM), as well as external data sources (technology characterizations, for example). Energy demands are forecast for ten end-use services 14 for eleven building categories 15 in each of the nine Census divisions (see Figure 5). The model begins by developing forecasts of floorspace for the 99 building category and Census division combinations. Next, the ten end-use service demands required for the projected floorspace are developed. The electricity generation and water and space heating supplied by distributed generation and combined heat and power technologies are projected. Technologies are then

265

Regular price  

E-Print Network [OSTI]

D-LINK DWL-1000AP 802.11B Wireless LAN Access Point 11Mbps Best Deal On Earth! Regular price: $399.00. Sale price: $234.00. DWL-120> D-LINK...

266

Cheese Prices  

E-Print Network [OSTI]

Cheese prices are derived from the USDA Agricultural Marketing Service Market News, the National Agricultural Statistics Service, and the Chicago Mercantile Exchange. This publication explains the process of cheese pricing. It includes information...

Schwart Jr., Robert B.; Anderson, David P.; Knutson, Ronald D.

2003-08-25T23:59:59.000Z

267

The impact of subsidies and carbon pricing on the wood biomass use for energy in the EU  

Science Journals Connector (OSTI)

Abstract This study examines how subsidies for wood-fired heat and power plants and wood with coal co-fired power plants influence the use of wood biomass for energy in the short (2020) to medium (2030) term in the EU (European Union). Analysis shows that without subsidies wood-fired electricity will take only a marginal market share due to limited availability of low-cost wood from logging residues. A high CO2 price of 100/t without subsidies results in 30millionm3 of industrial wood used for energy production, which is sourced from the reduction of 12millionm3 for wood products, 10millionm3 additional imports and 8millionm3 additional harvest. With a subsidy level of 30/MWh in the four EU member countries Denmark, Germany, Netherlands and UK, the total amount of industrial wood used for energy becomes 158millionm3. In the latter case, reduction of wood for wood-based products is 35millionm3, additional harvest in the EU is 21million m3, and import to the EU is 102millionm3. Subsidies to wood-fired and especially coal with wood co-fired mills substantially increase the use of wood and especially industrial wood for energy. However, even with a high 100/tCO2 price and subsidy, mostly gas-fired electricity is projected to be displaced in 2030 by the increasing use of industrial wood, which is not beneficial regarding reducing the high CO2 emission from power production using coal. To a large extent, subsidies for wood co-firing maintain the coal power share, which will otherwise be reduced at high carbon emission price level. In addition, the model results show that the main sources of the growing use of industrial wood for energy are imports from regions outside of the EU, which thus creates considerable carbon leakages.

Alexander Moiseyev; Birger Solberg; A. Maarit I. Kallio

2014-01-01T23:59:59.000Z

268

EIA - Assumptions to the Annual Energy Outlook 2009 - Electricity Market  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2009 Electricity Market Module figure 6. Electricity Market Model Supply Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2009, DOE/EIA-M068(2009). Based on fuel prices and electricity demands provided by the other modules

269

Pricing statistics sourcebook. 5. edition  

SciTech Connect (OSTI)

Thousands of historical and current prices for crude oil, NGL, petroleum products, natural gas and electric power are presented in easy to read tables. The book includes spot, posted and future prices; prices by state and by country; and monthly and annual prices. Most monthly price series go back 25 years. This comprehensive source for energy industry prices is a must for anyone involved in planning and budgeting. The Pricing Statistics Sourcebook has all of the essential key energy price statistics needed for analysis of the US and international oil and gas industries. Also include: an appendix of IEA, OECD and OPEC member lists, conversion factors heat content of fuels; and major events affecting the oil and gas industry since 1859. The book includes a summary analysis of significant changes in key data series written by Bob Beck, Economics Editor of the Oil and Gas Journal.

NONE

1999-11-01T23:59:59.000Z

270

Model documentation renewable fuels module of the National Energy Modeling System  

SciTech Connect (OSTI)

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1995 Annual Energy Outlook (AEO95) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. The RFM consists of six analytical submodules that represent each of the major renewable energy resources--wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. The RFM also reads in hydroelectric facility capacities and capacity factors from a data file for use by the NEMS Electricity Market Module (EMM). The purpose of the RFM is to define the technological, cost and resource size characteristics of renewable energy technologies. These characteristics are used to compute a levelized cost to be competed against other similarly derived costs from other energy sources and technologies. The competition of these energy sources over the NEMS time horizon determines the market penetration of these renewable energy technologies. The characteristics include available energy capacity, capital costs, fixed operating costs, variable operating costs, capacity factor, heat rate, construction lead time, and fuel product price.

NONE

1995-06-01T23:59:59.000Z

271

Class Pricing  

E-Print Network [OSTI]

A contract with K-class pricing divides a large set of goods or services into K classes and assigns a single price to any element of a class. Class pricing can be efficient when several different versions may be traded and ...

Wernerfelt, Birger

2008-01-15T23:59:59.000Z

272

Crude Oil Prices  

Gasoline and Diesel Fuel Update (EIA)

20.86 20.67 20.47 20.24 20.32 19.57 See footnotes at end of table. 21. Domestic Crude Oil First Purchase Prices Energy Information Administration Petroleum Marketing Annual...

273

Crude Oil Prices  

Gasoline and Diesel Fuel Update (EIA)

19.11 18.73 18.63 17.97 18.75 18.10 See footnotes at end of table. 21. Domestic Crude Oil First Purchase Prices Energy Information Administration Petroleum Marketing Annual...

274

Three Essays on Price Dynamics and Causations among Energy Markets and Macroeconomic Information  

E-Print Network [OSTI]

of within-sample-fit. The result supports innovation accounting analysis based on DAGs using residuals of out-of-sample-forecast. Second, we look at the effects of the federal fund rate and/or WTI crude oil price shock on US macroeconomic and financial...

Hong, Sung Wook 1977-

2012-09-20T23:59:59.000Z

275

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

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases Table E1. Summary of the AEO2013 cases Case name Description Reference Real GDP grows at an average annual rate of 2.5 percent from 2011 to 2040. Crude oil prices rise to about $163 per barrel (2011 dollars) in 2040. Complete projection tables in Appendix A. Low Economic Growth Real GDP grows at an average annual rate of 1.9 percent from 2011 to 2040. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B. High Economic Growth Real GDP grows at an average annual rate of 2.9 percent from 2011 to 2040. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B. Low Oil Price Low prices result from a combination of low demand for petroleum and other liquids in the non-OECD nations and higher global supply. Lower demand is measured by lower economic growth relative to the Reference case. On the supply side, OPEC increases its market share to 49 percent, and the costs of other liquids production technologies are lower than in the Reference case.Light, sweet crude oil prices fall to $75 per barrel in 2040. Partial projection tables in Appendix C.

276

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

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases Table E1. Summary of the AEO2013 cases Case name Description Reference Real GDP grows at an average annual rate of 2.5 percent from 2011 to 2040. Crude oil prices rise to about $163 per barrel (2011 dollars) in 2040. Complete projection tables in Appendix A. Low Economic Growth Real GDP grows at an average annual rate of 1.9 percent from 2011 to 2040. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B. High Economic Growth Real GDP grows at an average annual rate of 2.9 percent from 2011 to 2040. Other energy market assumptions are the same as in the Reference case. Partial projection tables in Appendix B. Low Oil Price Low prices result from a combination of low demand for petroleum and other liquids in the non-OECD nations and higher global supply. Lower demand is measured by lower economic growth relative to the Reference case. On the supply side, OPEC increases its market share to 49 percent, and the costs of other liquids production technologies are lower than in the Reference case.Light, sweet crude oil prices fall to $75 per barrel in 2040. Partial projection tables in Appendix C.

277

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

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

of NEMS that project energy consumption for marketed energy sources plus distributed solar and geothermal energy. Both the RDM and CDM include projections of energy...

278

Annual Energy Outlook 2001  

Gasoline and Diesel Fuel Update (EIA)

Homepage Homepage Annual Energy Outlook 2001 With Projections to 2020 Preface The Annual Energy Outlook 2001 (AEO2001) presents midterm forecasts of energy supply, demand, and prices through 2020 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA’s National Energy Modeling System (NEMS). The report begins with an “Overview” summarizing the AEO2001 reference case. The next section, “Legislation and Regulations,” discusses evolving legislative and regulatory issues. “Issues in Focus” discusses the macroeconomic projections, world oil and natural gas markets, oxygenates in gasoline, distributed electricity generation, electricity industry restructuring, and carbon dioxide emissions. It is followed by the analysis of energy market trends.

279

U.S. Energy Information Administration | Annual Energy Outlook Retrospective Review  

Gasoline and Diesel Fuel Update (EIA)

Energy Information Administration | Annual Energy Outlook Retrospective Review Energy Information Administration | Annual Energy Outlook Retrospective Review Annual Energy Outlook Retrospective Review Table 2. Summary of the number o fover-estimated results between AEO Reference cases and realized Outcomes All AEOs NEMS AEOs Percent of Projections Over-Estimated Percent of Projections Over-Estimated Table 3. Gross Domestic Product, (Average Cumulative Growth) Actual vs. Projected 24% 37% Table 4. World Oil Prices, Actual vs. Projected 52% 24% Table 5. Total Petroleum Consumption, Actual vs. Projected 44% 61% Table 6. Domestic Crude Oil Production, Actual vs. Projected 59% 65% Table 7. Petroleum Net Imports, Actual vs. Projected 56% 61% Table 8. Natural Gas Wellhead Prices, Actual vs. Projected 54% 23% Table 9. Total Natural Gas Consumption, Actual vs. Projected

280

Wind Energy Facilities and Residential Properties: The Effect of Proximity and View on Sales Prices  

E-Print Network [OSTI]

and Renewable Energy (Wind & Hydropower TechnologiesU.S. Department of Energy (Wind and Hydropower TechnologiesPublic Perceptions of Wind Energy. Wind Energy, 2004, 8:2,

Hoen, Ben

2012-01-01T23:59:59.000Z

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

Wind Energy Facilities and Residential Properties: The Effect of Proximity and View on Sales Prices  

E-Print Network [OSTI]

U.S. Department of Energy (Wind and Hydropower Technologiesand Renewable Energy (Wind & Hydropower TechnologiesPublic Perceptions of Wind Energy. Wind Energy, 2004, 8:2,

Hoen, Ben

2012-01-01T23:59:59.000Z

282

EIA - The National Energy Modeling System: An Overview 2003-Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module The National Energy Modeling System: An Overview 2003 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) links NEMS to the rest of the economy by providing projections of economic driver variables for use by the supply, demand, and conversion modules of NEMS. The derivation of the baseline macroeconomic forecast lays a foundation for the determination of the energy demand and supply forecast. MAM is used to present alternative macroeconomic growth cases to provide a range of uncertainty about the growth potential for the economy and its likely consequences for the energy system. MAM is also able to address the macroeconomic impacts associated with changing energy market conditions, such as alternative world oil price assumptions. Outside of the Annual Energy Outlook setting, MAM represents a system of linked modules which can assess the potential impacts on the economy of changes in energy events or policy proposals. These economic impacts then feed back into NEMS for an integrated solution. MAM consists of five modules:

283

EIA - Assumptions to the Annual Energy Outlook 2009 - International Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2009 International Energy Module Figure 2. World Oil Prices in three Cases, 1995-2030 (2006 dollars per barrel). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 3. OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 4. Non-OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. figure data The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously global and U.S.A. petroleum liquids

284

Pay-As-You-Drive Pricing in British Columbia | 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 Page Edit with form History Facebook icon Twitter icon » Pay-As-You-Drive Pricing in British Columbia Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Pay-As-You-Drive Pricing in British Columbia Agency/Company /Organization: Victoria Transport Policy Institute Focus Area: Standards - Incentives - Policies - Regulations Topics: Best Practices Website: www.vtpi.org/paydbc.pdf This paper describes Pay-As-You-Drive (PAYD), its history in British Columbia, and describes how it can help achieve provincial objectives. Additional PAYD resources are available via the Victoria Transport Policy Institute website at http://www.vtpi.org/documents/innovative.php.

285

Carbon and energy prices under uncertainty: A theoretical analysis of fuel switching with heterogenous power plants  

Science Journals Connector (OSTI)

Abstract European power producers have a major influence on the EU ETS, given that both their CO2 emissions and their EUA (European Union Allowance) allocations account for more than half of the total volumes of the scheme. Fuel switching is often considered as the main short-term abatement measure under the EU ETS. It consists in substituting combined cycle gas turbines (CCGTs) for hard-coal plants in power generation. Thereby coal plants run for shorter periods, and CO2 emissions are reduced. This paper provides the first theoretical analysis of fuel switching, in a context where power plants involved are not equally efficient. We begin with a preliminary work using illustrative examples and sensitivity analyses, which enables us to observe how differences in the efficiency of power plants impact the cost of fuel switching, and how this is related to the level of switching effort. Based on this, we build a theoretical model taking into account the effect of differences in the efficiency of power plants involved in fuel switching. We also investigate the effect of the timing of fuel switching abatements, within the temporally defined environment of our dynamic model. Results demonstrate that the gas price and uncontrolled CO2 emissions act together on the carbon price. We show that the influence of the gas price on the carbon price depends on the level of uncontrolled CO2 emissions, due to heterogeneity of power plants that are used in the fuel switching process. Furthermore, we show that the time of occurrence of uncontrolled emissions matters so that shocks have a stronger impact when they occur in a period that is closed to the end of the phase.

