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


1

Probabilistic Verification of Monthly Temperature Forecasts  

Science Conference Proceedings (OSTI)

Monthly forecasting bridges the gap between medium-range weather forecasting and seasonal predictions. While such forecasts in the prediction range of 1–4 weeks are vital to many applications in the context of weather and climate risk management, ...

Andreas P. Weigel; Daniel Baggenstos; Mark A. Liniger; Frédéric Vitart; Christof Appenzeller

2008-12-01T23:59:59.000Z

2

Rolling 12 Month Forecast November-2008.xls  

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

Month Exceedence Level: 90% (Dry) First Preference CVP Generation Project Use November 2008 October 2009 November 2008 Twelve-Month Forecast of CVP Generation and Base Resource...

3

Western Area Power Administration Starting Forecast Month: Sierra...  

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

Month CVP Generation Project Use First Preference Purchases and Exchanges Base Resource January 2014 Twelve-Month Forecast of CVP Generation and Base Resource January 2014 December...

4

Spatial Structure, Forecast Errors, and Predictability of the South Asian Monsoon in CFS Monthly Retrospective Forecasts  

Science Conference Proceedings (OSTI)

The spatial structure of the boreal summer South Asian monsoon in the ensemble mean of monthly retrospective forecasts by the Climate Forecast System of the National Centers for Environmental Prediction is examined. The forecast errors and ...

Hae-Kyung Lee Drbohlav; V. Krishnamurthy

2010-09-01T23:59:59.000Z

5

One-Month Forecast Experiments—without Anomaly Boundary Forcings  

Science Conference Proceedings (OSTI)

A series of one-month forecasts were carried out for eight January cases, using a particular prediction model and prescribing climatological sea-surface temperature as the boundary condition. Each forecast is a stochastic prediction that consists ...

K. Miyakoda; J. Sirutis; J. Ploshay

1986-12-01T23:59:59.000Z

6

Western Area Power Administration Starting Forecast Month: Sierra...  

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

Starting Forecast Month: Sierra Nevada Region Through Values at Load Center (Tracy Substation) Reg & Res CVP Maximum Capability CVP Energy Generation Peak Project Use Demand...

7

Western Area Power Administration Starting Forecast Month: Sierra...  

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

based on Green Book ("Average") values. Base Resource September 2013 Twelve-Month Forecast of CVP Generation and Base Resource September 2013 August 2014 Exceedence Level: 90%...

8

Western Area Power Administration Starting Forecast Month: Sierra...  

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

Use First Preference Purchases and Exchanges Base Resource October 2013 Twelve-Month Forecast of CVP Generation and Base Resource October 2013 September 2014 Exceedence Level: 90%...

9

Western Area Power Administration Starting Forecast Month: Sierra...  

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

the 10% Exceedence Level based on Green Book ("Above Normal") values. Base Resource December 2013 Twelve-Month Forecast of CVP Generation and Base Resource December 2013 November...

10

Western Area Power Administration Starting Forecast Month: Sierra...  

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

Use First Preference Purchases and Exchanges Base Resource April 2013 Twelve-Month Forecast of CVP Generation and Base Resource April 2013 March 2014 Exceedence Level: 90% (Dry)...

11

Western Area Power Administration Starting Forecast Month: Sierra...  

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

for 90% Exceedence Levels are based on USBR August 2012 50% Exceedence monthly water forecast for months prior to December 2012. For December 2012 and beyond, Green Book 2004...

12

Western Area Power Administration Starting Forecast Month: Sierra...  

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

for 90% Exceedence Levels are based on USBR Septem 2012 50% Exceedence monthly water forecast for months prior to December 2012. For December 2012 and beyond, Green Book 2004...

13

Forecasts of Monthly 700 mb Height: Verification and Specification Experiments  

Science Conference Proceedings (OSTI)

Twenty-five years (1958-82) of monthly 700 ml, geopotential forecasts produced by the U.S. National Weather Service are verified and then used in a series of temperature specification experiments. The forecasts show skill with respect to ...

John E. Walsh

1984-11-01T23:59:59.000Z

14

SLCA/IP Hydro Generation Estimates Month Forecast Generation  

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

42014 15:46 SLCAIP Hydro Generation Estimates Month Forecast Generation less losses (kWh) Less Proj. Use (kWh) Net Generation (kWh) SHP Deliveries (kWh) Firming Purchases (kWh)...

15

SLCA/IP Hydro Generation Estimates Month Forecast Generation  

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

13 16:39 SLCAIP Hydro Generation Estimates Month Forecast Generation less losses (kWh) Less Proj. Use (kWh) Net Generation (kWh) SHP Deliveries (kWh) Firming Purchases (kWh)...

16

Subgrid Scale Physics in 1-Month Forecasts. Part I: Experiment with Four Parameterization Packages  

Science Conference Proceedings (OSTI)

Four packages of subgrid scale (SGS) physics parameterization are tested by including them in a general circulation model and by applying the four models to 1-month forecasts. The four models are formulated by accumulatively increasing the ...

J. Sirutis; K. Miyakoda

1990-05-01T23:59:59.000Z

17

Autoregressive forecast of monthly total ozone concentration: A neurocomputing approach  

Science Conference Proceedings (OSTI)

The present study endeavors to generate autoregressive neural network (AR-NN) models to forecast the monthly total ozone concentration over Kolkata (22^o34', 88^o22'), India. The issues associated with the applicability of neural network to geophysical ... Keywords: Autoregressive moving average, Autoregressive neural network, Monthly total ozone, Predictive model

Goutami Chattopadhyay; Surajit Chattopadhyay

2009-09-01T23:59:59.000Z

18

Monthly Weather Forecasts in a Pest Forecasting Context: Downscaling, Recalibration, and Skill Improvement  

Science Conference Proceedings (OSTI)

Monthly weather forecasts (MOFCs) were shown to have skill in extratropical continental regions for lead times up to 3 weeks, in particular for temperature and if weekly averaged. This skill could be exploited in practical applications for ...

Martin Hirschi; Christoph Spirig; Andreas P. Weigel; Pierluigi Calanca; Jörg Samietz; Mathias W. Rotach

2012-09-01T23:59:59.000Z

19

Monthly streamflow forecasting based on improved support vector machine model  

Science Conference Proceedings (OSTI)

To improve the performance of the support vector machine (SVM) model in predicting monthly streamflow, an improved SVM model with adaptive insensitive factor is proposed in this paper. Meanwhile, considering the influence of noise and the disadvantages ... Keywords: Adaptive insensitive factor, Artificial neural network, Chaos and phase-space reconstruction theory, Streamflow forecast, Support vector machine, Wavelet

Jun Guo; Jianzhong Zhou; Hui Qin; Qiang Zou; Qingqing Li

2011-09-01T23:59:59.000Z

20

Electric power monthly, September 1990. [Glossary included  

SciTech Connect

The purpose of this report is to provide energy decision makers with accurate and timely information that may be used in forming various perspectives on electric issues. The power plants considered include coal, petroleum, natural gas, hydroelectric, and nuclear power plants. Data are presented for power generation, fuel consumption, fuel receipts and cost, sales of electricity, and unusual occurrences at power plants. Data are compared at the national, Census division, and state levels. 4 figs., 52 tabs. (CK)

1990-12-17T23:59:59.000Z

Note: This page contains sample records for the topic "include monthly forecasts" 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

A. G. A. six-month gas demand forecast July-December, 1984  

Science Conference Proceedings (OSTI)

Estimates of the total gas demand for 1984 (including pipeline fuel) range from 18,226 to 19,557 trillion (TBtu). The second half of the year shows a slower recovery rate as economic recovery moderates. The forecast show both actual and projected demand by month, and compares it with 1983 demand and by market sector. 6 tables.

Not Available

1984-01-01T23:59:59.000Z

22

Monthly Forecast of the Madden–Julian Oscillation Using a Coupled GCM  

Science Conference Proceedings (OSTI)

A set of five-member ensemble forecasts initialized daily for 48 days during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment period are performed with the ECMWF monthly forecasting system in order to assess its ...

Frédéric Vitart; Steve Woolnough; M. A. Balmaseda; A. M. Tompkins

2007-07-01T23:59:59.000Z

23

SLCA/IP Hydro Generation Estimates Month Forecast Generation  

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

5/2013 9:06 5/2013 9:06 SLCA/IP Hydro Generation Estimates Month Forecast Generation less losses (kWh) Less Proj. Use (kWh) Net Generation (kWh) SHP Deliveries (kWh) Firming Purchases (kWh) Generation above SHP Level (kWH) 2013-Oct 232,469,911 13,095,926 219,373,985 398,608,181 192,676,761 - 2013-Nov 211,770,451 2,989,074 208,781,376 408,041,232 214,204,345 - 2013-Dec 252,579,425 3,106,608 249,472,817 455,561,848 221,545,708 - 2014-Jan 337,006,077 3,105,116 333,900,962 463,462,717 139,278,887 -

24

Univariate Modeling and Forecasting of Monthly Energy Demand Time Series  

E-Print Network (OSTI)

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

Abdel-Aal, Radwan E.

25

NeuroInflow: The New Model to Forecast Average Monthly Inflow  

Science Conference Proceedings (OSTI)

In utilities using a mixture of hydroelectric and non-hydroelectricpower, the economics of the hydroelectricplants depend upon the reservoir height and the inflowinto the reservoir for several months into the future.Accurate forecasts of reservoir inflow ...

Mêuser Valença; Teresa Ludermir

2002-11-01T23:59:59.000Z

26

Performance of the Weather Research and Forecasting Model for Month-Long Pan-Arctic Simulations  

Science Conference Proceedings (OSTI)

The performance of the Weather Research and Forecasting (WRF) model was evaluated for month-long simulations over a large pan-Arctic model domain. The evaluation of seven different WRF (version 3.1) configurations for four months (January, April, ...

John J. Cassano; Matthew E. Higgins; Mark W. Seefeldt

2011-11-01T23:59:59.000Z

27

Medium-Range, Monthly, and Seasonal Prediction for Europe and the Use of Forecast Information  

Science Conference Proceedings (OSTI)

Operational probabilistic (ensemble) forecasts made at ECMWF during the European summer heat wave of 2003 indicate significant skill on medium (3–10 day) and monthly (10–30 day) time scales. A more general “unified” analysis of many medium-range, ...

Mark J. Rodwell; Francisco J. Doblas-Reyes

2006-12-01T23:59:59.000Z

28

Estimating Monthly and Seasonal Distributions of Temperature and Precipitation Using the New CPC Long-Range Forecasts  

Science Conference Proceedings (OSTI)

A method for transforming underlying climatological distributions for monthly and seasonal mean temperature and monthly and seasonal total precipitation, in a manner consistent with long-range forecasts by the U.S. Climate Prediction Center, is ...

William M. Briggs; Daniel S. Wilks

1996-04-01T23:59:59.000Z

29

Seasonal Precipitation Forecasting with a 6–7 Month Lead Time in the Pacific Northwest Using an Information Theoretic Model  

Science Conference Proceedings (OSTI)

An entropy minimax analysis for the forecast of seasonal precipitation with a 6–7 month lead time was performed for two regions in the Pacific Northwest. A model for the forecast of winter precipitation in the Willamette Valley, Oregon was ...

R. A. Christensen; R. F. Eilbert

1985-04-01T23:59:59.000Z

30

California Wind Energy Forecasting System Development and Testing Phase 2: 12-Month Testing  

Science Conference Proceedings (OSTI)

This report describes results from the second phase of the California Wind Energy Forecasting System Development and Testing Project.

2003-07-22T23:59:59.000Z

31

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

Science Conference Proceedings (OSTI)

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

R. E. Abdel-Aal

2008-05-01T23:59:59.000Z

32

Eta Model Precipitation Forecasts for a Period Including Tropical Storm Allison  

Science Conference Proceedings (OSTI)

A step-mountain (eta) coordinate limited-area model is being developed at the National Meteorological Center (NMC) to improve forecasts of severe weather and other mesoscale phenomena. Precipitation forecasts are reviewed for the 20-day period 16 ...

Fedor Mesinger; Thomas L. Black; David W. Plummer; John H. Ward

1990-09-01T23:59:59.000Z

33

Texas Wind Energy Forecasting System Development and Testing: Phase 2: 12-Month Testing  

Science Conference Proceedings (OSTI)

Wind energy forecasting systems are expected to support system operation in cases where wind generation contributes more than a few percent of total generating capacity. This report presents final results from the Texas Wind Energy Forecasting System Development and Testing Project at a 75-MW wind project in west Texas.

2004-09-30T23:59:59.000Z

34

The Role of Monthly Updated Climate Forecasts in Improving Intraseasonal Water Allocation  

Science Conference Proceedings (OSTI)

Seasonal streamflow forecasts contingent on climate information are essential for short-term planning (e.g., water allocation) and for setting up contingency measures during extreme years. However, the water allocated based on the climate ...

A. Sankarasubramanian; Upmanu Lall; Naresh Devineni; Susan Espinueva

2009-07-01T23:59:59.000Z

35

Statistical Model for Forecasting Monthly Large Wildfire Events in Western United States  

Science Conference Proceedings (OSTI)

The ability to forecast the number and location of large wildfire events (with specified confidence bounds) is important to fire managers attempting to allocate and distribute suppression efforts during severe fire seasons. This paper describes ...

Haiganoush K. Preisler; Anthony L. Westerling

2007-07-01T23:59:59.000Z

36

Verification of Monthly Mean Forecasts for Fire Weather Elements in the Contiguous United States  

Science Conference Proceedings (OSTI)

The authors first review a system for specifying monthly mean anomalies of midday temperature (T), dew-point (D), and wind speed (W) at a large network of surface stations across the United States. Multiple regression equations containing ...

Willlam H. Klein; Joseph J. Charney; Morris H. McCutchan; John W. Benoit

1996-12-01T23:59:59.000Z

37

Agency datasets monthly list | Data.gov  

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

Supply and Demand Estimates (WASDE) report is prepared monthly and includes forecasts for U.S. and world wheat, rice, and coarse grains (corn, barley, sorghum, and oats),...

38

An Evaluation of Precipitation Forecasts from Operational Models and Reanalyses Including Precipitation Variations Associated with MJO Activity  

Science Conference Proceedings (OSTI)

In this paper, the results of an examination of precipitation forecasts for 1–30-day leads from global models run at the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) ...

John E. Janowiak; Peter Bauer; Wanqiu Wang; Phillip A. Arkin; Jon Gottschalck

2010-12-01T23:59:59.000Z

39

Origins and Levels of Monthly and Seasonal Forecast Skill for United States Surface Air Temperatures Determined by Canonical Correlation Analysis  

Science Conference Proceedings (OSTI)

Statistical techniques have been used to study the ability of SLP, SST and a form of persistence to forecast cold/warm season air temperatures over the United States and to determine the space–time evolution of these fields that give rise to ...

T. P. Barnett; R. Preisendorfer

1987-09-01T23:59:59.000Z

40

Three-and-six-month-before forecast of water resources in a karst aquifer in the Terminio massif (Southern Italy)  

Science Conference Proceedings (OSTI)

The ability of artificial neural networks (ANN) to model the rainfall-discharge relationships of karstic aquifers has been studied in the Terminio massif (Southern Italy), which supplies the Naples area with a yearly mean discharge of approximately 1-3.5m^3/s. ... Keywords: Artificial neural network, Feature extraction, Forecast, Karstic aquifer, Serino, Spring discharge

Salvatore Rampone

2013-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "include monthly forecasts" 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

Another Approach to Forecasting Forecast Skill  

Science Conference Proceedings (OSTI)

The skill of a medium-range numerical forecast can fluctuate widely from day to day. Providing an a priori estimate of the skill of the forecast is therefore important. Existing approaches include Monte Carlo Forecasting and Lagged Average ...

