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Note: This page contains sample records for the topic "interindustry forecasting project" from the National Library of EnergyBeta (NLEBeta).
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1

Project Profile: Forecasting and Influencing Technological Progress...  

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

Forecasting and Influencing Technological Progress in Solar Energy Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Logos of the University of...

2

Wind Forecast Improvement Project Southern Study Area Final Report...  

Office of Environmental Management (EM)

Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern...

3

UHERO FORECAST PROJECT DECEMBER 5, 2014  

E-Print Network (OSTI)

deficits. After solid 3% growth this year, real GDP growth will recede a bit for the next two years. New household spending. Real GDP will firm above 3% in 2015. · The pace of growth in China has continuedUHERO FORECAST PROJECT DECEMBER 5, 2014 Asia-Pacific Forecast: Press Version: Embargoed Until 2

4

The Wind Forecast Improvement Project (WFIP): A Public/Private...  

Energy Savers (EERE)

Improvement Project (WFIP): A PublicPrivate Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The Wind Forecast...

5

Prediction versus Projection: How weather forecasting and  

E-Print Network (OSTI)

Prediction versus Projection: How weather forecasting and climate models differ. Aaron B. Wilson Context: Global http://data.giss.nasa.gov/ #12;Numerical Weather Prediction Collect Observations alters associated weather patterns. Models used to predict weather depend on the current observed state

Howat, Ian M.

6

Annual Energy Outlook with Projections to 2025-Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2004 with Projections to 2025 Forecast Comparisons Index (click to jump links) Economic Growth World Oil Prices Total Energy Consumption Electricity Natural Gas Petroleum Coal The AEO2004 forecast period extends through 2025. One other organization—Global Insight, Incorporated (GII)—produces a comprehensive energy projection with a similar time horizon. Several others provide forecasts that address one or more aspects of energy markets over different time horizons. Recent projections from GII and others are compared here with the AEO2004 projections. Economic Growth Printer Friendly Version Average annual percentage growth Forecast 2002-2008 2002-2013 2002-2025 AEO2003 3.2 3.3 3.1 AEO2004 Reference 3.3 3.2 3.0

7

An Interindustry Model of El Paso and Hudspeth Counties, Texas  

E-Print Network (OSTI)

TR- 69 1976 An Interindustry Model of El Paso and Hudspeth Counties, Texas W.S. Coffman B.R. Beattie L.L. Jones J.W. Adams Texas Water Resources Institute Texas A&M University ...

Coffman, W. S.; Beattie, B. R.; Jones, L. L.; Adams, J. W.

8

Annual Energy Outlook with Projections to 2025 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2005 Forecast Comparisons Table 32. Forecasts of annual average economic growth, 2003-2025 Printer Friendly Version Average annual percentage growth Forecast 2003-2009 2003-2014 2003-2025 AEO2004 3.5 3.2 3.0 AEO2005 Reference 3.4 3.3 3.1 Low growth 2.9 2.8 2.5 High growth 4.1 3.9 3.6 GII 3.4 3.2 3.1 OMB 3.6 NA NA CBO 3.5 3.1 NA OEF 3.5 3.5 NA Only one other organization—Global Insight, Incorporated (GII)—produces a comprehensive energy projection with a time horizon similar to that of AEO2005. Other organizations address one or more aspects of the energy markets. The most recent projection from GII, as well as other forecasts that concentrate on economic growth, international oil prices, energy

9

Annual Energy Outlook 2006 with Projections to 2030 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Annual Energy Outlook 2006 with Projections to 2030 Only GII produces a comprehensive energy projection with a time horizon similar to that of AEO2006. Other organizations address one or more aspects of the energy markets. The most recent projection from GII, as well as others that concentrate on economic growth, international oil prices, energy consumption, electricity, natural gas, petroleum, and coal, are compared here with the AEO2006 projections. Economic Growth In the AEO2006 reference case, the projected growth in real GDP, based on 2000 chain-weighted dollars, is 3.0 percent per year from 2004 to 2030 (Table 19). For the period from 2004 to 2025, real GDP growth in the AEO2006 reference case is similar to the average annual growth projected in AEO2005. The AEO2006 projections of economic growth are based on the August short-term forecast of GII, extended by EIA through 2030 and modified to reflect EIA’s view on energy prices, demand, and production.

10

Forecasting potential project risks through leading indicators to project outcome  

E-Print Network (OSTI)

During project execution, the status of the project is periodically evaluated, using traditional methods or standard practices. However, these traditional methods or standard practices may not adequately identify certain issues, such as lack...

Choi, Ji Won

2007-09-17T23:59:59.000Z

11

Next Generation Short-Term Forecasting of Wind Power Overview of the ANEMOS Project.  

E-Print Network (OSTI)

1 Next Generation Short-Term Forecasting of Wind Power ­ Overview of the ANEMOS Project. G outperform current state-of-the-art methods, for onshore and offshore wind power forecasting. Advanced forecasts for the power system management and market integration of wind power. Keywords: Wind power, short

Boyer, Edmond

12

Upcoming Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain  

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

The DOE Wind Program has issued a Notice of Intent for a funding opportunity, tentatively titled Wind Forecasting Improvement Project in Complex Terrain.

13

The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations  

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

The Wind Forecast Improvement Project (WFIP) is a U. S. Department of Energy (DOE) sponsored research project whose overarching goals are to improve the accuracy of short-term wind energy forecasts, and to demonstrate the economic value of these improvements.

14

Energy Forecast, ForskEL (Smart Grid Project) | Open Energy Information  

Open Energy Info (EERE)

Forecast, ForskEL (Smart Grid Project) Forecast, ForskEL (Smart Grid Project) Jump to: navigation, search Project Name Energy Forecast, ForskEL Country Denmark Coordinates 56.26392°, 9.501785° 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":56.26392,"lon":9.501785,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

15

Evaluation of Advanced Wind Power Forecasting Models Results of the Anemos Project  

E-Print Network (OSTI)

1 Evaluation of Advanced Wind Power Forecasting Models ­ Results of the Anemos Project I. Martí1.kariniotakis@ensmp.fr Abstract An outstanding question posed today by end-users like power system operators, wind power producers or traders is what performance can be expected by state-of-the-art wind power prediction models. This paper

Paris-Sud XI, Université de

16

Short-term Forecasting of Offshore Wind Farm Production Developments of the Anemos Project  

E-Print Network (OSTI)

Short-term Forecasting of Offshore Wind Farm Production ­ Developments of the Anemos Project J.a.brownsword@rl.ac.uk 6 Overspeed GmBH & Co.KG, 26129 Oldenburg, Germany Email: h.p.waldl@overspeed.de Key words: Offshore to the large dimensions of offshore wind farms, their electricity production must be known well in advance

Paris-Sud XI, Université de

17

EIA - AEO2010 - Comparison With Other Projections  

Gasoline and Diesel Fuel Update (EIA)

Comparison With Other Projections Comparison With Other Projections Annual Energy Outlook 2010 with Projections to 2035 Comparison With Other Projections Only IHS Global Insights, Inc. (IHSGI) produces a comprehensive energy projection with a time horizon similar to that of AEO2010. Other organizations, however, address one or more aspects of the U.S. energy market. The most recent projection from IHSGI, as well as others that concentrate on economic growth, international oil prices, energy consumption, electricity, natural gas, petroleum, and coal, are compared here with the AEO2010 projections. Economic growth Projections of the average annual growth rate of real GDP in the United States from 2008 to 2018 range from 2.1 percent to 2.8 percent (Table 9). In the AEO2010 Reference case, real GDP grows by an average of 2.2 percent per year over the period, lower than projected by the Office of Management and Budget (OMB), the Congressional Budget Office (CBO), the Social Security Administration (SSA), and the Bureau of Labor Statistics (BLS)—although none of those projections has been updated since August 2009. The AEO2010 projection is similar to the IHSGI projection and slightly higher than projections by the Interindustry Forecasting Project at the University of Maryland (INFORUM). In March 2009, the consensus Blue Chip projection was for 2.2-percent average annual growth from 2008 to 2018.

18

Economic Analysis Interindustry Effects of a Declining Groundwater Supply: Southern High Plains of Texas.  

E-Print Network (OSTI)

for each year from 1966 through 2015 and on an interindustry study for the study area. The years 1967, 1970. 19f,fl. 1990, 2000,2010 and 2015 were selected for the study. The expenditures for inputs from the linear programing study were delineated... in 1967 to 2.4. million acre5 in 2015. The value of all crop production was estimated to decrease by 39.9 percent from 1967 to 2015. Direct benefits associated with irrigation were $433.5 million in 1967, which were 68 percent of the total output...

Osborn, J. E.; Harris, T. R.

1973-01-01T23:59:59.000Z

19

EIA - Annual Energy Outlook 2009 - Comparison with Other Projections  

Gasoline and Diesel Fuel Update (EIA)

Comparison with Other Projections Comparison with Other Projections Annual Energy Outlook 2009 with Projections to 2030 Comparison with Other Projections Only IHS Global Insight (IHSGI) produces a comprehensive energy projection with a time horizon similar to that of AEO2009. Other organizations, however, address one or more aspects of the U.S. energy market. The most recent projection from IHSGI, as well as others that concentrate on economic growth, international oil prices, energy consumption, electricity, natural gas, petroleum, and coal, are compared here with the AEO2009 projections. Economic Growth Projections of the average annual real GDP growth rate for the United States from 2007 through 2010 range from 0.2 percent to 3.1 percent (Table 15). Real GDP grows at an annual rate of 0.6 percent in the AEO2009 reference case over the period, significantly lower than the projections made by the Office of Management and Budget (OMB), the Bureau of Labor Statistics (BLS), and the Social Security Administration (SSA)—although not all of those projections have been updated to take account of the current economic downturn. The AEO2009 projection is slightly lower than the projection by IHSGI and slightly higher than the projection by the Interindustry Forecasting Project at the University of Maryland (INFORUM). In March 2009, the consensus Blue Chip projection was for 2.2-percent average annual growth from 2007 to 2010.

20

OPTIMAL CONTROL OF PROJECTS BASED ON KALMAN FILTER APPROACH FOR TRACKING & FORECASTING THE PROJECT PERFORMANCE  

E-Print Network (OSTI)

Traditional scheduling tools like Gantt Charts and CPM while useful in planning and execution of complex construction projects with multiple interdependent activities haven?t been of much help in implementing effective control systems for the same...

Bondugula, Srikant

2010-07-14T23:59:59.000Z

Note: This page contains sample records for the topic "interindustry forecasting project" 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

The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations the Southern Study Area  

SciTech Connect

This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP)--Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 3 hours.

Freedman, Jeffrey M.; Manobianco, John; Schroeder, John; Ancell, Brian; Brewster, Keith; Basu, Sukanta; Banunarayanan, Venkat; Hodge, Bri-Mathias; Flores, Isabel

2014-04-30T23:59:59.000Z

22

Improving Inventory Control Using Forecasting  

E-Print Network (OSTI)

This project studied and analyzed Electronic Controls, Inc.s forecasting process for three high-demand products. In addition, alternative forecasting methods were developed to compare to the current forecast method. The ...

Balandran, Juan

2005-12-16T23:59:59.000Z

23

Waste generation forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1995-FY 2002, September 1994 revision  

SciTech Connect

A comprehensive waste-forecasting task was initiated in FY 1991 to provide a consistent, documented estimate of the volumes of waste expected to be generated as a result of U.S. Department of Energy-Oak Ridge Operations (DOE-ORO) Environmental Restoration (ER) OR-1 Project activities. Continual changes in the scope and schedules for remedial action (RA) and decontamination and decommissioning (D&D) activities have required that an integrated data base system be developed that can be easily revised to keep pace with changes and provide appropriate tabular and graphical output. The output can then be analyzed and used to drive planning assumptions for treatment, storage, and disposal (TSD) facilities. The results of this forecasting effort and a description of the data base developed to support it are provided herein. The initial waste-generation forecast results were compiled in November 1991. Since the initial forecast report, the forecast data have been revised annually. This report reflects revisions as of September 1994.

Not Available

1994-12-01T23:59:59.000Z

24

Wind Power Forecasting  

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

Retrospective Reports 2011 Smart Grid Wind Integration Wind Integration Initiatives Wind Power Forecasting Wind Projects Email List Self Supplied Balancing Reserves Dynamic...

25

1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.  

SciTech Connect

This publication documents the load forecast scenarios and assumptions used to prepare BPA`s Whitebook. It is divided into: intoduction, summary of 1993 Whitebook electricity demand forecast, conservation in the load forecast, projection of medium case electricity sales and underlying drivers, residential sector forecast, commercial sector forecast, industrial sector forecast, non-DSI industrial forecast, direct service industry forecast, and irrigation forecast. Four appendices are included: long-term forecasts, LTOUT forecast, rates and fuel price forecasts, and forecast ranges-calculations.

United States. Bonneville Power Administration.

1994-02-01T23:59:59.000Z

26

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

27

RACORO Forecasting  

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

Daniel Hartsock CIMMS, University of Oklahoma ARM AAF Wiki page Weather Briefings Observed Weather Cloud forecasting models BUFKIT forecast soundings + guidance...

28

ANL Software Improves Wind Power Forecasting | Department of...  

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

principal investigator for the project. For wind power point forecasting, ARGUS PRIMA trains a neural network using data from weather forecasts, observations, and actual wind...

29

Waste Generation Forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1994--FY 2001. Environmental Restoration Program, September 1993 Revision  

SciTech Connect

This Waste Generation Forecast for DOE-ORO`s Environmental Restoration OR-1 Project. FY 1994--FY 2001 is the third in a series of documents that report current estimates of the waste volumes expected to be generated as a result of Environmental Restoration activities at Department of Energy, Oak Ridge Operations Office (DOE-ORO), sites. Considered in the scope of this document are volumes of waste expected to be generated as a result of remedial action and decontamination and decommissioning activities taking place at these sites. Sites contributing to the total estimates make up the DOE-ORO Environmental Restoration OR-1 Project: the Oak Ridge K-25 Site, the Oak Ridge National Laboratory, the Y-12 Plant, the Paducah Gaseous Diffusion Plant, the Portsmouth Gaseous Diffusion Plant, and the off-site contaminated areas adjacent to the Oak Ridge facilities (collectively referred to as the Oak Ridge Reservation Off-Site area). Estimates are available for the entire fife of all waste generating activities. This document summarizes waste estimates forecasted for the 8-year period of FY 1994-FY 2001. Updates with varying degrees of change are expected throughout the refinement of restoration strategies currently in progress at each of the sites. Waste forecast data are relatively fluid, and this document represents remediation plans only as reported through September 1993.

Not Available

1993-12-01T23:59:59.000Z

30

Forecasting Water Use in Texas Cities  

E-Print Network (OSTI)

In this research project, a methodology for automating the forecasting of municipal daily water use is developed and implemented in a microcomputer program called WATCAL. An automated forecast system is devised by modifying the previously...

Shaw, Douglas T.; Maidment, David R.

31

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sánchez The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors,

32

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by Esmeralda Sanchez by Esmeralda Sanchez Errata -(7/14/04) The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors, expressed as the percentage difference between the Reference Case projection and actual historic value, shown for every AEO and for each year in the forecast horizon (for a given variable). The historical data are typically taken from the Annual Energy Review (AER). The last column of Table 1 provides a summary of the most recent average absolute forecast errors. The calculation of the forecast error is shown in more detail in Tables 2 through 18. Because data for coal prices to electric generating plants were not available from the AER, data from the Monthly Energy Review (MER), July 2003 were used.

33

The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations the Northern Study Area.  

SciTech Connect

This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times. A comprehensive analysis of wind energy forecast errors for the various model-based power forecasts was presented for a suite of wind energy ramp definitions. The results compiled over the year-long study period showed that the power forecasts based on the research models (ESRL_RAP, HRRR) more accurately predict wind energy ramp events than the current operational forecast models, both at the system aggregate level and at the local wind plant level. At the system level, the ESRL_RAP-based forecasts most accurately predict both the total number of ramp events and the occurrence of the events themselves, but the HRRR-based forecasts more accurately predict the ramp rate. At the individual site level, the HRRR-based forecasts most accurately predicted the actual ramp occurrence, the total number of ramps and the ramp rates (40-60% improvement in ramp rates over the coarser resolution forecast

Finley, Cathy [WindLogics

2014-04-30T23:59:59.000Z

34

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation by Susan H. Holte In this paper, the Office of Integrated Analysis and Forecasting (OIAF) of the Energy Information Administration (EIA) evaluates the projections published in the Annual Energy Outlook (AEO), (1) by comparing the projections from the Annual Energy Outlook 1982 through the Annual Energy Outlook 2001 with actual historical values. A set of major consumption, production, net import, price, economic, and carbon dioxide emissions variables are included in the evaluation, updating similar papers from previous years. These evaluations also present the reasons and rationales for significant differences. The Office of Integrated Analysis and Forecasting has been providing an

35

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Title of Paper Annual Energy Outlook Forecast Evaluation Title of Paper Annual Energy Outlook Forecast Evaluation by Susan H. Holte OIAF has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Natural gas has generally been the fuel with the least accurate forecasts of consumption, production, and prices. Natural gas was the last fossil fuel to be deregulated following the strong regulation of energy markets in the 1970s and early 1980s. Even after deregulation, the behavior

36

Energy consumption and expenditure projections by income quintile on the basis of the Annual Energy Outlook 1997 forecast  

SciTech Connect

This report presents an analysis of the relative impacts of the base-case scenario used in the Annual Energy Outlook 1997, published by the US Department of Energy, Energy Information Administration, on income quintile groups. Projected energy consumption and expenditures, and projected energy expenditures as a share of income, for the period 1993 to 2015 are reported. Projected consumption of electricity, natural gas, distillate fuel, and liquefied petroleum gas over this period is also reported for each income group. 33 figs., 11 tabs.

Poyer, D.A.; Allison, T.

1998-03-01T23:59:59.000Z

37

Forecasting Agriculturally Driven Global Environmental Change  

Science Journals Connector (OSTI)

...of each variable on GDP (13, 17), combined with global GDP projections (14...population, and per capita GDP, combined with projected...measure of agricultural demand for water, is forecast...Just as demand for energy is the major cause...

David Tilman; Joseph Fargione; Brian Wolff; Carla D'Antonio; Andrew Dobson; Robert Howarth; David Schindler; William H. Schlesinger; Daniel Simberloff; Deborah Swackhamer

2001-04-13T23:59:59.000Z

38

Data Mining in Load Forecasting of Power System  

Science Journals Connector (OSTI)

This project applies Data Mining technology to the prediction of electric power system load forecast. It proposes a mining program of electric power load forecasting data based on the similarity of time series .....

Guang Yu Zhao; Yan Yan; Chun Zhou Zhao

2013-01-01T23:59:59.000Z

39

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

H Tables H Tables Appendix H Comparisons With Other Forecasts, and Performance of Past IEO Forecasts for 1990, 1995, and 2000 Forecast Comparisons Three organizations provide forecasts comparable with those in the International Energy Outlook 2005 (IEO2005). The International Energy Agency (IEA) provides “business as usual” projections to the year 2030 in its World Energy Outlook 2004; Petroleum Economics, Ltd. (PEL) publishes world energy forecasts to 2025; and Petroleum Industry Research Associates (PIRA) provides projections to 2015. For this comparison, 2002 is used as the base year for all the forecasts, and the comparisons extend to 2025. Although IEA’s forecast extends to 2030, it does not publish a projection for 2025. In addition to forecasts from other organizations, the IEO2005 projections are also compared with those in last year’s report (IEO2004). Because 2002 data were not available when IEO2004 forecasts were prepared, the growth rates from IEO2004 are computed from 2001.

40

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

by by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: * Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Evaluation Evaluation Annual Energy Outlook Forecast Evaluation by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the impacts were not incorporated in the AEO projections until their enactment or effective dates in accordance with EIA's requirement to remain policy neutral and include only current laws and regulations in the AEO reference case projections.

42

Annual Energy Outlook Forecast Evaluation 2005  

Gasoline and Diesel Fuel Update (EIA)

Forecast Evaluation 2005 Forecast Evaluation 2005 Annual Energy Outlook Forecast Evaluation 2005 Annual Energy Outlook Forecast Evaluation 2005 * Then Energy Information Administration (EIA) produces projections of energy supply and demand each year in the Annual Energy Outlook (AEO). The projections in the AEO are not statements of what will happen but of what might happen, given the assumptions and methodologies used. The projections are business-as-usual trend projections, given known technology, technological and demographic trends, and current laws and regulations. Thus, they provide a policy-neutral reference case that can be used to analyze policy initiatives. EIA does not propose or advocate future legislative and regulatory changes. All laws are assumed to remain as currently enacted; however, the impacts of emerging regulatory changes, when defined, are reflected.

43

Annual Energy Outlook 2001 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

Forecast Comparisons Forecast Comparisons Economic Growth World Oil Prices Total Energy Consumption Residential and Commercial Sectors Industrial Sector Transportation Sector Electricity Natural Gas Petroleum Coal Three other organizations—Standard & Poor’s DRI (DRI), the WEFA Group (WEFA), and the Gas Research Institute (GRI) [95]—also produce comprehensive energy projections with a time horizon similar to that of AEO2001. The most recent projections from those organizations (DRI, Spring/Summer 2000; WEFA, 1st Quarter 2000; GRI, January 2000), as well as other forecasts that concentrate on petroleum, natural gas, and international oil markets, are compared here with the AEO2001 projections. Economic Growth Differences in long-run economic forecasts can be traced primarily to

44

Annual Energy Outlook Forecast Evaluation 2004  

Gasoline and Diesel Fuel Update (EIA)

2004 2004 * The Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) has produced annual evaluations of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and replacing the historical year of data with the most recent. The forecast evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute percent errors for several of the major variables for AEO82 through AEO2004. (There is no report titled Annual Energy Outlook 1988 due to a change in the naming convention of the AEOs.) The average absolute percent error is the simple mean of the absolute values of the percentage difference between the Reference Case projection and the

45

ANL Wind Power Forecasting and Electricity Markets | Open Energy  

Open Energy Info (EERE)

ANL Wind Power Forecasting and Electricity Markets ANL Wind Power Forecasting and Electricity Markets Jump to: navigation, search Logo: Wind Power Forecasting and Electricity Markets Name Wind Power Forecasting and Electricity Markets Agency/Company /Organization Argonne National Laboratory Partner Institute for Systems and Computer Engineering of Porto (INESC Porto) in Portugal, Midwest Independent System Operator and Horizon Wind Energy LLC, funded by U.S. Department of Energy Sector Energy Focus Area Wind Topics Pathways analysis, Technology characterizations Resource Type Software/modeling tools Website http://www.dis.anl.gov/project References Argonne National Laboratory: Wind Power Forecasting and Electricity Markets[1] Abstract To improve wind power forecasting and its use in power system and electricity market operations Argonne National Laboratory has assembled a team of experts in wind power forecasting, electricity market modeling, wind farm development, and power system operations.

46

Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting: Preprint  

SciTech Connect

The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.

Zhang, J.; Florita, A.; Hodge, B. M.; Freedman, J.

2014-05-01T23:59:59.000Z

47

Forecasting wireless communication technologies  

Science Journals Connector (OSTI)

The purpose of the paper is to present a formal comparison of a variety of multiple regression models in technology forecasting for wireless communication. We compare results obtained from multiple regression models to determine whether they provide a superior fitting and forecasting performance. Both techniques predict the year of wireless communication technology introduction from the first (1G) to fourth (4G) generations. This paper intends to identify the key parameters impacting the growth of wireless communications. The comparison of technology forecasting approaches benefits future researchers and practitioners when developing a prediction of future wireless communication technologies. The items of focus will be to understand the relationship between variable selection and model fit. Because the forecasting error was successfully reduced from previous approaches, the quadratic regression methodology is applied to the forecasting of future technology commercialisation. In this study, the data will show that the quadratic regression forecasting technique provides a better fit to the curve.

Sabrina Patino; Jisun Kim; Tugrul U. Daim

2010-01-01T23:59:59.000Z

48

Solar forecasting review  

E-Print Network (OSTI)

2.1.2 European Solar Radiation Atlas (ESRA)2.4 Evaluation of Solar Forecasting . . . . . . . . .2.4.1 Solar Variability . . . . . . . . . . . . .

Inman, Richard Headen

2012-01-01T23:59:59.000Z

49

Wind Power Forecasting  

Science Journals Connector (OSTI)

The National Center for Atmospheric Research (NCAR) has configured a Wind Power Forecasting System for Xcel Energy that integrates high resolution and ensemble...

Sue Ellen Haupt; William P. Mahoney; Keith Parks

2014-01-01T23:59:59.000Z

50

Energy Demand Forecasting  

Science Journals Connector (OSTI)

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

S. C. Bhattacharyya

2011-01-01T23:59:59.000Z

51

Today's Forecast: Improved Wind Predictions | Department of Energy  

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

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

52

Today's Forecast: Improved Wind Predictions | Department of Energy  

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

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

53

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 3 AUGUST 16, 2012  

E-Print Network (OSTI)

there is significant uncertainty in its future intensity, the current forecast is for a slowly strengthening TC which, 3) forecast output from global models, 4) the current and projected state of the Madden with these two-week forecasts is the Accumulated Cyclone Energy (ACE) index, which is defined to be all

Gray, William

54

Technology Forecasting Scenario Development  

E-Print Network (OSTI)

Technology Forecasting and Scenario Development Newsletter No. 2 October 1998 Systems Analysis was initiated on the establishment of a new research programme entitled Technology Forecasting and Scenario and commercial applica- tion of new technology. An international Scientific Advisory Panel has been set up

55

CAPP 2010 Forecast.indd  

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

Forecast, Markets & Pipelines 1 Crude Oil Forecast, Markets & Pipelines June 2010 2 CANADIAN ASSOCIATION OF PETROLEUM PRODUCERS Disclaimer: This publication was prepared by the...

56

Projected growth effects of the biotechnology industry in Finland: the fourth pillar of the economy?  

Science Journals Connector (OSTI)

This study assesses the impact of the Finnish biotechnology industry on economic growth in Finland. The study employs official data from Statistics Finland and new survey data covering 84 Finnish biotechnology companies. An econometric forecast for the economy-wide growth impact of the biotechnology industry in Finland is presented. In the estimation procedure, this study employs the survey data both in forming growth anticipations within a new emerging industry and assessing inter-industrial growth effects. Applied Monte Carlo simulations predict that the contribution of the biotechnology industry to annual GDP growth in 2002??2006 will be in the range of 0.05??0.09 percentage points per annum with a probability of 90%. These results imply that it will take decades rather than years for the biotechnology industry to become a fourth pillar of the Finnish economy beside the forest industry, the metal products and machinery industry, and the electronics industry.

Raine Hermans; Martti Kulvik

2005-01-01T23:59:59.000Z

57

PI Research Organisation Project Title NE/J024678/1 Dr Christopher Davis University of Reading Driving space weather forecasts with real data  

E-Print Network (OSTI)

Lead Grant Reference PI Research Organisation Project Title NE/J024678/1 Dr Christopher Davis Troposphere and the Routing of Aircraft (EXTRA)Professor Keith Shine University of Reading NE/J023760

58

Valuing Climate Forecast Information  

Science Journals Connector (OSTI)

The article describes research opportunities associated with evaluating the characteristics of climate forecasts in settings where sequential decisions are made. Illustrative results are provided for corn production in east central Illinois. ...

Steven T. Sonka; James W. Mjelde; Peter J. Lamb; Steven E. Hollinger; Bruce L. Dixon

1987-09-01T23:59:59.000Z

59

Comparing Forecast Skill  

Science Journals Connector (OSTI)

A basic question in forecasting is whether one prediction system is more skillful than another. Some commonly used statistical significance tests cannot answer this question correctly if the skills are computed on a common period or using a common ...

Timothy DelSole; Michael K. Tippett

2014-12-01T23:59:59.000Z

60

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Highlights Highlights World energy consumption is projected to increase by 57 percent from 2002 to 2025. Much of the growth in worldwide energy use in the IEO2005 reference case forecast is expected in the countries with emerging economies. Figure 1. World Marketed Energy Consumptiion by Region, 1970-2025. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data In the International Energy Outlook 2005 (IEO2005) reference case, world marketed energy consumption is projected to increase on average by 2.0 percent per year over the 23-year forecast horizon from 2002 to 2025—slightly lower than the 2.2-percent average annual growth rate from 1970 to 2002. Worldwide, total energy use is projected to grow from 412 quadrillion British thermal units (Btu) in 2002 to 553 quadrillion Btu in

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Forecast of geothermal drilling activity  

SciTech Connect

The numbers of each type of geothermal well expected to be drilled in the United States for each 5-year period to 2000 AD are specified. Forecasts of the growth of geothermally supplied electric power and direct heat uses are presented. The different types of geothermal wells needed to support the forecasted capacity are quantified, including differentiation of the number of wells to be drilled at each major geothermal resource for electric power production. The rate of growth of electric capacity at geothermal resource areas is expected to be 15 to 25% per year (after an initial critical size is reached) until natural or economic limits are approached. Five resource areas in the United States should grow to significant capacity by the end of the century (The Geysers; Imperial Valley; Valles Caldera, NM; Roosevelt Hot Springs, UT; and northern Nevada). About 3800 geothermal wells are expected to be drilled in support of all electric power projects in the United States between 1981 and 2000 AD. Half of the wells are expected to be drilled in the Imperial Valley. The Geysers area is expected to retain most of the drilling activity for the next 5 years. By the 1990's, the Imperial Valley is expected to contain most of the drilling activity.

Brown, G.L.; Mansure, A.J.

1981-10-01T23:59:59.000Z

62

Sandia National Laboratories: solar forecasting  

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

Energy, Modeling & Analysis, News, News & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource...

63

Consensus Coal Production Forecast for  

E-Print Network (OSTI)

Rate Forecasts 19 5. EIA Forecast: Regional Coal Production 22 6. Wood Mackenzie Forecast: W.V. Steam to data currently published by the Energy Information Administration (EIA), coal production in the state in this report calls for state production to decline by 11.3 percent in 2009 to 140.2 million tons. During

Mohaghegh, Shahab

64

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Table 2. Total Energy Consumption, Actual vs. Forecasts Table 3. Total Petroleum Consumption, Actual vs. Forecasts Table 4. Total Natural Gas Consumption, Actual vs. Forecasts Table 5. Total Coal Consumption, Actual vs. Forecasts Table 6. Total Electricity Sales, Actual vs. Forecasts Table 7. Crude Oil Production, Actual vs. Forecasts Table 8. Natural Gas Production, Actual vs. Forecasts Table 9. Coal Production, Actual vs. Forecasts Table 10. Net Petroleum Imports, Actual vs. Forecasts Table 11. Net Natural Gas Imports, Actual vs. Forecasts Table 12. Net Coal Exports, Actual vs. Forecasts Table 13. World Oil Prices, Actual vs. Forecasts Table 14. Natural Gas Wellhead Prices, Actual vs. Forecasts Table 15. Coal Prices to Electric Utilities, Actual vs. Forecasts

65

On Sequential Probability Forecasting  

E-Print Network (OSTI)

at the same time. [Probability, Statistics and Truth, MacMillan 1957. page 11] ... the collective "denotes a collective wherein the attribute of the single event is the number of points thrown. [Probability, StatisticsOn Sequential Probability Forecasting David A. Bessler 1 David A. Bessler Texas A&M University

McCarl, Bruce A.