Vincent Bertrand

2014-01-01T23:59:59.000Z

286

Residential Photovoltaic Energy Systems in California: The Effect on Home Sales Prices  

E-Print Network [OSTI]

Residential Photovoltaic Energy Systems in California: Themarginal impacts of photovoltaic (PV) energy systems on home

Hoen, Ben

2014-01-01T23:59:59.000Z

287

Residential Photovoltaic Energy Systems in California: The Effect on Home Sales Prices  

E-Print Network [OSTI]

Residential Photovoltaic Energy Systems in California: Themarginal impacts of photovoltaic (PV) energy systems on home

Hoen, Ben

2013-01-01T23:59:59.000Z

288

Workshop on Opportunities for Magnetism in MEMS/NEMS, April 16-17, 2010  

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

Opportunities for Magnetism in MEMS/NEMS Opportunities for Magnetism in MEMS/NEMS Argonne National Laboratory - April 16-17, 2010 Sponsored by NSF, NIST and Argonne National Laboratory Friday, April 16 13:00 Welcome and Introduction Chair: John Moreland 13:10 Pritiraj Mohanty Boston University "Study of Spin Dynamics using Nanomechanics" 13:50 T. Mitch Wallis NIST, Boulder "Measurement of the Einstein-de Haas Effect with a Microcantilever" 14:30 Albrecht Jander Oregon State University "Application of Torques to Nanostructures using Ferromagnetic Resonance" 15:10 Coffee Break Chair: Dennis Greywall 15:30 Rassul Karabalin Caltech "Next-Generation NEMS Functionality Enable by Advances in Novel Materials"

289

Forecast Prices  

Gasoline and Diesel Fuel Update (EIA)

Notes: Notes: Prices have already recovered from the spike, but are expected to remain elevated over year-ago levels because of the higher crude oil prices. There is a lot of uncertainty in the market as to where crude oil prices will be next winter, but our current forecast has them declining about $2.50 per barrel (6 cents per gallon) from today's levels by next October. U.S. average residential heating oil prices peaked at almost $1.50 as a result of the problems in the Northeast this past winter. The current forecast has them peaking at $1.08 next winter, but we will be revisiting the outlook in more detail next fall and presenting our findings at the annual Winter Fuels Conference. Similarly, diesel prices are also expected to fall. The current outlook projects retail diesel prices dropping about 14 cents per gallon

290

Energy Factors, Leasing Structure and the Market Price of Office Buildings in the U.S.  

E-Print Network [OSTI]

such as the energy efficiency of building engineeringIEA, 2008, Energy efficiency requirements in building codes,motivating energy-efficiency in these buildings. 2 Direct

Jaffee, Dwight; Stanton, Richard; Wallace, Nancy

2012-01-01T23:59:59.000Z

291

An Analysis of the Effects of Residential Photovoltaic Energy Systems on Home Sales Prices in California  

E-Print Network [OSTI]

Effects of Residential Photovoltaic Energy Systems on HomeEffects of Residential Photovoltaic Energy Systems on Homewith existing photovoltaic (PV) energy systems have sold in

Hoen, Ben

2011-01-01T23:59:59.000Z

292

Do Photovoltaic Energy Systems Effect Residential Selling Prices? Results from a California Statewide Investigation.  

E-Print Network [OSTI]

DO PHOTOVOLTAIC ENERGY SYSTEMS AFFECT RESIDENTIAL SELLINGopportunity employer. DO PHOTOVOLTAIC ENERGY SYSTEMS AFFECThave sold with photovoltaic (PV) energy systems installed at

Hoen, Ben

2012-01-01T23:59:59.000Z

293

An Analysis of the Effects of Photovoltaic Energy Systems on Residential Selling Prices in California.  

E-Print Network [OSTI]

Effects of Residential Photovoltaic Energy Systems on Homewith existing photovoltaic (PV) energy systems have sold ingrid-connected solar photovoltaic (PV) energy systems were

Cappers, Peter

2012-01-01T23:59:59.000Z

294

Wind Energy Facilities and Residential Properties: The Effect of Proximity and View on Sales Prices  

E-Print Network [OSTI]

and Renewable Energy (Wind & Hydropower Technologiesfor Understanding Public Perceptions of Wind Energy.Wind Energy. 8(2): 125 - 139. Durbin, J. and Watson, G. S. (

Hoen, Ben

2010-01-01T23:59:59.000Z

295

Assumptions to the Annual Energy Outlook - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumption to the Annual Energy Outlook Petroleum Market Module Figure 8. Petroleum Administration for Defense Districts. Having problems, call our National Energy Information Center at 202-586-8800 for help. The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohols, ethers, and bioesters natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of U.S. refining

296

Natural Gas Transmission and Distribution Model of the National Energy Modeling System. Volume 1  

SciTech Connect (OSTI)

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic design, provides detail on the methodology employed, and describes the model inputs, outputs, and key assumptions. Subsequent chapters of this report provide: an overview of NGTDM; a description of the interface between the NEMS and NGTDM; an overview of the solution methodology of the NGTDM; the solution methodology for the Annual Flow Module; the solution methodology for the Distributor Tariff Module; the solution methodology for the Capacity Expansion Module; the solution methodology for the Pipeline Tariff Module; and a description of model assumptions, inputs, and outputs.

NONE

1998-01-01T23:59:59.000Z

297

El Paso Gasoline Prices  

Gasoline and Diesel Fuel Update (EIA)

0 0 Notes: Good morning. I’m glad to be here in El Paso to share some of my agency’s insights on crude oil and gasoline prices. I represent the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. My division has the responsibility to monitor petroleum supplies and prices in the United States. As part of that work, we operate a number of surveys on a weekly, monthly, and annual basis. One of these is a weekly survey of retail gasoline prices at about 800 stations nationwide. This survey in particular allows us to observe the differences between local gasoline markets in the United States. While we track relatively few stations in the El Paso area, we have compared our price data with that collected by the El Paso City-County Health and Environmental District and

298

National Energy Modeling System: An Overview  

Gasoline and Diesel Fuel Update (EIA)

6) 6) Distribution Category UC-950 The National Energy Modeling System: An Overview March 1996 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. The information contained herein should not be construed as advocating or reflecting any policy position of the Department of Energy or of any other organization. PREFACE The National Energy Modeling System: An Overview (Overview) provides a summary description of the National Energy Modeling System (NEMS), which was used to generate the forecasts of energy production, demand, imports, and prices through the year 2015 for the Annual Energy Outlook 1996 (AEO96), (DOE/EIA- 0383(96)), released in January

299

Average Residential Price  

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

Data Series: Average Residential Price Residential Price - Local Distribution Companies Residential Price - Marketers Residential % Sold by Local Distribution Companies Average...

300

Essays on Price Dynamics  

E-Print Network [OSTI]

Small Regular Price Changes . . . . . . . . . . . . . . .4 The Cyclicality of Effective Prices2.3 Wholesale Price vs. Retail

Hong, Gee Hee

2012-01-01T23:59:59.000Z

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

Understanding Wind Turbine Price Trends in the U.S. Over the Past Decade  

E-Print Network [OSTI]

In comparison, the rise in coal prices has been slower andFiberglass Energy Prices Diesel Coal Natural Gas Currencyconsumption) Coal (20% of consumption) Real Price Change in

Bolinger, Mark

2013-01-01T23:59:59.000Z

302

The Potential of Energy Management and Control Systems for Real-Time Electricity Pricing Programs  

E-Print Network [OSTI]

at critical periods of high demand, hoping that users will lower their demand. Increasing the customer load factor increases the overall system load factor and helps decrease the capital costs of supplied power. In this way, also, @eater system reliability.... The communications path for the transfer of the prices from the utility to the customer can take several forms. Most of the required software and hardware already exist in typical systems, or can be easily added. Sensor lnput f System Load Control Output 4...

Akbari, H.; Heinemeier, K. E.

1990-01-01T23:59:59.000Z

303

Essays on Three Price Judgments: Price Fairness, Price Magnitude, and Price Expectation.  

E-Print Network [OSTI]

??This dissertation addresses three important price judgments: price fairness, price magnitude, and price expectation. Developed over three chapters, the main objective of this research is (more)

Bhowmick, Sandeep

2010-01-01T23:59:59.000Z

304

Fossil fuel prices and the economic and budgetary challenges of a small energy-importing economy: the case of Portugal  

Science Journals Connector (OSTI)

This paper examines the economic and budgetary impacts of fuel prices using a dynamic general equilibrium model of ... detailed modeling of the public sector. The fuel price scenarios are based on forecasts by th...

Alfredo Marvo Pereira; Rui Marvo Pereira

2013-12-01T23:59:59.000Z

305

Distributed Energy Consumption Control via Real-TimePricing Feedback in Smart Grid  

E-Print Network [OSTI]

on game- theoretic energy consumption scheduling for theK }). We denote the energy consumption of consumers as l kwhere l i k is the energy consumption of consumer i (i ? N )

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

2014-01-01T23:59:59.000Z

306

Costs and prices for renewable energy development in industrialized countries and applications to China  

Science Journals Connector (OSTI)

Developing renewable energy is now becoming a hot topic as ... important in dealing with climate change issue and energy supply issue. With the growing demand of energy, it has become urgent to develop the ... es...

Hugo Salamanca; Miao Chang; Xin Tian

2012-06-01T23:59:59.000Z

307

An Analysis of the Effects of Residential Photovoltaic Energy Systems on Home Sales Prices in California  

E-Print Network [OSTI]

CPUC) (2010) CPUC California Solar Initiative: 2009 Impactsystems through the California Solar Initiative program.California Prepared for the Office of Energy Efficiency and Renewable Energy Solar

Hoen, Ben

2011-01-01T23:59:59.000Z

308

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2003, DOE/EIA-M068(2003) April 2003. 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. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

309

Short and Long-Term Perspectives: The Impact on Low-Income Consumers of Forecasted Energy Price Increases in 2008 and A Cap & Trade Carbon Policy in 2030  

SciTech Connect (OSTI)

The Department of Energy's Energy Information Administration (EIA) recently released its short-term forecast for residential energy prices for the winter of 2007-2008. The forecast indicates increases in costs for low-income consumers in the year ahead, particularly for those using fuel oil to heat their homes. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation's low-income households by primary heating fuel type, nationally and by Census Region. The report provides an update of bill estimates provided in a previous study, "The Impact Of Forecasted Energy Price Increases On Low-Income Consumers" (Eisenberg, 2005). The statistics are intended for use by policymakers in the Department of Energy's Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2008 fiscal year. In addition to providing expenditure forecasts for the year immediately ahead, this analysis uses a similar methodology to give policy makers some insight into one of the major policy debates that will impact low-income energy expenditures well into the middle decades of this century and beyond. There is now considerable discussion of employing a cap-and-trade mechanism to first limit and then reduce U.S. emissions of carbon into the atmosphere in order to combat the long-range threat of human-induced climate change. The Energy Information Administration has provided an analysis of projected energy prices in the years 2020 and 2030 for one such cap-and-trade carbon reduction proposal that, when integrated with the RECS 2001 database, provides estimates of how low-income households will be impacted over the long term by such a carbon reduction policy.

Eisenberg, Joel Fred [ORNL

2008-01-01T23:59:59.000Z

310

http://www.energy.gov/media/F...Biofuels_Lower_Gas_Prices.pdf  

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

ƒ Higher oil and gas prices leading to increased costs of fertilizer, harvest, and transportation; ƒ Increased demand as developing countries grow and people improve their diets; ƒ Two years of bad weather and drought leading to poor harvests in parts of the world; ƒ Export restrictions imposed by some countries. Future Biofuels Will Alleviate Much of the Concern about Competition Between Food and Fuel. * Cellulosic biofuel feedstocks can be produced on land not suitable for crops or it can be collected from forest residues. * The Administration has announced more than $1 billion for the research, development, and demonstration of new biofuels technology, with a special focus on cellulosic biofuels. Funding supports: ƒ Bioenergy Research Centers where scientists work together to make the conversion of plant

311

Analysis of the Clean Energy Standard Act of 2012  

Gasoline and Diesel Fuel Update (EIA)

0 0 Appendix B: Estimating Price Impacts of the BCES12 Small Retailer Exemption The CES policy proposal analyzed in this paper, as outlined in the letter and draft legislation provided in Appendix D, exempts small electricity retailers. Small electricity retailers are defined as those with sales less than 2,000,000 megawatthours (MWh) in 2015, with the exemption level decreasing linearly to 1,000,000 MWh in 2025 and beyond. EIA is not able to disaggregate the price impacts of exempt small retailers from those of larger covered retailers within the National Energy Modeling System (NEMS). Given the exemption, there is likely to be a considerable divergence in the price impacts for customers of exempt and non-exempt electricity providers. Using historical data and assuming that small retailer

312

Residential Photovoltaic Energy Systems in California: The Effect on Home Sales Prices  

E-Print Network [OSTI]

ABSTRACT Relatively little research exists estimating the marginal impacts of photovoltaic (PV) energy

Hoen, Ben

2014-01-01T23:59:59.000Z

313

Food price volatility  

Science Journals Connector (OSTI)

...of commodity price changes in energy and metals as well as for foods...commodities, in particular corn, sugar and vegetable oils...smaller in food markets than in energy and metals markets, reflecting...insignificant fall grains (%) maize (corn) 19.3 19.4 19.2 1.02...

2010-01-01T23:59:59.000Z

314

Table 19. U.S. Refiner Residual Fuel Oil Prices  

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

Prices," source for backcast estimates prior to January 1983. 19. U.S. Refiner Residual Fuel Oil Prices 36 Energy Information Administration Petroleum Marketing Annual 1996...

315

Table 19. U.S. Refiner Residual Fuel Oil Prices  

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

Prices," source for backcast estimates prior to January 1983. 19. U.S. Refiner Residual Fuel Oil Prices 36 Energy Information Administration Petroleum Marketing Annual 1997...

316

Fact Sheet: Gas Prices and Oil Consumption Would Increase Without...  

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

Gas Prices and Oil Consumption Would Increase Without Biofuels Fact Sheet: Gas Prices and Oil Consumption Would Increase Without Biofuels Secretary of Energy Samuel W. Bodman and...

317

Estimating exergy prices for energy carriers in heating systems: Country analyses of exergy substitution with capital expenditures  

Science Journals Connector (OSTI)

Exergy represents the ability of an energy carrier to perform work and can be seen as a core indicator for measuring its quality. In this article we postulate that energy prices reflect the exergy content of the underlying energy carrier and that capital expenditures can substitute for exergy to some degree. We draw our line of argumentation from cost and technology data for heating systems of four European countries: Austria, Finland, The Netherlands, and Sweden. Firstly, this paper shows that the overall consumer costs for different heating options, widely installed in those countries, are in the same range. In this analysis we derived an overall standard deviation of about 8%. Secondly, additional analysis demonstrates that the share of capital costs on total heating cost increases with lower exergy input. Based on the data used in this analysis, we conclude that for the case of modern cost effective heating systems the substitution rate between exergy and capital is in the vicinity of 2/3. This means that by reducing the average specific exergy input of the applied energy carriers by one unit, the share of capital costs on the total costs increases by 2/3 of a unit.