W. Y. Chen

1989-02-01T23:59:59.000Z

42

Base Resource Forecasts - Power Marketing - Sierra Nevada Region...  

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

Marketing > Base Resource Forecasts Base Resource Forecasts Note: Annual, rolling (monthly for 12 months), base resource forecasts are posted when they become available. Annual...

43

Verification of High-Resolution RAMS Forecasts over East-Central Florida during the 1999 and 2000 Summer Months  

Science Conference Proceedings (OSTI)

This paper presents an objective and subjective verification of a high-resolution configuration of the Regional Atmospheric Modeling System (RAMS) over east-central Florida during the 1999 and 2000 summer months. Centered on the Cape Canaveral ...

Jonathan L. Case; John Manobianco; Allan V. Dianic; Mark M. Wheeler; Dewey E. Harms; Carlton R. Parks

2002-12-01T23:59:59.000Z

44

Electricity Monthly Update - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Analysis & Projections. Monthly and yearly energy forecasts, analysis of energy topics, financial analysis, Congressional reports. Markets & ...

45

Forecast Correlation Coefficient Matrix of Stock Returns in Portfolio Analysis  

E-Print Network (OSTI)

Unadjusted Forecasts . . . . . . . . . . . . . . . .Forecasts . . . . . . . . . . . . . . . . . . . . . . . . . .Unadjusted Forecasts . . . . . . . . . . . . . . . . . . .

Zhao, Feng

2013-01-01T23:59:59.000Z

46

Can earnings forecasts be improved by taking into account the forecast bias?  

E-Print Network (OSTI)

Can earnings forecasts be improved by taking into account the forecast bias? François DOSSOU allow the calculation of earnings adjusted forecasts, for horizons from 1 to 24 months. We explain variables. From the forecast evaluation statistics viewpoints, the adjusted forecasts make it possible quasi

Paris-Sud XI, Université de

47

Forecast Technical Document Forecast Types  

E-Print Network (OSTI)

Forecast Technical Document Forecast Types A document describing how different forecast types are implemented in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Forecast Types Background Different `types' of forecast are possible for a specified area

48

The Influence of Variations in Surface Treatment on 24-Hour Forecasts with a Limited Area Model, Including a Comparison of Modeled and Satellite-Measured Surface Temperatures  

Science Conference Proceedings (OSTI)

The effect of variations in surface parameters on 24-hour limited area forecasts has been examined on a day in July 1981. The vehicle for the study is a ten-level primitive equation model covering most of the continental United States. Variations ...

George Diak; Stacey Heikkinen; John Rates

1986-01-01T23:59:59.000Z

49

RACORO Forecasting  

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

Weather Briefings Observed Weather Cloud forecasting models BUFKIT forecast soundings + guidance from Norman NWS enhanced pages and discussions NAM-WRF updated...

50

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

Science Conference Proceedings (OSTI)

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

51

Business forecasting methods  

E-Print Network (OSTI)

Forecasting is a common statistical task in business, where it helps inform decisions about scheduling of production, transportation and personnel, and provides a guide to long-term strategic planning. However, business forecasting is often done poorly and is frequently confused with planning and goals. They are three different things. Forecasting is about predicting the future as accurately as possible, given all the information available including historical data and knowledge of any future events that might impact the forecasts. Goals are what you would like to happen. Goals should be linked to forecasts and plans, but this does not always occur. Too often, goals are set without any plan for how to achieve them, and no forecasts for whether they are realistic. Planning is a response to forecasts and goals. Planning involves determining the appropriate actions that are required to make your forecasts match your goals. Forecasting should be an integral part of the decision-making activities of management, as it can play an important role in many areas of a company. Modern organizations require short-, medium- and long-term forecasts, depending on the specific application.

Rob J Hyndman

2009-01-01T23:59:59.000Z

52

Forecasting Forecast Skill  

Science Conference Proceedings (OSTI)

We have shown that it is possible to predict the skill of numerical weather forecasts—a quantity which is variable from day to day and region to region. This has been accomplished using as predictor the dispersion (measured by the average ...

Eugenia Kalnay; Amnon Dalcher

1987-02-01T23:59:59.000Z

53

Forecast Combinations  

E-Print Network (OSTI)

Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this chapter we analyze theoretically the factors that determine the advantages from combining forecasts (for example, the degree of correlation between forecast errors and the relative size of the individual models’ forecast error variances). Although the reasons for the success of simple combination schemes are poorly understood, we discuss several possibilities related to model misspecification, instability (non-stationarities) and estimation error in situations where thenumbersofmodelsislargerelativetothe available sample size. We discuss the role of combinations under asymmetric loss and consider combinations of point, interval and probability forecasts. Key words: Forecast combinations; pooling and trimming; shrinkage methods; model misspecification, diversification gains

Allan Timmermann; Jel Codes C

2006-01-01T23:59:59.000Z

54

A Short-Range Forecasting Experiment Conducted during the Canadian Atlantic Storms Program  

Science Conference Proceedings (OSTI)

During the Canadian Atlantic Storms Program (CASP), a dedicated forecast center conducted experiments in mesoscale forecasting. Several forecast products, including a marine forecast and a site-specific public forecast, were written every 3 h. ...

K. A. Macdonald; M. Danks; J. D. Abraham

1988-06-01T23:59:59.000Z

55

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Market and STEO Error Forecast Error from 1998 to 2003 (2 Futures Market and STEO Error Forecast Error from 1998to 2003 (Months 13- Forecast from 1998 to 2003 (Months 1-12)

Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

2005-01-01T23:59:59.000Z

56

Forecast Technical Document Tree Species  

E-Print Network (OSTI)

Forecast Technical Document Tree Species A document listing the tree species included in the 2011 Production Forecast Tom Jenkins Justin Gilbert Ewan Mackie Robert Matthews #12;PF2011 ­ List of tree species The following is the list of species used within the Forecast System. Species are ordered alphabetically

57

Forecasting overview  

E-Print Network (OSTI)

Forecasting is required in many situations: deciding whether to build another power generation plant in the next five years requires forecasts of future demand; scheduling staff in a call centre next week requires forecasts of call volume; stocking an inventory requires forecasts of stock requirements. Forecasts can be required several years in advance (for the case of capital investments), or only a few minutes beforehand (for telecommunication routing). Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. Some things are easier to forecast than others. The time of the sunrise tomorrow morning can be forecast very precisely. On the other hand, currency exchange rates are very difficult to forecast with any accuracy. The predictability of an event or a quantity depends on how well we understand the factors that contribute to it, and how much unexplained variability is involved. Forecasting situations vary widely in their time horizons, factors determining actual outcomes, types of data patterns, and many other aspects. Forecasting methods can be very simple such as using the most recent observation as a forecast (which is called the “naïve method”), or highly complex such as neural nets and econometric systems of simultaneous equations. The

Rob J Hyndman

2009-01-01T23:59:59.000Z

58

Monthly generator capacity factor data now available by ...  

U.S. Energy Information Administration (EIA)

weather; gasoline; capacity; exports; nuclear; forecast; ... Solar generators—particularly solar thermal—operate at a minimum during winter months, ...

59

Evaluation of Probabilistic Medium-Range Temperature Forecasts from the North American Ensemble Forecast System  

Science Conference Proceedings (OSTI)

Ensemble temperature forecasts from the North American Ensemble Forecast System were assessed for quality against observations for 10 cities in western North America, for a 7-month period beginning in February 2007. Medium-range probabilistic ...

Doug McCollor; Roland Stull

2009-02-01T23:59:59.000Z

60

Monthly Biodiesel Production Report - Energy Information ...  

U.S. Energy Information Administration (EIA)

Monthly and yearly energy forecasts, analysis of energy topics, ... With Data for August 2013 | Release Date: October 30, 2013 | Next Release Date: November ...

Note: This page contains sample records for the topic "include monthly forecasts" 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

Natural Gas Monthly (NGM) - Energy Information Administration ...  

U.S. Energy Information Administration (EIA)

Monthly and yearly energy forecasts, analysis of energy topics, ... Data for August 2013 | Release Date: October 31, 2013 | Next Release: December 6, ...

62

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 4 AUGUST 17, 2010  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 4 ­ AUGUST 17, 2010) of activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts that we This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

63

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 29 OCTOBER 12, 2010  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 29 ­ OCTOBER 12 (greater than 130 percent of climatology.) These new two-week forecasts have replaced the monthly forecasts. Gray2 This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

64

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 28 OCTOBER 11, 2012  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 28 ­ OCTOBER 11) of hurricane activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts. Gray2 This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

65

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 31 SEPTEMBER 13, 2012  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 31 ­ SEPTEMBER 13) of activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts that we This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

66

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 1 SEPTEMBER 14, 2010  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 1 ­ SEPTEMBER 14 percent of) climatology. These new two-week forecasts have replaced the monthly forecasts that we have This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

67

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 13 SEPTEMBER 26, 2013  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 13 ­ SEPTEMBER 26) of hurricane activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts. Gray2 This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

68

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 18 AUGUST 31, 2010  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 18 ­ AUGUST 31, 2010) of activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts that we This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

69

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 15 SEPTEMBER 28, 2010  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 15 ­ SEPTEMBER 28 (greater than 130 percent of climatology.) These new two-week forecasts have replaced the monthly forecasts. Gray2 This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

70

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 13 OCTOBER 26, 2010  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 13 ­ OCTOBER 26 percent of climatology.) These new two-week forecasts have replaced the monthly forecasts that we have This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

71

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 12 OCTOBER 25, 2012  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM OCTOBER 12 ­ OCTOBER 25%) of hurricane activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts. Gray2 This forecast as well as past forecasts and verifications are available online at http://hurricane.atmos.colostate.edu/Forecasts

Gray, William

72

Forecast of auroral activity  

Science Conference Proceedings (OSTI)

A new technique is developed to predict auroral activity based on a sample of over 9000 auroral sites identified in global auroral images obtained by an ultraviolet imager on the NASA Polar satellite during a 6-month period. Four attributes of auroral activity sites are utilized in forecasting

A. T. Y. Lui

2004-01-01T23:59:59.000Z

73

Short-Termed Integrated Forecasting System: 1993 Model documentation report  

Science Conference Proceedings (OSTI)

The purpose of this report is to define the Short-Term Integrated Forecasting System (STIFS) and describe its basic properties. The Energy Information Administration (EIA) of the US Energy Department (DOE) developed the STIFS model to generate short-term (up to 8 quarters), monthly forecasts of US supplies, demands, imports exports, stocks, and prices of various forms of energy. The models that constitute STIFS generate forecasts for a wide range of possible scenarios, including the following ones done routinely on a quarterly basis: A base (mid) world oil price and medium economic growth. A low world oil price and high economic growth. A high world oil price and low economic growth. This report is written for persons who want to know how short-term energy markets forecasts are produced by EIA. The report is intended as a reference document for model analysts, users, and the public.

Not Available

1993-05-01T23:59:59.000Z

74

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.

75

Monthly Biodiesel Production Report  

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

Monthly Biodiesel Production Monthly Biodiesel Production Report November 2013 With Data for September 2013 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Monthly Biodiesel Production Report This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or

76

The Skill of Extended-Range Extratropical Winter Dynamical Forecasts  

Science Conference Proceedings (OSTI)

The global T42 version of the French numerical weather prediction model has been used to produce monthly mean forecasts. A study based on 21 cases of 44-day forecasts (for winter months from 1983 to 1990) is presented. Nine forecasts in this ...

M. Déquá; J. F. Royer

1992-11-01T23:59:59.000Z

77

An Alternative Tropical Cyclone Intensity Forecast Verification Technique  

Science Conference Proceedings (OSTI)

The National Hurricane Center (NHC) does not verify official or model forecasts if those forecasts call for a tropical cyclone to dissipate or if the real tropical cyclone dissipates. A new technique in which these forecasts are included in a ...

Sim D. Aberson

2008-12-01T23:59:59.000Z

78

A Local Forecast of Land Surface Wetness Conditions Derived from Seasonal Climate Predictions  

Science Conference Proceedings (OSTI)

An ensemble local hydrologic forecast derived from the seasonal forecasts of the International Research Institute for Climate Prediction (IRI) is presented. Three-month seasonal forecasts were used to resample historical meteorological conditions ...

Jeffrey Shaman; Marc Stieglitz; Stephen Zebiak; Mark Cane

2003-06-01T23:59:59.000Z

79

Performance of Recent Multimodel ENSO Forecasts  

Science Conference Proceedings (OSTI)

The performance of the International Research Institute for Climate and Society “ENSO forecast plume” during the 2002–11 period is evaluated using deterministic and probabilistic verification measures. The plume includes multiple model forecasts ...

Michael K. Tippett; Anthony G. Barnston; Shuhua Li

2012-03-01T23:59:59.000Z

80

Load Forecasting for Modern Distribution Systems  

Science Conference Proceedings (OSTI)

Load forecasting is a fundamental activity for numerous organizations and activities within a utility, including planning, operations, and control. Transmission and Distribution (T&D) planning and design engineers use the load forecast to determine whether any changes and additions are needed to the electric system to satisfy the anticipated load. Other load forecast users include system operations, financial ...

2013-03-08T23:59:59.000Z

Note: This page contains sample records for the topic "include monthly forecasts" 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

Solar forecasting review  

E-Print Network (OSTI)

of Solar Forecasting . . . . . . . . . 2.4.1 Solarbudget at the foundation of satellite based forecastingWeather Research and Forecasting (WRF) Model 7.1 Global

Inman, Richard Headen

2012-01-01T23:59:59.000Z

82

NFI Forecasts Methodology NFI Forecasts Methodology  

E-Print Network (OSTI)

NFI Forecasts Methodology NFI Forecasts Methodology Overview Issued by: National Forest Inventory.brewer@forestry.gsi.gov.uk Website: www.forestry.gov.uk/inventory 1 NFI Softwood Forecasts Methodology Overview #12;NFI Forecasts ........................................................................................................4 Rationale behind the new approach to the GB Private sector production forecast ........4 Volume

83

Forecast Technical Document Restocking in the Forecast  

E-Print Network (OSTI)

Forecast Technical Document Restocking in the Forecast A document describing how restocking of felled areas is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley in the forecast Background During the period of a production forecast it is assumed that, as forest sub

84

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS FORECAST IMPROVEMENTS  

E-Print Network (OSTI)

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS BRISBANE FORECAST IMPROVEMENTS The Bureau of Meteorology is progressively upgrading its forecast system to provide more detailed forecasts across Australia. From October 2013 new and improved 7 day forecasts will be introduced for Brisbane, Gold Coast

Greenslade, Diana

85

Monthly Reports  

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

Environmental Management Monthly Reports - FY 2012 The Department of Energy Nevada Field Office Environmental Management Program creates monthly reports for the NSSAB. These...

86

Monthly Reports  

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

Environmental Management Monthly Reports - FY 2013 The Department of Energy Nevada Field Office Environmental Management Program creates monthly reports for the NSSAB. These...

87

Evaluating Density Forecasts: Forecast Combinations, Model Mixtures, Calibration and Sharpness  

E-Print Network (OSTI)

In a recent article Gneiting, Balabdaoui and Raftery (JRSSB, 2007) propose the criterion of sharpness for the evaluation of predictive distributions or density forecasts. They motivate their proposal by an example in which standard evaluation procedures based on probability integral transforms cannot distinguish between the ideal forecast and several competing forecasts. In this paper we show that their example has some unrealistic features from the perspective of the time-series forecasting literature, hence it is an insecure foundation for their argument that existing calibration procedures are inadequate in practice. We present an alternative, more realistic example in which relevant statistical methods, including information-based methods, provide the required discrimination between competing forecasts. We conclude that there is no need for a subsidiary criterion of sharpness.

James Mitchell; Kenneth F. Wallis

2008-01-01T23:59:59.000Z

88

Petroleum Marketing Monthly (PMM) - November 2013 With Data ...  