66

Beyond "Partly Sunny": A Better Solar Forecast | Department of Energy  

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

Beyond "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast December 7, 2012 - 10:00am Addthis The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods of cloud coverage. | Photo by Dennis Schroeder/NREL. The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods of cloud coverage. | Photo by Dennis Schroeder/NREL. Minh Le Minh Le Program Manager, Solar Program What Do These Projects Do? The Energy Department is investing $8 million in two cutting-edge projects to increase the accuracy of solar forecasting at sub-hourly,

67

Wind Forecasting Improvement Project | Department of Energy  

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

3, 2011 - 12:12pm Addthis This is an excerpt from the Third Quarter 2011 edition of the Wind Program R&D Newsletter. In July, the Department of Energy launched a 6 million...

68

Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) | Open  

Open Energy Info (EERE)

Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Jump to: navigation, search LEDSGP green logo.png FIND MORE DIA TOOLS This tool is part of the Development Impacts Assessment (DIA) Toolkit from the LEDS Global Partnership. Tool Summary LAUNCH TOOL Name: Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Agency/Company /Organization: Energy Sector Management Assistance Program of the World Bank Sector: Energy Focus Area: Non-renewable Energy Topics: Baseline projection, Co-benefits assessment, GHG inventory Resource Type: Software/modeling tools User Interface: Spreadsheet Complexity/Ease of Use: Simple Website: www.esmap.org/esmap/EFFECT Cost: Free Equivalent URI: www.esmap.org/esmap/EFFECT Energy Forecasting Framework and Emissions Consensus Tool (EFFECT) Screenshot

69

Short-Term World Oil Price Forecast  

Gasoline and Diesel Fuel Update (EIA)

4 4 Notes: This graph shows monthly average spot West Texas Intermediate crude oil prices. Spot WTI crude oil prices peaked last fall as anticipated boosts to world supply from OPEC and other sources did not show up in actual stocks data. So where do we see crude oil prices going from here? Crude oil prices are expected to be about $28-$30 per barrel for the rest of this year, but note the uncertainty bands on this projection. They give an indication of how difficult it is to know what these prices are going to do. Also, EIA does not forecast volatility. This relatively flat forecast could be correct on average, with wide swings around the base line. Let's explore why we think prices will likely remain high, by looking at an important market barometer - inventories - which measures the

70

FORSITE: a geothermal site development forecasting system  

SciTech Connect

The Geothermal Site Development Forecasting System (FORSITE) is a computer-based system being developed to assist DOE geothermal program managers in monitoring the progress of multiple geothermal electric exploration and construction projects. The system will combine conceptual development schedules with site-specific status data to predict a time-phased sequence of development likely to occur at specific geothermal sites. Forecasting includes estimation of industry costs and federal manpower requirements across sites on a year-by-year basis. The main advantage of the system, which relies on reporting of major, easily detectable industry activities, is its ability to use relatively sparse data to achieve a representation of status and future development.

Entingh, D.J.; Gerstein, R.E.; Kenkeremath, L.D.; Ko, S.M.

1981-10-01T23:59:59.000Z

71

Short-term Wind Power Forecasting Using Advanced Statistical T.S. Nielsen1  

E-Print Network (OSTI)

Short-term Wind Power Forecasting Using Advanced Statistical Methods T.S. Nielsen1 , H. Madsen1 , H considered in the ANEMOS project for short-term fore- casting of wind power. The total procedure typically in for prediction of wind power or wind speed, estimating the uncertainty of the wind power forecast, and finally

Paris-Sud XI, Université de

72

Price forecasting for notebook computers.  

E-Print Network (OSTI)

??This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a (more)

Rutherford, Derek Paul

2012-01-01T23:59:59.000Z

73

Ensemble Forecasts and their Verification  

E-Print Network (OSTI)

· Ensemble forecast verification ­ Performance metrics: Brier Score, CRPSS · New concepts and developments of weather Sources: Insufficient spatial resolution, truncation errors in the dynamical equations

Maryland at College Park, University of

74

Probabilistic manpower forecasting  

E-Print Network (OSTI)

- ing E. Results- Probabilistic Forecasting . 26 27 Z8 29 31 35 36 38 39 IV. CONCLUSIONS. V. GLOSSARY 42 44 APPENDICES REFERENCES 50 70 LIST OF TABLES Table Page Outline of Job-Probability Matrix Job-Probability Matrix. Possible... Outcomes of Job A Possible Outcomes of Jobs A and B 10 Possible Outcomes of Jobs A, B and C II LIST GF FIGURES Figure Page Binary Representation of Numbers 0 Through 7 12 First Cumulative Probability Table 14 3. Graph of Cumulative Probability vs...

Koonce, James Fitzhugh

1966-01-01T23:59:59.000Z

75

Diagnosing Forecast Errors in Tropical Cyclone Motion  

Science Journals Connector (OSTI)

This paper reports on the development of a diagnostic approach that can be used to examine the sources of numerical model forecast error that contribute to degraded tropical cyclone (TC) motion forecasts. Tropical cyclone motion forecasts depend ...

Thomas J. Galarneau Jr.; Christopher A. Davis

2013-02-01T23:59:59.000Z

76

Project  

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

Exploring the Standard Model Exploring the Standard Model       You've heard a lot about the Standard Model and the pieces are hopefully beginning to fall into place. However, even a thorough understanding of the Standard Model is not the end of the story but the beginning. By exploring the structure and details of the Standard Model we encounter new questions. Why do the most fundamental particles have the particular masses we observe? Why aren't they all symmetric? How is the mass of a particle related to the masses of its constituents? Is there any other way of organizing the Standard Model? The activities in this project will elucidate but not answer our questions. The Standard Model tells us how particles behave but not necessarily why they do so. The conversation is only beginning. . . .

77

Forecasting with adaptive extended exponential smoothing  

Science Journals Connector (OSTI)

Much of product level forecasting is based upon time series techniques. However, traditional time series forecasting techniques have offered either smoothing constant adaptability or consideration of various t...

John T. Mentzer Ph.D.

78

Electricity price forecasting in a grid environment.  

E-Print Network (OSTI)

??Accurate electricity price forecasting is critical to market participants in wholesale electricity markets. Market participants rely on price forecasts to decide their bidding strategies, allocate (more)

Li, Guang, 1974-

2007-01-01T23:59:59.000Z

79

Energy Department Forecasts Geothermal Achievements in 2015 ...  

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

Forecasts Geothermal Achievements in 2015 Energy Department Forecasts Geothermal Achievements in 2015 The 40th annual Stanford Geothermal Workshop in January featured speakers in...

80

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Electricity Electricity Electricity consumption nearly doubles in the IEO2005 projection period. The emerging economies of Asia are expected to lead the increase in world electricity use. Figure 58. World Net Electricity Consumption, 2002-2025 (Billion Kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 59. World Net Electricity Consumption by Region, 2002-2025 (Billion Kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data The International Energy Outlook 2005 (IEO2005) reference case projects that world net electricity consumption will nearly double over the next two decades.10 Over the forecast period, world electricity demand is projected to grow at an average rate of 2.6 percent per year, from 14,275 billion

Note: This page contains sample records for the topic "interindustry forecasting project" 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

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

82

CRSP CASH PROJECTIONS  

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

CASH PROJECTIONS CASH PROJECTIONS FY 2012-FY 2014 ($ IN THOUSANDS) KEY: = more than $70 million = less than $70 million more than $35 million = less than $35 million ACTUAL FORECAST ACTUAL ACTUAL ACTUAL ACTUAL ACTUAL ACTUAL ACTUAL ACTUAL ACTUAL ACTUAL ACTUAL FORECAST ACTUAL ACTUAL FORECAST FORECAST FY 2012 FY 2013 OCT 2012 NOV 2012 DEC 2012 JAN 2013 FEB 2013 MAR 2013 APR 2013 MAY 2013 JUN 2013 JUL 2013 AUG 2013 SEP 2013 SEP 2013 FY 2013 FY 2014 FY 2015 Note REVENUES Firm 141,638 $ 150,984 $ 9,356 $ 14,951 $ 15,015 $ 13,131 $ 12,470 $ 11,088 $ 11,817 $ 11,754 $ 12,954 $ 19,737 $ 13,914 $ 12,582 $ 10,652 $ 156,839 $ 152,591 $ 164,182 $ a WRP 32,170 $ 62,774 $ 755 $ 2,418

83

Contract/Project Management  

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

Second Quarter Second Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Primary Performance Metrics FY 2011 Target FY 2011 Forecast FY 2011 Pre- & Post-CAP Forecast Comment 1a. Capital Asset Line Item Projects: (Pre-RCA/CAP) Projects completed within 110% of CD-2 TPC. 1b. Capital Asset Line Item Projects: (Post-RCA/CAP) 90% Line Item 84% Line Item 78% Pre-CAP 100% Post-CAP This is based on a 3-year rolling average (FY09 to FY11). TPC is Total Project Cost. 2a. EM Cleanup (Soil and Groundwater Remediation, D&D, and Waste Treatment and Disposal) Projects: (Pre- RAC/CAP) 90% of Projects completed within 110% of CD-2 TPC by FY12. 2b. EM Cleanup (Soil and Groundwater Remediation,

84

Contract/Project Management  

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

Third Quarter Third Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Primary Performance Metrics FY 2011 Target FY 2011 Forecast FY 2011 Pre- & Post-CAP Forecast Comment 1a. Capital Asset Line Item Projects: (Pre-RCA/CAP) Projects completed within 110% of CD-2 TPC. 1b. Capital Asset Line Item Projects: (Post-RCA/CAP) 90% Line Item 84% Line Item 78% Pre-CAP 100% Post-CAP This is based on a 3-year rolling average (FY09 to FY11). TPC is Total Project Cost. 2a. EM Cleanup (Soil and Groundwater Remediation, D&D, and Waste Treatment and Disposal) Projects: (Pre- RAC/CAP) 90% of Projects completed within 110% of CD-2 TPC by FY12. 2b. EM Cleanup (Soil and Groundwater Remediation,

85

Conceptual design of a geothermal site development forecasting system  

SciTech Connect

A site development forecasting system has been designed in response to the need to monitor and forecast the development of specific geothermal resource sites for electrical power generation and direct heat applications. The system is comprised of customized software, a site development status data base, and a set of complex geothermal project development schedules. The system would use site-specific development status information obtained from the Geothermal Progress Monitor and other data derived from economic and market penetration studies to produce reports on the rates of geothermal energy development, federal agency manpower requirements to ensure these developments, and capital expenditures and technical/laborer manpower required to achieve these developments.

Neham, E.A.; Entingh, D.J.

1980-03-01T23:59:59.000Z

86

CCPP-ARM Parameterization Testbed Model Forecast Data  

DOE Data Explorer (OSTI)

Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

Klein, Stephen

87

Correcting and combining time series forecasters  

Science Journals Connector (OSTI)

Combined forecasters have been in the vanguard of stochastic time series modeling. In this way it has been usual to suppose that each single model generates a residual or prediction error like a white noise. However, mostly because of disturbances not ... Keywords: Artificial neural networks hybrid systems, Linear combination of forecasts, Maximum likelihood estimation, Time series forecasters, Unbiased forecasters

Paulo Renato A. Firmino; Paulo S. G. De Mattos Neto; Tiago A. E. Ferreira

2014-02-01T23:59:59.000Z

88

NOAA Harmful Algal Bloom Operational Forecast System Southwest Florida Forecast Region Maps  

E-Print Network (OSTI)

Bloom Operational Forecast System Southwest Florida Forecast Region Maps 0 5 102.5 Miles #12;Bay Harmful Algal Bloom Operational Forecast System Southwest Florida Forecast Region Maps 0 5 102.5 Miles #12 N Collier N Charlotte S Charlotte NOAA Harmful Algal Bloom Operational Forecast System Southwest

89

Forecast Energy | Open Energy Information  

Open Energy Info (EERE)

Forecast Energy Forecast Energy Jump to: navigation, search Name Forecast Energy Address 2320 Marinship Way, Suite 300 Place Sausalito, California Zip 94965 Sector Services Product Intelligent Monitoring and Forecasting Services Year founded 2010 Number of employees 11-50 Company Type For profit Website http://www.forecastenergy.net Coordinates 37.865647°, -122.496315° 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":37.865647,"lon":-122.496315,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

90

Price forecasting for notebook computers  

E-Print Network (OSTI)

This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a series of time periods, and the rates of change in the influence...

Rutherford, Derek Paul

2012-06-07T23:59:59.000Z

91

Forecasting phenology under global warming  

Science Journals Connector (OSTI)

...Forrest Forecasting phenology under global warming Ines Ibanez 1 * Richard B. Primack...and site-specific responses to global warming. We found that for most species...climate change|East Asia, global warming|growing season, hierarchical...

2010-01-01T23:59:59.000Z

92

Demand Forecasting of New Products  

E-Print Network (OSTI)

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

Sun, Yu

93

Cloudnet Project  

DOE Data Explorer (OSTI)

Cloudnet is a research project supported by the European Commission. This project aims to use data obtained quasi-continuously for the development and implementation of cloud remote sensing synergy algorithms. The use of active instruments (lidar and radar) results in detailed vertical profiles of important cloud parameters which cannot be derived from current satellite sensing techniques. A network of three already existing cloud remote sensing stations (CRS-stations) will be operated for a two year period, activities will be co-ordinated, data formats harmonised and analysis of the data performed to evaluate the representation of clouds in four major european weather forecast models.

Hogan, Robin

94

Contract/Project Management  

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

First Quarter First Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Performance Metric FY 2012 Target FY 2012 Forecast FY 2012 Pre- & Post-CAP Forecast Comment Capital Asset Project Success: Complete 90% of capital asset projects at original scope and within 110% of CD-2 TPC. 90%* 84% Construction 83% Cleanup 85% 77% Pre-CAP 86% Post- CAP This is based on a 3- year rolling average (FY10 to FY12). TPC is Total Project Cost. Contract/Project Management Performance Metrics FY 2012 Target FY 2012 1st Qtr Actual Comment Certified EVM Systems: Post CD-3, (greater than $20 million). 95%* 94% EVM represents Earned Value Management. Certified FPD's at CD-1: Projects

95

Contract/Project Management  

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

Second Quarter Second Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Performance Metric FY 2012 Target FY 2012 Forecast FY 2012 Pre- & Post-CAP Forecast Comment Capital Asset Project Success: Complete 90% of capital asset projects at original scope and within 110% of CD-2 TPC. 90%* 88% Construction 87% Cleanup 89% 77% Pre-CAP 92% Post- CAP This is based on a 3- year rolling average (FY10 to FY12). TPC is Total Project Cost. Contract/Project Management Performance Metrics FY 2012 Target FY 2012 2nd Qtr Actual Comment Certified EVM Systems: Post CD-3, (greater than $20 million). 95%* 96% EVM represents Earned Value Management. Certified FPD's at CD-1: Projects

96

Contract/Project Management  

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

Third Quarter Third Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Performance Metric FY 2012 Target FY 2012 Forecast FY 2012 Pre- & Post-CAP Forecast Comment Capital Asset Project Success: Complete 90% of capital asset projects at original scope and within 110% of CD-2 TPC. 90%* 87% Construction 87% Cleanup 87% 77% Pre-CAP 90% Post- CAP This is based on a 3- year rolling average (FY10 to FY12). TPC is Total Project Cost. Contract/Project Management Performance Metrics FY 2012 Target FY 2012 3rd Qtr Actual Comment Certified EVM Systems: Post CD-3, (greater than $20 million). 95%* 98% EVM represents Earned Value Management. Certified FPD's at CD-1: Projects

97

Weather forecasting : the next generation : the potential use and implementation of ensemble forecasting  

E-Print Network (OSTI)

This thesis discusses ensemble forecasting, a promising new weather forecasting technique, from various viewpoints relating not only to its meteorological aspects but also to its user and policy aspects. Ensemble forecasting ...

Goto, Susumu

2007-01-01T23:59:59.000Z

98

Applying Bayesian Forecasting to Predict New Customers' Heating Oil Demand.  

E-Print Network (OSTI)

??This thesis presents a new forecasting technique that estimates energy demand by applying a Bayesian approach to forecasting. We introduce our Bayesian Heating Oil Forecaster (more)

Sakauchi, Tsuginosuke

2011-01-01T23:59:59.000Z

99

Solar Energy Market Forecast | Open Energy Information  

Open Energy Info (EERE)

Solar Energy Market Forecast Solar Energy Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast Agency/Company /Organization: United States Department of Energy Sector: Energy Focus Area: Solar Topics: Market analysis, Technology characterizations Resource Type: Publications Website: giffords.house.gov/DOE%20Perspective%20on%20Solar%20Market%20Evolution References: Solar Energy Market Forecast[1] Summary " Energy markets / forecasts DOE Solar America Initiative overview Capital market investments in solar Solar photovoltaic (PV) sector overview PV prices and costs PV market evolution Market evolution considerations Balance of system costs Silicon 'normalization' Solar system value drivers Solar market forecast Additional resources"

100

Voluntary Green Power Market Forecast through 2015  

SciTech Connect

Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

2010-05-01T23:59:59.000Z

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101

Summary Verification Measures and Their Interpretation for Ensemble Forecasts  

Science Journals Connector (OSTI)

Ensemble prediction systems produce forecasts that represent the probability distribution of a continuous forecast variable. Most often, the verification problem is simplified by transforming the ensemble forecast into probability forecasts for ...

A. Allen Bradley; Stuart S. Schwartz

2011-09-01T23:59:59.000Z

102

Aggregate vehicle travel forecasting model  

SciTech Connect

This report describes a model for forecasting total US highway travel by all vehicle types, and its implementation in the form of a personal computer program. The model comprises a short-run, econometrically-based module for forecasting through the year 2000, as well as a structural, scenario-based longer term module for forecasting through 2030. The short-term module is driven primarily by economic variables. It includes a detailed vehicle stock model and permits the estimation of fuel use as well as vehicle travel. The longer-tenn module depends on demographic factors to a greater extent, but also on trends in key parameters such as vehicle load factors, and the dematerialization of GNP. Both passenger and freight vehicle movements are accounted for in both modules. The model has been implemented as a compiled program in the Fox-Pro database management system operating in the Windows environment.

Greene, D.L.; Chin, Shih-Miao; Gibson, R. [Tennessee Univ., Knoxville, TN (United States)

1995-05-01T23:59:59.000Z

103

Communication of uncertainty in temperature forecasts  

Science Journals Connector (OSTI)

We used experimental economics to test whether undergraduate students presented with a temperature forecast with uncertainty information in a table and bar graph format were able to use the extra information to interpret a given forecast. ...

Pricilla Marimo; Todd R. Kaplan; Ken Mylne; Martin Sharpe

104

FORECASTING THE ROLE OF RENEWABLES IN HAWAII  

E-Print Network (OSTI)

FORECASTING THE ROLE OF RENEWABLES IN HAWAII Jayant SathayeFORECASTING THE ROLF OF RENEWABLES IN HAWAII J Sa and Henrythe Conservation Role of Renewables November 18, 1980 Page 2

Sathaye, Jayant

2013-01-01T23:59:59.000Z

105

Massachusetts state airport system plan forecasts.  

E-Print Network (OSTI)

This report is a first step toward updating the forecasts contained in the 1973 Massachusetts State System Plan. It begins with a presentation of the forecasting techniques currently available; it surveys and appraises the ...

Mathaisel, Dennis F. X.

106

Antarctic Satellite Meteorology: Applications for Weather Forecasting  

Science Journals Connector (OSTI)

For over 30 years, weather forecasting for the Antarctic continent and adjacent Southern Ocean has relied on weather satellites. Significant advancements in forecasting skill have come via the weather satellite. The advent of the high-resolution ...

Matthew A. Lazzara; Linda M. Keller; Charles R. Stearns; Jonathan E. Thom; George A. Weidner

2003-02-01T23:59:59.000Z

107

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Natural Gas Natural gas is the fastest growing primary energy source in the IEO2005 forecast. Consumption of natural gas is projected to increase by nearly 70 percent between 2002 and 2025, with the most robust growth in demand expected among the emerging economies. Figure 34. World Natural Gas Consumption, 1980-2025 (Trillion Cubic Feet). Need help, contact the National Energy Information Center on 202-586-8800. Figure Data Figure 35. Natural Gas Consumption by Region, 1980-2025 (Trillion Cubic Feet). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 36. Increase in Natural Gas Consumption by Region and Country, 2002-2025. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data

108

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Energy Consumption by End-Use Sector Energy Consumption by End-Use Sector In the IEO2005 projections, end-use energy consumption in the residential, commercial, industrial, and transportation sectors varies widely among regions and from country to country. One way of looking at the future of world energy markets is to consider trends in energy consumption at the end-use sector level. With the exception of the transportation sector, which is almost universally dominated by petroleum products at present, the mix of energy use in the residential, commercial, and industrial sectors can vary widely from country to country, depending on a combination of regional factors, such as the availability of energy resources, the level of economic development, and political, social, and demographic factors. This chapter outlines the International Energy Outlook 2005 (IEO2005) forecast for regional energy consumption by end-use sector.

109

Energy demand forecasting: industry practices and challenges  

Science Journals Connector (OSTI)

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

Mathieu Sinn

2014-06-01T23:59:59.000Z

110

Consensus Coal Production And Price Forecast For  

E-Print Network (OSTI)

Consensus Coal Production And Price Forecast For West Virginia: 2011 Update Prepared for the West December 2011 © Copyright 2011 WVU Research Corporation #12;#12;W.Va. Consensus Coal Forecast Update 2011 i Table of Contents Executive Summary 1 Recent Developments 3 Consensus Coal Production And Price Forecast

Mohaghegh, Shahab

111

Short-term wind forecast for the safety management of complex areas during hazardous wind events  

Science Journals Connector (OSTI)

Abstract This paper describes the short-term wind forecast system realised in the framework of the European Project Wind and Ports: The forecast of wind for the management and safety of port areas. The project?s aim is to contribute improving the safety and accessibility to the harbour areas of the largest ports in the Northern Tyrrhenian Sea, which are frequently exposed to hazardous winds, in order to minimise the risks for users, structures, transport means, stored goods and boats within the ports. The short-term wind forecast system is based on a mixed statistical-numerical procedure, trained by means of local wind measurements and implemented into an operational chain for the real-time prediction of the maximum expected wind velocity corresponding to three forecast horizons (30, 60 and 90min) and three non-exceeding probabilities (90%, 95%, and 99%). The local wind measurements used to train the forecast algorithms have been recorded from the 15 ultra-sonic anemometers installed in the Ports of Savona, La Spezia, and Livorno. This wind-monitoring network is used also to carry out the short-term forecast system a posteriori verification and validation.

M. Burlando; M. Pizzo; M.P. Repetto; G. Solari; P. De Gaetano; M. Tizzi

2014-01-01T23:59:59.000Z

112

On Bayesian forecasting of procurement delays: a case study: Research Articles  

Science Journals Connector (OSTI)

In the engineering and contracting sector, the on-time availability of materials is a crucial element of any project. In recent years, there has been increasing competition in the supply of such components, as a result of market globalization. This has ... Keywords: bidding process, delivery times' forecasts, dynamic linear models, procurement process, project management

Jesus Palomo; Fabrizio Ruggeri; David Rios Insua; Enrico Cagno; Franco Caron; Mauro Mancini

2006-03-01T23:59:59.000Z

113

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

Analysis Papers > Annual Energy Outlook Forecast Evaluation Analysis Papers > Annual Energy Outlook Forecast Evaluation Release Date: February 2005 Next Release Date: February 2006 Printer-friendly version Annual Energy Outlook Forecast Evaluation* Table 1.Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Printer Friendly Version Average Absolute Percent Error Variable AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 AEO82 to AEO2004 Consumption Total Energy Consumption 1.9 2.0 2.1 2.1 2.1 2.1 Total Petroleum Consumption 2.9 3.0 3.1 3.1 3.0 2.9 Total Natural Gas Consumption 7.3 7.1 7.1 6.7 6.4 6.5 Total Coal Consumption 3.1 3.3 3.5 3.6 3.7 3.8 Total Electricity Sales 1.9 2.0 2.3 2.3 2.3 2.4 Production Crude Oil Production 4.5 4.5 4.5 4.5 4.6 4.7

114

Load Forecasting of Supermarket Refrigeration  

E-Print Network (OSTI)

energy system. Observed refrigeration load and local ambient temperature from a Danish su- permarket renewable energy, is increasing, therefore a flexible energy system is needed. In the present ThesisLoad Forecasting of Supermarket Refrigeration Lisa Buth Rasmussen Kongens Lyngby 2013 M.Sc.-2013

115

Essays on macroeconomics and forecasting  

E-Print Network (OSTI)

explanatory variables. Compared to Stock and Watson (2002)â??s models, the models proposed in this chapter can further allow me to select the factors structurally for each variable to be forecasted. I find advantages to using the structural dynamic factor...

Liu, Dandan

2006-10-30T23:59:59.000Z

116

Forecasting-based SKU classification  

Science Journals Connector (OSTI)

Different spare parts are associated with different underlying demand patterns, which in turn require different forecasting methods. Consequently, there is a need to categorise stock keeping units (SKUs) and apply the most appropriate methods in each category. For intermittent demands, Croston's method (CRO) is currently regarded as the standard method used in industry to forecast the relevant inventory requirements; this is despite the bias associated with Croston's estimates. A bias adjusted modification to CRO (SyntetosBoylan Approximation, SBA) has been shown in a number of empirical studies to perform very well and be associated with a very robust behaviour. In a 2005 article, entitled On the categorisation of demand patterns published by the Journal of the Operational Research Society, Syntetos et al. (2005) suggested a categorisation scheme, which establishes regions of superior forecasting performance between CRO and SBA. The results led to the development of an approximate rule that is expressed in terms of fixed cut-off values for the following two classification criteria: the squared coefficient of variation of the demand sizes and the average inter-demand interval. Kostenko and Hyndman (2006) revisited this issue and suggested an alternative scheme to distinguish between CRO and SBA in order to improve overall forecasting accuracy. Claims were made in terms of the superiority of the proposed approach to the original solution but this issue has never been assessed empirically. This constitutes the main objective of our work. In this paper the above discussed classification solutions are compared by means of experimentation on more than 10,000 \\{SKUs\\} from three different industries. The results enable insights to be gained into the comparative benefits of these approaches. The trade-offs between forecast accuracy and other implementation related considerations are also addressed.

G. Heinecke; A.A. Syntetos; W. Wang

2013-01-01T23:59:59.000Z

117

Forecasting wind speed financial return  

E-Print Network (OSTI)

The prediction of wind speed is very important when dealing with the production of energy through wind turbines. In this paper, we show a new nonparametric model, based on semi-Markov chains, to predict wind speed. Particularly we use an indexed semi-Markov model that has been shown to be able to reproduce accurately the statistical behavior of wind speed. The model is used to forecast, one step ahead, wind speed. In order to check the validity of the model we show, as indicator of goodness, the root mean square error and mean absolute error between real data and predicted ones. We also compare our forecasting results with those of a persistence model. At last, we show an application of the model to predict financial indicators like the Internal Rate of Return, Duration and Convexity.

D'Amico, Guglielmo; Prattico, Flavio

2013-01-01T23:59:59.000Z

118

Contract/Project Management  

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

Third Quarter Third Quarter Overall Contract and Project Management Performance Metrics and Targets 1 Contract/Project Management Primary Performance Metrics FY 2010 Target FY 2010 Forecast FY 2010 Pre- & Post-CAP Comment 1a. Capital Asset Line Item Projects: (Pre-RCA/CAP) 90% of projects completed within 110% of CD-2 TPC by FY11. 1b. Capital Asset Line Item Projects: (Post-RCA/CAP) 85% Line Item 71% Line Item 70% Pre-CAP 100% Post-CAP This is a projection based on a 3-year rolling average (FY08 to FY10). TPC is Total Project Cost. 2a. EM Cleanup (Soil and Groundwater Remediation, D&D, and Waste Treatment and Disposal) Projects: (Pre- RAC/CAP) 90% of projects completed within 110% of CD-2 TPC by FY11. 2b. EM Cleanup (Soil and Groundwater Remediation,

119

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

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

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

2008-01-01T23:59:59.000Z

120

Where can I find free economic forecasts? Economic forecasts have become an integral part of business and individual investment decisions. Economic  

E-Print Network (OSTI)

, the Conference Board provides short term (quarterly and annual) forecasts for real GDP, real consumer spending include (among others): GDP and real GDP, price indices for GDP and consumer spending, unemployment are projections of economic activity including GDP growth. These reports can be found on-line at: http

Johnson, Eric E.

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Weather Forecast Data an Important Input into Building Management Systems  

E-Print Network (OSTI)

Lewis Poulin Implementation and Operational Services Section Canadian Meteorological Centre, Dorval, Qc National Prediction Operations Division ICEBO 2013, Montreal, Qc October 10 2013 Version 2013-09-27 Weather Forecast Data An Important... and weather information ? Numerical weather forecast production 101 ? From deterministic to probabilistic forecasts ? Some MSC weather forecast (NWP) datasets ? Finding the appropriate data for the appropriate forecast ? Preparing for probabilistic...

Poulin, L.

2013-01-01T23:59:59.000Z

122

Short Mountain Landfill gas recovery project  

SciTech Connect

The Bonneville Power Administration (BPA), a Federal power marketing agency, has statutory responsibilities to supply electrical power to its utility, industrial, and other customers in the Pacific Northwest. BPA's latest load/resource balance forecast, projects the capability of existing resources to satisfy projected Federal system loads. The forecast indicates a potential resource deficit. The underlying need for action is to satisfy BPA customers' demand for electrical power.

Not Available

1992-05-01T23:59:59.000Z

123

BMA Probabilistic Quantitative Precipitation Forecasting over the Huaihe Basin Using TIGGE Multimodel Ensemble Forecasts  

Science Journals Connector (OSTI)

Bayesian model averaging (BMA) probability quantitative precipitation forecast (PQPF) models were established by calibrating their parameters using 17-day ensemble forecasts of 24-h accumulated precipitation, and observations from 43 ...

Jianguo Liu; Zhenghui Xie

2014-04-01T23:59:59.000Z

124

Calibrated Precipitation Forecasts for a Limited-Area Ensemble Forecast System Using Reforecasts  

Science Journals Connector (OSTI)

The calibration of numerical weather forecasts using reforecasts has been shown to increase the skill of weather predictions. Here, the precipitation forecasts from the Consortium for Small Scale Modeling Limited Area Ensemble Prediction System (...

Felix Fundel; Andre Walser; Mark A. Liniger; Christoph Frei; Christof Appenzeller

2010-01-01T23:59:59.000Z

125

Funding Opportunity Announcement for Wind Forecasting Improvement...  

Office of Environmental Management (EM)

to improved forecasts, system operators and industry professionals can ensure that wind turbines will operate at their maximum potential. Data collected during this field...

126

Upcoming Funding Opportunity for Wind Forecasting Improvement...  

Office of Environmental Management (EM)

to improved forecasts, system operators and industry professionals can ensure that wind turbines will operate at their maximum potential. Data collected during this field...

127

Huge market forecast for linear LDPE  

Science Journals Connector (OSTI)

Huge market forecast for linear LDPE ... It now appears that the success of the new technology, which rests largely on energy and equipment cost savings, could be overwhelming. ...