A. Mller; L. Kranzl; P. Tuominen; E. Boelman; M. Molinari; A.G. Entrop

2011-01-01T23:59:59.000Z

318

Assumptions to the Annual Energy Outlook 2000 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2000, DOE/EIA-M060(2000) January 2000. The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2000, DOE/EIA-M060(2000) January 2000. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of coal production, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

319

EIA - Assumptions to the Annual Energy Outlook 2008 - Electricity Market  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2008 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2008, DOE/EIA-M068(2008). 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. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

320

Assumptions to the Annual Energy Outlook - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumption to the Annual Energy Outlook Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2004, DOE/EIA- M068(2004). 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. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

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

Business Cycle Effects on Metal and Oil Prices: Understanding the Price Retreat of 2008-9  

E-Print Network [OSTI]

1 Business Cycle Effects on Metal and Oil Prices: Understanding the Price Retreat of 2008 of macroeconomic business cycles on six metals traded on the London Metal Exchange and oil prices. Reduced GDP oil prices (as a proxy for energy inputs in metals production) are derived. The estimated trend

322

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

E-Print Network [OSTI]

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

323

Reforming Household Energy Markets: Some Welfare Effects in the United Catherine Waddams Price  

E-Print Network [OSTI]

Reforming Household Energy Markets: Some Welfare Effects in the United Kingdom by Catherine Waddams remain vulnerable. The implications of these findings for the future of energy markets both in the UK This paper summarises some early effects of deregulating the UK energy sector, focusing on the effects

Feigon, Brooke

324

Concurrent Optimization of Consumer's Electrical Energy Bill and Producer's Power Generation Cost under a Dynamic Pricing  

E-Print Network [OSTI]

Concurrent Optimization of Consumer's Electrical Energy Bill and Producer's Power Generation Cost lower cost. I. INTRODUCTION There is no substitute for the status of electrical energy, which. Availability of affordable and sustainable electrical energy has been the key to prosperity and continued socio

Pedram, Massoud

325

Quantifying the value that energy efficiency and renewable energy provide as a hedge against volatile natural gas prices  

E-Print Network [OSTI]

Technology. Stoffel, F.C. (Xcel Energy). 2001. In the Matternatural gas utilities, Xcel Energy noted that the cost of

Bolinger, Mark; Wiser, Ryan; Bachrach, Devra; Golove, William

2002-01-01T23:59:59.000Z

326

U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Policy Analysts Policy Analysts This page features the most requested EIA reports and features for policy analysts. If you can't find what you're looking for, please contact the EIA Information Center. Featured Links Responses to Congressional and other requests Congressional testimony Analysis papers from Annual Energy Outlook Financial data and analysis Environmental data and analysis National Energy Modeling System (NEMS) documentation Energy in Brief Maps Featured Reports Annual Energy Outlook International Energy Outlook Short-Term Energy Outlook The Availability and Price of Petroleum and Petroleum Products Produced in Countries Other Than Iran Potential Impacts of Reductions in Refinery Activity on Northeast Petroleum Product Markets Effect of Increased Natural Gas Exports on Domestic Energy Markets

327

EIA - Annual Energy Outlook 2008 - Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface Annual Energy Outlook 2008 with Projections to 2030 Preface The Annual Energy Outlook 2008 (AEO2008), prepared by the Energy Information Administration (EIA), presents long-term projections of energy supply, demand, and prices through 2030. The projections are based on results from EIA’s National Energy Modeling System (NEMS). EIA published an “early release” version of the AEO2008 reference case in December 2007; however, the Energy Independence and Security Act of 2007 (EISA2007), which was enacted later that month, will have a major impact on energy markets, and given the year-long life of AEO2008 and its use as a baseline for analyses of proposed policy changes, EIA decided to update the reference case to reflect the provisions of EISA2007.

328

Annual Energy Outlook 1998 Forecasts - Preface  

Gasoline and Diesel Fuel Update (EIA)

1998 With Projections to 2020 1998 With Projections to 2020 Annual Energy Outlook 1999 Report will be Available on December 9, 1998 Preface The Annual Energy Outlook 1998 (AEO98) presents midterm forecasts of energy supply, demand, and prices through 2020 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA's National Energy Modeling System (NEMS). The report begins with an “Overview” summarizing the AEO98 reference case. The next section, “Legislation and Regulations,” describes the assumptions made with regard to laws that affect energy markets and discusses evolving legislative and regulatory issues. “Issues in Focus” discusses three current energy issues—electricity restructuring, renewable portfolio standards, and carbon emissions. It is followed by the analysis

329

Price Server System for Automated Critical Peak Pricing  

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

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

330

Robust Strategy Synthesis for Probabilistic Systems Applied to Risk-Limiting Renewable-Energy Pricing  

E-Print Network [OSTI]

, which nowadays has higher capacity than solar energy, and is expected to consti- tute a significant Engineering and Computer Science University of California, Berkeley {puggelli, alberto, sseshia

Seshia, Sanjit A.

331

The Influence of a CO2 Pricing Scheme on Distributed Energy Resources in California's Commercial Buildings  

E-Print Network [OSTI]

Firestone 2004, EPRI-DOE Handbook 2003, Mechanical Cost Datahttp://der.lbl.gov) EPRI-DOE Handbook of Energy Storage for

Stadler, Michael

2010-01-01T23:59:59.000Z

332

Electricity Market Module: Electricity finance and pricing submodule  

SciTech Connect (OSTI)

The purpose of this report is to document the updates to the Electricity Financial Pricing Module (EFP) to reflect the rate impacts of nuclear decommissioning. The EFP is part of the National Energy Modeling System (NEMS). The updates to the EFP related to nuclear decommissioning include both changes to the underlying data base and the methodology. Nuclear decommissioning refers to the activities performed to take a nuclear plant permanently out of service. The costs of nuclear decommissioning are substantial and uncertain. The recovery of these costs from ratepayers is to occur over the operating life of the nuclear plant. Utilities are obligated to make estimates of the nuclear decommissioning cost every few years. Given this estimate, utilities are to assess a charge upon ratepayers, such that over the operating life of the plant they collect sufficient funds to pay for the decommissioning. However, cost estimates for decommissioning have been increasing and it appears that utilities have not been collecting adequate funds to date. In addition, there is a real risk that many nuclear plants may be closed earlier than originally planned, further exacerbating the under collection problem. The updates performed in this project provide the EFP with the capability to analyze these issues. The remainder of this document is divided into two discussions: (1) Nuclear Decommissioning Data Base, and (2) Methodology. Appendix A contains the actual data base developed during the project.

NONE

1996-06-01T23:59:59.000Z

333

"Table A42. Average Prices of Purchased Energy Sources by Census Region,"  

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

1" 1" " (Estimates in Dollars per Physical Units)" ,,,,,"Noncombustible Energy Sources",,,,,,,,,,,,,,,,,,"Combustible Energy Sources" ,,,,,,,,,,,,,,,"Solids",,,,,,,,,,"Gases",,,,,,,,,"Liquids" " "," ",," "," ",,,,," "," "," "," "," "," "," ",,,"Wood","Wood Residues",,,,,,,,,,,,,,,,,,,," " " "," ",,"Electricity","Electricity","Electricity","Steam","Steam","Steam","Industrial",," ","Bituminous and"," ",," ",,,"Harvested","and Byproducts","Wood and",,"Natural Gas",,,,,,,"Total Diesel Fuel",,,,,"Motor Gasoline",,,,," "

334

Distributed storage management using dynamic pricing in a self-organized energy community  

Science Journals Connector (OSTI)

We consider a future self-organized energy community that is composed of "prosumer" households that can autonomously generate, store, import and export power, and also selfishly strive to minimize their cost by adjusting their load profiles using the ...

Ebisa Negeri; Nico Baken

2012-03-01T23:59:59.000Z

335

disposition. prices | OpenEI  

Open Energy Info (EERE)

disposition. prices disposition. prices 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 15, and contains only the reference case. The dataset uses gigawatts. The data is broken down into production, net imports, consumption by sector and price. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO coal coal supply disposition. prices EIA Data application/vnd.ms-excel icon AEO2011: Coal Supply, Disposition, and Prices- Reference Case (xls, 91.7 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period 2008-2035 License License Open Data Commons Public Domain Dedication and Licence (PDDL)

336

Minemouth Prices | OpenEI  

Open Energy Info (EERE)

Minemouth Prices Minemouth Prices 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 139, and contains only the reference case. The dataset uses million short tons and the US Dollar. The data is broken down into production and minemouth prices. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO Coal Production EIA Minemouth Prices Data application/vnd.ms-excel icon AEO2011: Coal Production and Minemouth Prices by Region- Reference Case (xls, 41.5 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period 2008-2035 License License Open Data Commons Public Domain Dedication and Licence (PDDL)

337

Open Automated Demand Response Technologies for Dynamic Pricing and Smart Grid  

E-Print Network [OSTI]

6/16/2010. OASIS SDO. Energy Market Information Exchange (of Prices CAISOs Wholesale Energy Market Prices PG&Es PDPWe used the CAISO wholesale energy market prices for the RTP

Ghatikar, Girish

2010-01-01T23:59:59.000Z

338

price | OpenEI  

Open Energy Info (EERE)

price price Dataset Summary Description Global PV grid parity and market potential. Data is courtesy of Sean Ong. Source National Renewable Energy Laboratory Date Released Unknown Date Updated Unknown Keywords grid Parity Payback photovoltaic price PV Residential Data text/csv icon globalgridparity.csv (csv, 4.8 KiB) Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage Frequency Time Period License License Creative Commons CCZero Comment Rate this dataset Usefulness of the metadata Average vote Your vote Usefulness of the dataset Average vote Your vote Ease of access Average vote Your vote Overall rating Average vote Your vote Comments Login or register to post comments If you rate this dataset, your published comment will include your rating. Dataset Summary

339

NEM modication prevents high-anity ATP binding to the rst nucleotide binding fold of the sulphonylurea receptor, SUR1  

E-Print Network [OSTI]

NEM modi¢cation prevents high-a¤nity ATP binding to the ¢rst nucleotide binding fold, UK Received 7 July 1999; received in revised form 11 August 1999 Abstract Pancreatic LL-cell ATP WWM 8-azido- [KK-32 P]ATP or 8-azido-[QQ-32 P]ATP was inhibited by NEM with Ki of 1.8 WWM and 2.4 WWM

Tucker, Stephen J.

340

EIA-Assumptions to the Annual Energy Outlook - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2007 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2007, DOE/EIA- M068(2007). 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. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

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

Modelling futures price volatility in energy markets: Is there a role for financial speculation?  

Science Journals Connector (OSTI)

Abstract This paper models volatility in four energy futures markets, adopting GARCH models. The variance equation is enriched with alternative measures of speculation, based on CFTC data: the market share of non-commercial traders, the Working's T index, and the percentage of net long positions of non-commercials over total open interest in future markets. It also includes a control for market liquidity. We consider four energy commodities (light sweet crude oil, heating oil, gasoline and natural gas) over the period 20002014, analysed at weekly frequency. We find that speculation presents a negative and significant sign. The robustness exercise shows that: i) results remain unchanged through different model specifications (GARCH-in-mean, EGARCH, and TARCH); ii) results are robust to different specifications of the mean and variance equation.

Matteo Manera; Marcella Nicolini; Ilaria Vignati

2014-01-01T23:59:59.000Z

342

EIA - Assumptions to the Annual Energy Outlook 2008 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2008 Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and Distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

343

EIA - Assumptions to the Annual Energy Outlook 2009 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2009 Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

344

Assumptions to the Annual Energy Outlook - Natural Gas Transmission and  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumption to the Annual Energy Outlook Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and Distribution Model Regions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

345

EIA - Assumptions to the Annual Energy Outlook 2010 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2010 Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and

346

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 1 July 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 July 7, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $75.34 per barrel in June 2010 ($1.60 per barrel above the prior month's average), close to the $76 per barrel projected in the forecast in last month's Outlook. EIA projects WTI prices will average about $79 per barrel over the second half of this year and rise to $84 by the end of next year (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown (Energy Price Volatility and Forecast Uncertainty). WTI futures for September 2010 delivery for the

347

Fact #766: February 11, 2013 Electricity Prices are More Stable than Gasoline Prices  

Broader source: Energy.gov [DOE]

All energy prices vary from month to month and year to year. However, when comparing the national average retail price for a gallon of regular gasoline and a kilowatt-hour (kWh) for residential...

348

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface This report presents international energy projections through 2025, prepared by the Energy Information Administration, including outlooks for major energy fuels and associated carbon dioxide emissions. The International Energy Outlook 2005 (IEO2005) presents an assessment by the Energy Information Administration (EIA) of the outlook for international energy markets through 2025. U.S. projections appearing in IEO2005 are consistent with those published in EIA’s Annual Energy Outlook 2005 (AEO2005), which was prepared using the National Energy Modeling System (NEMS). Although the IEO typically uses the same reference case as the AEO, IEO2005 has adopted the October futures case from AEO2005 as its reference case for the United States. The October futures case, which has an assumption of higher world oil prices than the AEO2005 reference case, now appears to be a more likely projection. The reference case prices will be reconsidered for the next AEO. Based on information available as of July 2005, the AEO2006 reference case will likely reflect world oil prices higher than those in the IEO2005 reference case.

349

The Price of Feed Utilities.  

E-Print Network [OSTI]

the averages which appeared most probable. Table 1-Assumed selling prices, per ton, used in calculations. - I Wholesale ! Pennsylvania Indiana - - -' -__- Texa 1916 ..................... 1917 .................... 1918 ..................... 1920... in these cases it is put down as zero and the productive energy calculated with digestible protein having nc The figures for Texas 1923 are the averages for January an( value. Marc2 Table 3-Comparative prices of therms of productive energy and pounds...

Fraps, G. S. (George Stronach)

1924-01-01T23:59:59.000Z

350

Final report of the Rhode Island State Energy Office on residential no. 2 heating oil and propane prices [SHOPP  

SciTech Connect (OSTI)

Summary report on residential No.2 heating oil and propane prepared under grant. Summarizes the monitoring and analysis of heating oil and propane prices from October 2000 through March 2001.