U.S. Energy Information Administration (EIA)

Monthly and yearly energy forecasts, analysis of energy topics, ... Release Date: November 1, 2013 | Next Release: December 2, 2013 | full report.

89

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

90

Fuzzy forecasting with DNA computing  

Science Conference Proceedings (OSTI)

There are many forecasting techniques including: exponential smoothing, ARIMA model, GARCH model, neural networks and genetic algorithm, etc. Since financial time series may be influenced by many factors, conventional model based techniques and hard ...

Don Jyh-Fu Jeng; Junzo Watada; Berlin Wu; Jui-Yu Wu

2006-06-01T23:59:59.000Z

91

ELECTRICITY DEMAND FORECAST COMPARISON REPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005 ..............................................................................3 Residential Forecast Comparison ..............................................................................................5 Nonresidential Forecast Comparisons

92

Skill of Multimodel ENSO Probability Forecasts  

Science Conference Proceedings (OSTI)

The cross-validated hindcast skills of various multimodel ensemble combination strategies are compared for probabilistic predictions of monthly SST anomalies in the ENSO-related Niño-3.4 region of the tropical Pacific Ocean. Forecast data from ...

Michael K. Tippett; Anthony G. Barnston

2008-10-01T23:59:59.000Z

93

River flow forecasting with constructive neural network  

Science Conference Proceedings (OSTI)

In utilities using a mixture of hydroelectric and non-hydroelectric power, the economics of the hydroelectric plants depend upon the reservoir height and the inflow into the reservoir for several months into the future. Accurate forecasts of reservoir ...

Mêuser Valença; Teresa Ludermir; Anelle Valença

2005-12-01T23:59:59.000Z

94

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

95

The Forecast Gap: Linking Forwards and Forecasts  

Science Conference Proceedings (OSTI)

This report addresses a common problem in price forecasting: What to do when confronted with a persistent gap between results obtained from a structural forecast model and actual forward or spot prices? The report examines examples taken from natural gas and electric power forecasts and presents a novel approach to closing this “forecast gap.” Inspection reveals that the ratio of actual prices to forecast prices often exhibits stochastic movements that resemble those of commodity price movements. By usin...

2008-12-15T23:59:59.000Z

96

Update On The Wholesale Electricity Price Forecast & Modeling Results  

E-Print Network (OSTI)

Forecast Base Case includes § Medium Demand Forecast § Medium Natural Gas Price Forecast § Federal CO2 Rathdrum Power LLC-ID 4) CO2 Emissions - 2009 Selected Natural Gas Plants Plant level, emission percentage § Significantly lower electricity prices than 6th Plan Forecast, due to lower demand, lower gas prices, deferred

97

SolarAnywhere forecast (Perez & Hoff) This chapter describes, and presents an evaluation of, the forecast models imbedded in the  

E-Print Network (OSTI)

SolarAnywhere forecast (Perez & Hoff) ABSTRACT This chapter describes, and presents an evaluation of, the forecast models imbedded in the SolarAnywhere platform. The models include satellite derived cloud motion based forecasts for the short to medium horizon (1 5 hours) and forecasts derived from NOAA

Perez, Richard R.

98

Forecasting in Meteorology  

Science Conference Proceedings (OSTI)

Public weather forecasting heralded the beginning of modern meteorology less than 150 years ago. Since then, meteorology has been largely a forecasting discipline. Thus, forecasting could have easily been used to test and develop hypotheses, ...

C. S. Ramage

1993-10-01T23:59:59.000Z

99

Monthly Energy Review - December 2009  

Gasoline and Diesel Fuel Update (EIA)

Formats Formats (PDF) files; however, all annual data are shown in the Excel and comma-separated values (CSV) files. Also, only two to three years of monthly data are displayed in the PDF files; however, for many series, monthly data beginning with January 1973 are available in the Excel and CSV files. Comprehensive Changes: Each month, most MER tables and figures carry a new month of data, which is usually preliminary (and sometimes estimated or even forecast) and likely to be revised in the succeeding month. Annual Data From 1949: The emphasis of the MER is on recent monthly and annual data trends. Analysts may wish to use the data in this report in conjunction with EIA's Annual Energy Review (AER) that offers annual data beginning in 1949 for many of the data series found in the

100

Monthly Energy Review - February 2009  

Annual Energy Outlook 2012 (EIA)

2) Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are...

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


101

Appendix A: Fuel Price Forecast Introduction..................................................................................................................................... 1  

E-Print Network (OSTI)

Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts............................................................................................................................... 12 Oil Price Forecast Range

102

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 of individual features are estimated. A time series analysis is used to forecast and can be used, for example, to forecast (1) notebook computer price at introduction, and (2) rate of price erosion for a notebook's life cycle. Results indicate that this approach can forecast the price of a notebook computer up to four months in advance of its introduction with an average error of under 10% and the rate of price erosion to within 10% of the price for seven months after introduction-the length of the typical life cycle of a notebook. Since all data are publicly available, this approach can be used to assist managerial decision making in the notebook computer industry, for example, in determining when and how to upgrade a model and when to introduce a new model.

Rutherford, Derek Paul

1997-01-01T23:59:59.000Z

103

A Model for Decision Making Based on NWS Monthly Temperature Outlooks  

Science Conference Proceedings (OSTI)

A Gaussian model for evaluating the probability of occurrence of forecast-contingent monthly average temperature and degree day outcomes is developed by use of forecast-verification data, and proposed for use in decision making. The model 1) ...

Richard L. Lehman

1987-02-01T23:59:59.000Z

104

Monthly Energy Review - December 2012  

Gasoline and Diesel Fuel Update (EIA)

EIA's Office of Communications via email EIA's Office of Communications via email at infoctr@eia.gov. Important Notes About the Data Data Displayed: For tables beginning in 1973, some annual data (usually 1974, 1976-1979, 1981-1984, 1986-1989, and 1991-1994) are not shown in the tables in Portable Document Format (PDF) files; however, all annual data are shown in the Excel and comma-separated values (CSV) files. Also, only two to three years of monthly data are displayed in the PDF files; however, for many series, monthly data beginning with January 1973 are available in the Excel and CSV files. Comprehensive Changes: Each month, most MER tables and figures carry a new month of data, which is usually preliminary (and sometimes estimated or even forecast) and likely to be revised in the succeeding month.

105

Operations of the National Severe Storms Forecast Center  

Science Conference Proceedings (OSTI)

The National Severe Storms Forecast Center in Kansas City, Missouri, is composed of several operational forecasting units, all national in scope. It includes the Severe Local Storms Unit (SELS), the National Aviation Weather Advisory Unit (NAWAU),...

Frederick P. Ostby

1992-12-01T23:59:59.000Z

106

Forecasts, Meteorology Services, Environmental Sciences Department  

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

Forecasts Short Term Forecast Suffolk County Northern Nassau Southern Nassau Area Forecast Discussion - OKX Area Forecast Discussion - NYS Area Forecast Discussion Mount Holly Area...

107

Wind Energy Forecasting Technology Update: 2004  

Science Conference Proceedings (OSTI)

This report describes the status of wind energy forecasting technology for predicting wind speed and energy generation of wind energy facilities short-term (minutes to hours), intermediate-term (hours to days), and long-term (months to years) average wind speed and energy generation. The information should be useful to companies that are evaluating or planning to incorporate wind energy forecasting into their operations.

2005-04-26T23:59:59.000Z

108

Model documentation report: Short-term Integrated Forecasting System demand model 1985. [(STIFS)  

DOE Green Energy (OSTI)

The Short-Term Integrated Forecasting System (STIFS) Demand Model consists of a set of energy demand and price models that are used to forecast monthly demand and prices of various energy products up to eight quarters in the future. The STIFS demand model is based on monthly data (unless otherwise noted), but the forecast is published on a quarterly basis. All of the forecasts are presented at the national level, and no regional detail is available. The model discussed in this report is the April 1985 version of the STIFS demand model. The relationships described by this model include: the specification of retail energy prices as a function of input prices, seasonal factors, and other significant variables; and the specification of energy demand by product as a function of price, a measure of economic activity, and other appropriate variables. The STIFS demand model is actually a collection of 18 individual models representing the demand for each type of fuel. The individual fuel models are listed below: motor gasoline; nonutility distillate fuel oil, (a) diesel, (b) nondiesel; nonutility residual fuel oil; jet fuel, kerosene-type and naphtha-type; liquefied petroleum gases; petrochemical feedstocks and ethane; kerosene; road oil and asphalt; still gas; petroleum coke; miscellaneous products; coking coal; electric utility coal; retail and general industry coal; electricity generation; nonutility natural gas; and utility petroleum. The demand estimates produced by these models are used in the STIFS integrating model to produce a full energy balance of energy supply, demand, and stock change. These forecasts are published quarterly in the Outlook. Details of the major changes in the forecasting methodology and an evaluation of previous forecast errors are presented once a year in Volume 2 of the Outlook, the Methodology publication.

Not Available

1985-07-01T23:59:59.000Z

109

Electric Power Monthly - Monthly Data Tables Monthly electricity...  

Open Energy Info (EERE)

Electric Power Monthly - Monthly Data Tables Monthly electricity generation figures (and the fuel consumed to produce it). Source information available at

110

Verifying Forecasts Spatially  

Science Conference Proceedings (OSTI)

Numerous new methods have been proposed for using spatial information to better quantify and diagnose forecast performance when forecasts and observations are both available on the same grid. The majority of the new spatial verification methods can be ...

Eric Gilleland; David A. Ahijevych; Barbara G. Brown; Elizabeth E. Ebert

2010-10-01T23:59:59.000Z

111

Forecasting of Supercooled Clouds  

Science Conference Proceedings (OSTI)

Using parameterizations of cloud microphysics, a technique to forecast supercooled cloud events is suggested. This technique can be coupled on the mesoscale with a prognostic equation for cloud water to improve aircraft icing forecasts. The ...

André Tremblay; Anna Glazer; Wanda Szyrmer; George Isaac; Isztar Zawadzki

1995-07-01T23:59:59.000Z

112

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 or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide collections of included monetary assets. In our forecasting experiment we use two non-linear techniques

Tino, Peter

113

Time Series and Forecasting  

Science Conference Proceedings (OSTI)

Time Series and Forecasting. Leigh, Stefan and Perlman, S. (1991). "An Index for Comovement of Time Sequences With ...

114

Forecast Technical Document Volume Increment  

E-Print Network (OSTI)

Forecast Technical Document Volume Increment Forecasts A document describing how volume increment is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Volume increment forecasts Background A volume increment forecast is a fundamental output of the forecast

115

Petroleum Supply Monthly Archives  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Supply Monthly Petroleum Supply Monthly Petroleum Supply Monthly Archives With Data for December 2011 | Release Date: February 29, 2012 Changes to Table 26. "Production of Crude Oil by PAD District and State": Current State-level data are now included in Table 26, in addition to current U.S. and PAD District sums. State offshore production for Louisiana, Texas, Alaska, and California, which are included in the State totals, are no longer reported separately in a "State Offshore Production" category. Previously, State-level values lagged 2 months behind the U.S. and PAD District values. Beginning with this publication, they will be on the same cycle. Also included in this publication are two additional pages for Table 26 that provide October and November data. With the release of

116

Monthly Newsletter  

SciTech Connect

This is a personal letter to Kenneth Davis, AEC, concerning ORNL reactor activities. Topics covered include: HRP status; the gas-cooled system; molten fluorides; the ANP project; and maritime work.

Weinberg, A.M.

1957-11-07T23:59:59.000Z

117

Long-Lead Seasonal Forecasts—Where Do We Stand?  

Science Conference Proceedings (OSTI)

The National Weather Service intends to begin routinely issuing long-lead forecasts of 3-month mean U.S. temperature and precipitation by the beginning of 1995. The ability to produce useful forecasts for certain seasons and regions at projection ...

Anthony G. Barnston; Huug M. van den Dool; David R. Rodenhuis; Chester R. Ropelewski; Vernon E. Kousky; Edward A. O'Lenic; Robert E. Livezey; Stephen E. Zebiak; Mark A. Cane; Tim P. Barnett; Nicholas E. Graham; Ming Ji; Ants Leetmaa

1994-11-01T23:59:59.000Z

118

The Strategy of Professional Forecasting  

E-Print Network (OSTI)

This paper develops and compares two theories of strategic behavior of professional forecasters. The first theory posits that forecasters compete in a forecasting contest with pre-specified rules. In equilibrium of a winner-take-all contest, forecasts are excessively differentiated. According to the alternative reputational cheap talk theory, forecasters aim at convincing the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts and the realized state. If the market expects forecaster honesty, forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded.

Marco Ottaviani; Peter Norman Sørensen

2003-01-01T23:59:59.000Z

119

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 28 OCTOBER 11, 2011  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 28 ­ OCTOBER 11 percent) of hurricane activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts that we have been issuing in recent years. (as of 28 September 2011) By Philip J

Gray, William

120

USING BOX-JENKINS MODELS TO FORECAST FISHERY DYNAMICS: IDENTIFICATION, ESTIMATION, AND CHECKING  

E-Print Network (OSTI)

USING BOX-JENKINS MODELS TO FORECAST FISHERY DYNAMICS: IDENTIFICATION, ESTIMATION, AND CHECKING Roy MENDELSSOHN! ABSTRACT Box·Jenkins models are suggested as appropriate models for forecasting fishery dynamics in Hawaii. An actual 12-month forecast is shown to give a reasonable fit to the observed data. Most

Note: This page contains sample records for the topic "include monthly forecasts" 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

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 14 SEPTEMBER 27, 2011  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 14 ­ SEPTEMBER 27 percent) of hurricane activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts that we have been issuing in recent years. (as of 14 September 2011) By Philip J

122

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 17 AUGUST 30, 2012  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 17 ­ AUGUST 30, 2012 percent) of activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts that we have been issuing in recent years. (as of 17 August 2012) By Philip J. Klotzbach1

Gray, William

123

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 31 SEPTEMBER 13, 2011  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM AUGUST 31 ­ SEPTEMBER 13 percent) of activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts that we have been issuing in recent years. (as of 31 August 2011) By Philip J. Klotzbach1

Birner, Thomas

124

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 14 SEPTEMBER 27, 2012  

E-Print Network (OSTI)

COLORADO STATE UNIVERSITY FORECAST OF ATLANTIC HURRICANE ACTIVITY FROM SEPTEMBER 14 ­ SEPTEMBER 27 percent) of hurricane activity relative to climatology. These new two-week forecasts have replaced the monthly forecasts that we have been issuing in recent years. (as of 14 September 2012) By Philip J

Gray, William

125

Monthly Energy Review  

Science Conference Proceedings (OSTI)

This publication presents an overview of the Energy information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. Two brief ``energy plugs`` (reviews of EIA publications) are included, as well.

NONE

1996-05-28T23:59:59.000Z

126

A Preliminary Investigation of Temperature Errors in Operational Forecasting Models  

Science Conference Proceedings (OSTI)

Temperatures taken from model output (FOUS reports) routinely transmitted by the National Centers for Environmental Prediction are tabulated to determine errors during three months in the summer of 1996. These short-term model forecasts are ...

Frank P. Colby Jr.

1998-03-01T23:59:59.000Z

127

River Flow Forecasting for Reservoir management through Neural Networks  

Science Conference Proceedings (OSTI)

In utilities using a mixture of hydroelectric and nonhydroelectric power, the economics of the hydroelectric plants depend upon the reservoir height and the inflow into the reservoir for several months into the future. Accurate forecasts of reservoir ...

Meuser Valenca; Teresa Ludermir; Anelle Valenca

2005-12-01T23:59:59.000Z

128

Retail Motor Gasoline Price* Forecast Doesn't Reflect Potential...  