1980-08-25T23:59:59.000Z

128

Contract/Project Management  

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

First Quarter First Quarter Overall Contract and Project Management Performance Metrics and Targets 1 Contract/Project Management Primary Performance Metrics FY 2011 Target FY 2011 Actual & Forecast FY 2011 Pre- & Post-CAP Comment 1a. Capital Asset Line Item Projects: (Pre-RCA/CAP) Projects completed within 110% of CD-2 TPC. 1b. Capital Asset Line Item Projects: (Post-RCA/CAP) 90% Line Item 79% Line Item 71% Pre-CAP 100% Post-CAP This is based on a 3-year rolling average (FY09 to FY11). TPC is Total Project Cost. 2a. EM Cleanup (Soil and Groundwater Remediation, D&D, and Waste Treatment and Disposal) Projects: (Pre- RAC/CAP) 90% of Projects completed within 110% of CD-2 TPC by FY12. 2b. EM Cleanup (Soil and Groundwater Remediation,

129

Analysis of PG&E`s residential end-use metered data to improve electricity demand forecasts -- final report  

SciTech Connect

This report summarizes findings from a unique project to improve the end-use electricity load shape and peak demand forecasts made by the Pacific Gas and Electric Company (PG&E) and the California Energy Commission (CEC). First, the direct incorporation of end-use metered data into electricity demand forecasting models is a new approach that has only been made possible by recent end-use metering projects. Second, and perhaps more importantly, the joint-sponsorship of this analysis has led to the development of consistent sets of forecasting model inputs. That is, the ability to use a common data base and similar data treatment conventions for some of the forecasting inputs frees forecasters to concentrate on those differences (between their competing forecasts) that stem from real differences of opinion, rather than differences that can be readily resolved with better data. The focus of the analysis is residential space cooling, which represents a large and growing demand in the PG&E service territory. Using five years of end-use metered, central air conditioner data collected by PG&E from over 300 residences, we developed consistent sets of new inputs for both PG&E`s and CEC`s end-use load shape forecasting models. We compared the performance of the new inputs both to the inputs previously used by PG&E and CEC, and to a second set of new inputs developed to take advantage of a recently added modeling option to the forecasting model. The testing criteria included ability to forecast total daily energy use, daily peak demand, and demand at 4 P.M. (the most frequent hour of PG&E`s system peak demand). We also tested the new inputs with the weather data used by PG&E and CEC in preparing their forecasts.

Eto, J.H.; Moezzi, M.M.

1993-12-01T23:59:59.000Z

130

NOAA GREAT LAKES COASTAL FORECASTING SYSTEM Forecasts (up to 5 days in the future)  

E-Print Network (OSTI)

conditions for up to 5 days in the future. These forecasts are run twice daily, and you can step through are generated every 6 hours and you can step backward in hourly increments to view conditions over the previousNOAA GREAT LAKES COASTAL FORECASTING SYSTEM Forecasts (up to 5 days in the future) and Nowcasts

131

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Oil Markets Oil Markets IEO2005 projects that world crude oil prices in real 2003 dollars will decline from their current level by 2010, then rise gradually through 2025. In the International Energy Outlook 2005 (IEO2005) reference case, world demand for crude oil grows from 78 million barrels per day in 2002 to 103 million barrels per day in 2015 and to just over 119 million barrels per day in 2025. Much of the growth in oil consumption is projected for the emerging Asian nations, where strong economic growth results in a robust increase in oil demand. Emerging Asia (including China and India) accounts for 45 percent of the total world increase in oil use over the forecast period in the IEO2005 reference case. The projected increase in world oil demand would require an increment to world production capability of more than 42 million barrels per day relative to the 2002 crude oil production capacity of 80.0 million barrels per day. Producers in the Organization of Petroleum Exporting Countries (OPEC) are expected to be the major source of production increases. In addition, non-OPEC supply is expected to remain highly competitive, with major increments to supply coming from offshore resources, especially in the Caspian Basin, Latin America, and deepwater West Africa. The estimates of incremental production are based on current proved reserves and a country-by-country assessment of ultimately recoverable petroleum. In the IEO2005 oil price cases, the substantial investment capital required to produce the incremental volumes is assumed to exist, and the investors are expected to receive at least a 10-percent return on investment.

132

Annual Energy Outlook Forecast Evaluation - Table 1. Forecast Evaluations:  

Gasoline and Diesel Fuel Update (EIA)

Average Absolute Percent Errors from AEO Forecast Evaluations: Average Absolute Percent Errors from AEO Forecast Evaluations: 1996 to 2000 Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Variable 1996 Evaluation: AEO82 to AEO93 1997 Evaluation: AEO82 to AEO97 1998 Evaluation: AEO82 to AEO98 1999 Evaluation: AEO82 to AEO99 2000 Evaluation: AEO82 to AEO2000 Consumption Total Energy Consumption 1.8 1.6 1.7 1.7 1.8 Total Petroleum Consumption 3.2 2.8 2.9 2.8 2.9 Total Natural Gas Consumption 6.0 5.8 5.7 5.6 5.6 Total Coal Consumption 2.9 2.7 3.0 3.2 3.3 Total Electricity Sales 1.8 1.6 1.7 1.8 2.0 Production Crude Oil Production 5.1 4.2 4.3 4.5 4.5

133

Optimal combined wind power forecasts using exogeneous variables  

E-Print Network (OSTI)

Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

134

Ensemble typhoon quantitative precipitation forecasts model in Taiwan  

Science Journals Connector (OSTI)

In this study, an ensemble typhoon quantitative precipitation forecast (ETQPF) model was developed to provide typhoon rainfall forecasts for Taiwan. The ETQPF rainfall forecast is obtained by averaging the pick-out cases, which are screened at a ...

Jing-Shan Hong; Chin-Tzu Fong; Ling-Feng Hsiao; Yi-Chiang Yu; Chian-You Tzeng

135

Project Plan UC Online Education (UCOE)  

E-Print Network (OSTI)

of Contents I. PROJECT DESCRIPTION II. COST REVENUE MODEL AND FINANCIAL FORECAST III. INCENTIVES1 Project Plan UC Online Education (UCOE) March 24, 2011 Office of the President SUPPORTING CAMPUS AND FACULTY PARTICIPATION IV. RISKS AND RISK MANAGEMENT V. PROJECT ORGANIZATION

Becker, Luann

136

New Concepts in Wind Power Forecasting Models  

E-Print Network (OSTI)

New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, João Gama, Guenter to the training of mappers such as neural networks to perform wind power prediction as a function of wind for more accurate short term wind power forecasting models has led to solid and impressive development

Kemner, Ken

137

QUIKSCAT MEASUREMENTS AND ECMWF WIND FORECASTS  

E-Print Network (OSTI)

. (2004) this forecast error was encountered when assimilating satellite measurements of zonal wind speeds between satellite measurements and meteorological forecasts of near-surface ocean winds. This type of covariance enters in assimilation techniques such as Kalman filtering. In all, six residual fields

Malmberg, Anders

138

QUIKSCAT MEASUREMENTS AND ECMWF WIND FORECASTS  

E-Print Network (OSTI)

. (2004) this forecast error was encountered when assimilating satellite measurements of zonal wind speeds between satellite measurements and meteorological forecasts of near­surface ocean winds. This type of covariance enters in assimilation techniques such as Kalman filtering. In all, six residual fields

Malmberg, Anders

139

PROBLEMS OF FORECAST1 Dmitry KUCHARAVY  

E-Print Network (OSTI)

: Technology Forecast, Laws of Technical systems evolution, Analysis of Contradictions. 1. Introduction Let us: If technology forecasting practice remains at the present level, it is necessary to significantly improve to new demands (like Green House Gases - GHG Effect reduction or covering exploded nuclear reactor

Paris-Sud XI, Université de

140

Amending Numerical Weather Prediction forecasts using GPS  

E-Print Network (OSTI)

. Satellite images and Numerical Weather Prediction (NWP) models are used together with the synoptic surfaceAmending Numerical Weather Prediction forecasts using GPS Integrated Water Vapour: a case study to validate the amounts of humidity in Numerical Weather Prediction (NWP) model forecasts. This paper presents

Stoffelen, Ad

Note: This page contains sample records for the topic "interindustry forecasting project" 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

A Forecasting Support System Based on Exponential Smoothing  

Science Journals Connector (OSTI)

This chapter presents a forecasting support system based on the exponential smoothing scheme to forecast time-series data. Exponential smoothing methods are simple to apply, which facilitates...

Ana Corbern-Vallet; Jos D. Bermdez; Jos V. Segura

2010-01-01T23:59:59.000Z

142

Improved Prediction of Runway Usage for Noise Forecast :.  

E-Print Network (OSTI)

??The research deals with improved prediction of runway usage for noise forecast. Since the accuracy of the noise forecast depends on the robustness of runway (more)

Dhanasekaran, D.

2014-01-01T23:59:59.000Z

143

PBL FY 2002 Third Quarter Review Forecast of Generation Accumulated...  

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

Power Business Line Generation Accumulated Net Revenues Forecast for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) FY 2002 Third Quarter Review Forecast in Millions...

144

Short-term energy outlook quarterly projections. First quarter 1994  

SciTech Connect

The Energy Information Administration (EIA) prepares quarterly, short- term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets.

Not Available

1994-02-07T23:59:59.000Z

145

1993 Solid Waste Reference Forecast Summary  

SciTech Connect

This report, which updates WHC-EP-0567, 1992 Solid Waste Reference Forecast Summary, (WHC 1992) forecasts the volumes of solid wastes to be generated or received at the US Department of Energy Hanford Site during the 30-year period from FY 1993 through FY 2022. The data used in this document were collected from Westinghouse Hanford Company forecasts as well as from surveys of waste generators at other US Department of Energy sites who are now shipping or plan to ship solid wastes to the Hanford Site for disposal. These wastes include low-level and low-level mixed waste, transuranic and transuranic mixed waste, and nonradioactive hazardous waste.

Valero, O.J.; Blackburn, C.L. [Westinghouse Hanford Co., Richland, WA (United States); Kaae, P.S.; Armacost, L.L.; Garrett, S.M.K. [Pacific Northwest Lab., Richland, WA (United States)

1993-08-01T23:59:59.000Z

146

Metrics for Evaluating the Accuracy of Solar Power Forecasting (Presentation)  

SciTech Connect

This presentation proposes a suite of metrics for evaluating the performance of solar power forecasting.

Zhang, J.; Hodge, B.; Florita, A.; Lu, S.; Hamann, H.; Banunarayanan, V.

2013-10-01T23:59:59.000Z

147

PSO (FU 2101) Ensemble-forecasts for wind power  

E-Print Network (OSTI)

PSO (FU 2101) Ensemble-forecasts for wind power Analysis of the Results of an On-line Wind Power Ensemble- forecasts for wind power (FU2101) a demo-application producing quantile forecasts of wind power correct) quantile forecasts of the wind power production are generated by the application. However

148

Forecasting Uncertainty Related to Ramps of Wind Power Production  

E-Print Network (OSTI)

Forecasting Uncertainty Related to Ramps of Wind Power Production Arthur Bossavy, Robin Girard - The continuous improvement of the accuracy of wind power forecasts is motivated by the increasing wind power study. Key words : wind power forecast, ramps, phase er- rors, forecasts ensemble. 1 Introduction Most

Boyer, Edmond

149

The effect of multinationality on management earnings forecasts  

E-Print Network (OSTI)

and number of countries withforeign subsidiaries) are significantly positively related to more optimistic management earnings forecasts....

Runyan, Bruce Wayne

2005-08-29T23:59:59.000Z

150

Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)  

SciTech Connect

This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.

Hodge, B. M.; Ela, E.; Milligan, M.

2011-10-01T23:59:59.000Z

151

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network (OSTI)

J.B. , 2004: Probabilistic wind power forecasts using localforecast intervals for wind power output using NWP-predictedsources such as wind and solar power. Integration of this

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

152

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network (OSTI)

United States California Solar Initiative Coastally Trappedparticipants in the California Solar Initiative (CSI)on location. In California, solar irradiance forecasts near

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

153

CERTS Review REAL-TIME PRICE FORECAST WITH BIG DATA A STATE SPACE APPROACH  

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

Review Review REAL-TIME PRICE FORECAST WITH BIG DATA A STATE SPACE APPROACH Lang Tong (PI), Robert J. Thomas, Yuting Ji, and Jinsub Kim School of Electrical and Computer Engineering, Cornell University Jie Mei, Georgia Institute of Technology August 7, 2013 CERTS Review DATA QUALITY AND ITS EFFECTS ON MARKET OPERATIONS DENY OF SERVICE ATTACK ON REAL-TIME ELECTRICITY MARKET COVER UP PROTECTION AGAINST TOPOLOGY ATTACK Lang Tong (PI), Robert J. Thomas, and Jinsub Kim Cornell University August 8, 2013 Project overview  Objectives  Accurate short-term probabilistic forecasting of real-time LMP.  Incorporate real-time measurements (e.g. SCADA/PMU).  Scalable computation techniques.  Summary of results  A real-time LMP model with forecasting and measurement

154

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Analysis Papers > Annual Energy Outlook Forecast Evaluation>Tables Analysis Papers > Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Download Adobe Acrobat Reader Printer friendly version on our site are provided in Adobe Acrobat Spreadsheets are provided in Excel Actual vs. Forecasts Formats Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF Table 12. World Oil Prices Excel, PDF Table 13. Natural Gas Wellhead Prices

155

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) MS Excel Viewer PDF (Acrobat Reader required Download Acrobat Reader ) Adobe Acrobat Reader Logo Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF

156

energy data + forecasting | OpenEI Community  

Open Energy Info (EERE)

energy data + forecasting energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in formulating policies and energy plans based on easy to use forecasting tools, visualizations, sankey diagrams, and open data. The platform will live on OpenEI and this community was established to initiate discussion around continuous development of this tool, integrating it with new datasets, and connecting with the community of users who will want to contribute data to the tool and use the tool for planning purposes. Links: FRED beta demo energy data + forecasting Syndicate content 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2084382122

157

Wind Speed Forecasting for Power System Operation  

E-Print Network (OSTI)

In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

Zhu, Xinxin

2013-07-22T23:59:59.000Z

158

Evaluation of hierarchical forecasting for substitutable products  

Science Journals Connector (OSTI)

This paper addresses hierarchical forecasting in a production planning environment. Specifically, we examine the relative effectiveness of Top-Down (TD) and Bottom-Up (BU) strategies for forecasting the demand for a substitutable product (which belongs to a family) as well as the demand for the product family under different types of family demand processes. Through a simulation study, it is revealed that the TD strategy consistently outperforms the BU strategy for forecasting product family demand. The relative superiority of the TD strategy further improves by as much as 52% as the product demand variability increases and the degree of substitutability between the products decreases. This phenomenon, however, is not always true for forecasting the demand for the products within the family. In this case, it is found that there are a few situations wherein the BU strategy marginally outperforms the TD strategy, especially when the product demand variability is high and the degree of product substitutability is low.

S. Viswanathan; Handik Widiarta; R. Piplani

2008-01-01T23:59:59.000Z

159

Testing Competing High-Resolution Precipitation Forecasts  

E-Print Network (OSTI)

Testing Competing High-Resolution Precipitation Forecasts Eric Gilleland Research Prediction Comparison Test D1 D2 D = D1 ­ D2 copyright NCAR 2013 Loss Differential Field #12;Spatial Prediction Comparison Test Introduced by Hering and Genton

Gilleland, Eric

160

Forecasting Capital Expenditure with Plan Data  

Science Journals Connector (OSTI)

The short-term forecasting of capital expenditure presents one of the most difficult problems ... reason is that year-to-year fluctuations in capital expenditure are extremely wide. Some simple methods which...

W. Gerstenberger

1977-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Medium- and Long-Range Forecasting  

Science Journals Connector (OSTI)

In contrast to short and extended range forecasts, predictions for periods beyond 5 days use time-averaged, midtropospheric height fields as their primary guidance. As time ranges are increased to 3O- and 90-day outlooks, guidance increasingly ...

A. James Wagner

1989-09-01T23:59:59.000Z

162

Updated Satellite Technique to Forecast Heavy Snow  

Science Journals Connector (OSTI)

Certain satellite interpretation techniques have proven quite useful in the heavy snow forecast process. Those considered best are briefly reviewed, and another technique is introduced. This new technique was found to be most valuable in cyclonic ...

Edward C. Johnston

1995-06-01T23:59:59.000Z

163

Forecasting energy markets using support vector machines  

Science Journals Connector (OSTI)

Abstract In this paper we investigate the efficiency of a support vector machine (SVM)-based forecasting model for the next-day directional change of electricity prices. We first adjust the best autoregressive SVM model and then we enhance it with various related variables. The system is tested on the daily Phelix index of the German and Austrian control area of the European Energy Exchange (???) wholesale electricity market. The forecast accuracy we achieved is 76.12% over a 200day period.

Theophilos Papadimitriou; Periklis Gogas; Efthimios Stathakis

2014-01-01T23:59:59.000Z

164

Microsoft Office Project - OpForecast 2013-11-20  

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

Cycle Cycle Start Finish Duration 100 449 EOC Sat 8/24/13 Tue 10/8/13 44.77 days 101 450A Tue 10/8/13 Tue 10/8/13 0.29 days 102 450A EOC Tue 10/8/13 Wed 10/9/13 0.51 days 103 450B Tue 10/8/13 Sun 11/3/13 26.22 days 104 450B EOC Sun 11/3/13 Tue 1/14/14 72 days 105 451 Tue 1/14/14 Fri 2/7/14 24 days 106 451 EOC Fri 2/7/14 Tue 2/25/14 18 days 107 452 Tue 2/25/14 Fri 3/21/14 24 days 108 452 EOC Fri 3/21/14 Tue 5/6/14 46 days 109 453 Tue 5/6/14 Fri 5/30/14 24 days 110 453 EOC Fri 5/30/14 Tue 6/17/14 18 days 111 454 Tue 6/17/14 Fri 7/11/14 24 days 112 454 EOC Fri 7/11/14 Tue 7/29/14 18 days 113 455 Tue 7/29/14 Fri 8/22/14 24 days 114 455 EOC Fri 8/22/14 Tue 10/7/14 46 days 115 456 Tue 10/7/14 Fri 10/31/14 24 days 116 456 EOC Fri 10/31/14 Tue 11/18/14 18 days 117 457 Tue 11/18/14 Fri 12/12/14 24 days 118 457 EOC Fri 12/12/14 Tue 1/6/15 25 days 119 458 Tue 1/6/15

165

Project Profile: Forecasting and Influencing Technological Progress in Solar Energy  

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

The University of North Carolina at Charlotte, along with their partners at Arizona State University and the University of Oxford, under theSolar Energy Evolution and Diffusion Studies (SEEDS)...

166

Forecasting aggregate time series with intermittent subaggregate components: top-down versus bottom-up forecasting  

Science Journals Connector (OSTI)

......optimum value through a grid-search algorithm...method outperformed TD for estimating the aggregate data series...variable, there is no benefit of forecasting each subaggregate...forecasting strategies in estimating the `component'-level...WILLEMAIN, T. R., SMART, C. N., SHOCKOR......

S. Viswanathan; Handik Widiarta; Rajesh Piplani

2008-07-01T23:59:59.000Z

167

Short Mountain Landfill Gas Recovery Project : Stage 1 Environmental Assessment.  

SciTech Connect

The Bonneville Power Administration (BPA), a Federal power marketing agency, has statutory responsibilities to supply electrical power to its utility, industrial, and other customers in the Pacific Northwest. BPA`s latest load/resource balance forecast, projects the capability of existing resources to satisfy projected Federal system loads. The forecast indicates a potential resource deficit. The underlying need for action is to satisfy BPA customers` demand for electrical power.

United States. Bonneville Power Administration.

1992-05-01T23:59:59.000Z

168

Analysis & Projections - Projection Data - U.S. Energy Information  

Gasoline and Diesel Fuel Update (EIA)

Find data from forecast models on crude oil and petroleum liquids, Find data from forecast models on crude oil and petroleum liquids, gasoline, diesel, natural gas, electricity, coal prices, supply, and demand projections and more. + EXPAND ALL Monthly Short-Term Forecasts to 2014 Additional Formats Short-Term Energy Outlook Released: January 8, 2013 WF01. Average Consumer Prices and Expenditures for Heating Fuels During the Winter PDF 1. U.S. Energy Market Summary PDF 2. U.S. Energy Prices PDF 3a. Internatioal Crude Oil and Liquid Fuels Supply, Consumption, and Inventories PDF 3b. Non-OPEC Crude Oil and Liquid Fuels Supply PDF 3c. OPEC Crude Oil and Liquid Fuels Supply PDF 3d. World Liquid Fuels Consumption PDF 4a. U.S. Crude Oil and Liquid Fuels Supply, Consumption, and Inventories PDF 4b. U.S. Petroleum Refinery Balance PDF

169

Radar-Derived Forecasts of Cloud-to-Ground Lightning Over Houston, Texas  

E-Print Network (OSTI)

Lightning Forecasts..........................................................................................45 2.7 First Flash Forecasts and Lead Times.....................................................................47 vii... Cell Number ? 25 August 2000..............................................68 3.4 First Flash Forecast Time........................................................................................70 3.5 Lightning Forecasting Algorithm (LFA) Development...

Mosier, Richard Matthew

2011-02-22T23:59:59.000Z

170

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) PDF (Acrobat Reader required) Table 2. Total Energy Consumption HTML, Excel, PDF Table 3. Total Petroleum Consumption HTML, Excel, PDF Table 4. Total Natural Gas Consumption HTML, Excel, PDF Table 5. Total Coal Consumption HTML, Excel, PDF Table 6. Total Electricity Sales HTML, Excel, PDF Table 7. Crude Oil Production HTML, Excel, PDF Table 8. Natural Gas Production HTML, Excel, PDF Table 9. Coal Production HTML, Excel, PDF Table 10. Net Petroleum Imports HTML, Excel, PDF Table 11. Net Natural Gas Imports HTML, Excel, PDF Table 12. Net Coal Exports HTML, Excel, PDF Table 13. World Oil Prices HTML, Excel, PDF

171

12-32021E2_Forecast  

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

FORECAST OF VACANCIES FORECAST OF VACANCIES Until end of 2014 (Issue No. 20) Page 2 OVERVIEW OF BASIC REQUIREMENTS FOR PROFESSIONAL VACANCIES IN THE IAEA Education, Experience and Skills: Professional staff at the P4-P5 levels: * Advanced university degree (or equivalent postgraduate degree); * 7 or 10 years, respectively, of experience in a field of relevance to the post; * Resource management experience; * Strong analytical skills; * Computer skills: standard Microsoft Office software; * Languages: Fluency in English. Working knowledge of other official languages (Arabic, Chinese, French, Russian, Spanish) advantageous; * Ability to work effectively in multidisciplinary and multicultural teams; * Ability to communicate effectively. Professional staff at the P1-P3 levels:

172

Building Energy Software Tools Directory: Degree Day Forecasts  

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

Forecasts Forecasts Degree Day Forecasts example chart Quick and easy web-based tool that provides free 14-day ahead degree day forecasts for 1,200 stations in the U.S. and Canada. Degree Day Forecasts charts show this year, last year and three-year average. Historical degree day charts and energy usage forecasts are available from the same site. Keywords degree days, historical weather, mean daily temperature Validation/Testing Degree day data provided by AccuWeather.com, updated daily at 0700. Expertise Required No special expertise required. Simple to use. Users Over 1,000 weekly users. Audience Anyone who needs degree day forecasts (next 14 days) for the U.S. and Canada. Input Select a weather station (1,200 available) and balance point temperature. Output Charts show (1) degree day (heating and cooling) forecasts for the next 14

173

Building Energy Software Tools Directory: Energy Usage Forecasts  

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

Energy Usage Forecasts Energy Usage Forecasts Energy Usage Forecasts Quick and easy web-based tool that provides free 14-day ahead energy usage forecasts based on the degree day forecasts for 1,200 stations in the U.S. and Canada. The user enters the daily non-weather base load and the usage per degree day weather factor; the tool applies the degree day forecast and displays the total energy usage forecast. Helpful FAQs explain the process and describe various options for the calculation of the base load and weather factor. Historical degree day reports and 14-day ahead degree day forecasts are available from the same site. Keywords degree days, historical weather, mean daily temperature, load calculation, energy simulation Validation/Testing Degree day data provided by AccuWeather.com, updated daily at 0700.

174

Forecasting Market Demand for New Telecommunications Services: An Introduction  

E-Print Network (OSTI)

Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc The marketing team of a new telecommunications company is usually tasked with producing forecasts for diverse three decades of experience working with telecommunications operators around the world we seek

McBurney, Peter

175

River Forecast Application for Water Management: Oil and Water?  

Science Journals Connector (OSTI)

Managing water resources generally and managing reservoir operations specifically have been touted as opportunities for applying forecasts to improve decision making. Previous studies have shown that the application of forecasts into water ...

Kevin Werner; Kristen Averyt; Gigi Owen

2013-07-01T23:59:59.000Z

176

Operational Rainfall and Flow Forecasting for the Panama Canal Watershed  

Science Journals Connector (OSTI)

An integrated hydrometeorological system was designed for the utilization of data from various sensors in the 3300 km2 Panama Canal Watershed for the purpose of producing ... forecasts. These forecasts are used b...

Konstantine P. Georgakakos; Jason A. Sperfslage

2005-01-01T23:59:59.000Z

177

Power System Load Forecasting Based on EEMD and ANN  

Science Journals Connector (OSTI)

In order to fully mine the characteristics of load data and improve the accuracy of power system load forecasting, a load forecasting model based on Ensemble Empirical Mode ... is proposed in this paper. Firstly,...

Wanlu Sun; Zhigang Liu; Wenfan Li

2011-01-01T23:59:59.000Z

178

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

179

Beyond "Partly Sunny": A Better Solar Forecast | Department of...  

Energy Savers (EERE)

Beyond "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast December 7, 2012 - 10:00am Addthis The Energy Department is investing in better solar...

180

The Energy Demand Forecasting System of the National Energy Board  

Science Journals Connector (OSTI)

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

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

1980-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Forecasting Energy Demand Using Fuzzy Seasonal Time Series  

Science Journals Connector (OSTI)

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

?Irem Ual Sar?; Basar ztaysi

2012-01-01T23:59:59.000Z

182

Wind power forecasting in U.S. electricity markets.  

SciTech Connect

Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts.

Botterud, A.; Wang, J.; Miranda, V.; Bessa, R. J.; Decision and Information Sciences; INESC Porto

2010-04-01T23:59:59.000Z

183

Wind power forecasting in U.S. Electricity markets  

SciTech Connect

Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts. (author)

Botterud, Audun; Wang, Jianhui; Miranda, Vladimiro; Bessa, Ricardo J.

2010-04-15T23:59:59.000Z

184

Sandia National Laboratories: Solar Energy Forecasting and Resource...  

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

Energy, Modeling & Analysis, News, News & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource...

185

Scientist warns against overselling climate change Climate change forecasters should admit that they cannot predict how global warming will affect  

E-Print Network (OSTI)

forward on climate change, he said the data produced by models used to project weather changes risks beingScientist warns against overselling climate change Climate change forecasters should admit climate ­ with dangerous results. Related Articles Second biggest wind farm to be built off UK (/earth

Stevenson, Paul

186

Application of a Combination Forecasting Model in Logistics Parks' Demand  

Science Journals Connector (OSTI)

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

Chen Qin; Qi Ming

2010-05-01T23:59:59.000Z

187

A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION  

E-Print Network (OSTI)

in the realm of solar radiation forecasting. In this work, two forecasting models: Autoregressive Moving1 A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION. The very first results show an improvement brought by this approach. 1. INTRODUCTION Solar radiation

Boyer, Edmond

188

PSO (FU 2101) Ensemble-forecasts for wind power  

E-Print Network (OSTI)

PSO (FU 2101) Ensemble-forecasts for wind power Wind Power Ensemble Forecasting Using Wind Speed the problems of (i) transforming the meteorological ensembles to wind power ensembles and, (ii) correcting) data. However, quite often the actual wind power production is outside the range of ensemble forecast

189

Accuracy of near real time updates in wind power forecasting  

E-Print Network (OSTI)

· advantage: no NWP data necessary ­ very actual shortest term forecasts possible · wind power inputAccuracy of near real time updates in wind power forecasting with regard to different weather October 2007 #12;EMS/ECAM 2007 ­ Nadja Saleck Outline · Study site · Wind power forecasting - method

Heinemann, Detlev

190

CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE -APRIL 2014  

E-Print Network (OSTI)

CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE - APRIL 2014 Anil Puri, Ph.D. -- Director, Center for Economic Analysis and Forecasting -- Dean, Mihaylo College of Business and Economics Mira Farka, Ph.D. -- Co-Director, Center for Economic Analysis and Forecasting -- Associate Professor

de Lijser, Peter

191

Forecasting wave height probabilities with numerical weather prediction models  

E-Print Network (OSTI)

Forecasting wave height probabilities with numerical weather prediction models Mark S. Roulstona; Numerical weather prediction 1. Introduction Wave forecasting is now an integral part of operational weather methods for generating such forecasts from numerical model output from the European Centre for Medium

Stevenson, Paul

192

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

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

193

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

E-Print Network (OSTI)

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

Povinelli, Richard J.

194

Stellar Astrophysics Requirements NERSC Forecast  

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

Requirements for Requirements for m461:Stellar Explosions in Three Dimensions Tomek Plewa (Florida State University) + 3 graduate students, Artur Gawryszczak (Warsaw), Konstantinos Kifonidis (Munich), Andrzej Odrzywolek (Cracow), Ju Zhang (FIT), Andrey Zhiglo (Kharkov) 1. m461: Stellar Explosions in Three Dimensions * Summarize your projects and expected scientific objectives through 2014 * Modeling and simulations of transient phenomena in stellar astrophysics driven by either radiation or thermonuclear processes * Numerical solution of a coupled system of PDEs and ODEs * Tame nonlinearity! * Our goal is to ... * Explain observed properties of exploding stellar objects * Present focus is ... * Neutrino-driven core-collapse supernova explosions * In the next 3 years we expect to ...

195

Wind and Load Forecast Error Model for Multiple Geographically Distributed Forecasts  

SciTech Connect

The impact of wind and load forecast errors on power grid operations is frequently evaluated by conducting multi-variant studies, where these errors are simulated repeatedly as random processes based on their known statistical characteristics. To generate these errors correctly, we need to reflect their distributions (which do not necessarily follow a known distribution law), standard deviations, auto- and cross-correlations. For instance, load and wind forecast errors can be closely correlated in different zones of the system. This paper introduces a new methodology for generating multiple cross-correlated random processes to simulate forecast error curves based on a transition probability matrix computed from an empirical error distribution function. The matrix will be used to generate new error time series with statistical features similar to observed errors. We present the derivation of the method and present some experimental results by generating new error forecasts together with their statistics.

Makarov, Yuri V.; Reyes Spindola, Jorge F.; Samaan, Nader A.; Diao, Ruisheng; Hafen, Ryan P.

2010-11-02T23:59:59.000Z

196

Forecasting the Market Penetration of Energy Conservation Technologies: The Decision Criteria for Choosing a Forecasting Model  

E-Print Network (OSTI)

An important determinant of our energy future is the rate at which energy conservation technologies, once developed, are put into use. At Synergic Resources Corporation, we have adapted and applied a methodology to forecast the use of conservation...

Lang, K.

1982-01-01T23:59:59.000Z

197

Project Year Project Title  

E-Print Network (OSTI)

the cost of the project to labor only. The efficacy of the examples will be assessed through their useProject Year 2012-2013 Project Title Sight-Reading at the Piano Project Team Ken Johansen, Peabody) Faculty Statement The goal of this project is to create a bank of practice exercises that student pianists

Gray, Jeffrey J.

198

Project Year Project Team  

E-Print Network (OSTI)

design goals for this project include low cost (less than $30 per paddle) and robustness. The projectProject Year 2001 Project Team Faculty: Allison Okamura, Mechanical Engineering, Whiting School Project Title Haptic Display of Dynamic Systems Audience 30 to 40 students per year, enrolled

Gray, Jeffrey J.