McClanahan, Janice

2001-04-01T23:59:59.000Z

351

The Value of Renewable Energy as a Hedge Against Fuel Price Risk: Analytic Contributions from Economic and Finance Theory  

E-Print Network [OSTI]

generation such as wind, solar, and geothermal power may provide economic benefits to ratepayers by displacing gas-firedpower prices as low-operating-cost renewable generation displaces high-operating-cost gas-fired

Bolinger, Mark A

2009-01-01T23:59:59.000Z

352

EIA - The National Energy Modeling System: An Overview 2003-Overview of  

Gasoline and Diesel Fuel Update (EIA)

Overview of NEMS Overview of NEMS The National Energy Modeling System: An Overview 2003 Overview of NEMS NEMS represents domestic energy markets by explicitly representing the economic decision making involved in the production, conversion, and consumption of energy products. Where possible, NEMS includes explicit representation of energy technologies and their characteristics. Summary of NEMS Detail Table. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Figure 1. Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. Figure 2. National Energy Modeling System. Need help, contact the National Energy Information Center at 202-586-8800. Since energy costs and availability and energy-consuming characteristics

353

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

May 2010 May 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 May 11, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $84 per barrel in April 2010, about $3 per barrel above the prior month's average and $2 per barrel higher than forecast in last month's Outlook. EIA projects WTI prices will average about $84 per barrel over the second half of this year and rise to $87 by the end of next year, an increase of about $2 per barrel from the previous Outlook (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown. Prices for near-term futures options contracts suggest that the market attaches

354

Microsoft Word - Price Probabilities Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 1 April 2010 Short-Term Energy Outlook Supplement: Probabilities of Possible Future Prices 1 EIA introduced a monthly analysis of energy price volatility and forecast uncertainty in the October 2009 Short-Term Energy Outlook (STEO). Included in the analysis were charts portraying confidence intervals around the New York Mercantile Exchange (NYMEX) futures prices of West Texas Intermediate (equivalent to light sweet crude oil) and Henry Hub natural gas contracts. The March 2010 STEO added another set of charts listing the probability of the future realized price exceeding or falling below given price levels (see Figures 1A and 1B for West Texas Intermediate crude oil price probabilities). These charts are also available as spreadsheets allowing users to input their own prices to

355

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 1 June 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 June 8, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged less than $74 per barrel in May 2010, almost $11 per barrel below the prior month's average and $7 per barrel lower than forecast in last month's Outlook. EIA projects WTI prices will average about $79 per barrel over the second half of this year and rise to $84 by the end of next year, a decrease of about $3 per barrel from the previous Outlook (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown. Prices for near-term futures options contracts suggest that the market attaches

356

Determining Price Reasonableness in Federal ESPCs  

Broader source: Energy.gov [DOE]

Document reports the findings and implementation recommendations of the Price Reasonableness Working Group to the Federal Energy Savings Performance Contract (ESPC) Steering Committee.

357

Summary Statistics Table 1. Crude Oil Prices  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Cost Report." Figure Energy Information Administration Petroleum Marketing Annual 1996 3 Table 2. U.S. Refiner Prices of Petroleum Products to End Users (Cents per Gallon...

358

Annual Energy Outlook 2006 with Projections to 2030 - Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface Annual Energy Outlook 2006 with Projections to 2030 The Annual Energy Outlook 2006 (AEO2006), prepared by the Energy Information Administration (EIA), presents long-term forecasts of energy supply, demand, and prices through 2030. The projections are based on results from EIA’s National Energy Modeling System (NEMS). The report begins with an “Overview” summarizing the AEO2006 reference case and comparing it with the AEO2005 reference case. The next section, “Legislation and Regulations,” discusses evolving legislation and regulatory issues, including recently enacted legislation and regulation, such as the Energy Policy Act of 2005, and some that are proposed. “Issues in Focus” includes a discussion of the basis of EIA’s substantial revision of the world oil price trend used in the projections. It also examines the following topics: implications of higher oil price expectations for economic growth; differences among types of crude oil available on world markets; energy technologies on the cusp of being introduced; nonconventional liquids technologies beginning to play a larger role in energy markets; advanced vehicle technologies included in AEO2006; mercury emissions control technologies; and U.S. greenhouse gas intensity. “Issues in Focus” is followed by “Energy Market Trends,” which provides a summary of the AEO2006 projections for energy markets.

359

Automobile Prices, Gasoline Prices, and Consumer Demand for Fuel Economy  

E-Print Network [OSTI]

Automobile Prices, Gasoline Prices, and Consumer Demand for Fuel Economy Ashley Langer University evidence that automobile manufacturers set vehicle prices as if consumers respond to gasoline prices. We consumer preferences for fuel efficiency. Keywords: automobile prices, gasoline prices, environmental

Sadoulet, Elisabeth

360

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

November 2010 November 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 November 9, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged almost $82 per barrel in October, about $7 per barrel higher than the September average, as expectations of higher oil demand pushed up prices. EIA has raised the average fourth quarter 2010 WTI spot price forecast to about $83 per barrel compared with $79 per barrel in last monthʹs Outlook. WTI spot prices rise to $87 per barrel by the fourth quarter of next year. Projected WTI prices average $79 per barrel in 2010 and $85 per barrel in 2011. WTI futures for January 2011 delivery (for the 5-day period ending November 4)

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

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

Outlook Price Uncertainty-January 2010 Outlook Price Uncertainty-January 2010 1 January 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 January 12, 2010 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged $74.50 per barrel in December 2009, about $3.50 per barrel lower than the prior month's average. The WTI spot price fell from $78 to $70 during the first 2 weeks of December, but colder-than-normal weather and U.S. crude oil and product inventory draws that exceeded the December 5-year averages helped push it back up to $79 per barrel by the end of the month. EIA forecasts that WTI spot prices will weaken over

362

Summary of Important Terms PETROLEUM PRICES  

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

Important Terms Important Terms PETROLEUM PRICES Refiner acquisition cost of crude oil (RAC): The average monthly cost of crude oil to U.S. refiners, including transportation and fees. The composite cost is the weighted average of domestic and imported crude oil costs. Typically, the imported RAC is about $1.50 per barrel below the monthly average spot price of West Texas Intermediate (WTI) crude oil and is within about $0.20 per barrel of the average monthly spot price of Brent crude oil. Unless otherwise stated, the imported RAC is what is referred to in this report as the 'world oil price" or "average crude oil price." Retail motor gasoline prices: The average pump prices for gasoline reported in the Short-term Energy Outlook are derived from the Energy Information

363

Assumptions to the Annual Energy Outlook 1999 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

coal.gif (4423 bytes) coal.gif (4423 bytes) The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Model Documentation: Coal Market Module of the National Energy Modeling System, DOE/EIA-MO60. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of coal production, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

364

Green Power Network: Green Pricing  

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

Table of Utility Programs by State Table of Utility Programs by State List of Utilities Offering Green Power Top Ten Utility Green Power Programs Green Power Marketing Green Certificates Carbon Offsets State Policies Green Pricing Green pricing is an optional utility service that allows customers an opportunity to support a greater level of utility company investment in renewable energy technologies. Participating customers pay a premium on their electric bills to cover the incremental cost of the additional renewable energy. To date, more than 860 utilities, including investor-owned, municipal utilities, and cooperatives, offer a green pricing option. Table of Utility Programs by State List of Utilities Offering Green Power Top Ten Utility Green Power Programs National Green Pricing Map

365

Wellhead prices | OpenEI  

Open Energy Info (EERE)

Wellhead prices Wellhead prices 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 133, and contains only the reference case. The data is broken down into Production, lower 48 onshore and lower 48 offshore. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Natural Gas Wellhead prices Data application/vnd.ms-excel icon AEO2011: Lower 48 Natural Gas Production and Wellhead Prices by Supply Region- Reference Case (xls, 59.1 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period 2008-2035 License License Open Data Commons Public Domain Dedication and Licence (PDDL)

366

California Gasoline Price Study  

Gasoline and Diesel Fuel Update (EIA)

DIRECTOR, PETROLEUM DIVISION DIRECTOR, PETROLEUM DIVISION ENERGY INFORMATION ADMINISTRATION U.S. DEPARTMENT OF ENERGY BEFORE THE SUBCOMMITTEE ON ENERGY AND RESOURCES COMMITTEE ON GOVERNMENT REFORM U.S. HOUSE OF REPRESENTATIVES MAY 9, 2005 Mr. Chairman, I appreciate this opportunity to testify today on the Energy Information Administration's (EIA) insights into factors affecting recent gasoline prices. EIA is the statutorily chartered statistical and analytical agency within the U.S. Department of Energy. We are charged with providing objective, timely, and relevant data, analysis, and projections for the use of the Department of Energy, other Government agencies, the U.S. Congress, and the public. We produce data and analysis reports that are meant to assist policy makers in determining energy policy. Because we have an element of

367

ESPC Task Order Schedules and Placement of Pricing Information  

Broader source: Energy.gov [DOE]

Document provides task order (TO) schedule descriptions and information on the placement of pricing for energy savings performance contracts (ESPCs).

368

EIA-Assumptions to the Annual Energy Outlook - National Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2007 National Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and Distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

369

Natural Gas Wellhead Price  

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

Pipeline and Distribution Use Price City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Vehicle Fuel Price Electric Power Price Period: Monthly Annual Pipeline and Distribution Use Price City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Vehicle Fuel Price Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2007 2008 2009 2010 2011 2012 View History U.S. 6.25 7.97 3.67 4.48 3.95 2.66 1922-2012 Alabama 7.44 9.65 4.32 4.46 1967-2010 Alaska 5.63 7.39 2.93 3.17 1967-2010 Arizona 5.98 7.09 3.19 4.11 1967-2010 Arkansas

370

Annual Energy Outlook with Projections to 2025- Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface Preface The Annual Energy Outlook 2004 (AEO2004) presents midterm forecasts of energy supply, demand, and prices through 2025 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA's National Energy Modeling System (NEMS). The report begins with an "Overview" summarizing the AEO2004 reference case. The next section, "Legislation and Regulations," discusses evolving legislation and regulatory issues. "Issues in Focus" includes discussions of future labor productivity growth; lower 48 natural gas depletion and productive capacity; natural gas supply options, with a focus on liquefied natural gas; natural gas demand for Canadian oil sands production; National Petroleum Council forecasts for natural gas; natural gas consumption in the industrial and electric power sectors; nuclear power plant construction costs; renewable electricity tax credits; and U.S. greenhouse gas intensity. It is followed by a discussion of "Energy Market Trends."

371

Analysis & Projections - U.S. Energy Information Administration (EIA) -  

Gasoline and Diesel Fuel Update (EIA)

Summary Table Summary Table Appendix B-Estimating Price Impacts of the BCES12 Small Retailer Exemption Appendix C-Map of NEMS Electricity Market Module Regions Appendix D-Request Letter and Bill Updates Scenario Case Data Reference case Clean energy standard Clean energy standard, constrained nuclear See interactive table viewer Analysis of the Clean Energy Standard Act of 2012 Release date: May 2, 2012 Background This report responds to a request from Senator Jeff Bingaman, Chairman of the Senate Committee on Energy and Natural Resources, for an analysis of the Clean Energy Standard (CES) Act of 2012. The request letter and the text of the proposed legislation are provided in Appendix D. The request

372

Retrospective Evaluation of Appliance Price Trends  

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

Evaluation of Appliance Price Trends Evaluation of Appliance Price Trends Title Retrospective Evaluation of Appliance Price Trends Publication Type Journal Article Year of Publication 2009 Authors Dale, Larry L., Camille Antinori, Michael A. McNeil, James E. McMahon, and Sydny K. Fujita Journal Energy Policy Volume 37 Issue 2 Pagination 597-605 Date Published November 20 Keywords appliance efficiency standards, price forecasts, EES-EG Abstract Real prices of major appliances (refrigerators, dishwashers, heating and cooling equipment) have been falling since the late 1970s despite increases in appliance efficiency and other quality variables. This paper demonstrates that historic increases in efficiency over time, including those resulting from minimum efficiency standards, incur smaller price increases than were expected by the Department of Energy (DOE) forecasts made in conjunction with standards. This effect can be explained by technological innovation, which lowers the cost of efficiency, and by market changes contributing to lower markups and economies of scale in production of higher efficiency units. We reach four principal conclusions about appliance trends and retail price setting:1. For the past several decades, the retail price of appliances has been steadily falling while efficiency has been increasing.2. Past retail price predictions made by the DOE analyses of efficiency standards, assuming constant prices over time, have tended to overestimate retail prices.3. The average incremental price to increase appliance efficiency has declined over time. DOE technical support documents have typically overestimated this incremental price and retail prices.4. Changes in retail markups and economies of scale in production of more efficient appliances may have contributed to declines in prices of efficient appliances.

373

The National Energy Modeling System: An Overview 2000 - Petroleum Market  

Gasoline and Diesel Fuel Update (EIA)

petroleum market module (PMM) represents domestic refinery operations and the marketing of petroleum products to consumption regions. PMM solves for petroleum product prices, crude oil and product import activity (in conjunction with the international energy module and the oil and gas supply module), and domestic refinery capacity expansion and fuel consumption. The solution is derived, satisfying the demand for petroleum products and incorporating the prices for raw material inputs and imported petroleum products, the costs of investment, and the domestic production of crude oil and natural gas liquids. The relationship of PMM to other NEMS modules is illustrated in Figure 17. petroleum market module (PMM) represents domestic refinery operations and the marketing of petroleum products to consumption regions. PMM solves for petroleum product prices, crude oil and product import activity (in conjunction with the international energy module and the oil and gas supply module), and domestic refinery capacity expansion and fuel consumption. The solution is derived, satisfying the demand for petroleum products and incorporating the prices for raw material inputs and imported petroleum products, the costs of investment, and the domestic production of crude oil and natural gas liquids. The relationship of PMM to other NEMS modules is illustrated in Figure 17. Figure 17. Petroleum Market Module Structure PMM is a regional, linear-programming representation of the U.S. petroleum market. Refining operations are represented by a three-region linear programming formulation of the five Petroleum Administration for Defense Districts (PADDs) (Figure 18). PADDs I and V are each treated as single regions, while PADDs II, III, and IV are aggregated into one region. Each region is considered as a single firm where more than 30 distinct refinery processes are modeled. Refining capacity is allowed to expand in each region, but the model does not distinguish between additions to existing refineries or the building of new facilities. Investment criteria are developed exogenously, although the decision to invest is endogenous.