Gasoline and Diesel Fuel Update (EIA)

5 Notes: EIA's gasoline price forecast has gasoline prices, on a monthly average, possibly exceeding 1.70 per gallon. Of course, weekly prices would likely peak this summer even...

129

ENSEMBLE RE-FORECASTING : IMPROVING MEDIUM-RANGE FORECAST SKILL  

E-Print Network (OSTI)

5.5 ENSEMBLE RE-FORECASTING : IMPROVING MEDIUM-RANGE FORECAST SKILL USING RETROSPECTIVE FORECASTS, Colorado 1. INTRODUCTION Improving weather forecasts is a primary goal of the U.S. National Oceanic predictions has been to improve the accuracy of the numerical forecast models. Much effort has been expended

Hamill, Tom

130

18-Month Outlook Executive Summary  

E-Print Network (OSTI)

This report presents an assessment of the security and adequacy of the Ontario Electricity System for the 18-month period from April 2002 through September 2003. This assessment is based on forecasts of electricity demand and available supply combined with current information on the configuration and capability of the transmission system. Outage plans of generators and transmitters are based on information available as of February 2002. During the Outlook period, the IMO forecasts show that Ontario’s available generation exceeds projected demands. Over this period, approximately 3,000 MW of additional generation resources are expected to either return to service or be placed in service for the first time – thereby enhancing the reliability of the Ontario electricity system. During the first half of the Outlook there are periods when Ontario’s available reserves are forecast to be between 2,000 and 2,500 MW. These reserves are below the IMO’s required planning reserve levels, but do not account for additional resources from outside Ontario that are expected to be available. Reserves are planning buffers identified to address circumstances that cannot be accurately predicted such as weather variations and unscheduled maintenance. The IMO anticipates that the Ontario market will be effective in attracting additional resources to provide adequate reliability. However, there

unknown authors

2002-01-01T23:59:59.000Z

131

Historical Monthly Energy Review  

Gasoline and Diesel Fuel Update (EIA)

73-92) 73-92) Distribution Category UC-950 Historical Monthly Energy Review 1973-1992 Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the Energy Information Administration, the independent statistical and analytical agency within the Department of Energy. The information contained herein should not be construed as advocating or reflecting any policy position of the Department of Energy or any other organization. Historical Monthly Energy Review The Historical Monthly Energy Review (HMER) presents monthly and annual data from 1973 through 1992 on production, consumption, stocks, imports, exports, and prices of the principal energy commodities in the United States. Also included are data on international

132

ORNL integrated forecasting system  

SciTech Connect

This paper describes the integrated system for forecasting electric energy and load. In the system, service area models of electrical energy (kWh) and load distribution (minimum and maximum loads and load duration curve) are linked to a state-level model of electrical energy (kWh). Thus, the service area forecasts are conditional upon the state-level forecasts. Such a linkage reduces considerably the data requirements for modeling service area electricity demand.

Rizy, C.G.

1983-01-01T23:59:59.000Z

133

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

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

in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar --...

134

Probabilistic Forecasts from the National Digital Forecast Database  

Science Conference Proceedings (OSTI)

The Bayesian processor of forecast (BPF) is developed for a continuous predictand. Its purpose is to process a deterministic forecast (a point estimate of the predictand) into a probabilistic forecast (a distribution function, a density function, ...

Roman Krzysztofowicz; W. Britt Evans

2008-04-01T23:59:59.000Z

135

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.

136

forecast | OpenEI  

Open Energy Info (EERE)

Browse Upload data GDR Community Login | Sign Up Search Facebook icon Twitter icon forecast Dataset Summary Description The EIA's annual energy outlook (AEO) contains yearly...

137

Seasonal tropical cyclone forecasts  

E-Print Network (OSTI)

Seasonal forecasts of tropical cyclone activity in various regions have been developed since the first attempts in the early 1980s by Neville

Suzana J. Camargo; Anthony G. Barnston; Philip J. Klotzbach; Christopher W. Landsea

2007-01-01T23:59:59.000Z

138

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

139

Solar forecasting review  

E-Print Network (OSTI)

Online 24-h solar power forecasting based on weather typeweather observations at blue hill massachusetts,” Solarof weather patterns on the intensity of solar irradiance;

Inman, Richard Headen

2012-01-01T23:59:59.000Z

140

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

Note: This page contains sample records for the topic "include monthly forecasts" 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

Essays in International Macroeconomics and Forecasting  

E-Print Network (OSTI)

This dissertation contains three essays in international macroeconomics and financial time series forecasting. In the first essay, I show, numerically, that a two-country New-Keynesian Sticky Prices model, driven by monetary and productivity shocks, is capable of explaining the highly positive correlation across the industrialized countries' inflation even though their cross-country correlation in money growth rate is negligible. The structure of this model generates cross-country correlations of inflation, output and consumption that appear to closely correspond to the data. Additionally, this model can explain the internal correlation between inflation and output observed in the data. The second essay presents two important results. First, gains from monetary policy cooperation are different from zero when the elasticity of substitution between domestic and imported goods consumption is different from one. Second, when monetary policy is endogenous in a two-country model, the only Nash equilibria supported by this model are those that are symmetrical. That is, all exporting firms in both countries choose to price in their own currency, or all exporting firms in both countries choose to price in the importer's currency. The last essay provides both conditional and unconditional predictive ability evaluations of the aluminum futures contracts prices, by using five different econometric models, in forecasting the aluminum spot price monthly return 3, 15, and 27-months ahead for the sample period 1989.01-2010.10. From these evaluations, the best model in forecasting the aluminum spot price monthly return 3 and 15 months ahead is followed by a (VAR) model whose variables are aluminum futures contracts price, aluminum spot price and risk free interest rate, whereas for the aluminum spot price monthly return 27 months ahead is a single equation model in which the aluminum spot price today is explained by the aluminum futures price 27 months earlier. Finally, it shows that iterated multiperiod-ahead time series forecasts have a better conditional out-of-sample forecasting performance of the aluminum spot price monthly return when an estimated (VAR) model is used as a forecasting tool.

Bejarano Rojas, Jesus Antonio

2011-08-01T23:59:59.000Z

142

Global and Local Skill Forecasts  

Science Conference Proceedings (OSTI)

A skill forecast gives the probability distribution for the error in a forecast. Statistically, Well-founded skill forecasting methods have so far only been applied within the context of simple models. In this paper, the growth of analysis errors ...

P. L. Houtekamer

1993-06-01T23:59:59.000Z

143

Arnold Schwarzenegger INTEGRATED FORECAST AND  

E-Print Network (OSTI)

Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN; the former with primary contributions in the areas of climate and hydrologic forecasting and the latter Service (NWS) California Nevada River Forecast Center (CNRFC), the California Department of Water

144

CONSULTANT REPORT DEMAND FORECAST EXPERT  

E-Print Network (OSTI)

CONSULTANT REPORT DEMAND FORECAST EXPERT PANEL INITIAL forecast, end-use demand modeling, econometric modeling, hybrid demand modeling, energyMahon, Carl Linvill 2012. Demand Forecast Expert Panel Initial Assessment. California Energy

145

Does the term structure forecast  

E-Print Network (OSTI)

provides more accurate forecasts of real consumption growth14. Harvey, C.R. (1989): \\Forecasts of economic growth fromC.R. (1993): \\Term structure forecasts economic growth", Fi-

Berardi, Andrea; Torous, Walter

2002-01-01T23:59:59.000Z

146

Distortion Representation of Forecast Errors  

Science Conference Proceedings (OSTI)

Forecast error is decomposed into three components, termed displacement error, amplitude error, mid residual error, respectively. Displacement error measures how much of the forecast error can be accounted for by moving the forecast to best fit ...

Ross N. Hoffman; Zheng Liu; Jean-Francois Louis; Christopher Grassoti

1995-09-01T23:59:59.000Z

147

Composite forecasting in commodity systems  

E-Print Network (OSTI)

Paper No. COMPOSI1E FORECASTING IN CO/Yt.flDITI SYSTfu\\1S1980 .i CfIAPTER COMPOSITE FORECASTING IN COMMOOITY SYSTEMS*to utilizeeconometric .modelsfor forecasting ! ,urposes. The

Johnson, Stanley R; Rausser, Gordon C.

1980-01-01T23:59:59.000Z

148

Monthly energy review, August 1997  

SciTech Connect

The Monthly Energy Review for the month of August 1997, presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors.

NONE

1997-08-01T23:59:59.000Z

149

Forecasting future volatility from option prices, Working  

E-Print Network (OSTI)

Weisbach are gratefully acknowledged. I bear full responsibility for all remaining errors. Forecasting Future Volatility from Option Prices Evidence exists that option prices produce biased forecasts of future volatility across a wide variety of options markets. This paper presents two main results. First, approximately half of the forecasting bias in the S&P 500 index (SPX) options market is eliminated by constructing measures of realized volatility from five minute observations on SPX futures rather than from daily closing SPX levels. Second, much of the remaining forecasting bias is eliminated by employing an option pricing model that permits a non-zero market price of volatility risk. It is widely believed that option prices provide the best forecasts of the future volatility of the assets which underlie them. One reason for this belief is that option prices have the ability to impound all publicly available information – including all information contained in the history of past prices – about the future volatility of the underlying assets. A second related reason is that option pricing theory maintains that if an option prices fails to embody optimal forecasts of the future volatility of the underlying asset, a profitable trading strategy should be available whose implementation would push the option price to the level that reflects the best possible forecast of future volatility.

Allen M. Poteshman

2000-01-01T23:59:59.000Z

150

Monthly energy review  

Science Conference Proceedings (OSTI)

This document presents an overview of the Energy Information Administration`s (EIA) recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors.

NONE

1997-12-01T23:59:59.000Z

151

Monthly energy review, January 1998  

SciTech Connect

This report presents an overview of recent monthly energy statistics. Major activities covered include production, consumption, trade, stocks, and prices for fossil fuels, electricity, and nuclear energy.

NONE

1998-01-01T23:59:59.000Z

152

Western Area Power Administration Starting Forecast Month: Sierra Nevada Region  

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

Feb-2013 Feb-2013 1,165.0 260.0 105.0 75.0 26.7 15.0 182.0 0.0 0.0 0.0 0.0 851.3 170.0 29.7 Mar-2013 1,280.0 310.0 125.0 110.0 24.7 14.7 182.0 0.0 0.0 0.0 0.0 948.3 185.3 26.3 Apr-2013 1,330.0 380.0 50.0 30.0 23.8 13.7 182.0 0.0 0.0 0.0 0.0 1,074.2 336.3 43.5 May-2013 1,560.0 530.0 75.0 50.0 21.9 13.9 182.0 0.0 0.0 0.0 0.0 1,281.1 466.1 48.9 Jun-2013 1,745.0 640.0 120.0 85.0 23.9 12.9 182.0 0.0 0.0 0.0 0.0 1,419.1 542.1 53.1 Jul-2013 1,780.0 650.0 210.0 145.0 27.9 15.2 182.0 0.0 0.0 0.0 0.0 1,360.1 489.8 48.4 Aug-2013 1,670.0 500.0 190.0 135.0 26.6 14.8 182.0 0.0 0.0 0.0 0.0 1,271.4 350.2 37.0 Sep-2013 1,445.0 380.0 145.0 100.0 23.2 13.2 182.0 0.0 0.0 0.0 0.0 1,094.8 266.8 33.9 Oct-2013 1,225.0 330.0 180.0 140.0 23.8 13.8 182.0 0.0 0.0 0.0 0.0 839.2 176.2 28.2 Nov-2013 1,340.0 200.0 170.0 140.0 26.4 15.6 182.0 0.0 0.0 0.0 0.0 961.6 44.4 6.4 Dec-2013 1,255.0 180.0 130.0 105.0 26.6 16.0 182.0 0.0 0.0 0.0 0.0 916.4

153

Western Area Power Administration Starting Forecast Month: Sierra Nevada Region  

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

Mar-2013 Mar-2013 1,475.0 220.0 30.0 20.0 24.7 14.7 182.0 0.0 0.0 0.0 0.0 1,238.3 185.3 20.1 Apr-2013 1,400.0 380.0 45.0 30.0 23.8 13.7 182.0 0.0 0.0 0.0 0.0 1,149.2 336.3 40.6 May-2013 1,455.0 550.0 65.0 45.0 21.9 13.9 182.0 0.0 0.0 0.0 0.0 1,186.1 491.1 55.7 Jun-2013 1,650.0 610.0 100.0 65.0 23.9 12.9 182.0 0.0 0.0 0.0 0.0 1,344.1 532.1 55.0 Jul-2013 1,590.0 630.0 195.0 135.0 27.9 15.2 182.0 0.0 0.0 0.0 0.0 1,185.1 479.8 54.4 Aug-2013 1,560.0 480.0 175.0 115.0 26.6 14.8 182.0 0.0 0.0 0.0 0.0 1,176.4 350.2 40.0 Sep-2013 1,290.0 360.0 145.0 110.0 23.2 13.2 182.0 0.0 0.0 0.0 0.0 939.8 236.8 35.0 Oct-2013 1,090.0 290.0 170.0 140.0 23.8 13.8 182.0 0.0 0.0 0.0 0.0 714.2 136.2 25.6 Nov-2013 1,115.0 170.0 125.0 105.0 26.4 15.6 182.0 0.0 0.0 0.0 0.0 781.6 49.4 8.8 Dec-2013 1,195.0 150.0 145.0 125.0 26.6 16.0 182.0 0.0 0.0 0.0 0.0 841.4 9.0 1.4 Jan-2014 1,180.0 150.0 100.0 95.0 26.0 16.0 182.0 0.0 0.0 0.0 0.0 872.0 39.0

154

Western Area Power Administration Starting Forecast Month: Sierra Nevada Region  

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

Jul-2013 Jul-2013 1,480.0 700.0 180.0 110.0 27.9 15.2 182.0 0.0 0.0 0.0 0.0 1,090.1 574.8 70.9 Aug-2013 1,430.0 550.0 195.0 120.0 26.6 14.8 182.0 0.0 0.0 0.0 0.0 1,026.4 415.2 54.4 Sep-2013 1,270.0 320.0 165.0 110.0 23.2 13.2 182.0 0.0 0.0 0.0 0.0 899.8 196.8 30.4 Oct-2013 1,070.0 270.0 125.0 105.0 23.8 13.8 182.0 0.0 0.0 0.0 0.0 739.2 151.2 27.5 Nov-2013 1,105.0 150.0 100.0 85.0 26.4 15.6 182.0 0.0 0.0 0.0 0.0 796.6 49.4 8.6 Dec-2013 1,175.0 130.0 100.0 95.0 26.6 16.0 182.0 0.0 0.0 0.0 0.0 866.4 19.0 3.0 Jan-2014 1,155.0 140.0 100.0 95.0 26.0 16.0 182.0 0.0 0.0 0.0 0.0 847.0 29.0 4.6 Feb-2014 1,180.0 140.0 30.0 15.0 26.7 15.0 182.0 0.0 0.0 0.0 0.0 941.3 110.0 17.4 Mar-2014 1,210.0 190.0 55.0 30.0 24.7 14.7 182.0 0.0 0.0 0.0 0.0 948.3 145.3 20.6 Apr-2014 1,320.0 230.0 50.0 30.0 23.8 13.7 182.0 0.0 0.0 0.0 0.0 1,064.2 186.3 24.3 May-2014 1,425.0 510.0 70.0 50.0 21.9 13.9 182.0 0.0 0.0 0.0 0.0 1,151.1 446.1 52.1 Jun-2014