199

Project Year Project Team  

E-Print Network (OSTI)

-year section of the summer project will cost $1344.) This project will be measured by the CER surveys conductedProject Year 2005 Project Team Sean Greenberg, Faculty, Philosophy Department, Krieger School of Arts & Sciences; Kevin Clark, Student, Philosophy Department, Krieger School of Arts & Sciences Project

Gray, Jeffrey J.

200

Forecasting the Locational Dynamics of Transnational Terrorism  

E-Print Network (OSTI)

Forecasting the Locational Dynamics of Transnational Terrorism: A Network Analytic Approach Bruce A-0406 Fax: (919) 962-0432 Email: skyler@unc.edu Abstract--Efforts to combat and prevent transnational terror of terrorism. We construct the network of transnational terrorist attacks, in which source (sender) and target

Massachusetts at Amherst, University of

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Do quantitative decadal forecasts from GCMs provide  

E-Print Network (OSTI)

' · Empirical models quantify our ability to predict without knowing the laws of physics · Climatology skill' model? 2. Dynamic climatology (DC) is a more appropriate benchmark for near- term (initialised) climate forecasts · A conditional climatology, initialised at launch and built from the historical archive

Stevenson, Paul

202

Sunny outlook for space weather forecasters  

Science Journals Connector (OSTI)

... For decades, companies have tailored public weather data for private customers from farmers to airlines. On Wednesday, a group of businesses said that they ... utilities and satellite operators. But Terry Onsager, a physicist at the SWPC, says that private forecasting firms are starting to realize that they can add value to these predictions. ...

Eric Hand

2012-04-27T23:59:59.000Z

203

Modeling of Uncertainty in Wind Energy Forecast  

E-Print Network (OSTI)

regression and splines are combined to model the prediction error from Tunø Knob wind power plant. This data of the thesis is quantile regression and splines in the context of wind power modeling. Lyngby, February 2006Modeling of Uncertainty in Wind Energy Forecast Jan Kloppenborg Møller Kongens Lyngby 2006 IMM-2006

204

Customized forecasting tool improves reserves estimation  

SciTech Connect

Unique producing characteristics of the Teapot sandstone formation, Powder River basin, Wyoming, necessitated the creation of individualized production forecasting methods for wells producing from this reservoir. The development and use of a set of production type curves and correlations for Teapot wells are described herein.

Mian, M.A.

1986-04-01T23:59:59.000Z

205

Storm-in-a-Box Forecasting  

Science Journals Connector (OSTI)

...But the WRF has no immediate...being tuned to local conditions...temperatures and winds with altitude...resulting WRF forecasts...captured the local sea-breeze winds better...spread the local operation of mesoscale...to be the WRF model now...

Richard A. Kerr

2004-05-14T23:59:59.000Z

206

FORECAST OF VACANCIES Until end of 2016  

E-Print Network (OSTI)

#12;FORECAST OF VACANCIES Until end of 2016 (Issue No. 22) #12;Page 2 OVERVIEW OF BASIC REQUIREMENTS FOR PROFESSIONAL VACANCIES IN THE IAEA Education, Experience and Skills: Professional staff the team of professionals. Second half 2015 VACANCY GRADE REQUIREMENTS / ROLE EXPECTED DATE OF VACANCY

207

Online short-term solar power forecasting  

SciTech Connect

This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model. (author)

Bacher, Peder; Madsen, Henrik [Informatics and Mathematical Modelling, Richard Pedersens Plads, Technical University of Denmark, Building 321, DK-2800 Lyngby (Denmark); Nielsen, Henrik Aalborg [ENFOR A/S, Lyngsoe Alle 3, DK-2970 Hoersholm (Denmark)

2009-10-15T23:59:59.000Z

208

Operational forecasting based on a modified Weather Research and Forecasting model  

SciTech Connect

Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

Lundquist, J; Glascoe, L; Obrecht, J

2010-03-18T23:59:59.000Z

209

UNCERTAINTY IN THE GLOBAL FORECAST SYSTEM  

SciTech Connect

We validated one year of Global Forecast System (GFS) predictions of surface meteorological variables (wind speed, air temperature, dewpoint temperature, air pressure) over the entire planet for forecasts extending from zero hours into the future (an analysis) to 36 hours. Approximately 12,000 surface stations world-wide were included in this analysis. Root-Mean-Square- Errors (RMSE) increased as the forecast period increased from zero to 36 hours, but the initial RMSE were almost as large as the 36 hour forecast RMSE for all variables. Typical RMSE were 3 C for air temperature, 2-3mb for sea-level pressure, 3.5 C for dewpoint temperature and 2.5 m/s for wind speed. Approximately 20-40% of the GFS errors can be attributed to a lack of resolution of local features. We attribute the large initial RMSE for the zero hour forecasts to the inability of the GFS to resolve local terrain features that often dominate local weather conditions, e.g., mountain- valley circulations and sea and land breezes. Since the horizontal resolution of the GFS (about 1{sup o} of latitude and longitude) prevents it from simulating these locally-driven circulations, its performance will not improve until model resolution increases by a factor of 10 or more (from about 100 km to less than 10 km). Since this will not happen in the near future, an alternative for the near term to improve surface weather analyses and predictions for specific points in space and time would be implementation of a high-resolution, limited-area mesoscale atmospheric prediction model in regions of interest.

Werth, D.; Garrett, A.

2009-04-15T23:59:59.000Z

210

Project Year Project Team  

E-Print Network (OSTI)

Project Year 2002 Project Team Faculty: Louise Pasternack, Chemistry Department, Krieger School, Krieger School of Arts & Sciences Project Title Introductory Chemistry Lab Demonstrations Audience an interactive virtual lab manual that will facilitate understanding of the procedures and techniques required

Gray, Jeffrey J.

211

Forecastability as a Design Criterion in Wind Resource Assessment: Preprint  

SciTech Connect

This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

Zhang, J.; Hodge, B. M.

2014-04-01T23:59:59.000Z

212

Project Year Project Team  

E-Print Network (OSTI)

(Karl) Zhang, Undergraduate Student, Biomedical Engineering, Whiting School of Engineering; Cheryl Kim Audio, Digital Video Project Abstract The goal of this project is to develop online modular units

Gray, Jeffrey J.

213

Line Projects  

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

(PDCI) Upgrade Project Whistling Ridge Energy Project Line Rebuild, Relocation and Substation Projects Wind Projects Line Projects BPA identifies critical infrastructure and...

214

Project Year Project Title  

E-Print Network (OSTI)

that incorporate video taped procedures for student preview. Solution This project will create videos for more to study the procedure and techniques before coming to class. Our previous fellowship project addressedProject Year 2009 Project Title Enhancing Biology Laboratory Preparation through Video

Gray, Jeffrey J.

215

Project Year Project Team  

E-Print Network (OSTI)

, there is no resource available to view the procedure before class. Solution The purpose of this project is to capture available to view the procedure before class. The purpose #12;of this project is to capture variousProject Year 2007 Project Team Kristina Obom, Faculty, Advanced Academic Programs, Krieger School

Gray, Jeffrey J.

216

Project Year Project Title  

E-Print Network (OSTI)

Project Year 2013-2014 Project Title German Online Placement Exam Project Team Deborah Mifflin to increased cost. As well, it lacked listening comprehension, writing and speaking components providing support, we will use Blackboard for this project. The creation will require numerous steps

Gray, Jeffrey J.

217

Project Cost Escalation Standards, document IEAB 2007-2 Page 1 Independent Economic Analysis Board  

E-Print Network (OSTI)

Project Cost Escalation Standards, document IEAB 2007-2 Page 1 Independent Economic Analysis Board Project Cost Escalation Standards Task 115 Council document IEAB 2007-2 March 30, 2007 Summary Project;Project Cost Escalation Standards, document IEAB 2007-2 Page 2 Third, managers are often asked to forecast

218

OpenEI Community - energy data + forecasting  

Open Energy Info (EERE)

FRED FRED http://en.openei.org/community/group/fred Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in formulating policies and energy plans based on easy to use forecasting tools, visualizations, sankey diagrams, and open data. The platform will live on OpenEI and this community was established to initiate discussion around continuous development of this tool, integrating it with new datasets, and connecting with the community of users who will want to contribute data to the tool and use the tool for planning purposes. energy data + forecasting Fri, 22 Jun 2012 15:30:20 +0000 Dbrodt 34

219

Voluntary Green Power Market Forecast through 2015  

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

158 158 May 2010 Voluntary Green Power Market Forecast through 2015 Lori Bird National Renewable Energy Laboratory Ed Holt Ed Holt & Associates, Inc. Jenny Sumner and Claire Kreycik National Renewable Energy Laboratory 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-6A2-48158 May 2010 Voluntary Green Power Market Forecast through 2015 Lori Bird National Renewable Energy Laboratory Ed Holt Ed Holt & Associates, Inc. Jenny Sumner and Claire Kreycik National Renewable Energy Laboratory

220

Forecasting hotspots using predictive visual analytics approach  

SciTech Connect

A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David

2014-12-30T23:59:59.000Z

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Exponential smoothing model selection for forecasting  

Science Journals Connector (OSTI)

Applications of exponential smoothing to forecasting time series usually rely on three basic methods: simple exponential smoothing, trend corrected exponential smoothing and a seasonal variation thereof. A common approach to selecting the method appropriate to a particular time series is based on prediction validation on a withheld part of the sample using criteria such as the mean absolute percentage error. A second approach is to rely on the most appropriate general case of the three methods. For annual series this is trend corrected exponential smoothing: for sub-annual series it is the seasonal adaptation of trend corrected exponential smoothing. The rationale for this approach is that a general method automatically collapses to its nested counterparts when the pertinent conditions pertain in the data. A third approach may be based on an information criterion when maximum likelihood methods are used in conjunction with exponential smoothing to estimate the smoothing parameters. In this paper, such approaches for selecting the appropriate forecasting method are compared in a simulation study. They are also compared on real time series from the M3 forecasting competition. The results indicate that the information criterion approaches provide the best basis for automated method selection, the Akaike information criteria having a slight edge over its information criteria counterparts.

Baki Billah; Maxwell L. King; Ralph D. Snyder; Anne B. Koehler

2006-01-01T23:59:59.000Z

222

Solar Wind Forecasting with Coronal Holes  

E-Print Network (OSTI)

An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang-Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best one-month periods, and it has a linear correlation coefficient of ~0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.

S. Robbins; C. J. Henney; J. W. Harvey

2007-01-09T23:59:59.000Z

223

Evaluation of artificial neural networks as a model for forecasting consumption of wood products  

Science Journals Connector (OSTI)

In specific sciences, such as forest policy, the need for anticipation becomes more urgent because it has to manage valuable natural resources whose protection and sustainable management is rendered essential. In this paper, a modern method has been used, known as artificial neural networks (ANNs). In order to forecast the necessary future volumes of timber in Greece, a neural network has been developed and trained, using a variety of time series derived from the database of the Food and Agriculture Organisation of the United Nations (FAO) (concerning Greece) as external values and as internal value the Consumer Price Index has been used. Comparing the results of this project with linear and non-linear econometric forecasting models, it has been found that neural networks correspond, as confirmed by the econometric indicators MAPE (average absolute percentage error) and RMSE (the square root of the percentage by the average sum of squares differences).

Giorgos Tigas; Panagiotis Lefakis; Konstantinos Ioannou; Athanasios Hasekioglou

2013-01-01T23:59:59.000Z

224

Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint  

SciTech Connect

Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The results show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.

Zhang, J.; Hodge, B. M.; Florita, A.; Lu, S.; Hamann, H. F.; Banunarayanan, V.

2013-10-01T23:59:59.000Z

225

Projectivities and Projective Embeddings  

Science Journals Connector (OSTI)

In this chapter, we aim to prove some of the main achievements in the theory of generalized polygons. First, we want to show what the little projective group and the groups of projectivities of some Moufang po...

Hendrik van Maldeghem

1998-01-01T23:59:59.000Z

226

Project Overview  

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

Questions Keeler-Pennwalt Wood Pole Removal Line Projects Line Rebuild, Relocation and Substation Projects Spacer Damper Replacement Program Wind Projects Project Overview BPA...

227

Babson Capital/UNC Charlotte Economic Forecast  

E-Print Network (OSTI)

with a projected real increase of 6.1 percent; Hospitality and Leisure Services with a projected real increase of 4.2 percent; and Educational and Heath Services with a projected real increase of 3.8 percent. · For 2012. The sectors with the strongest expected growth are Educational and Health Services with a projected real

Chen, Keh-Hsun

228

Project Year Project Title  

E-Print Network (OSTI)

operators, matrix indexing, vector computations, loops, functions, and plotting graphs, among others basic arithmetic operators, matrix indexing, and vector computations in MATLAB. After creatingProject Year 2011-2012 Project Title Online Tutorial for MATLAB Project Team Eileen Haase, Whiting

Gray, Jeffrey J.

229

Project Year Project Team  

E-Print Network (OSTI)

Project Year 2005 Project Team Krysia Hudson, Faculty, School of Nursing, Undergraduate Instruction for Educational Resources Project Title Enhanced Web-based Learning Environments for Beginning Nursing Students (e.g., demonstrations of procedures or tasks) into the WBL systems, it will be possible to increase

Gray, Jeffrey J.

230

Project Year Project Team  

E-Print Network (OSTI)

Project Year 2002 Project Team Faculty: Michael McCloskey, Cognitive Science/Neuroscience, Krieger of Arts & Sciences Project Title Cognitive Neuropsychology Audience The initial audience to access. The current procedure calls for individual students or researchers to contact the faculty member

Gray, Jeffrey J.

231

Project Year Project Title  

E-Print Network (OSTI)

Project Year 2011-2012 Project Title Using M-Health and GIS Technology in the Field to Improve into teams and having each team use a different m-health data collection tool (e.g., cellular phones, smart health patterns. The Tech Fellow, Jacqueline Ferguson, will assist in creating an m-health project

Gray, Jeffrey J.

232

Project Year Project Team  

E-Print Network (OSTI)

Project Year 2002 Project Team Faculty: Gregory Hager, Computer Science, Whiting School of Engineering Fellow: Alan Chen, Biomedical Engineering, Whiting School of Engineering Project Title Robotics is complicated, time-consuming, and costly, making a robot for an introductory-level class is not practical

Gray, Jeffrey J.

233

Project Proposal Project Logistics  

E-Print Network (OSTI)

Project Proposal · Project Logistics: ­ 2-3 person teams ­ Significant implementation, worth 55 and anticipated cost of copying to/from host memory. IV. Intellectual Challenges - Generally, what makes this computation worthy of a project? - Point to any difficulties you anticipate at present in achieving high

Hall, Mary W.

234

Electric Grid - Forecasting system licensed | ornl.gov  

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

Electric Grid - Forecasting system licensed Location Based Technologies has signed an agreement to integrate and market an Oak Ridge National Laboratory technology that provides...

235

Managing Wind Power Forecast Uncertainty in Electric Grids.  

E-Print Network (OSTI)

??Electricity generated from wind power is both variable and uncertain. Wind forecasts provide valuable information for wind farm management, but they are not perfect. Chapter (more)

Mauch, Brandon Keith

2012-01-01T23:59:59.000Z

236

Forecasting supply/demand and price of ethylene feedstocks  

SciTech Connect

The history of the petrochemical industry over the past ten years clearly shows that forecasting in a turbulent world is like trying to predict tomorrow's headlines.

Struth, B.W.

1984-08-01T23:59:59.000Z

237

PBL FY 2003 Third Quarter Review Forecast of Generation Accumulated...  

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

for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net Cost Recovery Adjustment Clause (SN CRAC) FY 2003 Third Quarter Review Forecast in Millions...

238

FY 2004 Second Quarter Review Forecast of Generation Accumulated...  

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

for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net Cost Recovery Adjustment Clause (SN CRAC) FY 2004 Second Quarter Review Forecast In Millions...

239

Integrating agricultural pest biocontrol into forecasts of energy biomass production  

E-Print Network (OSTI)

Analysis Integrating agricultural pest biocontrol into forecasts of energy biomass production T pollution, greenhouse gas emissions, and soil erosion (Nash, 2007; Searchinger et al., 2008). On the other

Gratton, Claudio

240

Forecasting for inventory control with exponential smoothing  

Science Journals Connector (OSTI)

Exponential smoothing, often used in sales forecasting for inventory control, has always been rationalized in terms of statistical models that possess errors with constant variances. It is shown in this paper that exponential smoothing remains appropriate under more general conditions, where the variance is allowed to grow or contract with corresponding movements in the underlying level. The implications for estimation and prediction are explored. In particular, the problem of finding the predictive distribution of aggregate lead-time demand, for use in inventory control calculations, is considered using a bootstrap approach. A method for establishing order-up-to levels directly from the simulated predictive distribution is also explored.

Ralph D. Snyder; Anne B. Koehler; J.Keith Ord

2002-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Probabilistic Verification of Global and Mesoscale Ensemble Forecasts of Tropical Cyclogenesis  

Science Journals Connector (OSTI)

Probabilistic forecasts of tropical cyclogenesis have been evaluated for two samples: a near-homogeneous sample of ECMWF and Weather Research and Forecasting (WRF) Modelensemble Kalman filter (EnKF) ensemble forecasts during the National Science ...

Sharanya J. Majumdar; Ryan D. Torn

2014-10-01T23:59:59.000Z

242

FORSITE, a multiple-project management system: overview and general description  

SciTech Connect

The Geothermal Site Development Forecasting System (FORSITE) is a computer-based multiproject monitoring, scheduling, and forecasting system. Its main purpose is to assist DOE geothermal program managers in monitoring the progress of multiple geothermal electric exploration and construction projects. The system actively combines conceptual project development schedules with site-specific status data to predict a time-phased sequence of development likely to occur at multiple specific geothermal sites. The forecasting capabilities of the model include estimation of industry costs and federal manpower requirements across sites on a year-by-year basis.

Entingh, D.J.; Bernstein, A.J.; Gerstein, R.E.; Kenkeremath, L.D.; Gould, A.V.

1982-10-01T23:59:59.000Z

243

2011 Project Management Workshop | Department of Energy  

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

Project Management Workshop Project Management Workshop 2011 Project Management Workshop 2011 DOE Project Management Workshop Paul Bosco, The New DOE O 413.3B Jeff Baker, EERE's Research Support Facility Patrick Ferraro, Contract Management/ Project Management Summit Outbrief Anirban Basu, Construction Economic Forecast John Curran, LED Lighting Michael Deane, Construction and Demolition Debris Recycle Mark Fallon, Leadership & Safety Cost Estimating Panel, The Science and Art of Cost Estimating Tom Fox, Leading in Tough Times Bob Raines, Project Management Update Tony Cannon, Nuclear Quality Assurance Issues Peer Review Panel, Peer Reviews 101 Terry Cooke-Davies, Project Complexity Rod Rimando, EM Project Management Framework PMCDP Panel, PMCDP CRB CRB Panel Questions & Answers Chad Henderson, FPD's Perspective

244

Random switching exponential smoothing and inventory forecasting  

Science Journals Connector (OSTI)

Abstract Exponential smoothing models represent an important prediction tool both in business and in macroeconomics. This paper provides the analytical forecasting properties of the random coefficient exponential smoothing model in the multiple source of error framework. The random coefficient state-space representation allows for switching between simple exponential smoothing and local linear trend. Therefore it enables controlling, in a flexible manner, the random changing dynamic behavior of the time series. The paper establishes the algebraic mapping between the state-space parameters and the implied reduced form ARIMA parameters. In addition, it shows that the parametric mapping allows overcoming the difficulties that are likely to emerge in estimating directly the random coefficient state-space model. Finally, it presents an empirical application comparing the forecast accuracy of the suggested model vis--vis other benchmark models, both in the ARIMA and in the exponential smoothing class. Using time series relative to wholesalers inventories in the USA, the out-of-sample results show that the reduced form of the random coefficient exponential smoothing model tends to be superior to its competitors.

Giacomo Sbrana; Andrea Silvestrini

2014-01-01T23:59:59.000Z

245

Expert Panel: Forecast Future Demand for Medical Isotopes  

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

Expert Panel: Expert Panel: Forecast Future Demand for Medical Isotopes March 1999 Expert Panel: Forecast Future Demand for Medical Isotopes September 25-26, 1998 Arlington, Virginia The Expert Panel ............................................................................................. Page 1 Charge To The Expert Panel........................................................................... Page 2 Executive Summary......................................................................................... Page 3 Introduction ...................................................................................................... Page 4 Rationale.......................................................................................................... Page 6 Economic Analysis...........................................................................................

246

A robust automatic phase-adjustment method for financial forecasting  

Science Journals Connector (OSTI)

In this work we present the robust automatic phase-adjustment (RAA) method to overcome the random walk dilemma for financial time series forecasting. It consists of a hybrid model composed of a qubit multilayer perceptron (QuMLP) with a quantum-inspired ... Keywords: Financial forecasting, Hybrid models, Quantum-inspired evolutionary algorithm, Qubit multilayer perceptron, Random walk dilemma

Ricardo de A. Arajo

2012-03-01T23:59:59.000Z

247

Short term forecasting of solar radiation based on satellite data  

E-Print Network (OSTI)

Short term forecasting of solar radiation based on satellite data Elke Lorenz, Annette Hammer University, D-26111 Oldenburg Forecasting of solar irradiance will become a major issue in the future integration of solar energy resources into existing energy supply structures. Fluctuations of solar irradiance

Heinemann, Detlev

248

Developing electricity forecast web tool for Kosovo market  

Science Journals Connector (OSTI)

In this paper is presented a web tool for electricity forecast for Kosovo market for the upcoming ten years. The input data i.e. electricity generation capacities, demand and consume are taken from the document "Kosovo Energy Strategy 2009-2018" compiled ... Keywords: .NET, database, electricity forecast, internet, simulation, web

Blerim Rexha; Arben Ahmeti; Lule Ahmedi; Vjollca Komoni

2011-02-01T23:59:59.000Z

249

FORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS  

E-Print Network (OSTI)

resources resulting in water stress. Effective water management ­ a solution Supply side management Demand side management #12;Developing a regression equation based on cluster analysis for forecasting waterFORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS by Bruce Bishop Professor of Civil

Keller, Arturo A.

250

Impact of PV forecasts uncertainty in batteries management in microgrids  

E-Print Network (OSTI)

production forecast algorithm is used in combination with a battery schedule optimisation algorithm. The size. On the other hand if forecasted high production events do not occur, the cost of de- optimisation Energies and Energy Systems Sophia Antipolis, France andrea.michiorri@mines-paristech.fr Abstract

Paris-Sud XI, Université de

251

Revised 1997 Retail Electricity Price Forecast Principal Author: Ben Arikawa  

E-Print Network (OSTI)

Revised 1997 Retail Electricity Price Forecast March 1998 Principal Author: Ben Arikawa Electricity 1997 FORE08.DOC Page 1 CALIFORNIA ENERGY COMMISSION ELECTRICITY ANALYSIS OFFICE REVISED 1997 RETAIL ELECTRICITY PRICE FORECAST Introduction The Electricity Analysis Office of the California Energy Commission

252

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center  

E-Print Network (OSTI)

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at wind energy sites are becoming paramount. Regime-switching space-time (RST) models merge meteorological forecast regimes at the wind energy site and fits a conditional predictive model for each regime

Washington at Seattle, University of

253

A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size  

E-Print Network (OSTI)

A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size Andrew. R.Lawrence@ecmwf.int #12;Abstract An ensemble-based data assimilation approach is used to transform old en- semble. The impact of the transformations are propagated for- ward in time over the ensemble's forecast period

Hansens, Jim

254

Improving baseline forecasts in a 500-industry dynamic CGE model of the USA.  

E-Print Network (OSTI)

??MONASH-style CGE models have been used to generate baseline forecasts illustrating how an economy is likely to evolve through time. One application of such forecasts (more)

Mavromatis, Peter George

2013-01-01T23:59:59.000Z

255

E-Print Network 3.0 - africa conditional forecasts Sample Search...  

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

Search Powered by Explorit Topic List Advanced Search Sample search results for: africa conditional forecasts Page: << < 1 2 3 4 5 > >> 1 COLORADO STATE UNIVERSITY FORECAST...

256

Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA  

SciTech Connect

In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of forecasts. We use automatically coupled wavelet transform and autoregressive integrated moving-average (ARIMA) forecasting to reflect multi-scale variability of forecast errors. The proposed analysis reveals slow-changing quasi-deterministic components of forecast errors. This helps improve forecasts produced by other means, e.g., using weather-based models, and reduce forecast errors prediction intervals.

Hou, Zhangshuan; Etingov, Pavel V.; Makarov, Yuri V.; Samaan, Nader A.

2014-10-27T23:59:59.000Z

257

Annual Energy Outlook with Projections to 2025  

Gasoline and Diesel Fuel Update (EIA)

4 with Projections to 2025 4 with Projections to 2025 Report #: DOE/EIA-0383(2004) Release date: January 2004 Next release date: January 2005 Errata August 25, 2004 The Annual Energy Outlook presents a midterm forecast and analysis of US energy supply, demand, and prices through 2025 Table of Contents Summary Tables Adobe Acrobat Logo Yearly Tables MS Excel Viewer Regional and other detailed tables (Supplemental) MS Excel Viewer Overview Market Drivers Trends in Economic Activity Economic Growth Cases International Oil Markets Energy Demand Projections Residential Sector Commercial Sector Industrial Sector Transportation Sector Alternative Technology Cases Electricity Forecast Electricity Sales Electricity Generating Capacity Electricity Fuel Costs and Prices Electricity from Nuclear Power

258

On the forecasting of the challenging world future scenarios  

Science Journals Connector (OSTI)

Logistic and power law methodologies for both retrospective and prospective analyses of extended time series describing evolutionary growth processes, in environments with finite resources, are confronted. While power laws may eventually apply only to the early stages of said growth process, the Allee logistic model seems applicable over the entire span of a long range process. On applying the Allee logistic model to both the world population and the world gross domestic product time series, from 1 to 2008AD, a projection was obtained that along the next few decades the world should experience a new economic boom phase with the world GDP peaking around the year 2020 and proceeding from then on towards a saturation value of about 142trillion international dollars, while the world population should reach 8.9billion people by 2050. These results were then used to forecast the behavior of the supply and consumption of energy and food, two of the main commodities that drive the world system. Our findings suggest that unless the currently prevailing focus on economic growth is changed into that of sustainable prosperity, human society may run into a period of serious economical and social struggles with unpredictable political consequences.

Luiz C.M. Miranda; C.A.S. Lima

2011-01-01T23:59:59.000Z

259

Solid waste integrated forecast technical (SWIFT) report: FY1997 to FY 2070, Revision 1  

SciTech Connect

This web site provides an up-to-date report on the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the WM Project; program-level and waste class-specific estimates; background information on waste sources; and comparisons with previous forecasts and with other national data sources. This web site does not include: liquid waste (current or future generation); waste to be managed by the Environmental Restoration (EM-40) contractor (i.e., waste that will be disposed of at the Environmental Restoration Disposal Facility (ERDF)); or waste that has been received by the WM Project to date (i.e., inventory waste). The focus of this web site is on low-level mixed waste (LLMW), and transuranic waste (both non-mixed and mixed) (TRU(M)). Some details on low-level waste and hazardous waste are also provided. Currently, this web site is reporting data th at was requested on 10/14/96 and submitted on 10/25/96. The data represent a life cycle forecast covering all reported activities from FY97 through the end of each program's life cycle. Therefore, these data represent revisions from the previous FY97.0 Data Version, due primarily to revised estimates from PNNL. There is some useful information about the structure of this report in the SWIFT Report Web Site Overview.

Valero, O.J.; Templeton, K.J.; Morgan, J.

1997-01-07T23:59:59.000Z

260

Probabilistic 0-12 h forecasts of (severe) thunderstorms in the Netherlands Maurice Schmeits (schmeits@knmi.nl), Kees Kok, Daan Vogelezang and Rudolf van Westrhenen  

E-Print Network (OSTI)

Probabilistic 0-12 h forecasts of (severe) thunderstorms in the Netherlands Maurice Schmeits (schmeits@knmi.nl), Kees Kok, Daan Vogelezang and Rudolf van Westrhenen Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands In this project the technique of Model Output Statistics (MOS)1

Schmeits, Maurice

Note: This page contains sample records for the topic "interindustry forecasting project" 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

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

Gasoline and Diesel Fuel Update (EIA)

Analysis & Projections Analysis & Projections Glossary › FAQS › Overview Projection Data Monthly Short-Term Forecasts to 2014 Annual Projections to 2040 International Projections Analysis & Projections Most Requested Annual Energy Outlook Related Congressional & Other Requests International Energy Outlook Related Presentations Short-Term Outlook Related Testimony All Reports Models & Documentation Full report Fuel Competition in Power Generation and Elasticities of Substitution Release date: June 2012 This report analyzes the competition between coal, natural gas and petroleum used for electricity generation by estimating what is referred to by economists as the elasticity of substitution among the fuels. The elasticity of substitution concept measures how the use of these fuels

262

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

Gasoline and Diesel Fuel Update (EIA)

Most Requested Most Requested Change category... Most Requested Annual Energy Outlook Related Congressional & Other Requests International Energy Outlook Related Presentations Short-Term Outlook Related Testimony All Reports Filter by: All Data Analysis Projections Weekly Reports Today in Energy - Projections Short, timely articles with graphs about recent analyses and projections. Monthly Reports Short-Term Energy Outlook Released: January 7, 2014 Short-term energy supply, demand, and price projections through 2013 for U.S. and International oil forecasts (archived versions) Archived Versions Short-Term Energy Outlook Feature Articles - Archive Short-Term Energy Outlook - Archive Short-Term Energy Outlook Annual Supplement Released: January 27, 2011

263

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Contacts Contacts The International Energy Outlook is prepared by the Energy Information Administration (EIA). General questions concerning the contents of the report should be referred to John J. Conti (john.conti@eia.doe.gov, 202-586-2222), Director, Office of Integrated Analysis and Forecasting. Specific questions about the report should be referred to Linda E. Doman (202/586-1041) or the following analysts: World Energy and Economic Outlook Linda Doman (linda.doman@eia.doe.gov, 202-586-1041) Macroeconomic Assumptions Nasir Khilji (nasir.khilji@eia.doe.gov, 202-586-1294) Energy Consumption by End-Use Sector Residential Energy Use John Cymbalsky (john.cymbalsky@eia.doe.gov, 202-586-4815) Commercial Energy Use Erin Boedecker (erin.boedecker@eia.doe.gov, 202-586-4791)

264

Volatility forecasting with smooth transition exponential smoothing  

Science Journals Connector (OSTI)

Adaptive exponential smoothing methods allow smoothing parameters to change over time, in order to adapt to changes in the characteristics of the time series. This paper presents a new adaptive method for predicting the volatility in financial returns. It enables the smoothing parameter to vary as a logistic function of user-specified variables. The approach is analogous to that used to model time-varying parameters in smooth transition generalised autoregressive conditional heteroskedastic (GARCH) models. These non-linear models allow the dynamics of the conditional variance model to be influenced by the sign and size of past shocks. These factors can also be used as transition variables in the new smooth transition exponential smoothing (STES) approach. Parameters are estimated for the method by minimising the sum of squared deviations between realised and forecast volatility. Using stock index data, the new method gave encouraging results when compared to fixed parameter exponential smoothing and a variety of GARCH models.