374

Energy use and energy intensity of the U.S. chemical industry  

E-Print Network [OSTI]

costs, fixed costs and ethylene price Purchased energy costsfeedstock and energy prices, ethylene yield (per unit ofof ethylene produced) and the generally higher energy prices

Worrell, Ernst; Phylipsen, Dian; Einstein, Dan; Martin, Nathan

2000-01-01T23:59:59.000Z

375

The National Energy Modeling System The  

Gasoline and Diesel Fuel Update (EIA)

2000 2000 (AEO2000) are generated from the National Energy Modeling System (NEMS), developed and main- tained by the Office of Integrated Analysis and Fore- casting of the Energy Information Administration (EIA). In addition to its use in the development of the AEO projections, NEMS is also used in analytical studies for the U.S. Congress and other offices within the Department of Energy. The AEO forecasts are also used by analysts and planners in other govern- ment agencies and outside organizations. The projections in NEMS are developed with the use of a market-based approach to energy analysis. For each fuel and consuming sector, NEMS balances the energy supply and demand, accounting for the eco- nomic competition between the various energy fuels and sources. The time horizon of NEMS is the mid- term period, approximately 20 years in the future. In order to represent the regional differences

376

Steadying of oil prices  

Science Journals Connector (OSTI)

Oil prices have fallen below the 30 dollar mark ... in the lower half of OPECs target price band. Will OPEC manage to maintain high prices and revenues by restricting production?

Klaus Matthies

377

Diesel prices flat  

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

Diesel prices flat The U.S. average retail price for on-highway diesel fuel saw no movement from last week. Prices remained flat at 3.89 a gallon on Monday, based on the weekly...

378

Diesel prices decrease  

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

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 4.05 a gallon on Monday. That's down 4.1 cents from a week ago, based on the weekly price...

379

Diesel prices increase  

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

Diesel prices increase The U.S. average retail price for on-highway diesel fuel rose to 3.90 a gallon on Monday. That's up 3 cents from a week ago, based on the weekly price...

380

Diesel prices decrease  

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

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.88 a gallon on Monday. That's down a penny from a week ago, based on the weekly price...

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

Diesel prices decrease  

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

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.82 a gallon on Monday. That's down 2.1 cents from a week ago, based on the weekly price...

382

Diesel prices decrease  

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

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.87 a gallon on Monday. That's down 1.6 cents from a week ago, based on the weekly price...

383

Diesel prices decrease  

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

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.85 a gallon on Monday. That's down 2 cents from a week ago, based on the weekly price...

384

All Price Tables.vp  

Gasoline and Diesel Fuel Update (EIA)

5. Energy Prices and Expenditures, Ranked by State, 2011 5. Energy Prices and Expenditures, Ranked by State, 2011 Rank Prices Expenditures a Energy Expenditures per Person Energy Expenditures as Percent of Current-Dollar GDP b State Dollars per Million Btu State Million Dollars State Dollars State Percent 1 Hawaii 38.41 Texas 169,290 Alaska 10,692 Louisiana 18.9 2 Connecticut 27.81 California 136,096 Louisiana 10,237 North Dakota 15.9 3 Vermont 27.77 Florida 68,013 Wyoming 9,529 Mississippi 15.5 4 New Hampshire 27.36 New York 65,877 North Dakota 9,360 Alaska 15.1 5 District of Columbia 27.04 Pennsylvania 55,164 Texas

385

Retail Price Changes Lag Spot Prices  

Gasoline and Diesel Fuel Update (EIA)

1 1 Notes: While EIA cannot claim to explain all of the factors that drive retail gasoline prices, we have had a fair amount of success in exploring the relationship between wholesale and retail prices. In particular, we have looked closely at the "pass-through" of changes in spot prices to the retail market. This graph shows a weighted national average of spot prices for regular gasoline -both conventional and reformulated (shown in red), and EIA's weekly survey price for retail regular (again both conventional and reformulated). As you can see, spot prices tend to be more volatile (and would be even more so on a daily basis), while these changes are smoother by the time they reach the retail pump. Furthermore, by looking at the peaks, you can see the retail prices seem to lag the spot price changes

386

U.S. Energy Information Administration | Annual Energy Outlook Retrospective Review  

Gasoline and Diesel Fuel Update (EIA)

Retrospective Review Retrospective Review 4 Annual Energy Outlook Retrospective Review Table 1. Comparison of absolute percent difference between AEO reference case projections and related outcomes Variable All AEOs (AEO82 to AEO2010) NEMS AEOs (AEO94 to AEO2010) Gross Domestic Product Real Gross Domestic Product (Growth Rate)* 0.8 0.9 Petroleum World Oil Prices 49.9 31.4 Total Petroleum Consumption 4.1 4.3 Crude Oil Production 5.8 6.4 Petroleum Net Imports 6.0 7.3 Natural Gas Natural Gas Wellhead Prices 56.6 31.9 Total Natural Gas Consumption 7.3 7.4 Natural Gas Production 6.2 6.9 Natural Gas Net Imports 17.9 17.1 Coal Coal Prices to Electric Generating Plants** 43.1 19.5 Total Coal Consumption 4.9 6.0 Coal Production 4.8 4.5 Electricity Average Electricity Prices 19.7 12.0 Total Electricity Sales 3.0 3.8 Total Energy, Carbon and Intensity

387

The Value of Renewable Energy as a Hedge Against Fuel Price Risk: Analytic Contributions from Economic and Finance Theory  

E-Print Network [OSTI]

Deployment of Renewable Energy and Energy Efficiency. LBNL-Can Deployment of Renewable Energy Put Downward Pressure onScientists. ________. 2004a. Renewable Energy Can Help Ease

Bolinger, Mark A

2009-01-01T23:59:59.000Z

388

The Value of Renewable Energy as a Hedge Against Fuel Price Risk: Analytic Contributions from Economic and Finance Theory  

E-Print Network [OSTI]

Deployment of Renewable Energy and Energy Efficiency. LBNL-Can Deployment of Renewable Energy Put Downward Pressure onEfficiency and Renewable Energy Practices and Policies.

Bolinger, Mark A

2009-01-01T23:59:59.000Z

389

CHEMICAL MARKET PRICES  

Science Journals Connector (OSTI)

CHEMICAL MARKET PRICES ... Compiled from weekly current price listings in the Oil, Paint and Drug Reporter , with permission of the publisher under its copyright. ...

1941-11-10T23:59:59.000Z

390

CHEMICAL MARKET PRICES  

Science Journals Connector (OSTI)

CHEMICAL MARKET PRICES ... Compiled from weakly current price listings in the Oil, Paint and Drug Reporter, with permission of the publisher under its copyright. ...

1941-01-10T23:59:59.000Z

391

Chemical Market Prices  

Science Journals Connector (OSTI)

Chemical Market Prices ... Compiled from weekly current price listings in the Oil, Paint and Drug Reporter with permission of the publisher under its copyright. ...

1945-01-10T23:59:59.000Z

392

CHEMICAL MARKET PRICES  

Science Journals Connector (OSTI)

CHEMICAL MARKET PRICES ... Compiled from weekly current price listings in the Oil, Paint and Drug Reporter, with permission of the publisher under its copyright. ...

1941-10-10T23:59:59.000Z

393

CHEMICAL MARKET PRICES  

Science Journals Connector (OSTI)

CHEMICAL MARKET PRICES ... Compiled from weekly current price listings in the Oil, Paint and Drug Reporter , with permission of the publisher under its copyright. ...

1941-02-10T23:59:59.000Z

394

CHEMICAL MARKET PRICES  

Science Journals Connector (OSTI)

CHEMICAL MARKET PRICES ... Compiled from weekly current price listings in the Oil, Paint and Drug Reporter , with permission of the publisher under its copyright. ...

1941-03-10T23:59:59.000Z

395

THE WEEK'S PRICE CHANGES  

Science Journals Connector (OSTI)

THE WEEK'S PRICE CHANGES ... Socony Vacuum Oil Co. effected a second reduction in its prices for No. 2 fuel oil and ... ...

1950-02-27T23:59:59.000Z

396

Determining Price Reasonableness in Federal ESPCs  

SciTech Connect (OSTI)

This document reports the findings and implementation recommendations of the Price Reasonableness Working Group to the Federal ESPC Steering Committee. The working group was formed to address concerns of agencies and oversight organizations related to pricing and fair and reasonable price determination in federal energy savings performance contracts (ESPCs). This report comprises the working group's recommendations and is the proposed draft of a training curriculum on fair and reasonable price determination for users of federal ESPCs. The report includes: (1) A review of federal regulations applicable to determining price reasonableness of federal ESPCs (section 2), (2) Brief descriptions of the techniques described in Federal Acquisition Regulations (FAR) 15.404-1 and their applicability to ESPCs (section 3), and (3) Recommended strategies and procedures for cost-effectively completing price reasonableness determinations (sections 4). Agencies have struggled with fair and reasonable price determinations in their ESPCs primarily because this alternative financing vehicle is relatively new and relatively rare in the federal sector. The methods of determining price reasonableness most familiar to federal contracting officers (price competition based on the government's design and specifications, in particular) are generally not applicable to ESPCs. The regulatory requirements for determining price reasonableness in federal ESPCs have also been misunderstood, as federal procurement professionals who are inexperienced with ESPCs are further confused by multiple directives, including Executive Order 13123, which stresses life-cycle cost-effectiveness. Uncertainty about applicable regulations and inconsistent practice and documentation among agencies have fueled claims that price reasonableness determinations have not been sufficiently rigorous in federal ESPCs or that the prices paid in ESPCs are generally higher than the prices paid for similar goods and services obtained through conventional procurements. While claims of excessive prices are largely unsubstantiated and based on anecdotal evidence, the perception that there is a problem is shared by many in the ESPC community and has been noted by auditors and oversight organizations. The Price Reasonableness Working Group determined that a more formal emphasis on FAR 15.404-1 in the ESPC process could remove much of the doubt about price reasonableness determinations. The working group's recommended consensus policy on price reasonableness stresses the price analysis techniques described in the FAR that are applicable to ESPCs and includes guidance for agencies use of these techniques in determining price reasonableness for their ESPC delivery orders. The recommended policy and guidance, if communicated to federal ESPC stakeholders, can ensure that agencies will comply with the FAR in awarding ESPCs, obtain fair and reasonable prices and best value for the government, and follow procedures that provide auditable documentation of due diligence in price reasonableness determinations.

Shonder, J.A.

2005-03-08T23:59:59.000Z

397

Annual Energy Outlook with Projections to 2025 - Preface  

Gasoline and Diesel Fuel Update (EIA)

Preface Preface Annual Energy Outlook 2005 Preface The Annual Energy Outlook 2005 (AEO2005) presents midterm forecasts of energy supply, demand, and prices through 2025 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA’s National Energy Modeling System (NEMS). The report begins with an “Overview” summarizing the AEO2005 reference case. The next section, “Legislation and Regulations,” discusses evolving legislation and regulatory issues, including legislation and regulations that have been enacted and some that are proposed. Next, the “Issues in Focus” section discusses key energy market issues and examines their potential impacts. In particular, it includes a discussion of the world oil price assumptions used in the reference case and four alternative world oil price cases examined in AEO2005. “Issues in Focus” is followed by “Market Trends,” which provides a summary of energy market trends in the AEO2005 forecast.

398

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

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases On This Page The National Energy Modeling... Component modules Annual Energy Outlook 2011... The National Energy Modeling System The projections in the Annual Energy Outlook 2011 (AEO2011) are generated from the National Energy Modeling System (NEMS) [1], developed and maintained by the Office of Energy Analysis (OEA), formerly known as the Office Integrated Analysis and Forecasting (OIAF), of the U.S. Energy Information Administration (EIA) [2]. In addition to its use in developing the Annual Energy Outlook (AEO) projections, NEMS is also used to complete analytical studies for the U.S. Congress, the Executive Office of the President, other offices within the U.S. Department of Energy (DOE), and other Federal agencies. NEMS is also used by other nongovernment groups,

399

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

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases JUMP TO: The National Energy Modeling System | Component modules | Annual Energy Outlook 2013 cases The National Energy Modeling System Projections in the Annual Energy Outlook 2013 (AEO2013) are generated using the National Energy Modeling System (NEMS) [148], developed and maintained by the Office of Energy Analysis of the U.S. Energy Information Administration (EIA). In addition to its use in developing the Annual Energy Outlook (AEO) projections, NEMS is also used to complete analytical studies for the U.S. Congress, the Executive Office of the President, other offices within the U.S. Department of Energy (DOE), and other Federal agencies. NEMS is also used by other nongovernment groups, such as the Electric Power Research Institute, Duke University, and Georgia Institute

400

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

Gasoline and Diesel Fuel Update (EIA)

NEMS overview and brief description of cases NEMS overview and brief description of cases JUMP TO: The National Energy Modeling System | Component modules | Annual Energy Outlook 2013 cases The National Energy Modeling System Projections in the Annual Energy Outlook 2013 (AEO2013) are generated using the National Energy Modeling System (NEMS) [148], developed and maintained by the Office of Energy Analysis of the U.S. Energy Information Administration (EIA). In addition to its use in developing the Annual Energy Outlook (AEO) projections, NEMS is also used to complete analytical studies for the U.S. Congress, the Executive Office of the President, other offices within the U.S. Department of Energy (DOE), and other Federal agencies. NEMS is also used by other nongovernment groups, such as the Electric Power Research Institute, Duke University, and Georgia Institute

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

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 1 September 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 September 8, 2010 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged about $77 per barrel in August 2010, very close to the July average, but $3 per barrel lower than projected in last month's Outlook. WTI spot prices averaged almost $82 per barrel over the first 10 days of August but then fell by $9 per barrel over the next 2 weeks as the market reacted to a series of reports of a stumbling economic recovery. EIA has lowered its average fourth quarter 2010 WTI spot price forecast to $77 per barrel, compared with $81 in last month's Outlook. WTI spot prices are projected to

402

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

October 2010 October 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 October 13, 2010 Release Crude Oil Prices. WTI oil prices averaged $75 per barrel in September but rose above $80 at the end of the month and into early October. EIA has raised the average fourth- quarter 2010 forecasted WTI spot price to $79 per barrel compared with $77 per barrel in last monthʹs Outlook. WTI spot prices are projected to rise to $85 per barrel by the fourth quarter of next year. As has been the case for most of 2010, WTI futures traded with a notable lack of volatility during the third quarter of 2010 (Figure 1). However, prices did bounce in

403

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

March 2010 March 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 March 9, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $76.39 per barrel in February 2010, almost $2 per barrel lower than the prior month's average and very near the $76 per barrel forecast in last month's Outlook. Last month, the WTI spot price reached a low of $71.15 on February 5 and peaked at $80.04 on February 22. EIA expects WTI prices to average above $80 per barrel this spring, rising to an average of about $82 per barrel by the end of the year and to $85 per barrel by the end of 2011 (West Texas Intermediate Crude Oil Price Chart).