155

Western Area Power Administration Starting Forecast Month: Sierra Nevada Region  

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

Aug-2013 Aug-2013 1,586.0 523.0 167.0 89.0 26.6 14.8 182.0 0.0 0.0 0.0 0.0 1,210.4 419.2 46.6 Sep-2013 1,499.0 309.0 216.0 92.0 23.2 13.2 182.0 0.0 0.0 0.0 0.0 1,077.8 203.8 26.3 Oct-2013 1,229.0 230.0 268.0 105.0 23.8 13.8 182.0 0.0 0.0 0.0 0.0 755.2 111.2 19.8 Nov-2013 1,384.0 192.0 268.0 96.0 26.4 15.6 182.0 0.0 0.0 0.0 0.0 907.6 80.4 12.3 Dec-2013 1,470.0 165.0 344.0 119.0 26.6 16.0 182.0 0.0 0.0 0.0 0.0 917.4 30.0 4.4 Jan-2014 1,509.0 160.0 351.0 126.0 26.0 16.0 182.0 0.0 0.0 0.0 0.0 950.0 18.0 2.5 Feb-2014 1,353.0 162.0 351.0 119.0 26.7 15.0 182.0 0.0 0.0 0.0 0.0 793.3 28.0 5.2 Mar-2014 1,559.0 191.0 282.0 95.0 24.7 14.7 182.0 0.0 0.0 0.0 0.0 1,070.3 81.3 10.2 Apr-2014 1,558.0 312.0 147.5 52.0 23.8 13.7 182.0 0.0 0.0 0.0 0.0 1,204.7 246.3 28.4 May-2014 1,677.0 455.0 108.5 40.0 21.9 13.9 182.0 0.0 0.0 0.0 0.0 1,364.6 401.1 39.5 Jun-2014 1,740.0 525.0 162.0 78.0 23.9 12.9 182.0 0.0 0.0 0.0 0.0 1,372.1 434.1

156

Western Area Power Administration Starting Forecast Month: Sierra Nevada Region  

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

Jun-2013 Jun-2013 1,560.0 640.0 55.0 35.0 23.9 12.9 182.0 0.0 0.0 0.0 0.0 1,299.1 592.1 63.3 Jul-2013 1,465.0 690.0 125.0 70.0 27.9 15.2 182.0 0.0 0.0 0.0 0.0 1,130.1 604.8 71.9 Aug-2013 1,400.0 500.0 170.0 95.0 26.6 14.8 182.0 0.0 0.0 0.0 0.0 1,021.4 390.2 51.4 Sep-2013 1,235.0 310.0 165.0 110.0 23.2 13.2 182.0 0.0 0.0 0.0 0.0 864.8 186.8 30.0 Oct-2013 1,040.0 270.0 125.0 100.0 23.8 13.8 182.0 0.0 0.0 0.0 0.0 709.2 156.2 29.6 Nov-2013 1,145.0 150.0 100.0 85.0 26.4 15.6 182.0 0.0 0.0 0.0 0.0 836.6 49.4 8.2 Dec-2013 1,190.0 120.0 100.0 95.0 26.6 16.0 182.0 0.0 0.0 0.0 0.0 881.4 9.0 1.4 Jan-2014 1,130.0 140.0 100.0 95.0 26.0 16.0 182.0 0.0 0.0 0.0 0.0 822.0 29.0 4.7 Feb-2014 1,145.0 130.0 30.0 15.0 26.7 15.0 182.0 0.0 0.0 0.0 0.0 906.3 100.0 16.4 Mar-2014 1,185.0 190.0 55.0 25.0 24.7 14.7 182.0 0.0 0.0 0.0 0.0 923.3 150.3 21.9 Apr-2014 1,330.0 220.0 45.0 30.0 23.8 13.7 182.0 0.0 0.0 0.0 0.0 1,079.2 176.3 22.7 May-2014

157

Western Area Power Administration Starting Forecast Month: Sierra Nevada Region  

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

Nov-2013 Nov-2013 1,165.0 150.0 85.0 75.0 26.4 15.6 182.0 0.0 0.0 0.0 0.0 871.6 59.4 9.5 Dec-2013 1,345.0 130.0 100.0 115.0 26.6 16.0 182.0 0.0 0.0 1.0 0.0 1,036.4 0.0 0.0 Jan-2014 1,100.0 120.0 100.0 115.0 26.0 16.0 182.0 0.0 0.0 11.0 0.0 792.0 0.0 0.0 Feb-2014 1,120.0 140.0 30.0 15.0 26.7 15.0 182.0 0.0 0.0 0.0 0.0 881.3 110.0 18.6 Mar-2014 1,275.0 190.0 35.0 20.0 24.7 14.7 182.0 0.0 0.0 0.0 0.0 1,033.3 155.3 20.2 Apr-2014 1,560.0 310.0 45.0 25.0 23.8 13.7 182.0 0.0 0.0 0.0 0.0 1,309.2 271.3 28.8 May-2014 1,550.0 410.0 55.0 35.0 21.9 13.9 182.0 0.0 0.0 0.0 0.0 1,291.1 361.1 37.6 Jun-2014 1,585.0 540.0 45.0 30.0 23.9 12.9 182.0 0.0 0.0 0.0 0.0 1,334.1 497.1 51.7 Jul-2014 1,470.0 500.0 115.0 65.0 27.9 15.2 182.0 0.0 0.0 0.0 0.0 1,145.1 419.8 49.3 Aug-2014 1,270.0 420.0 135.0 80.0 26.6 14.8 182.0 0.0 0.0 0.0 0.0 926.4 325.2 47.2 Sep-2014 1,105.0 310.0 140.0 90.0 23.2 13.2 182.0 0.0 0.0 0.0 0.0 759.8 206.8 37.8 Oct-2014

158

SLCA/IP Hydro Generation Estimates Month Forecast Generation  

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

Less Proj. Use (kWh) Net Generation (kWh) SHP Deliveries (kWh) Firming Purchases (kWh) Generation above SHP Level (kWH) 2012-Oct 253,769,055 13,095,926 240,673,129 398,608,181...

159

Western Area Power Administration Starting Forecast Month: Sierra...  

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

Pref. (FP) Peak Demand First Pref. (FP) Load Energy Estimated Ancillary Services Capacity PU Forward Purchase Off- Peak Energy PU & FP Capacity Purchase Reqmts. Additional PU & FP...

160

Western Area Power Administration Starting Forecast Month: Sierra...  

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

Reg & Res Maximum CVP Capacity CVP Energy Generation Peak Project Use Demand Project Use (PU) Load Energy First Pref. (FP) Peak Demand First Pref. (FP) Load Energy Estimated...

Note: This page contains sample records for the topic "include monthly forecasts" 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

Western Area Power Administration Starting Forecast Month: Sierra Nevada Region  

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

May-2013 May-2013 1,460.0 520.0 95.0 55.0 21.9 13.9 182.0 0.0 0.0 0.0 0.0 1,161.1 451.1 52.2 Jun-2013 1,580.0 620.0 55.0 40.0 23.9 12.9 182.0 0.0 0.0 0.0 0.0 1,319.1 567.1 59.7 Jul-2013 1,510.0 730.0 160.0 105.0 27.9 15.2 182.0 0.0 0.0 0.0 0.0 1,140.1 609.8 71.9 Aug-2013 1,590.0 510.0 150.0 95.0 26.6 14.8 182.0 0.0 0.0 0.0 0.0 1,231.4 400.2 43.7 Sep-2013 1,275.0 350.0 165.0 115.0 23.2 13.2 182.0 0.0 0.0 0.0 0.0 904.8 221.8 34.1 Oct-2013 1,070.0 270.0 125.0 120.0 23.8 13.8 182.0 0.0 0.0 0.0 0.0 739.2 136.2 24.8 Nov-2013 1,090.0 160.0 105.0 100.0 26.4 15.6 182.0 0.0 0.0 0.0 0.0 776.6 44.4 7.9 Dec-2013 1,170.0 140.0 105.0 120.0 26.6 16.0 182.0 0.0 0.0 0.0 0.0 856.4 4.0 0.6 Jan-2014 1,155.0 140.0 100.0 110.0 26.0 16.0 182.0 0.0 0.0 0.0 0.0 847.0 14.0 2.2 Feb-2014 1,210.0 130.0 55.0 25.0 26.7 15.0 182.0 0.0 0.0 0.0 0.0 946.3 90.0 14.1 Mar-2014 1,240.0 190.0 60.0 30.0 24.7 14.7 182.0 0.0 0.0 0.0 0.0 973.3 145.3 20.1 Apr-2014

162

Monthly Energy Review - March 2010  

Gasoline and Diesel Fuel Update (EIA)

March 31, 2010 March 31, 2010 DOE/EIA-0035(2010/03) Monthly Energy Review March 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies. Contacts The Monthly Energy Review is prepared by the U.S. Energy Information Administration, Office of Energy Markets and End Use, Integrated Energy Statistics Division, Domestic Energy Statistics Team, under the direction of Barbara T. Fichman,

163

Monthly Energy Review - May 2010  

Gasoline and Diesel Fuel Update (EIA)

June 30, 2010 June 30, 2010 DOE/EIA-0035(2010/06) Monthly Energy Review June 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies. Contacts The Monthly Energy Review is prepared by the U.S. Energy Information Administration, Office of Energy Markets and End Use, Integrated Energy Statistics Division, Domestic Energy Statistics Team, under the direction of Barbara T. Fichman,

164

Monthly Energy Review - February 2010  

Gasoline and Diesel Fuel Update (EIA)

February 26, 2010 February 26, 2010 DOE/EIA-0035(2010/02) Monthly Energy Review February 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies. Contacts The Monthly Energy Review is prepared by the U.S. Energy Information Administration, Office of Energy Markets and End Use, Integrated Energy Statistics Division, Domestic Energy Statistics Team, under the direction of Barbara T. Fichman,

165

Monthly Energy Review - July 2010  

Gasoline and Diesel Fuel Update (EIA)

July 30, 2010 July 30, 2010 DOE/EIA-0035(2010/07) Monthly Energy Review July 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies. Contacts The Monthly Energy Review is prepared by the U.S. Energy Information Administration, Office of Energy Markets and End Use, Integrated Energy Statistics Division, Domestic Energy Statistics Team, under the direction of Barbara T. Fichman,

166

Monthly Energy Review - April 2010  

Gasoline and Diesel Fuel Update (EIA)

April 30, 2010 April 30, 2010 DOE/EIA-0035(2010/04) Monthly Energy Review April 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies. Contacts The Monthly Energy Review is prepared by the U.S. Energy Information Administration, Office of Energy Markets and End Use, Integrated Energy Statistics Division, Domestic Energy Statistics Team, under the direction of Barbara T. Fichman,

167

Monthly Energy Review - May 2010  

Gasoline and Diesel Fuel Update (EIA)

May 27, 2010 May 27, 2010 DOE/EIA-0035(2010/05) Monthly Energy Review May 2010 U.S. Energy Information Administration Office of Energy Markets and End Use U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies. Contacts The Monthly Energy Review is prepared by the U.S. Energy Information Administration, Office of Energy Markets and End Use, Integrated Energy Statistics Division, Domestic Energy Statistics Team, under the direction of Barbara T. Fichman,

168

Forecasting the demand for commercial telecommunications satellites  

Science Conference Proceedings (OSTI)

This paper summarizes the key elements of a forecast methodology for predicting demand for commercial satellite services and the resulting demand for satellite hardware and launches. The paper discusses the characterization of satellite services into more than a dozen applications (including emerging satellite Internet applications) used by Futron Corporation in its forecasts. The paper discusses the relationship between demand for satellite services and demand for satellite hardware

Carissa Bryce Christensen; Carie A. Mullins; Linda A. Williams

2001-01-01T23:59:59.000Z

169

Coefficients for Debiasing Forecasts  

Science Conference Proceedings (OSTI)

Skill-score decompositions can be used to analyze the effects of bias on forecasting skill. However, since bias terms are typically squared, and bias is measured in skill-score units rather than in units of the forecasts, such decompositions only ...

Thomas R. Stewart; Patricia Reagan-Cirincione

1991-08-01T23:59:59.000Z

170

Evaluating Point Forecasts  

E-Print Network (OSTI)

Typically, point forecasting methods are compared and assessed by means of an error measure or scoring function, such as the absolute error or the squared error. The individual scores are then averaged over forecast cases, to result in a summary measure of the predictive performance, such as the mean absolute error or the (root) mean squared error. I demonstrate that this common practice can lead to grossly misguided inferences, unless the scoring function and the forecasting task are carefully matched. Effective point forecasting requires that the scoring function be specified ex ante, or that the forecaster receives a directive in the form of a statistical functional, such as the mean or a quantile of the predictive distribution. If the scoring function is specified ex ante, the forecaster can issue the optimal point forecast, namely, the Bayes rule. If the forecaster receives a directive in the form of a functional, it is critical that the scoring function be consistent for it, in the sense that the expect...

Gneiting, Tilmann

2009-01-01T23:59:59.000Z

171

Forecasters ’ Objectives and Strategies ?  

E-Print Network (OSTI)

This chapter develops a unified modeling framework for analyzing the strategic behavior of forecasters. The theoretical model encompasses reputational objectives, competition for the best accuracy, and bias. Also drawing from the extensive literature on analysts, we review the empirical evidence on strategic forecasting and illustrate how our model can be structurally estimated.

Iván Marinovic; Marco Ottaviani; Peter Norman Sørensen

2011-01-01T23:59:59.000Z

172

Weather Swap Pricing and the Optimal Size for Medium-Range Forecast Ensembles  

Science Conference Proceedings (OSTI)

Weather swap pricing involves predicting the mean temperature for the current month with the highest possible accuracy. The more days of skillful forecasts that are available, the better the monthly mean can be predicted. The ensemble mean of a ...

Stephen Jewson; Christine Ziehmann

2003-08-01T23:59:59.000Z

173

U.S. diesel fuel price forecast to be 1 penny lower this summer at $3.94 a gallon  

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

diesel fuel price forecast to be 1 penny lower this summer diesel fuel price forecast to be 1 penny lower this summer at $3.94 a gallon The retail price of diesel fuel is expected to average $3.94 a gallon during the summer driving season that which runs from April through September. That's close to last summer's pump price of $3.95, according to the latest monthly energy outlook from the U.S. Energy Information Administration. Demand for distillate fuel, which includes diesel fuel, is expected to be up less than 1 percent from last summer. Daily production of distillate fuel at U.S. refineries is forecast to be 70,000 barrels higher this summer. With domestic distillate output exceeding demand, U.S. net exports of distillate fuel are expected to average 830,000 barrels per day this summer. That's down 12 percent from last summer's

174

A New Verification Score for Public Forecasts  

Science Conference Proceedings (OSTI)

CREF, a new verification score for public forecasts, is introduced. This verification score rewards a forecaster who forecasts a rare event accurately. CREF was used to verify local forecasts at the Weather Service Forecast Office (WSFO) in ...

Dean P. Gulezian

1981-02-01T23:59:59.000Z

175

Getting the Most out of Ensemble Forecasts: A Valuation Model Based on User–Forecast Interactions  

Science Conference Proceedings (OSTI)

A flexible theoretical model of perceived forecast value is proposed that explicitly includes the effects of user and ensemble characteristics and their interactions. The model can be applied to arbitrary decision problems and is sensitive to a ...

Antony Millner

2008-10-01T23:59:59.000Z

176

Monthly Energy Review  

Gasoline and Diesel Fuel Update (EIA)

May May 26, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/05) Distribution Category UC-950 Monthly Energy Review

177

NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS  

E-Print Network (OSTI)

· NATIONAL AND GLOBAL FORECASTS · WEST VIRGINIA PROFILES AND FORECASTS · ENERGY · HEALTHCARE Industry Insight: West Virginia Fiscal Forecast 34 CHAPTER 4: WEST ViRGiNiA'S 35 COUNTiES AND MSAs West Forecast Summary 2 CHAPTER 1: THE UNiTED STATES ECONOMY Figure 1.1: United States Real GDP Growth 3 Figure

Mohaghegh, Shahab

178

APPLICATION OF PROBABILISTIC FORECASTS: DECISION MAKING WITH FORECAST UNCERTAINTY  

E-Print Network (OSTI)

1 APPLICATION OF PROBABILISTIC FORECASTS: DECISION MAKING WITH FORECAST UNCERTAINTY Rick Katz.isse.ucar.edu/HP_rick/dmuu.pdf #12;2 QUOTES ON USE OF PROBABILITY FORECASTS · Lao Tzu (Chinese Philosopher) "He who knows does and Value of Probability Forecasts (4) Cost-Loss Decision-Making Model (5) Simulation Example (6) Economic

Katz, Richard

179

Why are survey forecasts superior to model forecasts?  