James W. Taylor

2004-01-01T23:59:59.000Z

265

Incorporating Forecast Uncertainty in Utility Control Center  

SciTech Connect

Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)

Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian

2014-07-09T23:59:59.000Z

266

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

Table 1. Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Table 1. Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Average Absolute Percent Error Variable AEO82 to AEO98 AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 Consumption Total Energy Consumption 1.7 1.7 1.8 1.9 1.9 2.1 Total Petroleum Consumption 2.9 2.8 2.9 3.0 2.9 2.9 Total Natural Gas Consumption 5.7 5.6 5.6 5.5 5.5 6.5 Total Coal Consumption 3.0 3.2 3.3 3.5 3.6 3.7 Total Electricity Sales 1.7 1.8 1.9 2.4 2.5 2.4 Production Crude Oil Production 4.3 4.5 4.5 4.5 4.5 4.7 Natural Gas Production 4.8 4.7 4.6 4.6 4.4 4.4 Coal Production 3.6 3.6 3.5 3.7 3.6 3.8 Imports and Exports Net Petroleum Imports 9.5 8.8 8.4 7.9 7.4 7.5 Net Natural Gas Imports 16.7 16.0 15.9 15.8 15.8 15.4

267

Coal production forecast and low carbon policies in China  

Science Journals Connector (OSTI)

With rapid economic growth and industrial expansion, China consumes more coal than any other nation. Therefore, it is particularly crucial to forecast China's coal production to help managers make strategic decisions concerning China's policies intended to reduce carbon emissions and concerning the country's future needs for domestic and imported coal. Such decisions, which must consider results from forecasts, will have important national and international effects. This article proposes three improved forecasting models based on grey systems theory: the Discrete Grey Model (DGM), the Rolling DGM (RDGM), and the p value RDGM. We use the statistical data of coal production in China from 1949 to 2005 to validate the effectiveness of these improved models to forecast the data from 2006 to 2010. The performance of the models demonstrates that the p value RDGM has the best forecasting behaviour over this historical time period. Furthermore, this paper forecasts coal production from 2011 to 2015 and suggests some policies for reducing carbon and other emissions that accompany the rise in forecasted coal production.

Jianzhou Wang; Yao Dong; Jie Wu; Ren Mu; He Jiang

2011-01-01T23:59:59.000Z

268

Project Year Project Team  

E-Print Network (OSTI)

; Ian Sims, Student, Electrical and Computer Engineering, Whiting School of Engineering Project Title and Jazz Theory/Keyboard I & II. Technologies Used Digital Audio, Digital Video, Graphic Design, HTML

Gray, Jeffrey J.

269

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect

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

270

Comparison of AEO 2005 natural gas price forecast to NYMEX futures prices  

SciTech Connect

On December 9, the reference case projections from ''Annual Energy Outlook 2005 (AEO 2005)'' were posted on the Energy Information Administration's (EIA) web site. As some of you may be aware, we at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk. As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past four years, forward natural gas contracts (e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past four years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation (presuming that long-term price stability is valued). In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2005. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or, more recently (and briefly), http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past four AEO releases (AEO 2001-AE0 2004), we once again find that the AEO 2005 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEXAEO 2005 reference case comparison yields by far the largest premium--$1.11/MMBtu levelized over six years--that we have seen over the last five years. In other words, on average, one would have to pay $1.11/MMBtu more than the AEO 2005 reference case natural gas price forecast in order to lock in natural gas prices over the coming six years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation. Fixed-price renewables obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of six years.

Bolinger, Mark; Wiser, Ryan

2004-12-13T23:59:59.000Z

271

Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX FuturesPrices  

SciTech Connect

On December 5, 2006, the reference case projections from 'Annual Energy Outlook 2007' (AEO 2007) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past six years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past six years at least, levelized cost comparisons of fixed-price renewable generation with variable-price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are 'biased' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2007. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past six AEO releases (AEO 2001-AEO 2006), we once again find that the AEO 2007 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. Specifically, the NYMEX-AEO 2007 premium is $0.73/MMBtu levelized over five years. In other words, on average, one would have had to pay $0.73/MMBtu more than the AEO 2007 reference case natural gas price forecast in order to lock in natural gas prices over the coming five years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation (or other forms of generation whose costs are not tied to the price of natural gas). Fixed-price generation (like certain forms of renewable generation) obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of five years.

Bolinger, Mark; Wiser, Ryan

2006-12-06T23:59:59.000Z

272

Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX FuturesPrices  

SciTech Connect

On December 12, 2005, the reference case projections from ''Annual Energy Outlook 2006'' (AEO 2006) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past five years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past five years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2006. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past five AEO releases (AEO 2001-AEO 2005), we once again find that the AEO 2006 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEX-AEO 2006 reference case comparison yields by far the largest premium--$2.3/MMBtu levelized over five years--that we have seen over the last six years. In other words, on average, one would have had to pay $2.3/MMBtu more than the AEO 2006 reference case natural gas price forecast in order to lock in natural gas prices over the coming five years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation (or other forms of generation whose costs are not tied to the price of natural gas). Fixed-price generation (like certain forms of renewable generation) obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of five years.

Bolinger, Mark; Wiser, Ryan

2005-12-19T23:59:59.000Z

273

Measuring the forecasting accuracy of models: evidence from industrialised countries  

Science Journals Connector (OSTI)

This paper uses the approach suggested by Akrigay (1989), Tse and Tung (1992) and Dimson and Marsh (1990) to examine the forecasting accuracy of stock price index models for industrialised markets. The focus of this paper is to compare the Mean Absolute Percentage Error (MAPE) of three models, that is, the Random Walk model, the Single Exponential Smoothing model and the Conditional Heteroskedastic model with the MAPE of the benchmark Naive Forecast 1 case. We do not evidence that a single model to provide better forecasting accuracy results compared to other models.

Athanasios Koulakiotis; Apostolos Dasilas

2009-01-01T23:59:59.000Z

274

Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty  

E-Print Network (OSTI)

Solar irradiance data . . . . . . . . . . . . .Accuracy . . . . . . . . . . . . . . . . . Solar Resourcev Uncertainty In Solar Resource: Forecasting

Marquez, Ricardo

2012-01-01T23:59:59.000Z

275

18 Bureau of Meteorology Annual Report 201314 Hazards, warnings and forecasts  

E-Print Network (OSTI)

and numerical prediction models. #12;19Bureau of Meteorology Annual Report 2013­14 2 Performance Performance programs: · Weather forecasting services; · Flood forecasting and warning services; · Hazard prediction, Warnings and Forecasts portfolio provides a range of forecast and warning services covering weather, ocean

Greenslade, Diana

276

Annual Energy Outlook with Projections to 2025-Homepage  

Gasoline and Diesel Fuel Update (EIA)

Legislation & Regulations Overview Issues in Focus Economic Market Trends Energy Demand Market Trends Electricity and Renewable Market Trends Oil and Natural Gas Market Trends Coal Market Trnds Forecast Comparisons Emissions Market Trends Additional Links Preface Major Assumptions for the Forecasts Summary of the AEO2003 Cases Acronyms The projections in AEO2002 are not statements of what will happen but of what might happen, given the assumptions and methodologies used. The projections are business-as-usual trend forecasts, given known technology, technological and demographic trends, and current laws and regulations. Thus, they provide a policy-neutral reference case that can be used to analyze policy initiatives. EIA does not propose, advocate, or speculate on

277

Project Fact Sheet Project Brief  

E-Print Network (OSTI)

Project Fact Sheet Project Brief: Construction Project Team: Project Facts & Figures: Budget: £1.1M Funding Source: Departmental Construction Project Programme: Start on Site: November 2010 End Date : March 2011 Occupation Date: March 2011 For further information contact Project Manager as listed above

278

Project Fact Sheet Project Update  

E-Print Network (OSTI)

Project Fact Sheet Project Update: Project Brief: The works cover the refurbishment of floors 4, 5 operating theatre. The Bionanotechnology Centre is one of the projects funded from the UK Government's £20.imperial.ac.uk/biomedeng Construction Project Team: Project Facts & Figures: Budget: £13,095,963 Funding Source: SRIF II and Capital

279

Project Fact Sheet Project Brief  

E-Print Network (OSTI)

Project Fact Sheet Project Brief: This project refurbished half of the 5th and 7th floors on the Faculty of Medicine, please visit: http://www1.imperial.ac.uk/medicine/ Construction Project Team: Project Facts & Figures: Budget: £3,500,000 Funding Source: SRIF III Construction Project Programme: Start

280

Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory  

Gasoline and Diesel Fuel Update (EIA)

Forecasting Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels MICHAEL YE, ∗ JOHN ZYREN, ∗∗ AND JOANNE SHORE ∗∗ Abstract This paper presents a short-term monthly forecasting model of West Texas Intermedi- ate crude oil spot price using OECD petroleum inventory levels. Theoretically, petroleum inventory levels are a measure of the balance, or imbalance, between petroleum production and demand, and thus provide a good market barometer of crude oil price change. Based on an understanding of petroleum market fundamentals and observed market behavior during the post-Gulf War period, the model was developed with the objectives of being both simple and practical, with required data readily available. As a result, the model is useful to industry and government decision-makers in forecasting price and investigat- ing the impacts of changes on price, should inventories,

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Adaptive sampling and forecasting with mobile sensor networks  

E-Print Network (OSTI)

This thesis addresses planning of mobile sensor networks to extract the best information possible out of the environment to improve the (ensemble) forecast at some verification region in the future. To define the information ...

Choi, Han-Lim

2009-01-01T23:59:59.000Z

282

Pacific Adaptation Strategy Assistance Program Dynamical Seasonal Forecasting  

E-Print Network (OSTI)

Pacific Adaptation Strategy Assistance Program Dynamical Seasonal Forecasting Seasonal Prediction · POAMA · Issues for future Outline #12;Pacific Adaptation Strategy Assistance Program Major source Adaptation Strategy Assistance Program El Nino Mean State · Easterlies westward surface current upwelling

Lim, Eun-pa

283

Forecasting Volatility in Stock Market Using GARCH Models  

E-Print Network (OSTI)

Forecasting volatility has held the attention of academics and practitioners all over the world. The objective for this master's thesis is to predict the volatility in stock market by using generalized autoregressive ...

Yang, Xiaorong

2008-01-01T23:59:59.000Z

284

Exponential smoothing with covariates applied to electricity demand forecast  

Science Journals Connector (OSTI)

Exponential smoothing methods are widely used as forecasting techniques in industry and business. Their usual formulation, however, does not allow covariates to be used for introducing extra information into the forecasting process. In this paper, we analyse an extension of the exponential smoothing formulation that allows the use of covariates and the joint estimation of all the unknowns in the model, which improves the forecasting results. The whole procedure is detailed with a real example on forecasting the daily demand for electricity in Spain. The time series of daily electricity demand contains two seasonal patterns: here the within-week seasonal cycle is modelled as usual in exponential smoothing, while the within-year cycle is modelled using covariates, specifically two harmonic explanatory variables. Calendar effects, such as national and local holidays and vacation periods, are also introduced using covariates. [Received 28 September 2010; Revised 6 March 2011, 2 October 2011; Accepted 16 October 2011

José D. Bermúdez

2013-01-01T23:59:59.000Z

285

Initial conditions estimation for improving forecast accuracy in exponential smoothing  

Science Journals Connector (OSTI)

In this paper we analyze the importance of initial conditions in exponential smoothing models on forecast errors and prediction intervals. We work with certain exponential smoothing models, namely Holts additive...

E. Vercher; A. Corbern-Vallet; J. V. Segura; J. D. Bermdez

2012-07-01T23:59:59.000Z

286

A Bayesian approach to forecast intermittent demand for seasonal products  

Science Journals Connector (OSTI)

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

Mohammad Anwar Rahman; Bhaba R. Sarker

2012-01-01T23:59:59.000Z

287

Review/Verify Strategic Skills Needs/Forecasts/Future Mission...  

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

ReviewVerify Strategic Skills NeedsForecastsFuture Mission Shifts Annual Lab Plan (1-10 yrs) Fermilab Strategic Agenda (2-5 yrs) Sector program Execution Plans (1-3...

288

A Parameter for Forecasting Tornadoes Associated with Landfalling Tropical Cyclones  

Science Journals Connector (OSTI)

The authors develop a statistical guidance product, the tropical cyclone tornado parameter (TCTP), for forecasting the probability of one or more tornadoes during a 6-h period that are associated with landfalling tropical cyclones affecting the ...

Matthew J. Onderlinde; Henry E. Fuelberg

2014-10-01T23:59:59.000Z

289

Wind Power Forecasting: State-of-the-Art 2009  

E-Print Network (OSTI)

Wind Power Forecasting: State-of-the-Art 2009 ANL/DIS-10-1 Decision and Information Sciences about Argonne and its pioneering science and technology programs, see www.anl.gov. #12;Wind Power

Kemner, Ken

290

2007 National Hurricane Center Forecast Verification Report James L. Franklin  

E-Print Network (OSTI)

storms 17 4. Genesis Forecasts 17 5. Summary and Concluding Remarks 18 a. Atlantic Summary 18 statistical models, provided the best intensity guidance at each time period. The 2007 season marked the first

291

Recently released EIA report presents international forecasting data  

SciTech Connect

This report presents information from the Energy Information Administration (EIA). Articles are included on international energy forecasting data, data on the use of home appliances, gasoline prices, household energy use, and EIA information products and dissemination avenues.

NONE

1995-05-01T23:59:59.000Z

292

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network (OSTI)

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

293

Information-Based Skill Scores for Probabilistic Forecasts  

Science Journals Connector (OSTI)

The information content, that is, the predictive capability, of a forecast system is often quantified with skill scores. This paper introduces two ranked mutual information skill (RMIS) scores, RMISO and RMISY, for the evaluation of probabilistic ...

Bodo Ahrens; Andr Walser

2008-01-01T23:59:59.000Z

294

A methodology for forecasting carbon dioxide flooding performance  

E-Print Network (OSTI)

A methodology was developed for forecasting carbon dioxide (CO2) flooding performance quickly and reliably. The feasibility of carbon dioxide flooding in the Dollarhide Clearfork "AB" Unit was evaluated using the methodology. This technique is very...

Marroquin Cabrera, Juan Carlos

2012-06-07T23:59:59.000Z

295

Evolutionary Optimization of an Ice Accretion Forecasting System  

Science Journals Connector (OSTI)

The ability to model and forecast accretion of ice on structures is very important for many industrial sectors. For example, studies conducted by the power transmission industry indicate that the majority of failures are caused by icing on ...

Pawel Pytlak; Petr Musilek; Edward Lozowski; Dan Arnold

2010-07-01T23:59:59.000Z

296

Diagnosing the Origin of Extended-Range Forecast Errors  

Science Journals Connector (OSTI)

Experiments with the ECMWF model are carried out to study the influence that a correct representation of the lower boundary conditions, the tropical atmosphere, and the Northern Hemisphere stratosphere would have on extended-range forecast skill ...

T. Jung; M. J. Miller; T. N. Palmer

2010-06-01T23:59:59.000Z

297

Application of an Improved SVM Algorithm for Wind Speed Forecasting  

Science Journals Connector (OSTI)

An improved Support Vector Machine (SVM) algorithm is used to forecast wind in Doubly Fed Induction Generator (DFIG) wind power system without aerodromometer. The ... Validation (CV) method. Finally, 3.6MW DFIG w...

Huaqiang Zhang; Xinsheng Wang; Yinxiao Wu

2011-01-01T23:59:59.000Z

298

Research on Development Trends of Power Load Forecasting Methods  

Science Journals Connector (OSTI)

In practical problem, number of samples is often limited, for complex issues such as power load forecasting, generally available historical data and information of impact factor are very ... support vector mechan...

Litong Dong; Jun Xu; Haibo Liu; Ying Guo

2014-01-01T23:59:59.000Z

299

Representing Forecast Error in a Convection-Permitting Ensemble System  

Science Journals Connector (OSTI)

Ensembles provide an opportunity to greatly improve short-term prediction of local weather hazards, yet generating reliable predictions remain a significant challenge. In particular, convection-permitting ensemble forecast systems (CPEFSs) have ...

Glen S. Romine; Craig S. Schwartz; Judith Berner; Kathryn R. Fossell; Chris Snyder; Jeff L. Anderson; Morris L. Weisman

2014-12-01T23:59:59.000Z

300

Weather Research and Forecasting Model 2.2 Documentation  

E-Print Network (OSTI)

................................................................................................. 20 3.1.2 Integrate's Flow of ControlWeather Research and Forecasting Model 2.2 Documentation: A Step-by-step guide of a Model Run .......................................................................................................................... 19 3.1 The Integrate Subroutine

Sadjadi, S. Masoud

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Network Bandwidth Utilization Forecast Model on High Bandwidth Network  

SciTech Connect

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

Yoo, Wucherl; Sim, Alex

2014-07-07T23:59:59.000Z

302

Wind Speed Forecasting Using a Hybrid Neural-Evolutive Approach  

Science Journals Connector (OSTI)

The design of models for time series prediction has found a solid foundation on statistics. Recently, artificial neural networks have been a good choice as approximators to model and forecast time series. Designing a neural network that provides a good ...

Juan J. Flores; Roberto Loaeza; Hctor Rodrguez; Erasmo Cadenas

2009-11-01T23:59:59.000Z

303

A model for short term electric load forecasting  

E-Print Network (OSTI)

A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE, III Submitted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE May 1975 Major... Subject: Electrical Engineering A MODEL FOR SHORT TERM ELECTRIC LOAD FORECASTING A Thesis by JOHN ROBERT TIGUE& III Approved as to style and content by: (Chairman of Committee) (Head Depart t) (Member) ;(Me r (Member) (Member) May 1975 ABSTRACT...

Tigue, John Robert

1975-01-01T23:59:59.000Z

304

Radiation fog forecasting using a 1-dimensional model  

E-Print Network (OSTI)

measuring site (Molly Caren), the soil moisture measuring site (Wilmington), and (b) location of the forecast site (Ohio River Basin near Cincinnati including Lunken airport) . . 23 3 An example of a COBEL configuration file for 25 August 1996, showing... measuring site (Molly Caren), the soil moisture measuring site (Wilmington), and (b) location of the forecast site (Ohio River Basin near Cincinnati including Lunken airport) . . 23 3 An example of a COBEL configuration file for 25 August 1996, showing...

Peyraud, Lionel

2012-06-07T23:59:59.000Z

305

Weather-based forecasts of California crop yields  

SciTech Connect

Crop yield forecasts provide useful information to a range of users. Yields for several crops in California are currently forecast based on field surveys and farmer interviews, while for many crops official forecasts do not exist. As broad-scale crop yields are largely dependent on weather, measurements from existing meteorological stations have the potential to provide a reliable, timely, and cost-effective means to anticipate crop yields. We developed weather-based models of state-wide yields for 12 major California crops (wine grapes, lettuce, almonds, strawberries, table grapes, hay, oranges, cotton, tomatoes, walnuts, avocados, and pistachios), and tested their accuracy using cross-validation over the 1980-2003 period. Many crops were forecast with high accuracy, as judged by the percent of yield variation explained by the forecast, the number of yields with correctly predicted direction of yield change, or the number of yields with correctly predicted extreme yields. The most successfully modeled crop was almonds, with 81% of yield variance captured by the forecast. Predictions for most crops relied on weather measurements well before harvest time, allowing for lead times that were longer than existing procedures in many cases.

Lobell, D B; Cahill, K N; Field, C B

2005-09-26T23:59:59.000Z

306

Wave height forecasting in Dayyer, the Persian Gulf  

Science Journals Connector (OSTI)

Forecasting of wave parameters is necessary for many marine and coastal operations. Different forecasting methodologies have been developed using the wind and wave characteristics. In this paper, artificial neural network (ANN) as a robust data learning method is used to forecast the wave height for the next 3, 6, 12 and 24h in the Persian Gulf. To determine the effective parameters, different models with various combinations of input parameters were considered. Parameters such as wind speed, direction and wave height of the previous 3h, were found to be the best inputs. Furthermore, using the difference between wave and wind directions showed better performance. The results also indicated that if only the wind parameters are used as model inputs the accuracy of the forecasting increases as the time horizon increases up to 6h. This can be due to the lower influence of previous wave heights on larger lead time forecasting and the existing lag between the wind and wave growth. It was also found that in short lead times, the forecasted wave heights primarily depend on the previous wave heights, while in larger lead times there is a greater dependence on previous wind speeds.

B. Kamranzad; A. Etemad-Shahidi; M.H. Kazeminezhad

2011-01-01T23:59:59.000Z

307

Project Year Project Team  

E-Print Network (OSTI)

An Engineer's Guide to the Structures of Baltimore Audience Students from the Krieger School of Arts City, interfaced through a course website, the team will integrate descriptions of structural behavior format. Technologies Used HTML/Web Design, MySQL Project Abstract Structural analysis is typically taught

Gray, Jeffrey J.

308

Project Year Project Team  

E-Print Network (OSTI)

information systems (GIS) tools to design maps that integrate data for visualizing geographic concepts School of Engineering Project Title GIS & Introductory Geography Audience Undergraduate students on how to use the Internet for geographic research, and an interactive introduction to GIS through online

Gray, Jeffrey J.

309

Project Management Project Managment  

E-Print Network (OSTI)

­ Inspired by agile methods #12;Background · Large-scale software development & IT projects, plagued relations #12;One Agile Approach to Scheduling · The creative nature of game development resist heavy up Problems ­incompatible platforms, 3rd party etc. #12;Is Games Development Similar? · Yes & No

Stephenson, Ben

310

Forecasting Agriculturally Driven Global Environmental Change  

Science Journals Connector (OSTI)

...Mean projections are means of the three univariate and the one...Common Journey: A Transition Toward Sustainability (National Academy Press, Washington...processes combined. 21. S. L.-Postel, Pillar of Sand: Can the Irrigation Miracle...

David Tilman; Joseph Fargione; Brian Wolff; Carla D'Antonio; Andrew Dobson; Robert Howarth; David Schindler; William H. Schlesinger; Daniel Simberloff; Deborah Swackhamer

2001-04-13T23:59:59.000Z

311

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

312

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

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). 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). Table of Contents Projection Tables Reference Case High Economic Growth Case Low Economic Growth Case Reference Case Projections by End-Use Sector and Region Projections of Oil Production Capacity and Oil Production in Three Cases Projections of Nuclear Generating Capacity Highlights World Energy and Economic Outlook Outlook for World Energy Consumption World Economic Outlook Alternative Growth Cases

313

Energy Research and Development Division FINAL PROJECT REPORT  

E-Print Network (OSTI)

Energy Research and Development Division FINAL PROJECT REPORT PROBABILISTIC TRANSMISSION CONGESTION FORECASTING DECEMBER 2012 CEC-500-2013-120 Prepared for: California Energy Commission Prepared by: Electric Research Institute Contract Number: UC MR-052 Prepared for: California Energy Commission Jamie Patterson

314

Energy Research and Development Division FINAL PROJECT REPORT  

E-Print Network (OSTI)

Energy Research and Development Division FINAL PROJECT REPORT EVALUATION OF NUMERICAL WEATHER PREDICTION FOR SOLAR FORECASTING Prepared for: California Energy Commission Prepared by: California Solar Energy Collaborative University of California, San Diego APRIL 2012 CEC-500-2013-115 #12;PRIMARY AUTHOR

315

Project Accounts  

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

» Project Accounts » Project Accounts Project Accounts Overview Project accounts are designed to facilitate collaborative computing by allowing multiple users to use the same account. All actions performed by the project account are traceable back to the individual who used the project account to perform those actions via gsisshd accounting logs. Requesting a Project Account PI's, PI proxies and project managers are allowed to request a project account. In NIM do "Actions->Request a Project Account" and fill in the form. Select the repository that the Project Account is to use from the drop-down menu, "Sponsoring Repository". Enter the name you want for the account (8 characters maximum) and a description of what you will use the account for and then click on the "Request Project Account" button. You

316

Project Fact Sheet Project Update  

E-Print Network (OSTI)

Project Fact Sheet Project Update: Project Brief: A state of the art facility, at Hammersmith information visit the Faculty of Medicine web pages http://www1.imperial.ac.uk/medicine/ Construction Project Team: Project Facts & Figures: Budget: £60 000 000 Funding Source: SRIF II (Imperial College), GSK, MRC

317

Project Fact Sheet Project Update  

E-Print Network (OSTI)

Project Fact Sheet Project Update: Project Brief: The refurbishment of the instrumentation equipment. This project encompasses refurbishment work on over 1,150m2 of laboratory space across four, the completed project will allow researchers to expand their work in satellite instrumentation, the fabrication

318

Project Fact Sheet Project Brief  

E-Print Network (OSTI)

Project Fact Sheet Project Brief: In the first phase of the Union Building re.union.ic.ac.uk/marketing/building Construction Project Team: Project Facts & Figures: Budget: £1,400,000 Funding Source: Capital Plan and Imperial College Union reserves Construction Project Programme: Start on Site: August 2006 End Date: March

319

Volume Project  

E-Print Network (OSTI)

Math 13900. Volume Project. For the following project, you may use any materials. This must be your own original creation. Construct a right pyramid with a base...

rroames

2010-01-12T23:59:59.000Z

320

A suite of metrics for assessing the performance of solar power forecasting  

Science Journals Connector (OSTI)

Abstract Forecasting solar energy generation is a challenging task because of the variety of solar power systems and weather regimes encountered. Inaccurate forecasts can result in substantial economic losses and power system reliability issues. One of the key challenges is the unavailability of a consistent and robust set of metrics to measure the accuracy of a solar forecast. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, and applications) that were developed as part of the U.S. Department of Energy SunShot Initiatives efforts to improve the accuracy of solar forecasting. In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design-of-experiments methodology in conjunction with response surface, sensitivity analysis, and nonparametric statistical testing methods. The three types of forecasting improvements are (i) uniform forecasting improvements when there is not a ramp, (ii) ramp forecasting magnitude improvements, and (iii) ramp forecasting threshold changes. Day-ahead and 1-hour-ahead forecasts for both simulated and actual solar power plants are analyzed. The results show that the proposed metrics can efficiently evaluate the quality of solar forecasts and assess the economic and reliability impacts of improved solar forecasting. Sensitivity analysis results show that (i) all proposed metrics are suitable to show the changes in the accuracy of solar forecasts with uniform forecasting improvements, and (ii) the metrics of skewness, kurtosis, and Rnyi entropy are specifically suitable to show the changes in the accuracy of solar forecasts with ramp forecasting improvements and a ramp forecasting threshold.

Jie Zhang; Anthony Florita; Bri-Mathias Hodge; Siyuan Lu; Hendrik F. Hamann; Venkat Banunarayanan; Anna M. Brockway

2015-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "interindustry forecasting project" 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

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Low Economic Growth Case Projection Tables (1990-2025) Low Economic Growth Case Projection Tables (1990-2025) Formats Low Economic Growth Case Data Projection Tables (1 to 13 complete) Excel PDF Table Title Table C1 World Total Primary Energy Consumption by Region, Low Economic Growth Case Excel PDF Table C2 World Total Energy Consumption by Region and Fuel, Low Economic Growth Case Excel PDF Table C3 World Gross Domestic Product (GDP) by Region, Low Economic Growth Case Excel PDF Table C4 World Oil Consumption by Region, Low Economic Growth Case Excel PDF Table C5 World Natural Cas Consumption by Region, Low Economic Growth Case Excel PDF Table C6 World Coal Consumption by Region, Low Economic Growth Case Excel PDF Table C7 World Nuclear Energy Consumption by Region, Low Economic Growth Case Excel PDF Table C8 World Consumption of Hydroelectricity and Other Renewable Energy by Region, Low Economic Growth Case

322

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

High Economic Growth Case Projection Tables (1990-2025) High Economic Growth Case Projection Tables (1990-2025) Formats High Economic Growth Case Data Projection Tables (1 to 13 complete) Excel PDF Table Title Table B1 World Total Primary Energy Consumption by Region, High Economic Growth Case Excel PDF Table B2 World Total Energy Consumption by Region and Fuel, High Economic Growth Case Excel PDF Table B3 World Gross Domestic Product (GDP) by Region, High Economic Growth Case Excel PDF Table B4 World Oil Consumption by Region, High Economic Growth Case Excel PDF Table B5 World Natural Cas Consumption by Region, High Economic Growth Case Excel PDF Table B6 World Coal Consumption by Region, High Economic Growth Case Excel PDF Table B7 World Nuclear Energy Consumption by Region, High Economic Growth Case Excel PDF Table B8 World Consumption of Hydroelectricity and Other Renewable Energy by Region, High Economic Growth Case

323

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Projection Tables (1990-2025) Projection Tables (1990-2025) Formats All Reference Case Data Projection Tables (1 to 14 complete) Excel PDF Table Title Table A1 World Total Primary Energy Consumption by Region, Reference Case Excel PDF Table A2 World Total Energy Consumption by Region and Fuel, Reference Case Excel PDF Table A3 World Gross Domestic Product (GDP) by Region, Reference Case Excel PDF Table A4 World Oil Consumption by Region, Reference Case Excel PDF Table A5 World Natural Gas Consumption by Region, Reference Case Excel PDF Table A6 World Coal Consumption by Region, Reference Case Excel PDF Table A7 World Nuclear Energy Consumption by Region, Reference Case Excel PDF Table A8 World Consumption of Hydroelectricity and Other Renewable Energy by Region, Reference Case Excel PDF Table A9 World Net Electricity Consumption by Region, Reference Case

324

The World Energy Projection System April 2001  

Gasoline and Diesel Fuel Update (EIA)

The World Energy Projection System April 2001 The World Energy Projection System April 2001 Gasoline and Diesel Fuel Updates April 20, 2001 (Next Release: April, 2002) Related Links To Forecasting Home Page EIA Homepage Printer Friendly Version Continuing with this release, annual updates to the model will be available. Check this space for scheduled future releases. Note: If you are familiar with the model and just wish to download the latest version, click HERE. The World Energy Projection System The projections of world energy consumption published annually by the Energy Information Administration (EIA) in the International Energy Outlook (IEO) are derived from the World Energy Projection System (WEPS). WEPS is an integrated set of personal computer-based spreadsheets containing data compilations, assumption specifications, descriptive analysis procedures,

325

Survey of Variable Generation Forecasting in the West: August 2011 - June 2012  

SciTech Connect

This report surveyed Western Interconnection Balancing Authorities regarding their implementation of variable generation forecasting, the lessons learned to date, and recommendations they would offer to other Balancing Authorities who are considering variable generation forecasting. Our survey found that variable generation forecasting is at an early implementation stage in the West. Eight of the eleven Balancing Authorities interviewed began forecasting in 2008 or later. It also appears that less than one-half of the Balancing Authorities in the West are currently utilizing variable generation forecasting, suggesting that more Balancing Authorities in the West will engage in variable generation forecasting should more variable generation capacity be added.

Porter, K.; Rogers, J.