404

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

December 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 December 7, 2010 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged over $84 per barrel in November, more than $2 per barrel higher than the October average. EIA has raised the average winter 2010-2011 period WTI spot price forecast by $1 per barrel from the last monthʹs Outlook to $84 per barrel. WTI spot prices rise to $89 per barrel by the end of next year, $2 per barrel higher than in the last Outlook. Projected WTI prices average $79 per barrel in 2010 and $86 per barrel in 2011. WTI futures for February 2011 delivery during the 5-day period ending December 2

405

Microsoft Word - Price Uncertainty Supplement .docx  

Gasoline and Diesel Fuel Update (EIA)

1 1 1 January 2011 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 January 11, 2011 Release Crude Oil Prices. West Texas Intermediate (WTI) crude oil spot prices averaged over $89 per barrel in December, about $5 per barrel higher than the November average. Expectations of higher oil demand, combined with unusually cold weather in both Europe and the U.S. Northeast, contributed to prices. EIA has raised the first quarter 2011 WTI spot price forecast by $8 per barrel from last monthʹs Outlook to $92 per barrel with a continuing rise to an average $99 per barrel in the fourth quarter of 2012. The projected annual average WTI price is $93 per barrel in 2011 and $98 per barrel in

406

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market “hubs.” The major assumptions used within the NGTDM are grouped into five general categories. They relate to (1) the classification of demand into core and noncore transportation service classes, (2) the pricing of transmission and distribution services, (3) pipeline and storage capacity expansion and utilization, and (4) the implementation of recent regulatory reform. A complete listing of NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation: Natural Gas Transmission and Distribution Model of the National Energy Modeling System, Model Documentation 2003, DOE/EIA- M062(2003) (Washington, DC, January 2003).

407

Flexible procurement strategies smooth price spikes  

SciTech Connect (OSTI)

Pace Global Energy Services has been predicting for some time that the recent peaks in spot coal prices were not sustainable and this has been borne out. The latest available data on coal supply and demand fundamental suggest that spot coal prices may decline even more rapidly than previously forecast. Price volatility over the last five years suggests that a flexible procurement strategy that is well adapted to volatile market conditions may be just as important as knowledge of market fundamentals. 3 figs.

Gaalaas, T. [Pace Global Energy Services LLC (United States)

2006-12-15T23:59:59.000Z

408

CANNED FISH RETAIL PRICES  

E-Print Network [OSTI]

CANNED FISH RETAIL PRICES NOVEMBER 1958 UNITED STATES DEPARTMENT OF THE INTERIOR FISH AND WILDLIFE retail prices for selected canned fish items. The retail prices as contained herein for several types, 500 or over, and prices were obtained by personal visits of agents to the retail stores

409

CANNED FISH RETAIL .PRICES,  

E-Print Network [OSTI]

CANNED FISH RETAIL .PRICES, OC1rOIBrE~ UNITED STATES DEPARTMENT OF THE INT...n.~""n FISH retail prices for selected canned fish items. The retail prices as contained herein for several types, 500 or over, and prices were obtained by personal visits of agents to the retail stores

410

The Value of Renewable Energy as a Hedge Against Fuel Price Risk: Analytic Contributions from Economic and Finance Theory  

E-Print Network [OSTI]

recent studies of renewable energy policies have estimatedand Renewable Energy Practices and Policies. Report Numberand the policy scenario of increased renewable energy

Bolinger, Mark A

2009-01-01T23:59:59.000Z

411

The Value of Renewable Energy as a Hedge Against Fuel Price Risk: Analytic Contributions from Economic and Finance Theory  

E-Print Network [OSTI]

different renewable energy potential and cost assumptions.and negative impacts and costs of renewable energy on otherany incremental cost of renewable energy (relative to

Bolinger, Mark A

2009-01-01T23:59:59.000Z

412

Understanding Wind Turbine Price Trends in the U.S. Over the Past Decade  

E-Print Network [OSTI]

consequent impacts on wind turbine and wind energy pricing.Bloomberg NEF). 2011c. Wind Turbine Price Index, Issue V.Understanding Trends in Wind Turbine Prices Over the Past

Bolinger, Mark

2013-01-01T23:59:59.000Z

413

Minimum Purchase Price Regulations (Prince Edward Island, Canada)  

Broader source: Energy.gov [DOE]

The Minimum Purchase Price Regulations establish the price which utilities must pay for power produced by large-scale renewable energy generators that is those capable of producing more than 100...

414

Wind Power Price Trends in the United States  

E-Print Network [OSTI]

should eventually help wind power regain the downward priceModern Energy Review] Wind Power Price Trends in the Unitedled the world in adding new wind power capacity in 2008, and

Bolinger, Mark

2010-01-01T23:59:59.000Z

415

U.S. gasoline prices continue to increase (short version)  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

The U.S. average retail price for regular gasoline rose to 3.68 a gallon on Monday. That's up 4 12 cents from a week ago, based on the weekly price survey by the U.S. Energy...

416

U.S. gasoline prices continue to increase (short version)  

Gasoline and Diesel Fuel Update (EIA)

average retail price for regular gasoline rose to 3.61 a gallon on Labor Day Monday. That's up 5.6 cents from a week ago, based on the weekly price survey by the U.S. Energy...

417

U.S. gasoline prices continue to increase (long version)  

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

The U.S. average retail price for regular gasoline rose to 3.68 a gallon on Monday. That's up 4 12 cents from a week ago, based on the weekly price survey by the U.S. Energy...

418

U.S. Gasoline prices continue to increase (long version)  

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

average retail price for regular gasoline rose to 3.61 a gallon on Labor Day Monday. That's up 5.6 cents from a week ago, based on the weekly price survey by the U.S. Energy...

419

Fact #742: August 27, 2012 Oil Price and Economic Growth  

Broader source: Energy.gov [DOE]

Major oil price shocks have disrupted world energy markets five times in the past 30 years (1973-74, 1979-80, 1990-91, 1999-2000, and 2008). Most of the oil price shocks were followed by an...

420

Diesel Fuel Price Pass-through  

Gasoline and Diesel Fuel Update (EIA)

Diesel Fuel Price Pass-through Diesel Fuel Price Pass-through EIA Home > Petroleum > Petroleum Feature Articles Diesel Fuel Price Pass-through Printer-Friendly PDF Diesel Fuel Price Pass-through by Michael Burdette and John Zyren* Over the past several years, the Energy Information Administration (EIA) has extensively studied the relationships between wholesale and retail markets for petroleum products. Beginning with gasoline, we looked at the two ends of the pricing structure in the U.S. market: daily spot prices, which capture sales of large quantities of product between refiners, importers/exporters, and traders; and weekly retail prices, measured at local gasoline outlets nationwide. In the course of this analysis, EIA has found that the relationships between spot and retail prices are consistent and predictable, to the extent that changes in spot prices can be used to forecast subsequent changes in retail prices for the appropriate regions. This article represents the extension of this type of analysis and modeling into the diesel fuel markets.

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

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

April 2010 April 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 April 6, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $81 per barrel in March 2010, almost $5 per barrel above the prior month's average and $3 per barrel higher than forecast in last month's Outlook. Oil prices rose from a low this year of $71.15 per barrel on February 5 to $80 per barrel by the end of February, generally on news of robust economic and energy demand growth in non-OECD Asia and the Middle East, and held near $81 until rising to $85 at the start of April. EIA expects WTI prices to average above $81 per barrel this summer, slightly less that $81 for 2010 as a whole,

422

MTBE Prices Responded to Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: On top of the usual factors impacting gasoline prices, natural gas has had some influence recently. MTBE is an oxygenate used in most of the RFG consumed in the U.S. Generally, it follows gasoline prices and its own supply/demand balance factors. But this winter, we saw it respond strongly to natural gas prices. MTBE is made from methanol and isobutylene, which in turn come from methane and butane. Both methane and butane come from natural gas streams. Until this year, the price of natural gas has been so low that it had little effect. But the surge that occurred in December and January pulled MTBE up . Keep in mind that about 11% MTBE is used in a gallon of RFG, so a 30 cent increase in MTBE is only about a 3 cent increase in the price of RFG. While we look ahead at this summer, natural gas prices should be

423

U.S. diesel fuel price decrease  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

U.S. average retail price for on-highway diesel fuel fell to 3.66 a gallon on Monday. That's down 1.6 cents from a week ago, based on the weekly price survey by the U.S. Energy...

424

China Energy Primer  

E-Print Network [OSTI]

on Pricing and Cost Sharing for Renewable Energy Poweron Pricing and Cost Sharing for Renewable Energy Powerprices and share costs for renewable energy power generation

Ni, Chun Chun

2010-01-01T23:59:59.000Z

425

Appliance Efficiency Standards and Price Discrimination  

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

Appliance Efficiency Standards and Price Discrimination Appliance Efficiency Standards and Price Discrimination Title Appliance Efficiency Standards and Price Discrimination Publication Type Report LBNL Report Number LBNL-6283E Year of Publication 2013 Authors Spurlock, Anna C. Date Published 05/2013 Keywords EES-EG Abstract I explore the effects of two simultaneous changes in minimum energy efficiency and ENERGY STAR standards for clothes washers. Adapting the Mussa and Rosen (1978) and Ronnen (1991) second-degree price discrimination model, I demonstrate that clothes washer prices and menus adjusted to the new standards in patterns consistent with a market in which firms had been price discriminating. In particular, I show evidence of discontinuous price drops at the time the standards were imposed, driven largely by mid-low efficiency segments of the market. The price discrimination model predicts this result. On the other hand, in a perfectly competition market, prices should increase for these market segments. Additionally, new models proliferated in the highest efficiency market segment following the standard changes. Finally, I show that firms appeared to use different adaptation strategies at the two instances of the standards

426

Regional Retail Gasoline Prices  

Gasoline and Diesel Fuel Update (EIA)

7 7 Notes: Retail gasoline prices, like those for distillate fuels, have hit record prices nationally and in several regions this year. The national average regular gasoline price peaked at $1.68 per gallon in mid-June, but quickly declined, and now stands at $1.45, 17 cents higher than a year ago. Two regions, in particular, experienced sharp gasoline price runups this year. California, which often has some of the highest prices in the nation, saw prices peak near $1.85 in mid-September, while the Midwest had average prices over $1.87 in mid-June. Local prices at some stations in both areas hit levels well over $2.00 per gallon. The reasons for the regional price runups differed significantly. In the Midwest, the introduction of Phase 2 RFG was hampered by low stocks,

427

Virginia Gasoline Price Data  

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

Virginia Virginia Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Alexandria AlexandriaGasPrices.com Automotive.com Mapquest.com Arlington ArlingtonGasPrices.com Automotive.com Mapquest.com Chesapeake ChesapeakeGasPrices.com Automotive.com Mapquest.com Hampton HamptonGasPrices.com Automotive.com Mapquest.com Newport News NewportNewsGasPrices.com Automotive.com Mapquest.com Norfolk NorfolkGasPrices.com Automotive.com Mapquest.com Portsmouth PortsmouthGasPrices.com Automotive.com Mapquest.com Richmond RichmondGasPrices.com Automotive.com Mapquest.com Virginia Beach VirginiaBeachGasPrices.com Automotive.com Mapquest.com

428

Illinois Gasoline Price Data  

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

Illinois Illinois Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Arlington Heights ArlingtonHeightsGasPrices.com Automotive.com MapQuest.com Aurora AuroraGasPrices.com Automotive.com MapQuest.com Bloomington BloomingtonGasPrices.com Automotive.com MapQuest.com Champaign ChampaignGasPrices.com Automotive.com MapQuest.com Chicago ChicagoGasPrices.com Automotive.com MapQuest.com Decatur DecaturGasPrices.com Automotive.com Mapquest.com Elgin ElginGasPrices.com Automotive.com MapQuest.com Joliet JolietGasPrices.com Automotive.com MapQuest.com Naperville NapervilleGasPrices.com Automotive.com MapQuest.com

429

Oklahoma Gasoline Price Data  

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

Oklahoma Oklahoma Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Lawton LawtonGasPrices.com Automotive.com Mapquest.com Norman NormanGasPrices.com Automotive.com Mapquest.com Oklahoma City OklahomaCityGasPrices.com Automotive.com Mapquest.com Tulsa TulsaGasPrices.com Automotive.com Mapquest.com Other Oklahoma Cities OklahomaGasPrices.com (search by city or ZIP code) - GasBuddy.com Oklahoma Gas Prices (selected cities) - GasBuddy.com Oklahoma Gas Prices (organized by county) - Automotive.com Gas Prices of the United States: Oklahoma Cities - MapQuest Oklahoma Gas Prices (organized by county, search by ZIP code) -

430

Tennessee Gasoline Price Data  

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

Tennessee Tennessee Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Chattanooga ChattanoogaGasPrices.com Automotive.com Mapquest.com Clarksville ClarksvilleGasPrices.com Automotive.com Mapquest.com Knoxville KnoxvilleGasPrices.com Automotive.com Mapquest.com Memphis MemphisGasPrices.com Automotive.com Mapquest.com Murfreesboro MurfreesboroGasPrices.com Automotive.com Mapquest.com Nashville NashvilleGasPrices.com Automotive.com Mapquest.com Other Tennessee Cities TennesseeGasPrices.com (search by city or ZIP code) - GasBuddy.com Tennessee Gas Prices (selected cities) - GasBuddy.com Tennessee Gas Prices (organized by county) - Automotive.com

431

Wisconsin Gasoline Price Data  

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

Wisconsin Wisconsin Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Appleton AppletonGasPrices.com Automotive.com Mapquest.com Eau Claire EauClaireGasPrices.com Automotive.com Mapquest.com Green Bay GreenBayGasPrices.com Automotive.com Mapquest.com Kenosha KenoshaGasPrices.com Automotive.com Mapquest.com Madison MadisonGasPrices.com Automotive.com Mapquest.com Milwaukee MilwaukeeGasPrices.com Automotive.com Mapquest.com Other Wisconsin Cities WisconsinGasPrices.com (search by city or ZIP code) - GasBuddy.com Wisconsin Gas Prices (selected cities) - GasBuddy.com Wisconsin Gas Prices (organized by county) - Automotive.com