E-Print Network (OSTI)

We investigate two characteristics of survey forecasts that are shown to contribute to their superiority over purely model-based forecasts. These are that the consensus forecasts incorporate the effects of perceived changes in the long-run outlook, as well as embodying departures from the path toward the long-run expectation. Both characteristics on average tend to enhance forecast accuracy. At the level of the individual forecasts, there is scant evidence that the second characteristic enhances forecast accuracy, and the average accuracy of the individual forecasts can be improved by applying a mechanical correction.

Michael P. Clements; Michael P. Clements

2010-01-01T23:59:59.000Z

180

Monthly energy review: April 1996  

Science Conference Proceedings (OSTI)

This monthly report presents an overview of energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. A section is also included on international energy. The feature paper which is included each month is entitled ``Energy equipment choices: Fuel costs and other determinants.`` 37 figs., 59 tabs.

NONE

1996-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "include monthly forecasts" 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

Demand Forecast INTRODUCTION AND SUMMARY  

E-Print Network (OSTI)

Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required of any forecast of electricity demand and developing ways to reduce the risk of planning errors that could arise from this and other uncertainties in the planning process. Electricity demand is forecast

182

LOAD FORECASTING Eugene A. Feinberg  

E-Print Network (OSTI)

's electricity price forecasting model, produces forecast of gas demand consistent with electric load. #12Gas demand Council's Market Price of Electricity Forecast Natural GasDemand Electric Load Aggregating Natural between the natural gas and electricity and new uses of natural gas emerge. T natural gas forecasts

Feinberg, Eugene A.

183

Essays on macroeconomics and forecasting  

E-Print Network (OSTI)

This dissertation consists of three essays. Chapter II uses the method of structural factor analysis to study the effects of monetary policy on key macroeconomic variables in a data rich environment. I propose two structural factor models. One is the structural factor augmented vector autoregressive (SFAVAR) model and the other is the structural factor vector autoregressive (SFVAR) model. Compared to the traditional vector autogression (VAR) model, both models incorporate far more information from hundreds of data series, series that can be and are monitored by the Central Bank. Moreover, the factors used are structurally meaningful, a feature that adds to the understanding of the �black box� of the monetary transmission mechanism. Both models generate qualitatively reasonable impulse response functions. Using the SFVAR model, both the �price puzzle� and the �liquidity puzzle� are eliminated. Chapter III employs the method of structural factor analysis to conduct a forecasting exercise in a data rich environment. I simulate out-of-sample real time forecasting using a structural dynamic factor forecasting model and its variations. I use several structural factors to summarize the information from a large set of candidate explanatory variables. Compared to Stock and Watson (2002)�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 forecasting models compared to alternatives that include univariate autoregression (AR) model, the VAR model and Stock and Watson�s (2002) models, especially when forecasting real variables. In chapter IV, we measure U.S. technology shocks by implementing a dual approach, which is based on more reliable price data instead of aggregate quantity data. By doing so, we find the relative volatility of technology shocks and the correlation between output fluctuation and technology shocks to be much smaller than those revealed in most real-business-cycle (RBC) studies. Our results support the findings of Burnside, Eichenbaum and Rebelo (1996), who showed that the correlation between technology shocks and output is exaggerated in the RBC literature. This suggests that one should examine other sources of fluctuations for a better understanding of the business cycle phenomena.

Liu, Dandan

2005-08-01T23:59:59.000Z

184

Petroleum marketing monthly  

SciTech Connect

Petroleum Marketing Monthly (PPM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o. b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data in the Petroleum Marketing Monthly.

1996-07-01T23:59:59.000Z

185

Petroleum marketing monthly  

SciTech Connect

The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data in the Petroleum Marketing Monthly.

NONE

1996-02-01T23:59:59.000Z

186

Petroleum marketing monthly  

Science Conference Proceedings (OSTI)

The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data in the Petroleum Marketing Monthly.

NONE

1995-08-01T23:59:59.000Z

187

Monthly energy review  

SciTech Connect

The U.S. energy market for the first quarter of 1988 is discussed. Production, energy consumption, imports, price adjustments, and forecasts for the rest of the year are given.

1988-03-01T23:59:59.000Z

188

Factors Driving Prices & Forecast  

Gasoline and Diesel Fuel Update (EIA)

This spread is a function of the balance between demand and fresh supply (production and net imports). Finally I will discuss the current forecast for distillate prices this winter...

189

Modeling and Forecasting Aurora  

Science Conference Proceedings (OSTI)

Modeling the physical processes needed for forecasting space-weather events requires multiscale modeling. This article discusses several modelsresearchers use to treat the various auroral processes that influence space weather.

Dirk Lummerzheim

2007-01-01T23:59:59.000Z

190

Valuing Climate Forecast Information  

Science Conference Proceedings (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

191

Nambe Pueblo Water Budget and Forecasting model.  

SciTech Connect

This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

Brainard, James Robert

2009-10-01T23:59:59.000Z

192

Air Quality Forecasts in the Mid-Atlantic Region: Current Practice and Benchmark Skill  

Science Conference Proceedings (OSTI)

Air quality forecasts for the mid-Atlantic region (including the metropolitan areas of Baltimore, Washington, D.C., and Philadelphia) began in 1992. These forecasts were issued to the public beginning in 1995 and predict daily peak O3 ...

William F. Ryan; Charles A. Piety; Eric D. Luebehusen

2000-02-01T23:59:59.000Z

193

Hydrometeorological Short-Range Ensemble Forecasts in Complex Terrain. Part I: Meteorological Evaluation  

Science Conference Proceedings (OSTI)

This paper addresses the question of whether it is better to include lower-resolution members of a nested suite of numerical precipitation forecasts to increase ensemble size, or to utilize high-resolution members only to maximize forecast ...

Doug McCollor; Roland Stull

2008-08-01T23:59:59.000Z

194

Petroleum marketing monthly  

SciTech Connect

The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data.

NONE

1995-11-01T23:59:59.000Z

195

Electricity Price Curve Modeling and Forecasting by Manifold Learning  

E-Print Network (OSTI)

This paper proposes a novel nonparametric approach for the modeling and analysis of electricity price curves by applying the manifold learning methodology—locally linear embedding (LLE). The prediction method based on manifold learning and reconstruction is employed to make short-term and mediumterm price forecasts. Our method not only performs accurately in forecasting one-day-ahead prices, but also has a great advantage in predicting one-week-ahead and one-month-ahead prices over other methods. The forecast accuracy is demonstrated by numerical results using historical price data taken from the Eastern U.S. electric power markets.

Jie Chen; Shi-Jie Deng; Xiaoming Huo

2008-01-01T23:59:59.000Z

196

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.

197

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.

198

Short-Term Wind Speed Forecasting for Power System Operations  

E-Print Network (OSTI)

Global large scale penetration of wind energy is accompanied by significant challenges due to the intermittent and unstable nature of wind. High quality short-term wind speed forecasting is critical to reliable and secure power system operations. This paper gives an overview of the current status of worldwide wind power developments and future trends, and reviews some statistical short-term wind speed forecasting models, including traditional time series models and advanced space-time statistical models. It also discusses the evaluation of forecast accuracy, in particular the need for realistic loss functions. New challenges in wind speed forecasting regarding ramp events and offshore wind farms are also presented.

Xinxin Zhu; Marc G. Genton

2011-01-01T23:59:59.000Z

199

Subgrid Scale Physics in 1-Month Forecasts. Part II: Systematic Error and Blocking Forecasts  

Science Conference Proceedings (OSTI)

The capability of blocking prediction is investigated with respect to four models of different subgrid scale parameterization packages, which were described in Part I. In order to assess the capability, blocking indices are defined, and threat ...

K. Miyakoda; J. Sirutis

1990-05-01T23:59:59.000Z

200

Multivariate Forecast Evaluation And Rationality Testing  

E-Print Network (OSTI)

1062—1088. MULTIVARIATE FORECASTS Chaudhuri, P. (1996): “OnKingdom. MULTIVARIATE FORECASTS Kirchgässner, G. , and U. K.2005): “Estimation and Testing of Forecast Rationality under

Komunjer, Ivana; OWYANG, MICHAEL

2007-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "include monthly forecasts" 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

Forecasting in the Presence of Level Shifts  

E-Print Network (OSTI)

accuracy. Journal of Forecasting 19 : 537-560. Hamilton JD.430. Harvey AC. 1989. Forecasting, structural time seriesMH, Timmermann A. 1994. Forecasting stock returns: An

Smith, Aaron

2004-01-01T23:59:59.000Z

202

Monthly Energy Review  

Gasoline and Diesel Fuel Update (EIA)

December December 23, 1997 Electronic Access Monthly Energy Review (MER) data are also available through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/contents.html * A portable document format (pdf) file of the complete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.overview/monthly .energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-from-the-last

203

Electric power monthly  

SciTech Connect

The Energy Information Administration (EIA) prepares the Electric Power Monthly (EPM) for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. This publication provides monthly statistics for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source, consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead.

1995-08-01T23:59:59.000Z

204

Monthly energy review, November 1996  

SciTech Connect

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 75 tabs.

1996-11-01T23:59:59.000Z

205

Monthly energy review, May 1999  

Science Conference Proceedings (OSTI)

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 61 tabs.

NONE

1999-05-01T23:59:59.000Z

206

Monthly energy review, November 1997  

Science Conference Proceedings (OSTI)

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 91 tabs.

NONE

1997-11-01T23:59:59.000Z

207

Monthly energy review, July 1998  

SciTech Connect

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs. 73 tabs.

NONE

1998-07-01T23:59:59.000Z

208

Monthly energy review, June 1998  

SciTech Connect

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 36 figs., 61 tabs.

NONE

1998-06-01T23:59:59.000Z

209

Monthly Energy Review, February 1996  

Science Conference Proceedings (OSTI)

This monthly publication presents an overview of EIA`s recent monthly energy statistics, covering the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. Two brief descriptions (`energy plugs`) on two EIA publications are presented at the start.

NONE

1996-02-26T23:59:59.000Z

210

Monthly energy review, October 1998  

SciTech Connect

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 61 tabs.

NONE

1998-10-01T23:59:59.000Z

211

Monthly energy review, February 1999  

SciTech Connect

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 73 tabs.

NONE

1999-02-01T23:59:59.000Z

212

Monthly energy review, March 1999  

Science Conference Proceedings (OSTI)

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. 37 figs., 74 tabs.

NONE

1999-03-01T23:59:59.000Z

213

On Modeling and Forecasting Time Series of Smooth Curves  

E-Print Network (OSTI)

/fertility rate curves (Hyndman and Ullah, 2007; Erbas et al., 2007). Other examples include electricity system the rates are unobservable; hence one needs to forecast future rate profiles based on historical call of telephone customer service centers, where forecasts of daily call arrival rate profiles are needed

Shen, Haipeng

214

FROM ANALYSTS ' EARNINGS FORECASTS  

E-Print Network (OSTI)

We examine the accuracy and bias of intrinsic equity prices estimated from three accounting-based valuation models using analyst’s earnings forecasts over a four-year horizon. The models are: (a) the earnings capitalization model, (b) the residual income model without a terminal value, and (c) the residual income model with a terminal value that assumes residual income will grow beyond the horizon at a constant rate determined from the expected residual income growth rate over the forecast horizon. Our analysis is based on valuation errors that are calculated by comparing estimated prices to actual prices. We contribute to the literature by examining whether: (i) the analysts ’ earnings forecasts convey information about value beyond that conveyed by current earnings, book value and dividends, (ii) the use of firm specific growth rates in terminal value calculations results in more unbiased and accurate valuations than the use of constant growth rates, and (iii) different models perform better under different ex-ante conditions. We find that analysts ’ earnings forecasts convey information about value beyond that conveyed by current earnings, book values and dividends. Each of the models that we used has valuation errors that decline monotonically as the horizon increases implying that earnings forecasts at each horizon convey new value relevant information. We cannot find a clear advantage to using firm specific growth rates instead of a constant rate of 4 % across all sample

Theodore Sougiannis; Takashi Yaekura

2000-01-01T23:59:59.000Z

215

Natural gas monthly, July 1997  

Science Conference Proceedings (OSTI)

The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. From time to time, the NGM features articles designed to assist readers in using and interpreting natural gas information. The feature article this month is entitled ``Intricate puzzle of oil and gas reserves growth.`` A special report is included on revisions to monthly natural gas data. 6 figs., 24 tabs.

NONE

1997-07-01T23:59:59.000Z

216

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

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

217

Monthly energy review, July 1997  

SciTech Connect

This document presents an overview of recent monthly energy statistics. Activities covered include: U.S. production, consumption, trade, stock, and prices for petroleum, coal, natural gas, electricity, and nuclear energy.

NONE

1997-07-01T23:59:59.000Z

218

Petroleum Marketing Monthly  

U.S. Energy Information Administration (EIA)

ii U.S. Energy Information Administration/Petroleum Marketing Monthly August 2011 Preface The Petroleum Marketing Monthly (PMM) provides information and statistical ...

219

February Natural Gas Monthly  

Annual Energy Outlook 2012 (EIA)

Gas Annual. Preliminary Monthly Data Preliminary monthly data in the "balancing item" cat- egory are calculated by subtracting dry gas production, withdrawals from storage,...

220

November Natural Gas Monthly  

Annual Energy Outlook 2012 (EIA)

Gas Annual. Preliminary Monthly Data Preliminary monthly data in the "balancing item" cat- egory are calculated by subtracting dry gas production, withdrawals from storage,...

Note: This page contains sample records for the topic "include monthly forecasts" 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

January Natural Gas Monthly  

Annual Energy Outlook 2012 (EIA)

Gas Annual. Preliminary Monthly Data Preliminary monthly data in the "balancing item" cat- egory are calculated by subtracting dry gas production, withdrawals from storage,...

222

March Natural Gas Monthly  

Gasoline and Diesel Fuel Update (EIA)

Gas Annual. Preliminary Monthly Data Preliminary monthly data in the "balancing item" cat- egory are calculated by subtracting dry gas production, withdrawals from storage,...

223

May Natural Gas Monthly  

Annual Energy Outlook 2012 (EIA)

Gas Annual. Preliminary Monthly Data Preliminary monthly data in the "balancing item" cat- egory are calculated by subtracting dry gas production, withdrawals from storage,...

224

Value of medium range weather forecasts in the improvement of seasonal hydrologic prediction skill  

SciTech Connect

We investigated the contribution of medium range weather forecasts with lead times up to 14 days to seasonal hydrologic prediction skill over the Conterminous United States (CONUS). Three different Ensemble Streamflow Prediction (ESP)-based experiments were performed for the period 1980-2003 using the Variable Infiltration Capacity (VIC) hydrology model to generate forecasts of monthly runoff and soil moisture (SM) at lead-1 (first month of the forecast period) to lead-3. The first experiment (ESP) used a resampling from the retrospective period 1980-2003 and represented full climatological uncertainty for the entire forecast period. In the second and third experiments, the first 14 days of each ESP ensemble member were replaced by either observations (perfect 14-day forecast) or by a deterministic 14-day weather forecast. We used Spearman rank correlations of forecasts and observations as the forecast skill score. We estimated the potential and actual improvement in baseline skill as the difference between the skill of experiments 2 and 3 relative to ESP, respectively. We found that useful runoff and SM forecast skill at lead-1 to -3 months can be obtained by exploiting medium range weather forecast skill in conjunction with the skill derived by the knowledge of initial hydrologic conditions. Potential improvement in baseline skill by using medium range weather forecasts, for runoff (SM) forecasts generally varies from 0 to 0.8 (0 to 0.5) as measured by differences in correlations, with actual improvement generally from 0 to 0.8 of the potential improvement. With some exceptions, most of the improvement in runoff is for lead-1 forecasts, although some improvement in SM was achieved at lead-2.