2012-04-01T23:59:59.000Z

326

Environmental Restoration Projects  

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

Maturity Maturity Value Target Score Maturity Value Target Score A1 Cost Estimate H 7.5 2 15.0 5 37.5 A2 Cost Risk/Contingency Analysis P 3.0 1 3.0 5 15.0 A3 Funding Requirements/Profile H 7.5 2 15.0 5 37.5 A4 Independent Cost Estimate/Schedule Review P 3.0 N/A 0.0 5 15.0 A5 Life Cycle Cost P 3.0 1 3.0 5 15.0 A6 Forecast of Cost at Completion P 3.0 N/A 0.0 5 15.0 A7 Cost Estimate for Next Phase Work Scope P 3.0 5 15.0 5 15.0 Subtotal Cost 51.0 150.0 B1 Project Schedule H 7.5 2 15.0 5 37.5 B2 Major Milestones P 3.0 2 6.0 5 15.0 B3 Resource Loading P 3.0 1 3.0 5 15.0 B4 Critical Path Management H 7.5 1 7.5 5 37.5 B5 Schedule Risk/Contingency Analysis P 3.0 1 3.0 5 15.0 B6 Forecast of Schedule Completion P 3.0 N/A 0.0 5 15.0 B7 Schedule for Next Phase Work Scope P 3.0 5 15.0 5 15.0 Subtotal Schedule 49.5 150.0 C1 Preliminary Assessments/Site Investigation P 2.5 5 12.5 5 12.5 C2

327

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model's parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. (Lawrence Berkeley Lab., CA (United States) Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.); Hwang, R. (Lawrence Berkeley Lab., CA (United States))

1992-02-01T23:59:59.000Z

328

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model`s parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. [Lawrence Berkeley Lab., CA (United States)]|[Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics]|[Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.; Hwang, R. [Lawrence Berkeley Lab., CA (United States)

1992-02-01T23:59:59.000Z

329

An assessment of electrical load forecasting using artificial neural network  

Science Journals Connector (OSTI)

The forecasting of electricity demand has become one of the major research fields in electrical engineering. The supply industry requires forecasts with lead times, which range from the short term (a few minutes, hours, or days ahead) to the long term (up to 20 years ahead). The major priority for an electrical power utility is to provide uninterrupted power supply to its customers. Long term peak load forecasting plays an important role in electrical power systems in terms of policy planning and budget allocation. This paper presents a peak load forecasting model using artificial neural networks (ANN). The approach in the paper is based on multi-layered back-propagation feed forward neural network. For annual forecasts, there should be 10 to 12 years of historical monthly data available for each electrical system or electrical buss. A case study is performed by using the proposed method of peak load data of a state electricity board of India which maintain high quality, reliable, historical data providing the best possible results. Model's quality is directly dependent upon data integrity.

V. Shrivastava; R.B. Misra; R.C. Bansal

2012-01-01T23:59:59.000Z

330

Future Changes in the Western North Pacific Tropical Cyclone Activity Projected by a Multidecadal Simulation with a 16-km Global Atmospheric GCM  

Science Journals Connector (OSTI)

How tropical cyclone (TC) activity in the northwestern Pacific might change in a future climate is assessed using multidecadal Atmospheric Model Intercomparison Project (AMIP)-style and time-slice simulations with the ECMWF Integrated Forecast ...

Julia V. Manganello; Kevin I. Hodges; Brandt Dirmeyer; James L. Kinter III; Benjamin A. Cash; Lawrence Marx; Thomas Jung; Deepthi Achuthavarier; Jennifer M. Adams; Eric L. Altshuler; Bohua Huang; Emilia K. Jin; Peter Towers; Nils Wedi

2014-10-01T23:59:59.000Z

331

Project Controls  

Directives, Delegations, and Requirements

Project controls are systems used to plan, schedule, budget, and measure the performance of a project/program. The cost estimation package is one of the documents that is used to establish the baseline for project controls. This chapter gives a brief description of project controls and the role the cost estimation package plays.

1997-03-28T23:59:59.000Z

332

Short-term energy outlook. Quarterly projections, Third quarter 1994  

SciTech Connect

The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202). The feature article for this issue is Demand, Supply and Price Outlook for Reformulated Gasoline, 1995.

Not Available

1994-08-02T23:59:59.000Z

333

Numerical Simulation of 2010 Pakistan Flood in the Kabul River Basin by Using Lagged Ensemble Rainfall Forecasting  

Science Journals Connector (OSTI)

Lagged ensemble forecasting of rainfall and rainfallrunoffinundation (RRI) forecasting were applied to the devastating flood in the Kabul River basin, the first strike of the 2010 Pakistan flood. The forecasts were performed using the Global ...

Tomoki Ushiyama; Takahiro Sayama; Yuya Tatebe; Susumu Fujioka; Kazuhiko Fukami

2014-02-01T23:59:59.000Z

334

Expert Panel: Forecast Future Demand for Medical Isotopes | Department of  

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

Expert Panel: Forecast Future Demand for Medical Isotopes Expert Panel: Forecast Future Demand for Medical Isotopes Expert Panel: Forecast Future Demand for Medical Isotopes The Expert Panel has concluded that the Department of Energy and National Institutes of Health must develop the capability to produce a diverse supply of radioisotopes for medical use in quantities sufficient to support research and clinical activities. Such a capability would prevent shortages of isotopes, reduce American dependence on foreign radionuclide sources and stimulate biomedical research. The expert panel recommends that the U.S. government build this capability around either a reactor, an accelerator or a combination of both technologies as long as isotopes for clinical and research applications can be supplied reliably, with diversity in adequate

335

Forecasting correlated time series with exponential smoothing models  

Science Journals Connector (OSTI)

This paper presents the Bayesian analysis of a general multivariate exponential smoothing model that allows us to forecast time series jointly, subject to correlated random disturbances. The general multivariate model, which can be formulated as a seemingly unrelated regression model, includes the previously studied homogeneous multivariate Holt-Winters model as a special case when all of the univariate series share a common structure. MCMC simulation techniques are required in order to approach the non-analytically tractable posterior distribution of the model parameters. The predictive distribution is then estimated using Monte Carlo integration. A Bayesian model selection criterion is introduced into the forecasting scheme for selecting the most adequate multivariate model for describing the behaviour of the time series under study. The forecasting performance of this procedure is tested using some real examples.

Ana Corbern-Vallet; Jos D. Bermdez; Enriqueta Vercher

2011-01-01T23:59:59.000Z

336

Application of GIS on forecasting water disaster in coal mines  

SciTech Connect

In many coal mines of China, water disasters occur very frequently. It is the most important problem that water gets inrush into drifts and coal faces, locally known as water gush, during extraction and excavation. Its occurrence is controlled by many factors such as geological, hydrogeological and mining technical conditions, and very difficult to be predicted and prevented by traditional methods. By making use of overlay analysis of Geographic Information System, a multi-factor model can be built to forecast the potential of water gush. This paper introduced the method of establishment of the water disaster forecasting system and forecasting model and two practical successful cases of application in Jiaozuo and Yinzhuang coal mines. The GIS proved helpful for ensuring the safety of coal mines.

Sun Yajun; Jiang Dong; Ji Jingxian [China Univ. of Mining and Technology, Jiangshy (China)] [and others

1996-08-01T23:59:59.000Z

337

NREL: Energy Analysis - Energy Forecasting and Modeling Staff  

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

Energy Forecasting and Modeling Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Geraly Amador Clayton Barrows Greg Brinkman Brian W Bush Stuart Cohen Carolyn Davidson Paul Denholm Victor Diakov Aron Dobos Easan Drury Kelly Eurek Janine Freeman Marissa Hummon Jennie Jorganson Jordan Macknick Trieu Mai David Mulcahy David Palchak Ben Sigrin Daniel Steinberg Patrick Sullivan Aaron Townsend Laura Vimmerstedt Andrew Weekley Owen Zinaman Photo of Clayton Barrows. Clayton Barrows Postdoctoral Researcher Areas of expertise Power system modeling Primary research interests Power and energy systems

338

Forecast of contracting and subcontracting opportunities. Fiscal year 1996  

SciTech Connect

This forecast of prime and subcontracting opportunities with the U.S. Department of Energy and its MAO contractors and environmental restoration and waste management contractors, is the Department`s best estimate of small, small disadvantaged and women-owned small business procurement opportunities for fiscal year 1996. The information contained in the forecast is published in accordance with Public Law 100-656. It is not an invitation for bids, a request for proposals, or a commitment by DOE to purchase products or services. Each procurement opportunity is based on the best information available at the time of publication and may be revised or cancelled.

NONE

1996-02-01T23:59:59.000Z

339

Sales forecasting strategies for small businesses: an empirical investigation of statistical and judgemental methods  

Science Journals Connector (OSTI)

This study evolved from the mixed results shown in the reviewed forecasting literature and from the lack of sufficient forecasting research dealing with micro data. The main purpose of this study is to investigate and compare the accuracy of different quantitative and qualitative forecasting techniques, and to recommend a forecasting strategy for small businesses. Emphasis is placed on the testing of combining as a tool to improve forecasting accuracy. Of particular interest is whether combining time series and judgemental forecasts provides more accurate results than individual methods. A case study of a small business was used for this purpose to assess the accuracy and applicability of combining forecasts. The evidence indicates that combining qualitative and quantitative methods results in better and improved forecasts.

Imad J. Zbib

2006-01-01T23:59:59.000Z

340

Forecasting 65+ travel : an integration of cohort analysis and travel demand modeling  

E-Print Network (OSTI)

Over the next 30 years, the Boomers will double the 65+ population in the United States and comprise a new generation of older Americans. This study forecasts the aging Boomers' travel. Previous efforts to forecast 65+ ...

Bush, Sarah, 1973-

2003-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Distributed quantitative precipitation forecasts combining information from radar and numerical weather prediction model outputs  

E-Print Network (OSTI)

Applications of distributed Quantitative Precipitation Forecasts (QPF) range from flood forecasting to transportation. Obtaining QPF is acknowledged to be one of the most challenging areas in hydrology and meteorology. ...

Ganguly, Auroop Ratan

2002-01-01T23:59:59.000Z

342

A Comparison of Measures-Oriented and Distributions-Oriented Approaches to Forecast Verification  

Science Journals Connector (OSTI)

The authors have carried out verification of 590 1224-h high-temperature forecasts from numerical guidance products and human forecasters for Oklahoma City, Oklahoma, using both a measures-oriented verification scheme and a distributions-...

Harold E. Brooks; Charles A. Doswell III

1996-09-01T23:59:59.000Z

343

Correspondence among the Correlation, RMSE, and Heidke Forecast Verification Measures; Refinement of the Heidke Score  

Science Journals Connector (OSTI)

The correspondence among the following three forecast verification scores, based on forecasts and their associated observations, is described: 1) the correlation score, 2) the root-mean-square error (RMSE) score, and 3) the Heidke score (based on ...

Anthony G. Barnston

1992-12-01T23:59:59.000Z

344

Improving Seasonal Forecast Skill of North American Surface Air Temperature in Fall Using a Postprocessing Method  

Science Journals Connector (OSTI)

A statistical postprocessing approach is applied to seasonal forecasts of surface air temperatures (SAT) over North America in fall, when the original uncalibrated predictions have little skill. The data used are ensemble-mean seasonal forecasts ...

XiaoJing Jia; Hai Lin; Jacques Derome

2010-05-01T23:59:59.000Z

345

Computing electricity spot price prediction intervals using quantile regression and forecast averaging  

Science Journals Connector (OSTI)

We examine possible accuracy gains from forecast averaging in the context of interval forecasts of electricity spot prices. First, we test whether constructing empirical prediction intervals (PI) from combined electricity

Jakub Nowotarski; Rafa? Weron

2014-08-01T23:59:59.000Z

346

Medium-term forecasting of demand prices on example of electricity prices for industry  

Science Journals Connector (OSTI)

In the paper, a method of forecasting demand prices for electric energy for the industry has been suggested. An algorithm of the forecast for 20062010 based on the data for 19972005 has been presented.

V. V. Kossov

2014-09-01T23:59:59.000Z

347

Price Forecasting and Optimal Operation of Wholesale Customers in a Competitive Electricity Market.  

E-Print Network (OSTI)

??This thesis addresses two main issues: first, forecasting short-term electricity market prices; and second, the application of short-term electricity market price forecasts to operation planning (more)

Zareipour, Hamidreza

2006-01-01T23:59:59.000Z

348

Impacts of Improved Day-Ahead Wind Forecasts on Power Grid Operations: September 2011  

SciTech Connect

This study analyzed the potential benefits of improving the accuracy (reducing the error) of day-ahead wind forecasts on power system operations, assuming that wind forecasts were used for day ahead security constrained unit commitment.

Piwko, R.; Jordan, G.

2011-11-01T23:59:59.000Z

349

Combining Multi Wavelet and Multi NN for Power Systems Load Forecasting  

Science Journals Connector (OSTI)

In the paper, two pre-processing methods for load forecast sampling data including multiwavelet transformation and chaotic time series ... introduced. In addition, multi neural network for load forecast including...

Zhigang Liu; Qi Wang; Yajun Zhang

2008-01-01T23:59:59.000Z

350

Application of the Stretched Exponential Production Decline Model to Forecast Production in Shale Gas Reservoirs  

E-Print Network (OSTI)

Production forecasting in shale (ultra-low permeability) gas reservoirs is of great interest due to the advent of multi-stage fracturing and horizontal drilling. The well renowned production forecasting model, Arps? Hyperbolic Decline Model...

Statton, James Cody

2012-07-16T23:59:59.000Z

351

E-Print Network 3.0 - air pollution forecast Sample Search Results  

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

forecast Search Powered by Explorit Topic List Advanced Search Sample search results for: air pollution forecast Page: << < 1 2 3 4 5 > >> 1 DISCOVER-AQ Outlook for Wednesay, July...

352

Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States  

E-Print Network (OSTI)

andvalidation. SolarEnergy. 73:5,307? Perez,R. ,irradianceforecastsforsolarenergyapplicationsbasedonforecastdatabase. SolarEnergy. 81:6,809?812.

Mathiesen, Patrick; Kleissl, Jan

2011-01-01T23:59:59.000Z

353

A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height  

Science Journals Connector (OSTI)

The Weather Research and Forecasting Model (WRF) with 10-km horizontal grid spacing was used to explore improvements in wind speed forecasts at a typical wind turbine hub height (80 m). An ensemble consisting of WRF model simulations with ...

Adam J. Deppe; William A. Gallus Jr.; Eugene S. Takle

2013-02-01T23:59:59.000Z

354

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Projections by End-Use Sector and Region Tables (2002-2025) Projections by End-Use Sector and Region Tables (2002-2025) Formats Reference Case Projections by End-Use Sector and Region Data Tables (1 to 15 complete) Excel PDF Table Title Table D1 Delivered Energy Consumption in the United States by End-Use Sector and Fuel Excel PDF Table D2 Delivered Energy Consumption in Canada by End-Use Sector and Fuel Excel PDF Table D3 Delivered Energy Consumption in Mexico by End-Use Sector and Fuel Excel PDF Table D4 Delivered Energy Consumption in Western Europe by End-Use Sector and Fuel Excel PDF Table D5 Delivered Energy Consumption in Japan by End-Use Sector and Fuel Excel PDF Table D6 Delivered Energy Consumption in Australia/New Zealand by End-Use Sector and Fuel Excel PDF Table D7 Delivered Energy Consumption in the Former Soviet Union by End-Use Sector and Fuel

355

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

I: System for the Analysis of Global Energy Markets (SAGE) I: System for the Analysis of Global Energy Markets (SAGE) The projections of world energy consumption appearing in this year’s International Energy Outlook (IEO) are based on the Energy Information Administration’s (EIA’s) international energy modeling tool, System for the Analysis of Global Energy markets (SAGE). SAGE is an integrated set of regional models that provide a technology-rich basis for estimating regional energy consumption. For each region, reference case estimates of 42 end-use energy service demands (e.g., car, commercial truck, and heavy truck road travel; residential lighting; steam heat requirements in the paper industry) are developed on the basis of economic and demographic projections. Projections of energy consumption to meet the energy demands are estimated on the basis of each region’s existing energy use patterns, the existing stock of energy-using equipment, and the characteristics of available new technologies, as well as new sources of primary energy supply.

356

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.

357

Improving the forecasting function for a Credit Hire operator in the UK  

Science Journals Connector (OSTI)

This study aims to test on the predictability of Credit Hire services for the automobile and insurance industry. A relatively sophisticated time series forecasting procedure, which conducts a competition among exponential smoothing models, is employed to forecast demand for a leading UK Credit Hire operator (CHO). The generated forecasts are compared against the Naive method, resulting that demand for CHO services is indeed extremely hard to forecast, as the underlying variable is the number of road accidents a truly stochastic variable.

Nicolas D. Savio; K. Nikolopoulos; Konstantinos Bozos

2009-01-01T23:59:59.000Z

358

Central Wind Power Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities  

SciTech Connect

The report addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America.

Porter, K.; Rogers, J.

2009-12-01T23:59:59.000Z

359

The outlook for Operations Research: will business education supply enough management science new entrants to meet forecast demand  

Science Journals Connector (OSTI)

Can Management Science in Business Education become sufficiently popular to fill forecast demands for new entrants to its Operations Research (OR) subset? Based upon papers by numerous authors, this paper identifies an interesting phenomenon ?? an increasingly applicable field of Management Science plagued by students avoiding entry. This paper discusses the results of an examination of this phenomenon's background, provides data collected concerning current supply of and projected demand for new entrants in a subset of Management Science; examines the continuing call for new approaches to teaching Management Science as a means of attracting new entrants; and presents continued research suggestions.

Richard A. McMahon; Peter D. DeVries

2012-01-01T23:59:59.000Z

360

Draft forecast of the final report for the comparison to 40 CFR Part 191, Subpart B, for the Waste Isolation Pilot Plant  

SciTech Connect

The United States Department of Energy is planning to dispose of transuranic wastes, which have been generated by defense programs, at the Waste Isolation Pilot Plant. The WIPP Project will assess compliance with the requirements of the United States Environmental Protection Agency. This report forecasts the planned 1992 document, Comparison to 40 CFR, Part 191, Subpart B, for the Waste Isolation Pilot Plant (WIPP). 130 refs., 36 figs., 11 tabs.

Bertram-Howery, S.G.; Marietta, M.G.; Anderson, D.R.; Gomez, L.S.; Rechard, R.P. (Sandia National Labs., Albuquerque, NM (USA)); Brinster, K.F.; Guzowski, R.V. (Science Applications International Corp., Albuquerque, NM (USA))

1989-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "interindustry forecasting project" 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

BlackSeaHazNet Scientific Report - EU FP7 IRSES project 2011-2014  

E-Print Network (OSTI)

The aims of the project 2011-2014) are in the project title- Complex Research of Earthquakes Forecasting Possibilities, Seismic and Climate Change Correlations- to create a team for researching the above mentioned problem. In the Project participated 76 scientists from 16 Institutes and 8 countries- Armenia, Bulgaria, Georgia, Greece, Macedonia, Slovenia, Turkey and Ukraine. The main results are shortly listed in the next. Creating a group which is able to fulfill a Complex Research of Earthquakes Forecasting Possibilities; The main result is statistical prove of imminent forecasting possibility for seismic regional activity on the basis of the geomagnetic monitoring in the framework of special created data acquisition system for earthquakes archiving, visualization and analysis (geomagnetic quake approach). Illustrated with the data from INTERMAGNET stations- PAG (Panagurichte, Bulgaria), SUA (Surlari, Romania), GCK (Grocka, Serbia) and LAquila (AQU, Italy) for the last 5-8 years; The application of the geom...

Mavrodiev, Strachimir Cht; Pekevski, Lazo; Kikuashvili, Giorgi

2014-01-01T23:59:59.000Z

362

Combination of Long Term and Short Term Forecasts, with Application to Tourism  

E-Print Network (OSTI)

Combination of Long Term and Short Term Forecasts, with Application to Tourism Demand Forecasting that are combined. As a case study, we consider the problem of forecasting monthly tourism numbers for inbound tourism to Egypt. Specifically, we con- sider 33 source countries, as well as the aggregate. The novel

Abu-Mostafa, Yaser S.

363

VALIDATION OF SHORT AND MEDIUM TERM OPERATIONAL SOLAR RADIATION FORECASTS IN THE US  

E-Print Network (OSTI)

, and medium term forecasts (up to seven days ahead) from numerical weather prediction models [1]. Forecasts radiation forecasting. One approach relies on numerical weather prediction (NWP) models which can be global modeling of the atmosphere. NWP models cannot, at this stage of their development, predict the exact

Perez, Richard R.

364

Products and Service of Center for Weather Forecast and Climate Studies  

E-Print Network (OSTI)

) Seasonal Climate Forecast (1-6 months) #12;Weather Forecast Weather Bulletin PCD SCD1 SCD2 SX6 SatelliteLOG O Products and Service of Center for Weather Forecast and Climate Studies Simone Sievert da AND DEVELOP. DIVISION SATELLITE DIVISION ENVIROM. SYSTEM OPERATIONAL DIVISION CPTEC/INPE Msc / PHD &TRAINING

365

Lessons from Deploying NLG Technology for Marine Weather Forecast Text Generation  

E-Print Network (OSTI)

model along with other sources of weather data such as satellite pictures and their own forecastingLessons from Deploying NLG Technology for Marine Weather Forecast Text Generation Somayajulu G Language Generation (NLG) system that produces textual weather forecasts for offshore oilrigs from

Sripada, Yaji

366

Ensemble-based air quality forecasts: A multimodel approach applied to ozone  

E-Print Network (OSTI)

Ensemble-based air quality forecasts: A multimodel approach applied to ozone Vivien Mallet1., and B. Sportisse (2006), Ensemble-based air quality forecasts: A multimodel approach applied to ozone, J, the uncertainty in chem- istry transport models is a major limitation of air quality forecasting. The source

Boyer, Edmond

367

PARS II - Integrated Project Team Meeting  

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

John Makepeace (OECM) Kai Mong (EES), Ken Henderson (EES), Norm Ayers (EES) October 29, 2009 2 2 Agenda * PARS II OA & CPP Software * PARS II Deployment Timeline * Deployment Overview * Organizational Roles & Responsibilities * Project List and Schedule * Next Steps 3 PARS II OA & CPP Software * Oversight & Assessment (OA) * Web interface collects summary-level project data: status assessments, forecasts, PB, KPPs * Used by FPD, Program and OECM each month * Contractor Project Performance (CPP) * Web interface for uploading contractor's project files: earned value, schedule, variance, MR, risk * Used by contractor each month 4 PARS II Deployment Timeline 4 11/1/2009 12/1/2009 1/1/2010 2/1/2010 3/1/2010 4/1/2010 5/1/2010 6/1/2010 7/1/2010 8/1/2010 9/1/2010 10/1/2010 11/1/2010

368

Annual Energy Outlook with Projections to 2025  

Gasoline and Diesel Fuel Update (EIA)

5 with Projections to 2025 5 with Projections to 2025 Report #: DOE/EIA-0383(2005) Release date full report: January 2005 Next release date full report: January 2006 Early Release Reference Case date: December 2005 The Annual Energy Outlook presents a midterm forecast and analysis of US energy supply, demand, and prices through 2025. The projections are based on results from the Energy Information Administration's National Energy Modeling System. AEO2005 includes a reference case and over 30 sensitivities. Data Tables Summary Tables Adobe Acrobat Logo Yearly Tables Excel logo Regional and other detailed tables Excel logo (Supplemental) Contents Overview Market Drivers Trends in Economic Activity Economic Growth Cases International Oil Markets Energy Demand Projections Buildings Sector

369

Science Projects  

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

Argonne Argonne Science Project Ideas! Our Science Project section provides you with sample classroom projects and experiments, online aids for learning about science, as well as ideas for Science Fair Projects. Please select any project below to continue. Also, if you have an idea for a great project or experiment that we could share, please click our Ideas page. We would love to hear from you! Science Fair Ideas Science Fair Ideas! The best ideas for science projects are learning about and investigating something in science that interests you. NEWTON has a list of Science Fair linkd that can help you find the right topic. Toothpick Bridge Web Sites Toothpick Bridge Sites! Building a toothpick bridge is a great class project for physics and engineering students. Here are some sites that we recommend to get you started!

370

Projection Systems  

Science Journals Connector (OSTI)

As a general rule, broad-band sources which employ projection optics are the most difficult to evaluate. In addition to the problems encountered in evaluating exposed lamps, one must characterize the projected...

David Sliney; Myron Wolbarsht

1980-01-01T23:59:59.000Z

371

Circle Project  

E-Print Network (OSTI)

This project asks students to decide if a collection of points in space do or do not lie on a ... The project is accessible to linear algebra students who have studied...

372

Hydropower Projects  

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

This report covers the Wind and Water Power Technologies Office's hydropower project funding from fiscal years 2008 to 2014.

373

Optimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts  

E-Print Network (OSTI)

Optimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts Antonio that the inherent variability in wind power generation and the related difficulty in predicting future generation profiles, raise major challenges to wind power integration into the electricity grid. In this work we study

Giannitrapani, Antonello

374

Does Money Matter in Inflation Forecasting? JM Binner 1  

E-Print Network (OSTI)

1 Does Money Matter in Inflation Forecasting? JM Binner 1 P Tino 2 J Tepper 3 R Anderson4 B Jones 5 range of different definitions of money, including different methods of aggregation and different that there exists a long-run relationship between the growth rate of the money supply and the growth rate of prices

Tino, Peter

375

Detecting and Forecasting Economic Regimes in Automated Exchanges  

E-Print Network (OSTI)

, such as over- supply or scarcity, from historical data using computational methods to construct price density. The agent can use this information to make both tactical decisions such as pricing and strategic decisions historical data and identified from observable data. We outline how to identify regimes and forecast regime

Ketter, Wolfgang

376

Forecasting Market Demand for New Telecommunications Services: An Introduction  

E-Print Network (OSTI)

Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc, 2000 Abstract The marketing team of a new telecommunications company is usually tasked with producing involved in doing so. Based on our three decades of experience working with telecommunications operators

Parsons, Simon

377

SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS  

E-Print Network (OSTI)

SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS Detlev Heinemann Oldenburg.girodo@uni-oldenburg.de ABSTRACT Solar energy is expected to contribute major shares of the future global energy supply. Due to its and solar energy conversion processes has to account for this behaviour in respective operating strategies

Heinemann, Detlev

378

Short-Term Solar Energy Forecasting Using Wireless Sensor Networks  

E-Print Network (OSTI)

Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Stefan Achleitner, Tao Liu an advantage for output power prediction. Solar Energy Prediction System Our prediction model is based variability of more then 100 kW per minute. For practical usage of solar energy, predicting times of high

Cerpa, Alberto E.

379

Solar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting Questionnaire As someone who is familiar with solar energy issues, we hope that you will tak  

E-Print Network (OSTI)

is familiar with solar energy issues, we hope that you will take a few moments to answer this short survey on your needs for information on solar energy resources and forecasting. This survey is conducted with the California Solar Energy Collaborative (CSEC) and the California Solar Initiative (CSI) our objective

Islam, M. Saif

380

A FORECAST MODEL OF AGRICULTURAL AND LIVESTOCK PRODUCTS PRICE  

E-Print Network (OSTI)

A FORECAST MODEL OF AGRICULTURAL AND LIVESTOCK PRODUCTS PRICE Wensheng Zhang1,* , Hongfu Chen1 and excessive fluctuation of agricultural and livestock products price is not only harmful to residents' living, but also affects CPI (Consumer Price Index) values, and even leads to social crisis, which influences

Boyer, Edmond

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Forecasting Building Occupancy Using Sensor Network James Howard  

E-Print Network (OSTI)

) into the future. Our approach is to train a set of standard forecasting models to our time series data. Each model conditioning (HVAC) systems. In particular, if occupancy can be accurately pre- dicted, HVAC systems can potentially be controlled to op- erate more efficiently. For example, an HVAC system can pre-heat or pre

Hoff, William A.

382

Forecasting Hospital Bed Availability Using Simulation and Neural Networks  

E-Print Network (OSTI)

Forecasting Hospital Bed Availability Using Simulation and Neural Networks Matthew J. Daniels is a critical factor for decision-making in hospitals. Bed availability (or alternatively the bed occupancy in emergency departments, and many other important hospital decisions. To better enable a hospital to make

Kuhl, Michael E.

383

Predicting Solar Generation from Weather Forecasts Using Machine Learning  

E-Print Network (OSTI)

Predicting Solar Generation from Weather Forecasts Using Machine Learning Navin Sharma, Pranshu Sharma, David Irwin, and Prashant Shenoy Department of Computer Science University of Massachusetts Amherst Amherst, Massachusetts 01003 {nksharma,pranshus,irwin,shenoy}@cs.umass.edu Abstract--A key goal

Shenoy, Prashant

384

Review of Wind Energy Forecasting Methods for Modeling Ramping Events  

SciTech Connect

Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

Wharton, S; Lundquist, J K; Marjanovic, N; Williams, J L; Rhodes, M; Chow, T K; Maxwell, R

2011-03-28T23:59:59.000Z

385

Development and Deployment of an Advanced Wind Forecasting Technique  

E-Print Network (OSTI)

findings. Part 2 addresses how operators of wind power plants and power systems can incorporate advanced the output of advanced wind energy forecasts into decision support models for wind power plant and power in Porto) Power Systems Unit Porto, Portugal Industry Partners Horizon Wind Energy, LLC Midwest Independent

Kemner, Ken

386

Power load forecasting using data mining and knowledge discovery technology  

Science Journals Connector (OSTI)

Considering the importance of the peak load to the dispatching and management of the electric system, the error of peak load is proposed in this paper as criteria to evaluate the effect of the forecasting model. This paper proposes a systemic framework that attempts to use data mining and knowledge discovery (DMKD) to pretreat the data. And a new model is proposed which combines artificial neural networks with data mining and knowledge discovery for electric load forecasting. With DMKD technology, the system not only could mine the historical daily loading which had the same meteorological category as the forecasting day to compose data sequence with highly similar meteorological features, but also could eliminate the redundant influential factors. Then an artificial neural network is constructed to predict according to its characteristics. Using this new model, it could eliminate the redundant information, accelerate the training speed of neural network and improve the stability of the convergence. Compared with single BP neural network, this new method can achieve greater forecasting accuracy.

Yongli Wang; Dongxiao Niu; Ling Ji

2011-01-01T23:59:59.000Z

387

What constrains spread growth in forecasts ini2alized from  

E-Print Network (OSTI)

1 What constrains spread growth in forecasts ini2alized from ensemble Kalman filters? Tom from manner in which ini2al condi2ons are generated, some due to the model (e.g., stochas2c physics as error; part of spread growth from manner in which ini2al condi2ons are generated, some due

Hamill, Tom

388

Probabilistic Forecasts of Wind Speed: Ensemble Model Output Statistics  

E-Print Network (OSTI)

. Over the past two decades, ensembles of numerical weather prediction (NWP) models have been developed and phrases: Continuous ranked probability score; Density forecast; Ensem- ble system; Numerical weather prediction; Heteroskedastic censored regression; Tobit model; Wind energy. 1 #12;1 Introduction Accurate

Washington at Seattle, University of

389

Introduction An important goal in operational weather forecasting  

E-Print Network (OSTI)

sensitive areas. To answer these questions simulation experiments with state-of-the-art numerical weather prediction (NWP) models have proved great value to test future meteorological observing systems a priori102 Introduction An important goal in operational weather forecasting is to reduce the number

Haak, Hein

390

Operational Forecasts of Cloud Cover and Water Vapour  

E-Print Network (OSTI)

of the forecast programme, which involved the additional use of 10.7 µm GOES-8 satellite data and surface weather cirrus cloud cover 15 5. A satellite-derived extinction parameter 17 5.1 Background 17 5.2 Previous work 20 5.3 Continued development of a satellite-derived 22 extinction parameter 6. Suggestions

391

Increasing NOAA's computational capacity to improve global forecast modeling  

E-Print Network (OSTI)

competing numerical weather prediction centers such as the European Center for MediumRange Weather Forecasts (ECMWF). For most sensibleweather metrics, we lag 1 to 1.5 days (i.e., they make a 3.5day of NOAA's current investment in weather satellites. Without a modern data assimilation system

Hamill, Tom

392

Measuring forecast skill: is it real skill or  

E-Print Network (OSTI)

samples, then many verification metrics will credit a forecast with extra skill it doesn't deserve islands, zero meteorologists Imagine a planet with a global ocean and two isolated islands. Weather three metrics... (1) Brier Skill Score (2) Relative Operating Characteristic (3) Equitable Threat Score

Hamill, Tom

393

URBAN OZONE CONCENTRATION FORECASTING WITH ARTIFICIAL NEURAL NETWORK IN CORSICA  

E-Print Network (OSTI)

Perceptron; Ozone concentration. 1. Introduction Tropospheric ozone is a major air pollution problem, both, Ajaccio, France, e-mail: balu@univ-corse.fr Abstract: Atmospheric pollutants concentration forecasting is an important issue in air quality monitoring. Qualitair Corse, the organization responsible for monitoring air

Boyer, Edmond

394

Leveraging Weather Forecasts in Renewable Energy Navin Sharmaa,  

E-Print Network (OSTI)

Leveraging Weather Forecasts in Renewable Energy Systems Navin Sharmaa, , Jeremy Gummesonb , David, Binghamton, NY 13902 Abstract Systems that harvest environmental energy must carefully regulate their us- age to satisfy their demand. Regulating energy usage is challenging if a system's demands are not elastic, since

Shenoy, Prashant

395

Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems  

E-Print Network (OSTI)

Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems Navin Sharma,gummeson,irwin,shenoy}@cs.umass.edu Abstract--To sustain perpetual operation, systems that harvest environmental energy must carefully regulate their usage to satisfy their demand. Regulating energy usage is challenging if a system's demands

Shenoy, Prashant

396

Weather forecast-based optimization of integrated energy systems.  