432

Maryland Gasoline Price Data  

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

Maryland Maryland Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Baltimore BaltimoreGasPrices.com Automotive.com MapQuest.com Bethesda BethesdaGasPrices.com Automotive.com MapQuest.com Bowie BowieGasPrices.com Automotive.com MapQuest.com Frederick FrederickGasPrices.com Automotive.com MapQuest.com Gaithersburg GaithersburgGasPrices.com Automotive.com MapQuest.com Other Maryland Cities MarylandGasPrices.com (search by city or ZIP code) - GasBuddy.com Maryland Gas Prices (selected cities) - GasBuddy.com Maryland Gas Prices (organized by county) - Automotive.com Gas Prices of the United States: Maryland Cities - MapQuest

433

Massachusetts Gasoline Price Data  

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

Massachusetts Massachusetts Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Boston BostonGasPrices.com Automotive.com MapQuest.com Brockton BrocktonGasPrices.com Automotive.com MapQuest.com Cambridge CambridgeGasPrices.com Automotive.com MapQuest.com Fall River FallRiverGasPrices.com Automotive.com MapQuest.com Haverhill HaverhillGasPrices.com Automotive.com MapQuest.com Lawrence LawrenceGasPrices.com Automotive.com MapQuest.com Lowell LowellGasPrices.com Automotive.com MapQuest.com New Bedford NewBedfordGasPrices.com Automotive.com Mapquest.com Taunton TauntonGasPrices.com Automotive.com MapQuest.com

434

Ohio Gasoline Price Data  

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

Ohio Ohio Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Akron AkronGasPrices.com Automotive.com Mapquest.com Cincinnati CincinnatiGasPrices.com Automotive.com Mapquest.com Cleveland ClevelandGasPrices.com Automotive.com Mapquest.com Columbus ColumbusGasPrices.com Automotive.com Mapquest.com Dayton DaytonGasPrices.com Automotive.com Mapquest.com Toledo ToledoGasPrices.com Automotive.com Mapquest.com Other Ohio Cities OhioGasPrices.com (search by city or ZIP code) - GasBuddy.com Ohio Gas Prices (selected cities) - GasBuddy.com Ohio Gas Prices (organized by county) - Automotive.com

435

The Resilience of the Indian Economy to Rising Oil Prices as a Validation Test for a Global Energy-Environment-Economy CGE Model  

E-Print Network [OSTI]

1 The Resilience of the Indian Economy to Rising Oil Prices as a Validation Test for a Global., 2009, `The resilience of the Indian economy to rising oil prices as a validation test for a global so, it compares the modeled and observed responses of the Indian economy to the rise of oil price

Paris-Sud XI, Université de

436

The Value of Renewable Energy as a Hedge Against Fuel Price Risk: Analytic Contributions from Economic and Finance Theory  

E-Print Network [OSTI]

Analysis of a 10-Percent Renewable Portfolio Standard. SR/Impacts of a 15-Percent Renewable Portfolio Standard. SR/through Increased Deployment of Renewable Energy and Energy

Bolinger, Mark A

2009-01-01T23:59:59.000Z

437

State Volume Price Volume Price Volume Price Volume Price Volume Price  

Gasoline and Diesel Fuel Update (EIA)

7 7 2000 2001 2002 2003 2004 State Volume Price Volume Price Volume Price Volume Price Volume Price Pipeline (Canada) Eastport, ID..................... 830,351 3.79 802,182 4.71 759,647 2.83 R 623,652 4.72 707,885 5.30 Calais, ME ...................... 123,521 4.50 152,486 4.47 124,991 3.49 R 115,301 R 5.85 102,292 6.44 Detroit, MI ....................... 6,171 3.82 405 9.34 1,948 3.56 2,514 5.96 1,117 6.27 Marysville, MI.................. 0 -- 0 -- 74 3.95 0 -- 303 7.80 St. Clair, MI..................... 17,198 4.45 21,747 4.54 28,441 3.19 5,202 5.84 22,853 6.50 International Falls, MN .... 3,022 2.77 617 4.85 602 3.01 0 -- 0 -- Noyes, MN...................... 469,361 3.75 448,898 4.19 402,621 3.09 R 359,801 5.04 399,298 5.77 Warroad, MN .................. 4,576 3.95 5,318 4.52

438

Pricing data center demand response  

Science Journals Connector (OSTI)

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

Zhenhua Liu; Iris Liu; Steven Low; Adam Wierman

2014-06-01T23:59:59.000Z

439

Microsoft Word - Documentation - Price Forecast Uncertainty.doc  

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

October 2009 October 2009 1 October 2009 Short-Term Energy Outlook Supplement: Energy Price Volatility and Forecast Uncertainty 1 Summary It is often noted that energy prices are quite volatile, reflecting market participants' adjustments to new information from physical energy markets and/or markets in energy- related financial derivatives. Price volatility is an indication of the level of uncertainty, or risk, in the market. This paper describes how markets price risk and how the market- clearing process for risk transfer can be used to generate "price bands" around observed futures prices for crude oil, natural gas, and other commodities. These bands provide a quantitative measure of uncertainty regarding the range in which markets expect prices to

440

Assumptions to the Annual Energy Outlook  

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 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.

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

China Energy Primer  

E-Print Network [OSTI]

5 ENERGY PRICES Figure 5-1 Major Coal Price Reforms (1980-117 Figure 5-2 Ex-Factory Coal Price Index (1980-Figure 6-14 Comparison of Coal Prices in Chinas Domestic

Ni, Chun Chun

2010-01-01T23:59:59.000Z

442

EIA - The National Energy Modeling System: An Overview 2003-Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module The National Energy Modeling System: An Overview 2003 Natural Gas Transmission and Distribution Module Figure 15. Natural Gas Transmission and Distribution Module Structure. Need help, contact the National Energy Information Center at 202-586-8800. Figure 16. Natural Gas Transmission and distribution Module Network. Need help, contact the National Energy Information Center at 202-586-8800. Natural Gas Transmission and distribution Module Table. Need help, contact the National Energy Information Center at 202-586-8800. The natural gas transmission and distribution module (NGTDM) of NEMS represents the natural gas market and determines regional market–clearing prices for natural gas supplies and for end–use consumption, given the

443

SF 6432-LA Standard Terms and Conditions for Fixed Price Contracts Established Under the Renewable Energy Programs in Latin American Countries  

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

SF 6432-LA (04-95) SECTION II STANDARD TERMS AND CONDITIONS FOR FIXED PRICE CONTRACTS ESTABLISHED UNDER THE RENEWABLE ENERGY PROGRAMS IN LATIN AMERICAN COUNTRIES INDEX OF CLAUSES THE FOLLOWING CLAUSES APPLY TO REQUESTS FOR QUOTATION AND CONTRACTS AS INDICATED UNLESS SPECIFICALLY DELETED, OR EXCEPT TO THE EXTENT THEY AERE SPECIFICALLY SUPPLEMENTED OR AMENDED IN WRITING IN THE SIGNATURE PAGE OR SECTION I. No. Title Page "A" Clauses apply to Requests for Quotation and Contracts at any value for work performed A10 Definitions 2 A11 Unclassified Contract 2 A12 Assignment 2 *A13 Releases Void 2 *A14 Notice of Labor Disputes 2 A17 Delegated Representatives 2 A19 Terms and Conditions 2 *A20 Permits 2 *A23 Applicable Law 2 *A26 Officials Not to Benefit (FAR 52.203-1

444

Natural Gas Spot Prices:  

Gasoline and Diesel Fuel Update (EIA)

4 of 26 4 of 26 Notes: Spot wellhead prices last summer averaged well over $4.00 per thousand cubic feet during a normally low-price season. During the fall, these prices stayed above $5.00 per thousand cubic feet, more than double the year-ago average price. In January, the spot wellhead price averaged a record $8.98 per thousand cubic feet. Spot prices at the wellhead have never been this high for such a prolonged period. The chief reason for these sustained high gas prices was, and still is, uneasiness about the supply situation. Concern about the adequacy of winter supplies loomed throughout most of the summer and fall as storage levels remained significantly depressed. Last December, the most severe assumptions about low storage levels became real, when the spot price

445

The Minimum Price Contract  

E-Print Network [OSTI]

A minimum price contract is one of many tools a marketer may use to better manage price and production risk while trying to achieve financial goals and objectives. This publication discusses the advantages and disadvantages involved...

Waller, Mark L.; Amosson, Stephen H.; Welch, Mark; Dhuyvetter, Kevin C.

2008-10-17T23:59:59.000Z

446

Residential propane prices increase  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

propane prices increase The average retail price for propane rose 3.2 cents from a week ago to 2.86 per gallon. That's up 59.3 cents from a year ago, based on the residential...

447

Residential propane prices decreases  

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

5, 2014 Residential propane prices decreases The average retail price for propane fell to 3.89 per gallon, that's down 11.9 cents from a week ago, based on the residential heating...

448

Residential propane prices increase  

Gasoline and Diesel Fuel Update (EIA)

propane prices increase The average retail price for propane rose 10.3 cents from a week ago to 2.96 per gallon. That's up 68.1 cents from a year ago, based on the residential...

449

Residential propane prices increase  

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

propane prices increase The average retail price for propane rose 3.9 cents from a week ago to 2.80 per gallon. That's up 53.7 cents from a year ago, based on the residential...

450

Residential propane prices increase  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

propane prices increase The average retail price for propane rose 5.5 cents per gallon from last week to 2.62 per gallon; up 37.4 cents from a year ago, based on the residential...

451

Residential propane prices surges  

Gasoline and Diesel Fuel Update (EIA)

propane prices surges The average retail price for propane rose to an all-time high of 4.01 a gallon, that's up 1.05 from a week ago, based on the residential heating fuel survey...

452

Residential propane price increases  

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

propane price increases The average retail price for propane is 2.41 per gallon, up 6-tenths of a cent from last week, based on the residential heating fuel survey by the U.S....

453

Residential propane prices surges  

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

Midwest and Northeast propane prices much higher this winter than last year Households that heat with propane will pay for that propane at prices averaging 39 percent higher in the...

454

Residential propane prices stable  

Gasoline and Diesel Fuel Update (EIA)

propane price decreases The average retail price for propane is 2.40 per gallon, down 9-tenths of a cent from last week, based on the residential heating fuel survey by the U.S....

455

Residential propane price decreases  

Gasoline and Diesel Fuel Update (EIA)

6, 2014 Residential propane price decreases The average retail price for propane fell to 3.48 per gallon, down 15.9 cents from a week ago, based on the residential heating fuel...

456

Residential propane prices surges  

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

9, 2014 Residential propane price decreases The average retail price for propane fell to 3.08 per gallon, down 8.6 cents from a week ago, based on the residential heating fuel...

457

Residential propane prices increase  

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

propane prices increase The average retail price for propane rose 4.8 cents from a week ago to 2.76 per gallon. That's up 51.2 cents from a year ago, based on the residential...

458

Residential propane prices increase  

Gasoline and Diesel Fuel Update (EIA)

propane prices increase The average retail price for propane rose 2.5 cents from a week ago to 2.83 per gallon. That's up 56 cents from a year ago, based on the residential...

459

Residential propane price decreases  

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

05, 2014 Residential propane price decreases The average retail price for propane fell to 2.40 per gallon, down 1.2 cents from a week ago, based on the residential heating fuel...

460

Residential propane prices surges  

Gasoline and Diesel Fuel Update (EIA)

2, 2014 Residential propane price decreases The average retail price for propane fell to 3.17 per gallon, down 13.1 cents from a week ago, based on the residential heating fuel...

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

Residential propane prices increase  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

propane prices increase The average retail price for propane rose 2.3 cents per gallon from last week to 2.57 per gallon; up 32.2 cents from a year ago, based on the residential...

462

Residential propane prices increase  

Gasoline and Diesel Fuel Update (EIA)

propane prices increase The average retail price for propane rose 9.1 cents from a week ago to 2.71 per gallon. That's up 46.9 cents from a year ago, based on the residential...

463

Residential propane prices surges  

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

5, 2014 Residential propane price decreases The average retail price for propane fell to 3.30 per gallon, down 17.5 cents from a week ago, based on the residential heating fuel...

464

Livestock Seasonal Price Variation  

E-Print Network [OSTI]

Seasonal price movements can be measured and used to help in marketing livestock. This publication includes 10-year seasonal price indexes for several livestock categories, and explains how to interpret and use the information....

Davis, Ernest E.; Sartwelle III, James D.; Mintert, James R.

1999-09-21T23:59:59.000Z

465

Residential heating oil price  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

heating oil price decreases The average retail price for home heating oil fell 6.3 cents from a week ago to 2.91 per gallon. That's down 1.10 from a year ago, based on the...

466

Residential heating oil price  

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

heating oil price decreases The average retail price for home heating oil fell 7.5 cents from a week ago to 2.84 per gallon. That's down 1.22 from a year ago, based on the...

467

Residential heating oil price  

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

heating oil price decreases The average retail price for home heating oil fell 7.6 cents from a week ago to 2.97 per gallon. That's down 1.05 from a year ago, based on the...

468

Residential heating oil price  

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

heating oil price decreases The average retail price for home heating oil fell 3.6 cents from a week ago to 3.04 per gallon. That's down 99.4 cents from a year ago, based on the...

469

The National Energy Modeling System: An Overview 2000 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

natural gas transmission and distribution module (NGTDM) of NEMS represents the natural gas market and determines regional market-clearing prices for natural gas supplies and for end-use consumption, given the information passed from other NEMS modules. A transmission and distribution network (Figure 15), composed of nodes and arcs, is used to simulate the interregional flow and pricing of gas in the contiguous United States and Canada in both the peak (December through March) and offpeak (April through November) period. This network is a simplified representation of the physical natural gas pipeline system and establishes the possible interregional flows and associated prices as gas moves from supply sources to end users. natural gas transmission and distribution module (NGTDM) of NEMS represents the natural gas market and determines regional market-clearing prices for natural gas supplies and for end-use consumption, given the information passed from other NEMS modules. A transmission and distribution network (Figure 15), composed of nodes and arcs, is used to simulate the interregional flow and pricing of gas in the contiguous United States and Canada in both the peak (December through March) and offpeak (April through November) period. This network is a simplified representation of the physical natural gas pipeline system and establishes the possible interregional flows and associated prices as gas moves from supply sources to end users. Figure 15. Natural Gas Transmission and Distribution Module Network

470

A k-factor GIGARCH process: Estimation and Application on electricity market spot prices.  