Shukla, Shraddhanand; Voisin, Nathalie; Lettenmaier, D. P.

2012-08-15T23:59:59.000Z

225

THE PITTSBURGH REMI MODEL: LONG-TERM REMI MODEL FORECAST FOR  

E-Print Network (OSTI)

1 THE PITTSBURGH REMI MODEL: LONG-TERM REMI MODEL FORECAST FOR ALLEGHENY COUNTY AND THE PITTSBURGH made. REMI LONG-TERM FORECAST AND BEA PROJECTIONS This report includes UCSUR's 1998 economic and population projections for the Pittsburgh Region. The purpose of UCSUR's long-term regional forecasts

Sibille, Etienne

226

Consensus Coal Production Forecast for  

E-Print Network (OSTI)

Consensus Coal Production Forecast for West Virginia 2009-2030 Prepared for the West Virginia Summary 1 Recent Developments 2 Consensus Coal Production Forecast for West Virginia 10 Risks References 27 #12;W.Va. Consensus Coal Forecast Update 2009 iii List of Tables 1. W.Va. Coal Production

Mohaghegh, Shahab

227

ENERGY DEMAND FORECAST METHODS REPORT  

E-Print Network (OSTI)

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

228

Forecast Technical Document Technical Glossary  

E-Print Network (OSTI)

Forecast Technical Document Technical Glossary A document defining some of the terms used in the 2011 Production Forecast technical documentation. Tom Jenkins Robert Matthews Ewan Mackie Lesley in the Forecast documentation. In some cases, the terms and the descriptions are "industry standard", in others

229

3, 21452173, 2006 Probabilistic forecast  

E-Print Network (OSTI)

HESSD 3, 2145­2173, 2006 Probabilistic forecast verification F. Laio and S. Tamea Title Page for probabilistic forecasts of continuous hydrological variables F. Laio and S. Tamea DITIC ­ Department­2173, 2006 Probabilistic forecast verification F. Laio and S. Tamea Title Page Abstract Introduction

Paris-Sud XI, Université de

230

4, 189212, 2007 Forecast and  

E-Print Network (OSTI)

OSD 4, 189­212, 2007 Forecast and analysis assessment through skill scores M. Tonani et al. Title Science Forecast and analysis assessment through skill scores M. Tonani 1 , N. Pinardi 2 , C. Fratianni 1 Forecast and analysis assessment through skill scores M. Tonani et al. Title Page Abstract Introduction

Paris-Sud XI, Université de

231

FINANCIAL FORECASTING USING GENETIC ALGORITHMS  

E-Print Network (OSTI)

predecessors to forecast stock prices and manage portfolios for approximately 3 years.) We examineFINANCIAL FORECASTING USING GENETIC ALGORITHMS SAM MAHFOUD and GANESH MANI LBS Capital Management entitled Genetic Algorithms for Inductive Learning). Time-series forecasting is a special type

Boetticher, Gary D.

232

New Concepts in Wind Power Forecasting Models  

E-Print Network (OSTI)

of the motivations behind the project led by ANL ­ Argonne National Laboratory, together with INESC Porto from a manageable procedure to compute the solution. IV. ENTROPY AND PARZEN WINDOW PDF ESTIMATION The most well into the substation connecting it to the electric power network. Other model's input variables include forecasts

Kemner, Ken

233

Issues in midterm analysis and forecasting, 1996  

SciTech Connect

This document consists of papers which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1996. Topics include: The Potential Impact of Technological Progress on U.S. Energy Markets; The Outlook for U.S. Import Dependence; Fuel Economy, Vehicle Choice, and Changing Demographics, and Annual Energy Outlook Forecast Evaluation.

NONE

1996-08-01T23:59:59.000Z

234

Revised Draft Forecast of Electricity Demand  

E-Print Network (OSTI)

. Forecasts of higher electricity and natural gas prices will fundamentally challenge energy intensive. These include the reduced growth in natural gas supplies in spite of significant drilling activity and #12;DRAFT the medium-high case, while paper and allied products has been below the medium-low. Future natural gas

235

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

236

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,

237

Using adaptive network-based fuzzy inference system to forecast automobile sales  

Science Conference Proceedings (OSTI)

Improving the sales forecasting accuracy has become a primary concern for automobile industry. Here, we only focus on new automobile sales in Taiwan. The data set is based on monthly sales, and the data can be divided into three styles of automobile ... Keywords: ANFIS, ANN, ARIMA, Demand forecasting

Fu-Kwun Wang; Ku-Kuang Chang; Chih-Wei Tzeng

2011-08-01T23:59:59.000Z

238

The First Decade of Long-Lead U.S. Seasonal Forecasts  

Science Conference Proceedings (OSTI)

The first 10 yr (issued starting in mid-December 1994) of official, long-lead (out to 1 yr) U.S. 3-month mean temperature and precipitation forecasts are verified using a categorical skill score. Through aggregation of forecasts over overlapping ...

Robert E. Livezey; Marina M. Timofeyeva

2008-06-01T23:59:59.000Z

239

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

240

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,

Note: This page contains sample records for the topic "include monthly forecasts" 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

Electric Power Monthly  

Gasoline and Diesel Fuel Update (EIA)

Electric Power Monthly > Electric Power Monthly Back Issues Electric Power Monthly > Electric Power Monthly Back Issues Electric Power Monthly Back Issues Monthly Excel files zipped 2010 January February March April May June July August September October November December 2009 January February March April May June July August September October November December 2008 January February March March Supplement April May June July August September October November December 2007 January February March April May June July August September October November December 2006 January February March April May June July August September October November December 2005 January February March April May June July August September October November December

242

Long-Range Predictability in the Tropics. Part I: Monthly Averages  

Science Conference Proceedings (OSTI)

The sensitivity to initial and boundary conditions of monthly mean tropical long-range forecasts (1–14 weeks) during Northern Hemisphere winter is studied with a numerical model. Five predictability experiments with different combinations of ...

Thomas Reichler; John O. Roads

2005-03-01T23:59:59.000Z

243

U.S. monthly gasoline price in December on track to be lowest...  

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

to average 3.23 per gallon during December, according to the new monthly energy forecast from the U.S. Energy Information Administration. That would be down 1 penny from...

244

U.S. monthly oil production tops 8 million barrels per day for...  

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

barrels per day for the first time in 25 years, according to the new monthly energy forecast from the U.S. Energy Information Administration. Rising oil output from tight oil...

245

Monthly energy review, April 1998  

Science Conference Proceedings (OSTI)

This report presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy data. A brief summary of the monthly and historical comparison data is provided in Section 1 of the report. A highlight section of the report provides an assessment of summer 1997 motor gasoline price increases.

NONE

1998-04-01T23:59:59.000Z

246

Monthly energy review, August 1998  

Science Conference Proceedings (OSTI)

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. 37 figs., 73 tabs.

NONE

1998-08-01T23:59:59.000Z

247

Natural gas monthly: December 1993  

Science Conference Proceedings (OSTI)

The Natural Gas Monthly (NGM) highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. Articles are included which are designed to assist readers in using and interpreting natural gas information.

Not Available

1993-12-01T23:59:59.000Z

248

Monthly energy review, April 1999  

Science Conference Proceedings (OSTI)

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public.

NONE

1999-04-01T23:59:59.000Z

249

March Natural Gas Monthly  

Gasoline and Diesel Fuel Update (EIA)

'PGTI[+PHQTOCVKQP#FOKPKUVTCVKQP0CVWTCN)CU/QPVJN[/CTEJ 'PGTI[+PHQTOCVKQP#FOKPKUVTCVKQP0CVWTCN)CU/QPVJN[/CTEJ EIA Corrects Errors in Its Drilling Activity Estimates Series William Trapmann and Phil Shambaugh Introduction The Energy Information Administration (EIA) has published monthly and annual estimates of oil and gas drilling activity since 1978. These data are key information for many industry analysts, serving as a leading indicator of trends in the industry and a barometer of general industry status. They are assessed directly for trends, as well as in combination with other measures to assess the productivity and profitability of upstream industry operations. They are a major reference point for policymakers at both the Federal and State level. Users in the private sector include financial

250

Diagnosing Sources of U.S. Seasonal Forecast Skill  

Science Conference Proceedings (OSTI)

In this study the authors diagnose the sources for the contiguous U.S. seasonal forecast skill that are related to sea surface temperature (SST) variations using a combination of dynamical and empirical methods. The dynamical methods include ...

X. Quan; M. Hoerling; J. Whitaker; G. Bates; T. Xu

2006-07-01T23:59:59.000Z

251

Recently released EIA report presents international forecasting data  

Science Conference Proceedings (OSTI)

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

252

Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures  

E-Print Network (OSTI)

Forecasting Dangerous Inmate Misconduct: An Applications ofidentify with useful forecasting skill the very few inmatescontribute substantially to forecasting skill necessarily

Berk, Richard; Kriegler, Brian; Baek, Jong-Ho

2005-01-01T23:59:59.000Z

253

Information and Inference in Econometrics: Estimation, Testing and Forecasting  

E-Print Network (OSTI)

Application: Forecasting Equity Premium . . . . . . . . . .2.6.1 Forecasting4 Forecasting Using Supervised Factor Models 4.1

Tu, Yundong

2012-01-01T23:59:59.000Z

254

Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures  

E-Print Network (OSTI)

Forecasting Dangerous Inmate Misconduct: An Applications ofidentify with useful forecasting skill the very few inmatescontribute substantially to forecasting skill necessarily

Richard A. Berk; Brian Kriegler; Jong-Ho Baek

2011-01-01T23:59:59.000Z

255

Monthly Energy Review The Monthly Energy Review  

Gasoline and Diesel Fuel Update (EIA)

use use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the MER and in other EIA publications. Related Publication: Readers of the MER may also be interested in EIA's Annual Energy Review, where many of the same data series are provided annually beginning with 1949. Contact our National Energy Information Center at 202-586-8800 for more information. Timing of Release: MER data are normally released in the afternoon of the third-from-the-last workday of each month and are usually available electronically late that day. Internet Addresses: E-Mail: infoctr@eia.doe.gov World Wide Web Site: http://www.eia.doe.gov Gopher Site: gopher://gopher.eia.doe.gov FTP Site: ftp://ftp.eia.doe.gov The Monthly Energy Review (ISSN 0095-7356) is published monthly by the Energy Information

256

Long-Lead Forecasts of Seasonal Precipitation in Africa Using CCA  

Science Conference Proceedings (OSTI)

A potentially operational forecast system for 3-month total precipitation for three sections of the African continent has been developed at NOAA's Climate Prediction Center using the statistical method of canonical correlation analysis (CCA). The ...

Anthony G. Barnston; Wassila Thiao; Vadlamani Kumar

1996-12-01T23:59:59.000Z

257

The Effect of Spatial Aggregation on the Skill of Seasonal Precipitation Forecasts  

Science Conference Proceedings (OSTI)

Skillful forecasts of 3-month total precipitation would be useful for decision making in hydrology, agriculture, public health, and other sectors of society. However, with some exceptions, the skill of seasonal precipitation outlooks is modest, ...

Xiaofeng Gong; Anthony G. Barnston; M. Neil Ward

2003-09-01T23:59:59.000Z

258

Statistical Downscaling Forecasts for Winter Monsoon Precipitation in Malaysia Using Multimodel Output Variables  

Science Conference Proceedings (OSTI)

This paper compares the skills of four different forecasting approaches in predicting the 1-month lead time of the Malaysian winter season precipitation. Two of the approaches are based on statistical downscaling techniques of multimodel ...

Liew Juneng; Fredolin T. Tangang; Hongwen Kang; Woo-Jin Lee; Yap Kok Seng

2010-01-01T23:59:59.000Z

259

Long-Lead Forecasts of Seasonal Precipitation in the Tropical Pacific Islands Using CCA  

Science Conference Proceedings (OSTI)

A potentially operational system for 3-month total precipitation forecasts for island stations in the tropical Pacific has been developed at NOAA's Climate Prediction Center using the statistical method of canonical correlation analysis (CCA). ...

Yuxiang He; Anthony G. Barnston

1996-09-01T23:59:59.000Z

260

Reverse supply chain forecasting and decision modeling for improved inventory management  

E-Print Network (OSTI)

This thesis details research performed during a six-month engagement with Verizon Wireless (VzW) in the latter half of 2012. The key outcomes are a forecasting model and decision-support framework to improve management of ...

Petersen, Brian J. (Brian Jude)

2013-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "include monthly forecasts" 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

Comparison of Methods Used to Generate Probabilistic Quantitative Precipitation Forecasts over South America  

Science Conference Proceedings (OSTI)

In this work, the quality of several probabilistic quantitative precipitation forecasts (PQPFs) is examined. The analysis is focused over South America during a 2-month period in the warm season. Several ways of generating and calibrating the ...

Juan Ruiz; Celeste Saulo; Eugenia Kalnay

2009-02-01T23:59:59.000Z

262

Fermilab | Women's History Month  

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

Women's History Month at Fermilab Fermilab recognized Women's History Month through a series of lab-wide events during March 2010. During the past five decades, women from all...

263

Management Earnings Forecasts and Value of Analyst Forecast Revisions  

E-Print Network (OSTI)

Prior studies evaluate the relative importance of the sources of value that financial analysts bring to the market based on the price impact of forecast revisions over the event time. We find that management earnings forecasts influence the timing and precision of analyst forecasts. More importantly, evidence suggests that prior studies ’ finding of weaker (stronger) stock-price responses to forecast revisions in the period immediately after (before) the prior-quarter earnings announcement is likely to be the artifact of a temporal pattern of management earnings forecasts over the event time. To the extent that management earnings forecasts are public disclosures, our results suggest that the relative importance of analysts ' information discovery role documented in prior studies is likely to be overstated.

Yongtae Kim; Minsup Song

2013-01-01T23:59:59.000Z

264

Verification of The Weather Channel Probability of Precipitation Forecasts  

Science Conference Proceedings (OSTI)

The Weather Channel (TWC) is a leading provider of weather information to the general public. In this paper the reliability of their probability of precipitation (PoP) forecasts over a 14-month period at 42 locations across the United States is ...

J. Eric Bickel; Seong Dae Kim

2008-12-01T23:59:59.000Z

265

Chapter 11 Forecasting breaks and forecasting during breaks  

E-Print Network (OSTI)

Success in accurately forecasting breaks requires that they are predictable from relevant information available at the forecast origin using an appropriate model form, which can be selected and estimated before the break. To clarify the roles of these six necessary conditions, we distinguish between the information set for ‘normal forces ’ and the one for ‘break drivers’, then outline sources of potential information. Relevant non-linear, dynamic models facing multiple breaks can have more candidate variables than observations, so we discuss automatic model selection. As a failure to accurately forecast breaks remains likely, we augment our strategy by modelling breaks during their progress, and consider robust forecasting devices.

Jennifer L. Castle; Nicholas W. P. Fawcett; David F. Hendry

2011-01-01T23:59:59.000Z

266

Forecasting Uncertain Hotel Room Demand  

E-Print Network (OSTI)

Economic systems are characterized by increasing uncertainty in their dynamics. This increasing uncertainty is likely to incur bad decisions that can be costly in financial terms. This makes forecasting of uncertain economic variables an instrumental activity in any organization. This paper takes the hotel industry as a practical application of forecasting using the Holt-Winters method. The problem here is to forecast the uncertain demand for rooms at a hotel for each arrival day. Forecasting is part of hotel revenue management system whose objective is to maximize the revenue by making decisions regarding when to make rooms available for customers and at what price. The forecast approach discussed in this paper is based on quantitative models and does not incorporate management expertise. Even though, forecast results are found to be satisfactory for certain days, this is not the case for other arrival days. It is believed that human judgment is important when dealing with ...