SciTech Connect

In this work, we establish an on-line optimization framework to exploit detailed weather forecast information in the operation of integrated energy systems, such as buildings and photovoltaic/wind hybrid systems. We first discuss how the use of traditional reactive operation strategies that neglect the future evolution of the ambient conditions can translate in high operating costs. To overcome this problem, we propose the use of a supervisory dynamic optimization strategy that can lead to more proactive and cost-effective operations. The strategy is based on the solution of a receding-horizon stochastic dynamic optimization problem. This permits the direct incorporation of economic objectives, statistical forecast information, and operational constraints. To obtain the weather forecast information, we employ a state-of-the-art forecasting model initialized with real meteorological data. The statistical ambient information is obtained from a set of realizations generated by the weather model executed in an operational setting. We present proof-of-concept simulation studies to demonstrate that the proposed framework can lead to significant savings (more than 18% reduction) in operating costs.

Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.

2009-03-01T23:59:59.000Z

397

Journey data based arrival forecasting for bicycle hire schemes  

E-Print Network (OSTI)

Journey data based arrival forecasting for bicycle hire schemes Marcel C. Guenther and Jeremy T. The global emergence of city bicycle hire schemes has re- cently received a lot of attention of future bicycle migration trends, as these assist service providers to ensure availability of bicycles

Imperial College, London

398

FORECAST VERIFICATION OF EXTREMES: USE OF EXTREME VALUE THEORY  

E-Print Network (OSTI)

1 FORECAST VERIFICATION OF EXTREMES: USE OF EXTREME VALUE THEORY Rick Katz Institute for Study ON EXTREMES · Emil Gumbel (1891 ­ 1966) -- Pioneer in application of statistics of extremes (Germany, France) Conventional Methods (3) Extreme Value Theory (EVT) (4) Application of EVT to Verification (5) Frost

Katz, Richard

399

FORECAST VERIFICATION OF EXTREMES: USE OF EXTREME VALUE THEORY  

E-Print Network (OSTI)

1 FORECAST VERIFICATION OF EXTREMES: USE OF EXTREME VALUE THEORY Rick Katz Institute for Study on Extremes · Emil Gumbel (1891 ­ 1966) -- Pioneer in application of statistics of extremes "Il est impossible que l'improbable n'arrive jamais." #12;3 OUTLINE (1) Motivation (2) Conventional Methods (3) Extreme

Katz, Richard

400

FORECAST VERIFICATION OF EXTREMES: USE OF EXTREME VALUE THEORY  

E-Print Network (OSTI)

1 FORECAST VERIFICATION OF EXTREMES: USE OF EXTREME VALUE THEORY Rick Katz Institute for Study ON EXTREMES · Emil Gumbel (1891 ­ 1966) -- Pioneer in application of statistics of extremes "Il est impossible que l'improbable n'arrive jamais." #12;3 OUTLINE (1) Motivation (2) Conventional Methods (3) Extreme

Katz, Richard

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Seasonal Forecasting of Extreme Wind and Precipitation Frequencies in Europe  

E-Print Network (OSTI)

Seasonal Forecasting of Extreme Wind and Precipitation Frequencies in Europe Matthew J. Swann;Abstract Flood and wind damage to property and livelihoods resulting from extreme precipitation events variability of these extreme events can be closely related to the large-scale atmospheric circulation

Feigon, Brooke

402

Use of wind power forecasting in operational decisions.  

SciTech Connect

The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help efficiently address this challenge, and significant efforts have been invested in developing more accurate wind power forecasts. In this report, we document our work on the use of wind power forecasting in operational decisions.

Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V. (Decision and Information Sciences); (INESC Porto)

2011-11-29T23:59:59.000Z

403

U.S. Energy Information Administration (EIA)  

Gasoline and Diesel Fuel Update (EIA)

Release Date: June 2013 | Release Date: June 2013 | Report Number: DOE/EIA-0383(2012) Acronyms List of Acronyms AB Assembly Bill IHSGI IHS Global Insight AB32 California Assembly Bill 32 INFORUM Interindustry Forecasting Project at the University of Maryland ACI Activated carbon injection IOU Invester-owned utility AEO Annual Energy Outlook IREC Interstate Renewable Energy Council AEO2012 Annual Energy Outlook 2012 ITC Investment tax credit ANWR Arctic National Wildlife Refuge LCFS Low Carbon Fuel Standard ARRA2009 American Recovery and Reinvestment Act of 2009 LDV Light-duty vehicle ASHRAE American Society of Heating, Refrigerating, and Air-Conditioning Engineers LED Light-emitting diode Blue Chip Blue Chip Consensus LFMM Liquid Fuels Market Module

404

Power Projects  

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

Power Projects Power Projects Contact SN Customers Environmental Review-NEPA Operations & Maintenance Planning & Projects Power Marketing Rates You are here: SN Home page > About SNR Power Projects Central Valley: In California's Central Valley, 18 dams create reservoirs that can store 13 million acre-feet of water. The project's 615 miles of canals irrigate an area 400 miles long and 45 miles wide--almost one third of California. Powerplants at the dams have an installed capacity of 2,099 megawatts and provide enough energy for 650,000 people. Transmission lines total about 865 circuit-miles. Washoe: This project in west-central Nevada and east-central California was designed to improve the regulation of runoff from the Truckee and Carson river systems and to provide supplemental irrigation water and drainage, as well as water for municipal, industrial and fishery use. The project's Stampede Powerplant has a maximum capacity of 4 MW.

405

Navy mobility fuels forecasting system report: World petroleum trade forecasts for the year 2000  

SciTech Connect

The Middle East will continue to play the dominant role of a petroleum supplier in the world oil market in the year 2000, according to business-as-usual forecasts published by the US Department of Energy. However, interesting trade patterns will emerge as a result of the democratization in the Soviet Union and Eastern Europe. US petroleum imports will increase from 46% in 1989 to 49% in 2000. A significantly higher level of US petroleum imports (principally products) will be coming from Japan, the Soviet Union, and Eastern Europe. Several regions, the Far East, Japan, Latin American, and Africa will import more petroleum. Much uncertainty remains about of the level future Soviet crude oil production. USSR net petroleum exports will decrease; however, the United States and Canada will receive some of their imports from the Soviet Union due to changes in the world trade patterns. The Soviet Union can avoid becoming a net petroleum importer as long as it (1) maintains enough crude oil production to meet its own consumption and (2) maintains its existing refining capacities. Eastern Europe will import approximately 50% of its crude oil from the Middle East.

Das, S.

1991-12-01T23:59:59.000Z

406

EWEC 2006, Athens, The Anemos Wind Power Forecasting Platform Technology The Anemos Wind Power Forecasting Platform Technology -  

E-Print Network (OSTI)

EWEC 2006, Athens, The Anemos Wind Power Forecasting Platform Technology 1 The Anemos Wind Power a professional, flexible platform for operating wind power prediction models, laying the main focus on state models from all over Europe are able to work on this platform. Keywords: wind energy, wind power

Boyer, Edmond

407

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

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

Analysis & Projections Analysis & Projections Glossary › FAQS › Overview Projection Data Monthly Short-Term Forecasts to 2014 Annual Projections to 2040 International Projections Analysis & Projections Most Requested Annual Energy Outlook Related Congressional & Other Requests International Energy Outlook Related Presentations Short-Term Outlook Related Testimony All Reports Models & Documentation Price projections from Short-Term Energy Outlook › image chart of U.S. Gasoline and Crude Oil Prices as described in linked report Source: U.S. Energy Information Administration, Short-Term Energy Outlook, monthly. Increased tight oil production, vehicle efficiency reduce petroleum and liquid imports › graph of U.S. liquid fuels supply, as explained in the article text Source: U.S. Energy Information Administration, Today in Energy, December

408

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

Coal Coal Although coal use is expected to be displaced by natural gas in some parts of the world, only a slight drop in its share of total energy consumption is projected by 2025. Coal continues to dominate electricity and industrial sector fuel markets in emerging Asia. Figure 50. World Coal Consumption by Region, 1970-2025 (Billion Short Tons). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 51. Coal Share of World Energy Consumption by Sector, 2002, 2015, and 2025 (Percent). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 52. World Recoverable Coal Reserves. Need help, contact the National Energy Information Center at 202-586-8800. Figure Data In the International Energy Outlook 2005 (IEO2005) reference case, world

409

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

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

410

Progress report to the National Science Foundation for the period July 1, 1980 to December 31, 1981 of the project on cartel behavior and exhaustible resource supply : a case study of the world oil market  

E-Print Network (OSTI)

The M.I.T. World Oil Project has been developing forecasting methods that integrate the following considerations which influence investment in oil capacity and the level of oil exports: (1) the geology and microeconomics ...

International Energy Studies Program (Massachusetts Institute of Technology)

1982-01-01T23:59:59.000Z

411

Project Title  

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

CCS CCS August 20-22, 2013 2 Presentation Outline * Benefits to the program * Project overall objectives * Technical status * Project summary * Conclusions and future plans 3 Benefit to the Program * Develop technologies that will support industries' ability to predict CO 2 storage capacity in geologic formations to within ±30 percent. * Develop technologies to demonstrate that 99 percent of injected CO 2 remains in the injection zones. * This research project develops a reservoir scale CO 2 plume migration model at the Sleipner project, Norway. The Sleipner project in the Norwegian North Sea is the world's first commercial scale geological carbon storage project. 4D seismic data have delineated the CO 2 plume migration history. The relatively long history and high fidelity data make

412

Project Title  

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

Test and Evaluation of Test and Evaluation of Engineered Biomineralization Technology for Sealing Existing wells Project Number: FE0009599 Robin Gerlach Al Cunningham, Lee H Spangler Montana State University U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 Presentation Outline * Motivation & Benefit to the Program (required) * Benefit to the Program and Project Overview (required) * Background information - Project Concept (MICP) - Ureolytic Biomineralization, Biomineralization Sealing * Accomplishments to Date - Site Characterization - Site Preparation - Experimentation and Modeling - Field Deployable Injection Strategy Development * Summary

413

Project Title  

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

LBNL's Consolidated Sequestration Research Program (CSRP) Project Number FWP ESD09-056 Barry Freifeld Lawrence Berkeley National Laboratory U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 2 Presentation Outline * Benefits and Goals of GEO-SEQ * Technical Status - Otway Project (CO2CRC) - In Salah (BP, Sonatrach and Statoil) - Ketzin Project (GFZ, Potsdam) - Aquistore (PTRC) * Accomplishments and Summary * Future Plans 3 Benefit to the Program * Program goals being addressed: - Develop technologies to improve reservoir storage capacity estimation - Develop and validate technologies to ensure 99 percent storage permanence.

414

Project Title  

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

1-23, 2012 1-23, 2012 2 Presentation Outline I. Benefits II. Project Overview III. Technical Status A. Background B. Results IV. Accomplishments V. Summary 3 Benefit to the Program * Program goals. - Prediction of CO 2 storage capacity. * Project benefits. - Workforce/Student Training: Support of 3 student GAs in use of multiphase flow and geochemical models simulating CO 2 injection. - Support of Missouri DGLS Sequestration Program. 4 Project Overview: Goals and Objectives Project Goals and Objectives. 1. Training graduate students in use of multi-phase flow models related to CO 2 sequestration. 2. Training graduate students in use of geochemical models to assess interaction of CO

415

Project Title  

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

Center for Coal's Center for Coal's FY10 Carbon Sequestration Peer Review February 8 - 12, 2010 2 Collaborators * Tissa Illangasekare (Colorado School of Mines) * Michael Plampin (Colorado School of Mines) * Jeri Sullivan (LANL) * Shaoping Chu (LANL) * Jacob Bauman (LANL) * Mark Porter (LANL) 3 Presentation Outline * Benefit to the program * Project overview * Project technical status * Accomplishments to date * Future Plans * Appendix 4 Benefit to the program * Program goals being addressed (2011 TPP): - Develop technologies to demonstrate that 99 percent of injected CO 2 remains in the injection zones. * Project benefit: - This project is developing system modeling capabilities that can be used to address challenges associated with infrastructure development, integration, permanence &

416

Discontinued Projects  

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

This page lists projects that received a loan or a loan guarantee from DOE, but that are considered discontinued by LPO for one of several reasons.

417

project management  

National Nuclear Security Administration (NNSA)

the Baseline Change Proposal process. Two 400,000-gallon fire protection water supply tanks and associated pumping facilities were added. Later in the project, an additional...

418

Custom Projects  

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

and Incentive Payment - The ESIP works with utility, industry, and BPA to complete the measurement and verification, reporting and development of a custom project completion...

419

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

G: Key Assumptions for the IEO2005 Kyoto Protocol Case G: Key Assumptions for the IEO2005 Kyoto Protocol Case Energy-Related Emissions of Greenhouse Gases The System for the Analysis of Global energy Markets (SAGE)—the model used by the Energy Information Administration (EIA) to prepare the International Energy Outlook 2005 (IEO2005) mid-term projections—does not include non-energy-related emissions of greenhouse gases, which are estimated at about 15 to 20 percent of total greenhouse gas emissions, based on inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC). SAGE models global energy supply and demand and, therefore, does not address agricultural and other non-energy-related emissions. EIA implicitly assumes that percentage reductions of non-energy-related emissions and their associated abatement costs will be similar to those for energy-related emissions. Non-energy-related greenhouse gas emissions are likely to grow faster than energy-related emissions; however, the marginal abatement costs for non-energy-related greenhouse gas emissions are not known and cannot be estimated reliably. In SAGE, each region’s emissions reduction goal under the Kyoto Protocol is based only on the corresponding estimate of that region’s energy-related carbon dioxide emissions, as determined by EIA data. It is assumed that the required reductions will also be proportionately less than if all gases were included.

420

Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation  

SciTech Connect

Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards < forecasts) or natural gas-fired generation (if forwards > forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e.g., futures, swaps, and fixed-price physical supply contracts) to contemporaneous forecasts of spot natural gas prices, with the purpose of identifying any systematic differences between the two. Although our data set is quite limited, we find that over the past three years, forward gas prices for durations of 2-10 years have been considerably higher than most natural gas spot price forecasts, including the reference case forecasts developed by the Energy Information Administration (EIA). This difference is striking, and implies that resource planning and modeling exercises based on these forecasts over the past three years have yielded results that are biased in favor of gas-fired generation (again, presuming that long-term stability is desirable). As discussed later, these findings have important ramifications for resource planners, energy modelers, and policy-makers.

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-08-13T23:59:59.000Z

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Facility Disposition Projects  

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

Score Maturity Value Target Score Maturity Value Target Score A1 Cost Estimate H 7.5 1 7.5 5 37.5 5 37.5 A2 Cost Risk/Contingency Analysis P 3.0 1 3.0 5 15.0 5 15.0 A3 Funding Requirements/Profile H 7.5 1 7.5 4 30.0 5 37.5 A4 Independent Cost Estimate/Schedule Review P 3.0 N/A 0.0 5 15.0 5 15.0 A5 Life Cycle Cost P 3.0 1 3.0 4 12.0 5 15.0 A6 Forecast of Cost at Completion P 3.0 N/A 0.0 3 9.0 5 15.0 A7 Cost Estimate for Next Phase Work Scope P 3.0 5 15.0 5 15.0 5 15.0 Subtotal Cost 36.0 133.5 150.0 B1 Project Schedule H 7.5 1 7.5 4 30.0 5 37.5 B2 Major Milestones P 3.0 1 3.0 5 15.0 5 15.0 B3 Resource Loading P 3.0 1 3.0 4 12.0 5 15.0 B4 Critical Path Management H 7.5 1 7.5 4 30.0 5 37.5 B5 Schedule Risk/Contingency Analysis P 3.0 1 3.0 5 15.0 5 15.0 B6 Forecast of Schedule Completion P 3.0 N/A 0.0 3 9.0 5 15.0 B7 Schedule for Next Phase Work Scope P 3.0 5 15.0 5 15.0 5 15.0 Subtotal Schedule

422

Traditional (Conventional) Projects  

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

Score Maturity Value Target Score Maturity Value Target Score Maturity Value Target Score A1 Cost Estimate H 7.5 1 7.5 2 15.0 5 37.5 5 37.5 A2 Cost Risk/Contingency Analysis P 3.0 1 3.0 1 3.0 5 15.0 5 15.0 A3 Funding Requirements/Profile H 7.5 1 7.5 2 15.0 4 30.0 5 37.5 A4 Independent Cost Estimate/Schedule Review P 3.0 N/A 0.0 N/A 0.0 5 15.0 5 15.0 A5 Life Cycle Cost P 3.0 1 3.0 1 3.0 4 12.0 5 15.0 A6 Forecast of Cost at Completion P 3.0 N/A 0.0 N/A 0.0 3 9.0 5 15.0 A7 Cost Estimate for Next Phase Work Scope P 3.0 5 15.0 5 15.0 5 15.0 5 15.0 Subtotal Cost 36.0 51.0 133.5 150.0 B1 Project Schedule H 7.5 1 7.5 2 15.0 5 37.5 5 37.5 B2 Major Milestones P 3.0 1 3.0 2 6.0 5 15.0 5 15.0 B3 Resource Loading P 3.0 1 3.0 1 3.0 4 12.0 5 15.0 B4 Critical Path Management H 7.5 1 7.5 1 7.5 4 30.0 5 37.5 B5 Schedule Risk/Contingency Analysis P 3.0 1 3.0 1 3.0 5 15.0 5 15.0 B6 Forecast of Schedule Completion P 3.0

423

Forecast Calls for Better Models: Examining the Core  

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

Forecast Calls for Better Models: Examining the Core Forecast Calls for Better Models: Examining the Core Components of Arctic Clouds to Clear Their Influence on Climate For original submission and image(s), see ARM Research Highlights http://www.arm.gov/science/highlights/ Research Highlight Predicting how atmospheric aerosols influence cloud formation and the resulting feedback to climate is a challenge that limits the accuracy of atmospheric models. This is especially true in the Arctic, where mixed-phase (both ice- and liquid-based) clouds are frequently observed, but the processes that determine their composition are poorly understood. To obtain a closer look at what makes up Arctic clouds, scientists characterized cloud droplets and ice crystals collected at the North Slope of Alaska as part of the Indirect and Semi-Direct Aerosol Campaign (ISDAC) field study

424

Fundamentals, forecast combinations and nominal exchange-rate predictability  

Science Journals Connector (OSTI)

This paper investigates the out-predictability of fundamentals and forecast combinations. By adopting a panel-based specification, the paper obtains several interesting results. First, the Taylor-rule-based fundamental is the best among the four different fundamentals under consideration in out-of-sample contests. It provides strong evidence to out-predict the random walk over the PBW period. Second, relative to a single-equation prediction, panel predictions are generally able to enhance the statistical significance of beating the random walk. Third, combining forecasts from different fundamentals that have relatively strong out-predictability at a specific horizon does enhance both the statistical and economic significances of beating the random walk for the PBW period at short horizons.

Jyh-Lin Wu; Yi-Chiuan Wang

2013-01-01T23:59:59.000Z

425

Whistling Ridge Energy Project  

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

(PDCI) Upgrade Project Whistling Ridge Energy Project Line Rebuild, Relocation and Substation Projects Wind Projects Whistling Ridge Energy Project Bonneville Power...

426

Continuous Model Updating and Forecasting for a Naturally Fractured Reservoir  

E-Print Network (OSTI)

CONTINUOUS MODEL UPDATING AND FORECASTING FOR A NATURALLY FRACTURED RESERVOIR A Thesis by HISHAM HASSAN S. ALMOHAMMADI Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... guidance and support throughout my time here in Texas A&M University. I also would like to thank my committee members, Dr. Eduardo Gildin and Dr. Michael Sherman, for providing valued insight and help during the course of this research. I am indebted...

Almohammadi, Hisham

2013-07-26T23:59:59.000Z

427

NOAA National Weather Service I'm a weather forecaster.  

E-Print Network (OSTI)

.S.D EPARTMENT OF COM M ERCE How Do You Make a Weather Satellite? How Do You Make a Weather Satellite? #12;Well you put a truck in orbit? So it can carry all the things needed to make a working weather satelliteNOAA National Weather Service I'm a weather forecaster. I need to see clouds and storms from way up

Waliser, Duane E.

428

Application of a medium-range global hydrologic probabilistic forecast scheme to the Ohio River Basin  

SciTech Connect

A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003-2007. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium Range Weather Forecasts (ECMWF) analysis temperatures and wind, and Tropical Rainfall Monitoring Mission Multi Satellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF ensemble prediction system (EPS) 10-day ensemble forecast. A parallel set up was used where ECMWF EPS forecasts were interpolated to the spatial scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The flood prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. Initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.

Voisin, Nathalie; Pappenberger, Florian; Lettenmaier, D. P.; Buizza, Roberto; Schaake, John

2011-08-15T23:59:59.000Z

429

Project Title  

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

Snøhvit CO Snøhvit CO 2 Storage Project Project Number: FWP-FEW0174 Task 4 Principal Investigators: L. Chiaramonte, *J.A. White Team Members: Y. Hao, J. Wagoner, S. Walsh Lawrence Livermore National Laboratory This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Outline * Benefit to Program * Project Goals and Objectives * Technical Status * Summary & Accomplishments * Appendix 3 Benefit to the Program * The research project is focused on mechanical

430

Project title:  

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

Project title: Roseville Elverta (RSC-ELV) OPGW Replacement Project Project title: Roseville Elverta (RSC-ELV) OPGW Replacement Project Requested By: David Young Mail Code : N1410 Phone: 916-353-4542 Date Submitted: 5/4/2011 Date Required: 5/7/2011 Description of the Project: Purpose and Need The Western Area Power Administration (Western), Sierra Nevada Region (SNR), is responsible for the operation and maintenance (O&M) of federally owned and operated transmission lines, Switchyards, and facilities throughout California. Western and Reclamation must comply with the National Electric Safety Code, Western States Coordinating Council (WECC), and internal directives for protecting human safety, the physical environment, and maintaining the reliable operation of the transmission system. There is an existing OPGW communications fiber on the transmission towers between Roseville and Elverta

431

Project Title  

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

InSalah CO InSalah CO 2 Storage Project Project Number: FWP-FEW0174 Task 2 Principal Investigator: W. McNab Team Members: L. Chiaramonte, S. Ezzedine, W. Foxall, Y. Hao, A. Ramirez, *J.A. White Lawrence Livermore National Laboratory This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Outline * Benefit to Program * Project Goals and Objectives * Technical Status * Accomplishments * Summary * Appendix 3 Benefit to the Program * The research project is combining sophisticated

432

Project Title  

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

Space Geodesy, Seismology, Space Geodesy, Seismology, and Geochemistry for Monitoring Verification and Accounting of CO 2 in Sequestration Sites DE-FE0001580 Tim Dixon, University of South Florida Peter Swart, University of Miami U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Benefit to program * Goals & objectives * Preliminary InSAR results (site selection phase) * Project location * Project installed equipment * Specific project results * Summary 3 Benefit to the Program * Focused on monitoring, verification, and accounting (MVA) * If successful, our project will demonstrate the utility of low cost, surface

433

Project Title  

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

Carbon Storage R&D Project Review Meeting Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 DE-FE0001159 Advanced Technologies for Monitoring CO 2 Saturation and Pore Pressure in Geologic Formations Gary Mavko Rock Physics Project/Stanford University 2 Presentation Outline * Benefit to the Program * Project Overview * Motivating technical challenge * Approach * Technical Status - Laboratory results - Theoretical modeling * Summary Mavko: Stanford University 3 Benefit to the Program * Program goals being addressed. - Develop technologies that will support industries' ability to predict CO 2 storage capacity in geologic formations. - Develop technologies to demonstrate that 99% of injected CO 2 remains in injection zones. * Project benefits statement.

434

Project Title  

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

Large Volume Injection of CO Large Volume Injection of CO 2 to Assess Commercial Scale Geological Sequestration in Saline Formations in the Big Sky Region Project Number: DE-FC26-05NT42587 Dr. Lee Spangler Big Sky Carbon Sequestration Partnership Montana State University U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Goals and Objectives * Project overview * Kevin Dome characteristics * Project design philosophy * Infrastructure * Modeling * Monitoring * Project Opportunities 3 Benefit to the Program Program goals being addressed. * Develop technologies that will support industries' ability to predict CO

435

Project Title  

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

and Research on Probabilistic and Research on Probabilistic Hydro-Thermo-Mechanical (HTM) Modeling of CO 2 Geological Sequestration (GS) in Fractured Porous Rocks Project DE-FE0002058 Marte Gutierrez, Ph.D. Colorado School of Mines U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Benefit to the program (Program goals addressed and Project benefits) * Project goals and objectives * Technical status - Project tasks * Technical status - Key findings * Lessons learned * Summary - Accomplishments to date 3 Benefit to the Program * Program goals being addressed. - Develop technologies that will support industries'

436

Project Title  

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

Complexity and Choice of Complexity and Choice of Model Approaches for Practical Simulations of CO 2 Injection, Migration, Leakage, and Long- term Fate Karl W. Bandilla Princeton University U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 Project Number DE-FE0009563 2 Presentation Outline * Project Goals and Objectives * Project overview * Accomplishments * Summary 3 Benefit to the Program * The aim of the project is to develop criteria for the selection of the appropriate level of model complexity for CO 2 sequestration modeling at a given site. This will increase the confidence in modeling results, and reduce computational cost when appropriate.

437

EIA-Annual Energy Outlook Retrospective Review: Evaluation of Projections  

Gasoline and Diesel Fuel Update (EIA)

Retrospective Review: Evaluation of Projections in Past Editions (1982-2006) Retrospective Review: Evaluation of Projections in Past Editions (1982-2006) Annual Energy Outlook Retrospective Review: Evaluation of Projections in Past Editions (1982-2006) Each year since 1996, EIA's Office of Integrated Analysis and Forecasting has produced a comparison between realized energy outcomes and the projections included in previous editions of the AEO. Each year, the comparison adds the projections from the most recent AEO and updates the historical data to the most recently available. The comparison summarizes the relationship of the AEO reference case projections since 1982 to realized outcomes by calculating the average absolute percent differences for several of the major variables for AEO82 through AEO2006. Annual Energy Outlook Retrospective Review, 2006 Report

438

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

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

Analysis & Projections Analysis & Projections Glossary › FAQS › Overview Projection Data Monthly Short-Term Forecasts to 2014 Annual Projections to 2040 International Projections Analysis & Projections Most Requested Annual Energy Outlook Related Congressional & Other Requests International Energy Outlook Related Presentations Short-Term Outlook Related Testimony All Reports Models & Documentation Full report Sales of Fossil Fuels Produced from Federal and Indian Lands, FY 2003 through FY 2011 Release date: March 14, 2012 Background This paper was prepared in response to recent requests that the U.S. Energy Information Administration (EIA) provide updated summary information regarding fossil fuel production on Federal and Indian lands1 in the United States. It provides EIA's current best estimates of fossil fuels sales from

439

FORSITE, a multiple-project management system: production of critical-path development schedules for geothermal electric-power-generation projects  

SciTech Connect

FORSITE is an advanced project monitoring software system that is designed to track and forecast the development of multiple projects. This paper describes the organization and operation of the FORSITE system including its overall structure and the functional relationships between its files and data bases. The paper also illustrates the operation of the system with an example of a generic critical-path management schedule produced by FORSITE. A program listing and schedule summaries are included as appendices.

Bernstein, A.J.; Entingh, D.J.; Gerstein, R.E.; Gould, A.V.

1982-10-01T23:59:59.000Z

440

Projecting net incomes for Texas crop producers: an application of probabilistic forecasting  

E-Print Network (OSTI)

for this program, and expected prices. Payment planted acreage is calculated by subtracting set-aside, diverted and flex acres from complying base acreage. Set-aside, diverted and flex acres existed under past farm programs, but are not currently included...

Eggerman, Christopher Ryan

2006-10-30T23:59:59.000Z

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Live Webinar on the Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain  

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

On April 21, 2014 from 3:00 to 5:00 PM EST the Wind Program will hold a live webinar to provide information to potential applicants for this Funding Opportunity Announcement. There is no cost to...

442

NCEP Contributions to the WMO Severe Weather Forecasting Demonstration Project (SWFDP) and to the African Monsoon  

E-Print Network (OSTI)

wind convergences over Ethiopia, DCR, Gabon, Cameroon, CAR, and Congo-Brazzaville and the neighboring of Nigeria, Southern Chad, Cameroon, portion of Gabon, northern Congo-Brazzaville and DRC, Southern Sudan Gabon, Camer

443

Project Title  

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

CCS: CCS: Life Cycle Water Consumption for Carbon Capture and Storage Project Number 49607 Christopher Harto Argonne National Laboratory U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 2 Benefit to the Program * Program goals being addressed. - Develop technologies to improve reservoir storage efficiency while ensuring containment effectiveness. * Project benefits statement. - This work supports the development of active reservoir management approaches by identifying cost effective and environmentally benign strategies for managing extracted brines (Tasks 1 + 2). - This work will help identify water related constraints

444

Project Title  

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

Leakage Mitigation Leakage Mitigation using Engineered Biomineralized Sealing Technologies Project Number: FE0004478 Robin Gerlach Al Cunningham, Lee H Spangler Montana State University U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 2 Presentation Outline * Motivation & Benefit to the Program (required) * Benefit to the Program and Project Overview (required) * Background Information * Accomplishments to Date - Injection strategy development (control and prediction) - Large core tests - ambient pressure - Large core tests - high pressure - Small core tests - high pressure - MCDP, permeability and porosity assessments * Progress Assessment and Summary

445

Project Title  

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

CO2 Leakage Mitigation CO2 Leakage Mitigation using Engineered Biomineralized Sealing Technologies Project Number FE0004478 Lee H Spangler, Al Cunningham, Robin Gerlach Energy Research Institute Montana State University U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Motivation * Background information * Large core tests - ambient pressure * Large core tests - high pressure 3 Benefit to the Program Program goals being addressed. Develop technologies to demonstrate that 99 percent of injected CO 2 remains in the injection zones. Project benefits statement. The Engineered Biomineralized Sealing Technologies

446

Project Title  

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

CCS CCS Project Number 49607 Christopher Harto Argonne National Laboratory U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Benefit to the Program * Program goals being addressed. - Increased control of reservoir pressure, reduced risk of CO2 migration, and expanded formation storage capacity. * Project benefits statement. - This work supports the development of active reservoir management approaches by identifying cost effective and environmentally benign strategies for managing extracted brines (Tasks 1 + 2). - This work will help identify water related constraints on CCS deployment and provide insight into

447

Project Title  

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

of Multiphase of Multiphase Flow for Improved Injectivity and Trapping 4000.4.641.251.002 Dustin Crandall, URS PI: Grant Bromhal, NETL ORD Morgantown, West Virginia U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Benefit to the program * Project overview * Breakdown of FY12 project tasks * Facilities and personnel * Task progress to date * Planned task successes * Tech transfer and summary 3 Benefit to the Program * Program goal being addressed - Develop technologies that will support industries' ability to predict CO

448

Project Title  

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

Advanced Resources International, Inc. Advanced Resources International, Inc. U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Benefit to the Program * Project Overview * Technical Status * Accomplishments to Date * Summary * Appendix 3 Benefit to the Program * Program goal being addressed: - Develop technologies that will support industries' ability to predict CO 2 storage capacity in geologic formations to within ±30 percent. * Project benefits statement: - This research seeks to develop a set of robust mathematical modules to predict how coal and shale permeability and

449

Mid-term electricity market clearing price forecasting: A hybrid LSSVM and ARMAX approach  

Science Journals Connector (OSTI)

Abstract A hybrid mid-term electricity market clearing price (MCP) forecasting model combining both least squares support vector machine (LSSVM) and auto-regressive moving average with external input (ARMAX) modules is presented in this paper. Mid-term electricity MCP forecasting has become essential for resources reallocation, maintenance scheduling, bilateral contracting, budgeting and planning purposes. Currently, there are many techniques available for short-term electricity market clearing price (MCP) forecasting, but very little has been done in the area of mid-term electricity MCP forecasting. PJM interconnection data have been utilized to illustrate the proposed model with numerical examples. The proposed hybrid model showed improved forecasting accuracy compared to a forecasting model using a single LSSVM.