E-Print Network [OSTI]

A k-factor GIGARCH process: Estimation and Application on electricity market spot prices. Abdou Kâ time series of market data, such as electricity spot price, exhibit long-memory, in the sense of slowly this approach to electricity prices (spot prices) from the German energy market (European Energy e

Paris-Sud XI, Université de

471

Practical stochastic modelling of electricity prices Michel Culot  

E-Print Network [OSTI]

Practical stochastic modelling of electricity prices Michel Culot Electrabel SA, Belgium Val and forward electricity. The model captures various styl- ized features of power prices, including mean pricing, Electricity and energy mar- kets, Regime-switching spikes, State-space (Kalman filter) estimation

Paris-Sud XI, Université de

472

Mr. Harry Price  

Science Journals Connector (OSTI)

... THROUGH the death of Mr. Harry Price on March 29, psychical research has lost its most distinguished journalist and writer ...

1948-04-24T23:59:59.000Z

473

Assumptions to the Annual Energy Outlook 1999 - Natural Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by obtaining market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market “hubs.” The major assumptions used within the NGTDM are grouped into five general categories. They relate to (1) the classification of demand into core and noncore transportation service classes, (2) the pricing of transmission and distribution services, (3) pipeline and storage capacity expansion and utilization, (4) the implementation of recent regulatory reform, and (5) the implementation of provisions of the Climate Change Action Plan (CCAP). A complete listing of NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation Report: Natural Gas Transmission and Distribution Model of the National Energy Modeling System, DOE/EIA-MO62/1, January 1999.

474

EIA - Assumptions to the Annual Energy Outlook 2008 - Petroleum Market  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2008 Petroleum Market Module Figure 9. Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Petroleum Market Module (PMM) projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, bioesters, corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. The PMM contains a linear programming (LP) representation of U.S. refining

475

Cost-effective and comfort-aware residential energy management under different pricing schemes and weather conditions  

Science Journals Connector (OSTI)

Abstract Nowadays with the emerging of smart micro-grids(SM-Gs) in residential sectors, a large portion of energy consumption can be saved through optimal scheduling of household devices and management of domestic hybrid energy sources. By the aid of such technologies, residential consumers have the capability to mitigate their energy costs and satisfy their own requirements paying less attention to the configuration of the energy supply system. This paper presents a novel residential energy management system (REMS) to improve the efficiency of energy consumption in a typical SM-G taking into account minimum cost of energy as well as maximum user's comfort level as competitive objectives. The optimization model is also formulated as a mixed integer nonlinear problem (MINLP) and its performance is tested under different operating scenarios with real data. The simulation results show that the proposed model not only reduces energy consumption costs, but also ensures a comfortable lifestyle for occupants.

Amjad Anvari-Moghaddam; Hassan Monsef; Ashkan Rahimi-Kian

2015-01-01T23:59:59.000Z

476

CANNED FISH RETAIL PRICES  

E-Print Network [OSTI]

CANNED FISH RETAIL PRICES JUNE ll959 UNITED STATES DEPARTMENT OF THE INTERIOR FISH AND WILDUFE, Commissioner CANNED FISH RETAIL PRICES JUNE 1959 Prepared in the Bureau of Commercial Fisheries Branch Fisheries has contracted with the Bureau of Labo r Statistics to obtain average retail prices for selected

477

CANNED FISH RETAIL PRICES  

E-Print Network [OSTI]

CANNED FISH RETAIL PRICES MARCH 1959 UNITED STATES DEPARTMENT OF THE INTERIOR FISH AND WILDLIFE, Commissioner CANNED FISH RETAIL PRICES MARCH 1959 Prepared in the Bureau of Commercial Fisheries Branch canned fish items. The retail prices as contain d h rein for s veral types of canned tuna, canned salmon

478

CANNED FISH RETAIL PRICES  

E-Print Network [OSTI]

CANNED FISH RETAIL PRICES JA.NUARY 11959 UNITED STATES DEPARTMENT OF THE INTERIOR FISH AND WILDLIFE, Commissioner CANNED FISH RETAIL PRICES JANUARY 195 9 Prepared in the Bureau of Commercial Fisheries Branch Fisheries has contracted with the Bureau of Labor Statistics to obtain average retail prices for se lected

479

California Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2008 2009 2010 2011 2012 2013 View History Wellhead Price 8.38 3.96 4.87 1967-2010 Imports Price 9.15 2.83 4.76 3.57 -- 3.59 2007-2013 Exports Price 8.06 3.76 4.51 4.18 2.90 3.89...

480

Connecticut Natural Gas Prices  

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

2008 2009 2010 2011 2012 2013 View History Pipeline and Distribution Use Price 1967-2005 Citygate Price 10.24 6.81 6.58 5.92 5.12 5.42 1984-2013 Residential Price 17.85 14.81 14.93...

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

Utility spot pricing study : Wisconsin  

E-Print Network [OSTI]

Spot pricing covers a range of electric utility pricing structures which relate the marginal costs of electric generation to the prices seen by utility customers. At the shortest time frames prices change every five ...

Caramanis, Michael C.

1982-01-01T23:59:59.000Z

482

Grid Pricing of Fed Cattle  

E-Print Network [OSTI]

There are several value-based fed cattle pricing systems, including formula pricing, price grids and alliances. This publication describes the different cattle pricing methods and helps you decide which is best for you....

Schroeder, Ted C.; Hogan, Robert J.; Anderson, David P.

2009-03-02T23:59:59.000Z

483

Price Responsive Demand in New York Wholesale Electricity Market using  

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

Price Responsive Demand in New York Wholesale Electricity Market using Price Responsive Demand in New York Wholesale Electricity Market using OpenADR Title Price Responsive Demand in New York Wholesale Electricity Market using OpenADR Publication Type Report LBNL Report Number LBNL-5557E Year of Publication 2012 Authors Kim, Joyce Jihyun, and Sila Kiliccote Date Published 06/2012 Publisher LBNL/NYSERDA Keywords commercial, demand response, dynamic pricing, mandatory hourly pricing, open automated demand response, openadr, pilot studies & implementation, price responsive demand Abstract In New York State, the default electricity pricing for large customers is Mandatory Hourly Pricing (MHP), which is charged based on zonal day-ahead market price for energy. With MHP, retail customers can adjust their building load to an economically optimal level according to hourly electricity prices. Yet, many customers seek alternative pricing options such as fixed rates through retail access for their electricity supply. Open Automated Demand Response (OpenADR) is an XML (eXtensible Markup Language) based information exchange model that communicates price and reliability information. It allows customers to evaluate hourly prices and provide demand response in an automated fashion to minimize electricity costs. This document shows how OpenADR can support MHP and facilitate price responsive demand for large commercial customers in New York City.

484

Are oil prices going to remain volatile?  

Science Journals Connector (OSTI)

For numerous planning problems in industrial but also in private management the expectation of future energy prices remains a crucial parameter. On the basis ... a comprehensive demand/supply model for the world

Dr. F. Wirl

1985-04-01T23:59:59.000Z

485

Value of Irrigation Water with Alternative Input Prices, Product Prices and Yield Levels: Texas High Plains and Rio Grande Valley  

E-Print Network [OSTI]

risen to record levels; because of the energy crisis and the rapid rate of inflation, prices of fertilizer and fuel have at least doubled, and the price of other farm inputs have risen substantially. These price changes, in absolute and relative terms...

Lacewell, R. D.; Sprott, J. M.; Beattie, B. R.

486

How regulators should use natural gas price forecasts  

SciTech Connect (OSTI)

Natural gas prices are critical to a range of regulatory decisions covering both electric and gas utilities. Natural gas prices are often a crucial variable in electric generation capacity planning and in the benefit-cost relationship for energy-efficiency programs. High natural gas prices can make coal generation the most economical new source, while low prices can make natural gas generation the most economical. (author)

Costello, Ken

2010-08-15T23:59:59.000Z

487

DOE/EIA-0581(2000) The National Energy Modeling System: An Overview  

Gasoline and Diesel Fuel Update (EIA)

NEMS NEMS represents domestic energy markets by ex- plicitly representing the economic decision making involved in the production, conversion, and con- sumption of energy products. Where possible, NEMS includes explicit representation of energy technolo- gies and their characteristics. Since energy costs and availability and en- ergy-consuming characteristics can vary widely across regions, considerable regional detail is in- cluded. Other details of production and consumption cate- gories are represented to facilitate policy analysis and en- sure the validity of the results. A summary of the detail provided in NEMS is shown below. Major Assumptions Each module of NEMS embodies many assumptions and data to characterize the future production, conversion, or consumption of energy in the United States. Two major Energy Information Administration/The National Energy Modeling

488

Average Commercial Price  

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

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

489

Average Commercial Price  

Gasoline and Diesel Fuel Update (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

490

Natural Gas Industrial Price  

Gasoline and Diesel Fuel Update (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

491

Average Residential Price  

Gasoline and Diesel Fuel Update (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

492

Average Residential Price  

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

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

493

Asymmetric responses of highway travel demand to changes in fuel price: An explanation via fuel price uncertainty  

Science Journals Connector (OSTI)

Abstract Previous research has examined asymmetric effects of fuel price uncertainty on energy demand. If we consider that energy demand is related to travel demand, the changes in fuel prices may have asymmetric effects on highway travel demand via fuel price uncertainty. In other words, when in general fuel price is steadily rising, the highway traffic volume decreases by a small percentage. On the other hand, the highway traffic volume increases by a large percentage when fuel prices are falling. We hypothesize that the uncertainty in fuel prices generates this kind of asymmetric effect on highway traffic volume in Korea. We use the Korean monthly fuel price and highway traffic volume data from 2001 to 2009, and define the intra-month (weekly) fuel price changes as monthly fuel price volatility which is a proxy for monthly fuel price uncertainty. We found that the direction of the change in fuel prices had asymmetric effects on highway travel demand and that the fuel price uncertainty led drivers to respond asymmetrically to the changes in fuel prices.

Yongjae Kwon; Jaimin Lee

2014-01-01T23:59:59.000Z

494

Montana Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.72 7.50 3.16 3.64 1967-2010 Imports Price 6.66 8.22 3.88 4.13 3.75 2.45 1989-2012 Exports Price 6.16 8.14 3.63 4.05 3.82 2.40 1989-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.42 7.71 5.63 5.17 5.11 4.23 1984-2012 Residential Price 9.91 11.45 9.50 8.64 8.80 8.06 1967-2012 Percentage of Total Residential Deliveries included in Prices 99.9 99.9 99.8 99.8 99.8 99.8 1989-2012 Commercial Price 9.76 11.32 9.41 8.54 8.66 7.98 1967-2012 Percentage of Total Commercial Deliveries included in Prices 78.5 79.6 49.2 54.6 53.3 52.9 1990-2012 Industrial Price 9.75 11.04 9.06 8.07 8.13 7.54 1997-2012 Percentage of Total Industrial Deliveries included in Prices

495

Louisiana Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 7.02 8.73 3.82 4.23 1967-2010 Imports Price 6.98 9.76 3.89 4.84 7.57 7.98 1989-2012 Exports Price -- -- -- 7.07 9.63 11.80 2007-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.22 9.58 5.96 5.43 5.67 3.48 1984-2012 Residential Price 14.20 15.49 13.15 11.73 11.37 11.54 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 11.83 13.52 10.46 9.88 9.36 8.44 1967-2012 Percentage of Total Commercial Deliveries included in Prices 98.0 98.4 92.0 85.9 83.6 78.0 1990-2012 Industrial Price 7.08 9.32 4.31 4.68 4.25 2.96 1997-2012 Percentage of Total Industrial Deliveries included in Prices

496

Nebraska Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 4.86 6.22 2.97 3.98 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.67 8.12 5.87 5.62 5.11 4.31 1984-2012 Residential Price 11.15 11.11 9.34 8.95 8.84 8.68 1967-2012 Percentage of Total Residential Deliveries included in Prices 85.7 87.1 87.8 87.4 87.3 85.8 1989-2012 Commercial Price 9.16 9.62 7.44 7.08 6.69 6.19 1967-2012 Percentage of Total Commercial Deliveries included in Prices 63.9 57.5 61.3 60.6 60.6 55.8 1990-2012 Industrial Price 7.97 9.12 6.02 5.85 5.61 4.34 1997-2012 Percentage of Total Industrial Deliveries included in Prices 9.7 10.2 8.9 8.2 7.6 6.8 1997-2012 Vehicle Fuel Price 15.10 15.29 1994-2012 Electric Power Price

497

Consumer Prices During  

Gasoline and Diesel Fuel Update (EIA)

City Gate City Gate City gate prices represent the total cost paid by gas distribu- tion companies for gas received at the point where the gas is physically transferred from a pipeline company or trans- mission system. This price is intended to reflect all charges for the acquisition, storage, and transportation of gas as well as other charges associated with the LDC's obtaining the gas for sale to consumers. Prices paid at the city gate by local distribution companies rose substantially between 1995 and 1996, climbing from $2.78 per thousand cubic feet to $3.27, an increase of 18 percent. Residential Residential consumers pay the highest price for natural gas. It increased to $6.34 per thousand cubic feet from the 1995 price of $6.06 per thousand cubic feet. However, the 1996 price was 1 percent lower than the 1994 price. In recent years, only modest changes in constant dollars have been

498

Connecticut Gasoline Price Data  

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

Connecticut Connecticut Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Bridgeport BridgeportGasPrices.com Automotive.com MapQuest.com Hartford HartfordGasPrices.com Automotive.com MapQuest.com New Haven NewHavenGasPrices.com Automotive.com MapQuest.com Stamford Automotive.com MapQuest.com Waterbury Automotive.com MapQuest.com West Hartford Automotive.com MapQuest.com Other Connecticut Cities ConnecticutGasPrices.com (search by city or ZIP code) - GasBuddy.com Connecticut Gas Prices (selected cities) - GasBuddy.com Connecticut Gas Prices (organized by county) - Automotive.com Gas Prices of the United States: Connecticut Cities - MapQuest

499

Average Residential Price  

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

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

500

Fundamentals Explain High Prices  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: One can use a simple model to deal with price/fundamental relationships. This one predicts monthly average WTI price as a function of OECD total petroleum stock deviations from the normal levels . The graph shows the model as it begins predicting prices in 1992. It shows how well the model has predicted not only the direction, but the magnitude of prices over this 8+ year period. While the model is simple and not perfect, it does predict the overall trends and, in particular, the recent rise in prices. It also shows that prices may have over-shot the fundamental balance for a while -- at least partially due to speculative concerns over Mideast tensions, winter supply adequacy, and Iraq's export policies. Prices now seem to be correcting, and may even undershoot briefly