Xing Yan; Nurul A. Chowdhury

2013-01-01T23:59:59.000Z

450

Log-normal distribution based EMOS models for probabilistic wind speed forecasting  

E-Print Network (OSTI)

Ensembles of forecasts are obtained from multiple runs of numerical weather forecasting models with different initial conditions and typically employed to account for forecast uncertainties. However, biases and dispersion errors often occur in forecast ensembles, they are usually under-dispersive and uncalibrated and require statistical post-processing. We present an Ensemble Model Output Statistics (EMOS) method for calibration of wind speed forecasts based on the log-normal (LN) distribution, and we also show a regime-switching extension of the model which combines the previously studied truncated normal (TN) distribution with the LN. Both presented models are applied to wind speed forecasts of the eight-member University of Washington mesoscale ensemble, of the fifty-member ECMWF ensemble and of the eleven-member ALADIN-HUNEPS ensemble of the Hungarian Meteorological Service, and their predictive performances are compared to those of the TN and general extreme value (GEV) distribution based EMOS methods an...

Baran, Sndor

2014-01-01T23:59:59.000Z

451

Project Title  

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

SUMNER SUMNER COUNTY, KANSAS Project Number DE-FE0006821 W. Lynn Watney Kansas Geological Survey Lawrence, KS U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 Fountainview Wednesday 8-21-12 1:10-1:35 2 Presentation Outline * Benefits to the Program * Project Overview * Technical Status * Accomplishments to Date * Summary Small Scale Field Test Wellington Field Regional Assessment of deep saline Arbuckle aquifer Acknowledgements & Disclaimer Acknowledgements * The work supported by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL) under Grant DE-FE0002056 and DE- FE0006821, W.L. Watney and Jason Rush, Joint PIs. Project is managed and

452

Project Title  

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

0-22, 2013 0-22, 2013 Collaborators Zhengrong Wang, Yale University Kevin Johnson, University of Hawaii 2 Presentation Outline * Program Focus Area and DOE Connections * Goals and Objectives * Scope of Work * Technical Discussion * Accomplishments to Date * Project Wrap-up * Appendix (Organization Chart, Gantt Chart, and Bibliography 3 Benefit to the Program * Program goals addressed: - Technology development to predict CO 2 storage capacity - Demonstrate fate of injected CO 2 and most common contaminants * Project benefits statement: This research project conducts modeling, laboratory studies, and pilot-scale research aimed at developing new technologies and new systems for utilization of basalt formations for long term subsurface storage of CO 2 . Findings from this project

453

Project Title  

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

behavior of shales as behavior of shales as seals and storage reservoirs for CO2 Project Number: Car Stor_FY131415 Daniel J. Soeder USDOE/NETL/ORD U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 2 Project Overview: Goals and Objectives * Program Goals - Support industry's ability to predict CO 2 storage capacity in geologic formations to within ±30 percent. - Develop technologies to improve reservoir storage efficiency while ensuring containment effectiveness * Project Objectives - Assess how shales behave as caprocks in contact with CO 2 under a variety of conditions - Assess the viability of depleted gas shales to serve as storage reservoirs for sequestered CO

454

Project Title  

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

CO CO 2 leakage and cap rock remediation DE-FE0001132 Runar Nygaard Missouri University of Science and Technology U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 Presentation Outline * Benefit to the program * Project overview * Technical status * Accomplishments to date * Summary 2 3 Benefit to the Program * Program goals being addressed. - Develop technologies to demonstrate that 99 percent of injected CO 2 remains in the injection zones. * Project benefits statement. - The project develops a coupled reservoir and geomechanical modeling approach to simulate cap rock leakage and simulate the success of remediation

455

LUCF Projects  

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

RZWR'HVLJQDQG RZWR'HVLJQDQG +RZWR'HVLJQDQG ,PSOHPHQW&DUERQ ,PSOHPHQW&DUERQ 0HDVXULQJDQG0RQLWRULQJ 0HDVXULQJDQG0RQLWRULQJ $.WLYLWLHVIRU/8&) $.WLYLWLHVIRU/8&) 3URMH.WV 3URMH.WV Sandra Brown Winrock International sbrown@winrock.org Winrock International 2 3URMH.WGHVLJQLVVXHV 3URMH.WGHVLJQLVVXHV z Baselines and additionality z Leakage z Permanence z Measuring and monitoring z Issues vary with projects in developed versus developing countries Winrock International 3 /HDNDJH /HDNDJH z Leakage is the unanticipated loss or gain in carbon benefits outside of the project's boundary as a result of the project activities-divide into two types: - Primary leakage or activity shifting outside project area - Secondary leakage or market effects due to

456

Project Title  

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

Web-based CO Web-based CO 2 Subsurface Modeling Geologic Sequestration Training and Research Project Number DE-FE0002069 Christopher Paolini San Diego State University U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Project benefits and goals. * Web interface for simulating water-rock interaction. * Development of, and experience teaching, a new Carbon Capture and Sequestration course at San Diego State University. * Some noteworthy results of student research and training in CCS oriented geochemistry. * Status of active student geochemical and geomechancal modeling projects.

457

Project Title:  

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

Repair flowline 61-66-SX-3 Repair flowline 61-66-SX-3 DOE Code: Project Lead: Wes Riesland NEPA COMPLIANCE SURVEY # 291 Project Information Date: 3/1 1/2010 Contractor Code: Project Overview In order to repair this line it was decided to trench a line aproximately 100 feet and tie it into the line at 71-3- 1. What are the environmental sx-3. This will get us out of the old flow line which has been repaired 5-6 times. this will mitigate the chances impacts? of having spills in the future. 2. What is the legal location? This flowline runs from the well77-s-1 0 to the B-2-10 manifold.+ "/-,~?X3 3. What is the duration of the project? Approximately 10 hours(1 day) to complete 4. What major equipment will be used backhoe and operator and one hand if any (work over rig. drilling rig.

458

Project Title  

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

Co-Sequestration Co-Sequestration Studies Project Number 58159 Task 2 B. Peter McGrail Pacific Northwest National Laboratory U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Program Focus Area and DOE Connections * Goals and Objectives * Scope of Work * Technical Discussion * Accomplishments to Date * Project Wrap-up * Appendix (Organization Chart, Gantt Chart, and Bibliography 3 Benefit to the Program * Program goals addressed: - Technology development to predict CO 2 and mixed gas storage capacity in various geologic settings - Demonstrate fate of injected mixed gases * Project benefits statement:

459

Project X  

E-Print Network (OSTI)

provided by Project X would be a cost- effective approach toin Section I and for the cost estimate necessary as part ofby DOE order 413.3b. The cost range required for CD-0 will

Holmes, Steve

2014-01-01T23:59:59.000Z

460

Project Title  

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

Model Complexity in Geological Carbon Model Complexity in Geological Carbon Sequestration: A Design of Experiment (DoE) & Response Surface (RS) Uncertainty Analysis Project Number: DE-FE-0009238 Mingkan Zhang 1 , Ye Zhang 1 , Peter Lichtner 2 1. Dept. of Geology & Geophysics, University of Wyoming, Laramie, Wyoming 2. OFM Research, Inc., Santa Fe, New Mexico U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 2 Presentation Outline * Project major goals and benefits; * Detailed project objectives & success criteria; * Accomplishments to date; * Summary of results; * Appendix (organization chart; Gantt chart; additional results). Dept. of Geology & Geophysics, University of Wyoming

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Project Title  

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

Region Region DE-FE0001812 Brian J. McPherson University of Utah U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 2 Acknowledgements * NETL * Shell * Tri-State * Trapper Mining * State of Colorado 3 Presentation Outline * Program Benefits * Project / Program Goals * Technical Status: Finalizing 10-Point Protocol for CO 2 Storage Site Characterization * Key Accomplishments * Summary 4 Presentation Outline * Program Benefits * Project / Program Goals * Technical Status: Finalizing 10-Point Protocol for CO 2 Storage Site Characterization * Key Accomplishments * Summary 5 Benefit to the Program Program Goals Being Addressed by this Project

462

Central Wind Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities: Revised Edition  

SciTech Connect

The report and accompanying table addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America. The first part of the table focuses on electric utilities and regional transmission organizations that have central wind power forecasting in place; the second part focuses on electric utilities and regional transmission organizations that plan to adopt central wind power forecasting in 2010. This is an update of the December 2009 report, NREL/SR-550-46763.

Rogers, J.; Porter, K.

2011-03-01T23:59:59.000Z

463

Comparison of Airbus, Boeing, Rolls-Royce and AVITAS market forecasts  

Science Journals Connector (OSTI)

Forecasts of future world demand for commercial aircraft are published fairly regularly by Airbus and Boeing. Other players in the aviation business, Rolls Royce and AVITAS, have also published forecasts in the past year. This article analyses and compares the methods used and assumptions made by the several forecasters. It concludes that there are wide areas of similarity in the approaches used and highlights the most significant area of divergence.

Ralph Anker

2000-01-01T23:59:59.000Z

464

Forecasting the monthly volume of orders for southern pine lumber - an econometric model  

E-Print Network (OSTI)

to measure various aspects of the California redwood lumber industry. The first sought to explain the economic struc- ture of the short-run market for redwood lumber by preparing short-range forecasts of price, new orders, shipments, produc- tion, stocks... regression coefficients (20) . The second study was directed at developing a short-run forecast of new orders for redwood lumber (21) . Several forecasting techniques were developed, but econometrics, i. e. , multiple regression analysis, provided...

Jackson, Ben Douglas

2012-06-07T23:59:59.000Z

465

ENERGY-SPECIFIC SOLAR RADIATION DATA FROM MSG: CURRENT STATUS OF THE HELIOSAT-3 PROJECT  

E-Print Network (OSTI)

ENERGY-SPECIFIC SOLAR RADIATION DATA FROM MSG: CURRENT STATUS OF THE HELIOSAT-3 PROJECT Marion Solar energy technologies such as photovoltaics, solar thermal power plants, passive solar heating and operating of solar energy systems and as basis data set for electricity load forecasting. Both long term

Heinemann, Detlev

466

Energy Department Announces $2.5 Million to Improve Wind Forecasting...  

Energy Savers (EERE)

better forecasts, wind energy plant operators and industry professionals can ensure wind turbines operate closer to maximum capacity, leading to lower energy costs for consumers....

467

Intra-hour wind power variability assessment using the conditional range metric : quantification, forecasting and applications.  

E-Print Network (OSTI)

??The research presented herein concentrates on the quantification, assessment and forecasting of intra-hour wind power variability. Wind power is intrinsically variable and, due to the (more)

Boutsika, Thekla

2013-01-01T23:59:59.000Z

468

Crude oil prices and petroleum inventories : remedies for a broken oil price forecasting model.  

E-Print Network (OSTI)

??The empirical relationship between crude oil prices and petroleum inventories has been exploited in a number of short-term oil price forecasting models. Some of the (more)

Grimstad, Dan

2007-01-01T23:59:59.000Z

469

Study and implementation of mesoscale weather forecasting models in the wind industry.  

E-Print Network (OSTI)

?? As the wind industry is developing, it is asking for more reliable short-term wind forecasts to better manage the wind farms operations and electricity (more)

Jourdier, Bndicte

2012-01-01T23:59:59.000Z

470

Value of Improved Wind Power Forecasting in the Western Interconnection (Poster)  

SciTech Connect

Wind power forecasting is a necessary and important technology for incorporating wind power into the unit commitment and dispatch process. It is expected to become increasingly important with higher renewable energy penetration rates and progress toward the smart grid. There is consensus that wind power forecasting can help utility operations with increasing wind power penetration; however, there is far from a consensus about the economic value of improved forecasts. This work explores the value of improved wind power forecasting in the Western Interconnection of the United States.

Hodge, B.

2013-12-01T23:59:59.000Z

471

A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting  

E-Print Network (OSTI)

iscriticalforcoastalCaliforniasolarforecasting. affectingsolarirradianceinsouthernCalifornia. solar photovoltaicgeneration(thesouthernCalifornia

Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

2013-01-01T23:59:59.000Z

472

E-Print Network 3.0 - analytical energy forecasting Sample Search...  

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

of PV energy production using... Short term forecasting of solar radiation based on satellite data Elke Lorenz, Annette Hammer... , Detlev Heinemann Energy and Semiconductor...

473

Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe  

Science Journals Connector (OSTI)

Abstract This article combines and discusses three independent validations of global horizontal irradiance (GHI) multi-day forecast models that were conducted in the US, Canada and Europe. All forecast models are based directly or indirectly on numerical weather prediction (NWP). Two models are common to the three validation efforts the ECMWF global model and the GFS-driven WRF mesoscale model and allow general observations: (1) the GFS-based WRF- model forecasts do not perform as well as global forecast-based approaches such as ECMWF and (2) the simple averaging of models output tends to perform better than individual models.

Richard Perez; Elke Lorenz; Sophie Pelland; Mark Beauharnois; Glenn Van Knowe; Karl Hemker Jr.; Detlev Heinemann; Jan Remund; Stefan C. Mller; Wolfgang Traunmller; Gerald Steinmauer; David Pozo; Jose A. Ruiz-Arias; Vicente Lara-Fanego; Lourdes Ramirez-Santigosa; Martin Gaston-Romero; Luis M. Pomares

2013-01-01T23:59:59.000Z

474

ARM - Science Project Ideas  

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

forecasts in the local newspaper or television station. For this you will need a thermometer, and you will need to make your own barometer,and wind speed and wind direction...

475

Project Fact Sheet Project Update  

E-Print Network (OSTI)

medical and dental centre; shop and café area for students and vacation accommodation centre. The new & Figures: Budget: £51,074,000 Funding Source: Capital Plan Construction Project Programme: Start on Site

476

Preparing for Project Implementation Financing Project Implementation  

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

for Project Implementation Financing Project Implementation Save Energy Now LEADER Web Conference Project Implementation Seminar Series Save Energy Now LEADER Web Conference...

477

Forecast of Contracting and Subcontracting Opportunities, Fiscal year 1995  

SciTech Connect

Welcome to the US Department of Energy`s Forecast of Contracting and Subcontracting Opportunities. This forecast, which is published pursuant to Public Low 100--656, ``Business Opportunity Development Reform Act of 1988,`` is intended to inform small business concerns, including those owned and controlled by socially and economically disadvantaged individuals, and women-owned small business concerns, of the anticipated fiscal year 1995 contracting and subcontracting opportunities with the Department of Energy and its management and operating contractors and environmental restoration and waste management contractors. This document will provide the small business contractor with advance notice of the Department`s procurement plans as they pertain to small, small disadvantaged and women-owned small business concerns.Opportunities contained in the forecast support the mission of the Department, to serve as advocate for the notion`s energy production, regulation, demonstration, conservation, reserve maintenance, nuclear weapons and defense research, development and testing, when it is a national priority. The Department`s responsibilities include long-term, high-risk research and development of energy technology, the marketing of Federal power, and maintenance of a central energy data collection and analysis program. A key mission for the Department is to identify and reduce risks, as well as manage waste at more than 100 sites in 34 states and territories, where nuclear energy or weapons research and production resulted in radioactive, hazardous, and mixed waste contamination. Each fiscal year, the Department establishes contracting goals to increase contracts to small business concerns and meet our mission objectives.

Not Available

1995-02-01T23:59:59.000Z

478

Annual Energy Outlook 2006 with Projections to 2030  

Gasoline and Diesel Fuel Update (EIA)

Only Only GII produces a comprehensive energy projec- tion with a time horizon similar to that of AEO2006. Other organizations address one or more aspects of the energy markets. The most recent projection from GII, as well as others that concentrate on economic growth, international oil prices, energy consumption, electricity, natural gas, petroleum, and coal, are com- pared here with the AEO2006 projections. Economic Growth In the AEO2006 reference case, the projected growth in real GDP, based on 2000 chain-weighted dollars, is 3.0 percent per year from 2004 to 2030 (Table 19). For the period from 2004 to 2025, real GDP growth in the AEO2006 reference case is similar to the average annual growth projected in AEO2005. The AEO2006 projections of economic growth are based on the August short-term forecast of GII, extended by EIA through 2030 and modified to reflect EIA's view on energy prices,

479

EIA-Annual Energy Outlook Retrospective Review: Evaluation of Projections  

Gasoline and Diesel Fuel Update (EIA)

9) 9) Annual Energy Outlook Retrospective Review: Evaluation of Projections in Past Editions (1982-2009) Each year since 1996, EIA's Office of Integrated Analysis and Forecasting has produced a comparison between realized energy outcomes and the projections included in previous editions of the AEO. Each year, the comparison adds the projections from the most recent AEO and updates the historical data to the most recently available. The comparison summarizes the relationship of the AEO reference case projections since 1982 to realized outcomes by calculating the average absolute percent differences for several of the major variables for AEO82 through AEO2009. Annual Energy Outlook Restrospective Review, 2009 Report pdf images Table 1. Comparison of Absolute Percent Difference between AEO Reference Case Projections

480

Data transforms with exponential smoothing methods of forecasting  

Science Journals Connector (OSTI)

Abstract In this paper, transforms are used with exponential smoothing, in the quest for better forecasts. Two types of transforms are explored: those which are applied to a time series directly, and those which are applied indirectly to the prediction errors. The various transforms are tested on a large number of time series from the M3 competition, and ANOVA is applied to the results. We find that the non-transformed time series is significantly worse than some transforms on the monthly data, and on a distribution-based performance measure for both annual and quarterly data.

Adrian N. Beaumont

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "interindustry forecasting project" 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

Project Title  

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

Monitoring Geological CO Monitoring Geological CO 2 Sequestration using Perfluorocarbon and Stable Isotope Tracers Project Number FEAA-045 Tommy J. Phelps and David R. Cole* Oak Ridge National Laboratory Phone: 865-574-7290 email: phelpstj@ornl.gov (*The Ohio State University) U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Developing the Technologies and Building the Infrastructure for CO 2 Storage August 22, 2013 2 Project Overview: Goals and Objectives Goal: Develop methods to interrogate subsurface for improved CO 2 sequestration, field test characterization and MVA, demonstrate CO 2 remains in zone, and tech transfer. Objectives: 1. Assessment of injections in field. PFT gas tracers are analyzed by GC-ECD to

482

Project Homepage  

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

Middle School Home Energy Audit Middle School Home Energy Audit Project Homepage NTEP Home - Project Homepage - Teacher Homepage - Student Pages Abstract: This set of lessons provides an opportunity for midlevel students to gain a basic understanding of how energy is turned into power, how power is measured using a meter, the costs of those units and the eventual reduction of energy consumption and cost to the consumer. Introduction to Research: By conducting energy audits of their own homes and completing exercises to gain baclground information, students begin to see the importance of energy in their daily lives. By using the Internet as a research tool, students gain develop research skills as they gain knowledge for their project. They use e-mail to collaborate with energy experts and share results with other

483

Project Title  

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

Title: DEVELOPING A Title: DEVELOPING A COMPREHENSIVE RISK ASSESMENT FRAMEWORK FOR GEOLOGICAL STORAGE OF CO2 Ian Duncan University of Texas U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 2 Presentation Outline 1. Benefit to the Program 2. Goals and Objectives 3. Technical Status Project 4. Accomplishments to Date 5. Summary 3 Benefit to the Program The research project is developing a comprehensive understanding of the programmatic (business), and technical risks associated with CCS particularly the likelihood of leakage and its potential consequences. This contributes to the Carbon Storage Program's effort of ensuring 99 percent CO

484

Project Title  

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

Carbon Storage R&D Project Review Meeting Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Acknowledgments Dave Harris, Kentucky Geological Survey Dave Barnes, Western Michigan University John Rupp, Indiana Geological Survey Scott Marsteller, Schlumberger Carbon Services John McBride, Brigham Young University * Project is funded by the U.S. Department of Energy through the National Energy Technology Laboratory (NETL) and by a cost share agreement with the Illinois Department of Commerce and Economic Opportunity, Office of Coal Development through the Illinois Clean Coal Institute * ConocoPhillips: in-kind match * Western Kentucky Carbon Storage Foundation: matching funding * SeisRes 2020, Houston: VSP acquisition and processing

485

Project Title  

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

to Analyze Spatial and Temporal to Analyze Spatial and Temporal Heterogeneities in Reservoir and Seal Petrology, Mineralogy, and Geochemistry: Implications for CO 2 Sequestration Prediction, Simulation, and Monitoring Project Number DE-FE0001852 Dr. Brenda B. Bowen Purdue University (now at the University of Utah) U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Introduction to the project * Tasks * Student training * Student research successes * Lessons learned and future plans 3 Benefit to the Program * Addresses Carbon Storage Program major goals: - Develop technologies that will support industries' ability to predict CO

486

Project Title  

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

Project Results from Simulation Project Results from Simulation Framework for Regional Geologic CO 2 Storage Infrastructure along Arches Province of Midwest United States DOE Award No. DE-FE0001034 Ohio Dept. of Dev. Grant CDO/D-10-03 U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting August 21-23, 2012 Joel Sminchak and Neeraj Gupta Battelle Energy Systems sminchak@battelle.org, 614-424-7392 gupta@battelle.org, 614-424-3820 BUSINESS SENSITIVE 2 Presentation Outline 1. Technical Status 2. Background (CO 2 Sources, Geologic Setting) 3. Injection Well history 4. Geocellular Model Development 5. Geological Data (Geological dataset, Geostatistics) 6. Geocellular porosity/permeability model development 7. Pipeline Routing Analysis

487

Research projects  

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

Yuan » Research projects Yuan » Research projects Research projects Research Interests Scientific computing, domain decomposition methods Linear solvers for sparse matrices Computational plasma physics Grid generation techniques GPU computing Current Research PDSLin: A hybrid linear solver for large-scale highly-indefinite linear systems The Parallel Domain decomposition Schur complement based Linear solver (PDSLin), which implements a hybrid (direct and iterative) linear solver based on a non-overlapping domain decomposition technique called chur complement method, and it has two levels of parallelism: a) to solve independent subdomains in parallel and b) to apply multiple processors per subdomain. In such a framework, load imbalance and excessive communication lead to the performance bottlenecks, and several techniques are developed

488

Project Title  

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

SECARB Anthropogenic Test: SECARB Anthropogenic Test: CO 2 Capture/Transportation/Storage Project # DE-FC26-05NT42590 Jerry Hill, Southern Sates Energy Board Richard A. Esposito, Southern Company U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 Presentation Outline * Benefit to the Program * Project Overview * Technical Status - CO 2 Capture - CO 2 Transportation - CO 2 Storage * Accomplishments to Date * Organization Chart * Gantt Chart * Bibliography * Summary Benefit to the Program 1. Predict storage capacities within +/- 30% * Conducted high resolution reservoir characterization of the Paluxy saline formation key

489

Project Title  

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

Investigation of the CO Investigation of the CO 2 Sequestration in Depleted Shale Gas Formations Project Number DE-FE-0004731 Jennifer Wilcox, Tony Kovscek, Mark Zoback Stanford University, School of Earth Sciences U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Outline * Project Benefits * Technical Status * Imaging at mm- to micron-scales using CT - Permeability measurements and application of the Klinkenberg effect - Molecular Dynamics simulations for permeability and viscosity estimates * Accomplishments to Date * Summary Stanford University 3 Benefit to the Program * Carbon Storage Program major goals

490

Project Title  

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

Fidelity Computational Analysis of Fidelity Computational Analysis of CO2 Trappings at Pore-scales Project Number: DE-FE0002407 Vinod Kumar (vkumar@utep.edu) & Paul Delgado (pmdelgado2@utep.edu) University of Texas at El Paso U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 Collaborators: Dr. C. Harris (Shell Oil Company/Imperial College), Dr. G. Bromhal (NETL), Dr. M. Ferer (WVU/NETL), Dr. D. Crandall (NETL-Ctr), and Dr. D. McIntyre (NETL). 2 Presentation Outline * Benefit to the Program * Project Overview * Technical Status - Pore-network modeling - Conductance derivation for irregular geom. - Pore-to-CFD Computations

491

Project Title  

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

Project Number (DE-FE0002056) W. Lynn Watney & Jason Rush (Joint PIs) Kansas Geological Survey Lawrence, KS 66047 U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Benefits to the Program * Project Overview * Technical Status * Accomplishments to Date * Summary KANSAS STATE UNIVERSITY Bittersweet Energy Inc. Partners FE0002056 Devilbiss Coring Service Basic Energy Services Wellington Field Operator Industrial and Electrical Power Sources of CO 2 Southwest Kansas CO 2 -EOR Initiative Industry Partners (modeling 4 Chester/Morrowan oil fields to make CO2 ready) +drilling and seismic contractors TBN

492

Project Title  

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

Project Number (DE-FE0002056) U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 W. Lynn Watney & Jason Rush (Joint PIs) Kansas Geological Survey Lawrence, KS 66047 Brighton 1&2 2:40 August 20, 2013 2 Presentation Outline * Benefits to the Program * Project Overview * Technical Status * Accomplishments to Date * Summary ORGANIZATIONAL STRUCTURE Modeling CO 2 Sequestration in Saline A quifer and Depleted Oil Reservoir to Evaluate Regional CO 2 Sequestration Potential of Ozark Plateau A quifer System, South-Central Kansas Co-Principal Investigators Co-Principal Investigators Kerry D. Newell -- stratigraphy, geochemistry

493

Project Title  

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

Tracer for Tracking Permanent CO 2 Storage in Basaltic Rocks DE-FE0004847 Jennifer Hall Columbia University in the City of New York U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Benefit to the Program * Project Overview * Technical Status * Conservative and Reactive Tracer Techniques * Accomplishments to Date * Summary 3 Benefit to the Program * The goal of the project is to develop and test novel geochemical tracer techniques for quantitative monitoring, verification and accounting of stored CO 2 . These techniques contribute to the Carbon Storage Program's

494

Project Title  

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

and Geotechnical Site and Geotechnical Site Investigations for the Design of a CO 2 Rich Flue Gas Direct Injection Facility Project Number DOE Grant FE0001833 Paul Metz Department of Mining & Geological Engineering University of Alaska Fairbanks U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Presentation Outline * Benefit to the Program * Project Overview: Goals and Objectives * Technical Status * Accomplishments to Date * Summary * Appendix: Not Included in Presentation 3 Benefit to the Program * Carbon Storage Program Major Goals: - Develop technologies that will support industries' ability to

495

Project Title  

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

Scale CO Scale CO 2 Injection and Optimization of Storage Capacity in the Southeastern United States Project Number: DE-FE0010554 George J. Koperna, Jr. Shawna Cyphers Advanced Resources International U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 Presentation Outline * Program Goals * Benefits Statement * Project Overview - Goals - Objectives * Technical Status * Accomplishments to Date * Summary * Appendix USDOE/NETL Program Goals * Support industry's ability to predict CO 2 storage capacity in geologic formations to within ±30 percent. * Develop and validate technologies to ensure 99 percent storage permanence. * Develop technologies to improve reservoir storage

496

Project Title  

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

SUMNER COUNTY, KANSAS DE-FE0006821 W. Lynn Watney, Jason Rush, Joint PIs Kansas Geological Survey The University of Kansas Lawrence, KS U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 Brighton 1&2 Wednesday 8-21-13 1:10-1:35 2 Presentation Outline * Benefit to the Program * Project Overview * Technical Status * Accomplishments to Date * Summary 2 Small Scale Field Test Wellington Field Regional Assessment of deep saline Arbuckle aquifer Project Team DOE-NETL Contract #FE0006821 KANSAS STATE UNIVERSITY 3 L. Watney (Joint PI), J. Rush (Joint PI), J. Doveton, E. Holubnyak, M. Fazelalavi, R. Miller, D. Newell, J. Raney

497

Project Title  

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

Seal Repair Using Seal Repair Using Nanocomposite Materials Project Number DE-FE0009562 John Stormont, Mahmoud Reda Taha University of New Mexico U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 Ed Matteo, Thomas Dewers Sandia National Laboratories 2 Presentation Outline * Introduction and overview * Materials synthesis * Materials testing and characterization * Annular seal system testing * Numerical simulation * Summary 3 Benefit to the Program * BENEFITS STATEMENT: The project involves the development and testing of polymer-cement nanocomposites for repairing flaws in annular wellbore seals. These materials will have superior characteristics compared to conventional

498

Project Title  

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

Wyoming: MVA Techniques for Determining Gas Transport and Caprock Integrity Project Number DE-FE0002112 PIs Drs. John Kaszuba and Kenneth Sims Virginia Marcon University of Wyoming U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Benefits to the Program * Project Overview * Technical Status - Results - Conclusions - Next Steps * Summary 3 Benefit to the Program * Program goal being addressed. - Develop technologies to demonstrate that 99 percent of injected CO 2 remains in the injection zones. - Monitoring, Verification, and Accounting (MVA). MVA technologies seek to monitor, verify, and

499

Project Title  

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

Impact of CO Impact of CO 2 Injection on the Subsurface Microbial Community in an Illinois Basin CCS Reservoir: Integrated Student Training in Geoscience and Geomicrobiology Project Number (DEFE0002421) Dr. Yiran Dong Drs. Bruce W. Fouke, Robert A. Sanford, Stephen Marshak University of Illinois-Urbana Champaign U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Benefit to the Program * Technical status * Results and discussion * Summary * Appendix 3 Benefit to the Program This research project has developed scientific, technical and institutional collaborations for the development of

500

Project Title  

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

Mohammad Piri and Felipe Pereira Mohammad Piri and Felipe Pereira University of Wyoming U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 2013 2 Presentation Outline * Benefit to the Program * Project Overview * Technical Status o Experimentation: core-flooding and IFT/CA o Pore-scale modeling modeling * Accomplishments to Date * Summary University of Wyoming 3 Benefit to the Program * Program goal: o 'Develop technologies that will support industries' ability to predict CO 2 storage capacity in geologic formations to within ±30 percent.' * Benefits statement: o The research project is focused on performing reservoir conditions experiments to measure steady-state relative permeabilities,