Mihir Rajopadhye Mounir; Mounir Ben Ghaliay; Paul P. Wang; Timothy Baker; Craig V. Eister

2001-01-01T23:59:59.000Z

267

Forecasting Model for Crude Oil Price Using Artificial Neural Networks and Commodity Futures Prices  

E-Print Network (OSTI)

This paper presents a model based on multilayer feedforward neural network to forecast crude oil spot price direction in the short-term, up to three days ahead. A great deal of attention was paid on finding the optimal ANN model structure. In addition, several methods of data pre-processing were tested. Our approach is to create a benchmark based on lagged value of pre-processed spot price, then add pre-processed futures prices for 1, 2, 3,and four months to maturity, one by one and also altogether. The results on the benchmark suggest that a dynamic model of 13 lags is the optimal to forecast spot price direction for the short-term. Further, the forecast accuracy of the direction of the market was 78%, 66%, and 53% for one, two, and three days in future conclusively. For all the experiments, that include futures data as an input, the results show that on the short-term, futures prices do hold new information on the spot price direction. The results obtained will generate comprehensive understanding of the cr...

Kulkarni, Siddhivinayak

2009-01-01T23:59:59.000Z

268

Forecast Technical Document Growing Stock Volume  

E-Print Network (OSTI)

Forecast Technical Document Growing Stock Volume Forecasts A document describing how growing stock (`standing') volume is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Growing stock volume forecasts Background A forecast of standing volume (or

269

Natural gas monthly  

Science Conference Proceedings (OSTI)

This report presents current data on the consumption, disposition, production, prices, storage, import and export of natural gas in the United States. Also included are operating and financial data for major interstate natural gas pipeline companies plus data on fillings, ceiling prices, and transportation under the Natural Gas Policy Act of 1978. A feature article, entitled Main Line Natural Gas Sales to Industrial Users, 1981, is included. Highlights of this month's publication are: Marketed production of natural gas during 1982 continued its downward trend compared to 1981, with November production of 1511 Bcf compared to 1583 Bcf for November 1981; total natural gas consumption also declined when compared to 1981; as of November 1982, working gas in underground storage was running ahead of a similar period in 1981 by 109 Bcf (3.4 percent); the average wellhead price of natural gas continued to rise in 1982; and applications for determination of maximum lawful prices under the Natural Gas Policy Act (NGPA) showed a decrease from October to November, principally for Section 103 classification wells (new onshore production wells).

Not Available

1983-01-01T23:59:59.000Z

270

Forecasting of mine price for central Appalachian steam coal  

SciTech Connect

In reaction to Virginia's declining share of the steam coal market and the subsequent depression in southwest Virginia's economy, an optimization model of the central Appalachian steam coal market was developed. The input to the cost vector was the delivered cost of coal, which is comprised of the mine price (FOB) and transportation cost. One objective of the study was to develop a purchasing model that could be used to minimize the cost of coal procurement over a multi-period time span. The initial case study used a six-month period (7/86-12/86); this requires short-term, forecasts of the mine price of coal. Mine-cost equations and regression models were found to be inadequate for forecasting the mine price of coal. Instead forecasts were generated using modified time series models. This paper describes the application of classical time-series modeling to forecasting the mine price of coal in central Appalachia; in particular, the special modification to the classical methodology needed to generate short-term forecasts and their confidence limits and the need to take into account market-specific considerations such as the split between long-term contracts and the spot market. Special consideration is given to forecasting the spot market. 7 references, 4 figures, 3 tables.

Smith, M.L.

1988-01-01T23:59:59.000Z

271

Monthly Energy Review - September 1999  

Gasoline and Diesel Fuel Update (EIA)

September September 27, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(99/09) Monthly Energy

272

Monthly Energy Review - June 2000  

Gasoline and Diesel Fuel Update (EIA)

June June 27, 2000 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(2000/06) Monthly Energy Review

273

Monthly Energy Review - October 1999  

Gasoline and Diesel Fuel Update (EIA)

October October 26, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(99/10) Monthly Energy

274

Monthly Energy Review - May 2000  

Gasoline and Diesel Fuel Update (EIA)

May May 26, 2000 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(2000/05) Monthly Energy Review

275

Monthly Energy Review - December 1999  

Gasoline and Diesel Fuel Update (EIA)

December December 22, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(99/12) Monthly Energy

276

Monthly Energy Review - April 200  

Gasoline and Diesel Fuel Update (EIA)

April April 26, 2000 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(2000/04) Monthly Energy

277

Monthly Energy Review - January 2000  

Gasoline and Diesel Fuel Update (EIA)

January January 28, 2000 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(00/01) Monthly Energy

278

Monthly Energy Review - February 2000  

Gasoline and Diesel Fuel Update (EIA)

February February 24, 2000 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. DOE/EIA-0035(00/02) Monthly Energy

279

Monthly petroleum product price report  

SciTech Connect

Monthly report supplies national weighted average prices on a monthly basis at different levels of the marketing chain, for petroleum products sold by refiners, large resellers, gas plant operators, and importers. Data are for the year to date and previous year. Some historic data are included to indicate trends. Gasoline price data are collected from retail gasoline dealers. Heating oil prices come from sellers of heating oil to ultimate consumers. A glossary of petroleum products is appended. Petroleum products include motor gasoline, distillate fuel oil, diesel fuel, heating oil, residual fuel oil, aviation fuel, kerosene, petrochemical feedstocks, propane, butane, ethane, and natural gasoline. 12 tables.

1977-11-01T23:59:59.000Z

280

Petroleum marketing monthly, May 1994  

SciTech Connect

The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data in the Petroleum Marketing Monthly.

Not Available

1994-05-26T23:59:59.000Z

Note: This page contains sample records for the topic "include monthly forecasts" 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

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

282

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

against the risk of energy price fluctuations. In theory,The poor track record of energy price forecasting models hasof information about future energy prices, including most

Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

2005-01-01T23:59:59.000Z

283

Issues in midterm analysis and forecasting 1998  

SciTech Connect

Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.

NONE

1998-07-01T23:59:59.000Z

284

MSSM Forecast for the LHC  

E-Print Network (OSTI)

We perform a forecast of the MSSM with universal soft terms (CMSSM) for the LHC, based on an improved Bayesian analysis. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises from the Bayesian analysis itself when the experimental value of $M_Z$ is considered. This allows to scan the whole parameter space, allowing arbitrarily large soft terms. Still the low-energy region is statistically favoured (even before including dark matter or g-2 constraints). Contrary to other studies, the results are almost unaffected by changing the upper limits taken for the soft terms. The results are also remarkable stable when using flat or logarithmic priors, a fact that arises from the larger statistical weight of the low-energy region in both cases. Then we incorporate all the important experimental constrains to the analysis, obtaining a map of the probability density of the MSSM parameter space, i.e. the forecast of the MSSM. Since not all the experimental information is equally robust, we perform separate analyses depending on the group of observables used. When only the most robust ones are used, the favoured region of the parameter space contains a significant portion outside the LHC reach. This effect gets reinforced if the Higgs mass is not close to its present experimental limit and persits when dark matter constraints are included. Only when the g-2 constraint (based on $e^+e^-$ data) is considered, the preferred region (for $\\mu>0$) is well inside the LHC scope. We also perform a Bayesian comparison of the positive- and negative-$\\mu$ possibilities.

Maria Eugenia Cabrera; Alberto Casas; Roberto Ruiz de Austri

2009-11-24T23:59:59.000Z

285

Aviation forecasting and systems analyses  

SciTech Connect

The 9 papers in this report deal with the following areas: method of allocating airport runway slots; method for forecasting general aviation activity; air traffic control network-planning model based on second-order Markov chains; analyzing ticket-choice decisions of air travelers; assessing the safety and risk of air traffic control systems: risk estimation from rare events; forecasts of aviation fuel consumption in Virginia; estimating the market share of international air carriers; forecasts of passenger and air-cargo activity at Logan International Airport; and forecasting method for general aviation aircraft and their activity.

Geisinger, K.E.; Brander, J.R.G.; Wilson, F.R.; Kohn, H.M.; Polhemus, N.W.

1980-01-01T23:59:59.000Z

286

Studies of inflation and forecasting.  

E-Print Network (OSTI)

??This dissertation contains five research papers in the area of applied econometrics. The two broad themes of the research are inflation and forecasting. The first… (more)

Bermingham, Colin

2011-01-01T23:59:59.000Z

287

UWIG Forecasting Workshop -- Albany (Presentation)  

SciTech Connect

This presentation describes the importance of good forecasting for variable generation, the different approaches used by industry, and the importance of validated high-quality data.

Lew, D.

2011-04-01T23:59:59.000Z

288

Native American Heritage Month  

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

This month, we celebrate the rich heritage and myriad contributions of American Indians and Alaska Natives, and we rededicate ourselves to supporting tribal sovereignty, tribal self-determination,...

289

Natural Gas Monthly  

U.S. Energy Information Administration (EIA)

sector organizations associated with the natural gas industry. Volume and price data are presented each month for ... Tables 1 and 2 ...

290

Electric Power Monthly  

U.S. Energy Information Administration (EIA)

Electric Power Monthly with Data for October 2012. December 2012 . Independent Statistics & Analysis . www.eia.gov . U.S. Department of Energy . ...

291

Electric Power Monthly  

U.S. Energy Information Administration (EIA)

Electric Power Monthly with Data for August 2012. October 2012 . Independent Statistics & Analysis . www.eia.gov . U.S. Department of Energy . ...

292

Natural Gas Monthly Update  

Annual Energy Outlook 2012 (EIA)

2013 | Next Release: February 28, 2013 | full report  | Re-Release Date: February 22, 2013 Previous Issues Month: December 2012 November 2012 October 2012 September 2012 August...

293

Petroleum Supply Monthly  

U.S. Energy Information Administration (EIA)

Energy Information Administration/Petroleum Supply Monthly, October 2011 49 Table 37. Imports of Crude Oil and Petroleum Products by PAD District, ...

294

Monthly Energy Review  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration September 2013 Monthly Energy Review. Note: Information about data precision and revisions. Release Date: September 25, 2013

295

Density Forecasting for Long-Term Peak Electricity Demand  

E-Print Network (OSTI)

Long-term electricity demand forecasting plays an important role in planning for future generation facilities and transmission augmentation. In a long-term context, planners must adopt a probabilistic view of potential peak demand levels. Therefore density forecasts (providing estimates of the full probability distributions of the possible future values of the demand) are more helpful than point forecasts, and are necessary for utilities to evaluate and hedge the financial risk accrued by demand variability and forecasting uncertainty. This paper proposes a new methodology to forecast the density of long-term peak electricity demand. Peak electricity demand in a given season is subject to a range of uncertainties, including underlying population growth, changing technology, economic conditions, prevailing weather conditions (and the timing of those conditions), as well as the general randomness inherent in individual usage. It is also subject to some known calendar effects due to the time of day, day of week, time of year, and public holidays. A comprehensive forecasting solution is described in this paper. First, semi-parametric additive models are used to estimate the relationships between demand and the driver variables, including temperatures, calendar effects and some demographic and economic variables. Then the demand distributions are forecasted by using a mixture of temperature simulation, assumed future economic scenarios, and residual bootstrapping. The temperature simulation is implemented through a new seasonal bootstrapping method with variable blocks. The proposed methodology has been used to forecast the probability distribution of annual and weekly peak electricity demand for South Australia since 2007. The performance of the methodology is evaluated by comparing the forecast results with the actual demand of the summer 2007–2008.

Rob J. Hyndman; Shu Fan

2009-01-01T23:59:59.000Z

296

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

Science Conference Proceedings (OSTI)

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

297

On the Prediction of Forecast Skill  

Science Conference Proceedings (OSTI)

Using 10-day forecast 500 mb height data from the last 7 yr, the potential to predict the skill of numerical weather forecasts is discussed. Four possible predictor sets are described. The first, giving the consistency between adjacent forecasts, ...

T. N. Palmer; S. Tibaldi

1988-12-01T23:59:59.000Z

298

Equitable Skill Scores for Categorical Forecasts  

Science Conference Proceedings (OSTI)

Many skill scores used to evaluate categorical forecasts of discrete variables are inequitable, in the sense that constant forecasts of some events lead to better scores than constant forecasts of other events. Inequitable skill scores may ...

Lev S. Gandin; Allan H. Murphy

1992-02-01T23:59:59.000Z

299

Evaluation of errors in national energy forecasts.  

E-Print Network (OSTI)

??Energy forecasts are widely used by the U.S. government, politicians, think tanks, and utility companies. While short-term forecasts were reasonably accurate, medium and long-range forecasts… (more)

Sakva, Denys

2005-01-01T23:59:59.000Z

300

What Is the True Value of Forecasts?  

Science Conference Proceedings (OSTI)

Understanding the economic value of weather and climate forecasts is of tremendous practical importance. Traditional models that have attempted to gauge forecast value have focused on a best-case scenario, in which forecast users are assumed to ...

Antony Millner

2009-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "include monthly forecasts" 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

Lagged Ensembles, Forecast Configuration, and Seasonal Predictions  

Science Conference Proceedings (OSTI)

An analysis of lagged ensemble seasonal forecasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), is presented. The focus of the analysis is on the construction of lagged ensemble forecasts ...

Mingyue Chen; Wanqiu Wang; Arun Kumar

2013-10-01T23:59:59.000Z

302

Whither the Weather Analysis and Forecasting Process?  

Science Conference Proceedings (OSTI)

An argument is made that if human forecasters are to continue to maintain a skill advantage over steadily improving model and guidance forecasts, then ways have to be found to prevent the deterioration of forecaster skills through disuse. The ...

Lance F. Bosart

2003-06-01T23:59:59.000Z

303

Lagged Ensembles, Forecast Configuration, and Seasonal Predictions  

Science Conference Proceedings (OSTI)

An analysis of lagged ensemble seasonal forecasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) is presented. The focus of the analysis is on the construction of lagged ensemble forecasts ...

Mingyue Chen; Wanqiu Wang; Arun Kumar

304

Improving Forecast Communication: Linguistic and Cultural Considerations  

Science Conference Proceedings (OSTI)

One goal of weather and climate forecasting is to inform decision making. Effective communication of forecasts to various sectors of the public is essential for meeting that goal, yet studies repeatedly show that forecasts are not well understood ...

Karen Pennesi

2007-07-01T23:59:59.000Z

305

Ensemble Cloud Model Applications to Forecasting Thunderstorms  

Science Conference Proceedings (OSTI)

A cloud model ensemble forecasting approach is developed to create forecasts that describe the range and distribution of thunderstorm lifetimes that may be expected to occur on a particular day. Such forecasts are crucial for anticipating severe ...

Kimberly L. Elmore; David J. Stensrud; Kenneth C. Crawford

2002-04-01T23:59:59.000Z

306

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

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

307

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

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

308

A Forecast for the California Labor Market  

E-Print Network (OSTI)

issue for the state. A Forecast for the California Laborto Go? ” The UCLA Anderson Forecast for the Nation andAngeles: UCLA Anderson Forecast: Nation 1.1 – 1.9. Dhawan,

Mitchell, Daniel J. B.

2001-01-01T23:59:59.000Z

309

STAFF FORECAST OF 2007 PEAK STAFFREPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION STAFF FORECAST OF 2007 PEAK DEMAND STAFFREPORT June 2006 CEC-400.................................................................................. 9 Sources of Forecast Error....................................................................... .................11 Tables Table 1: Revised versus September 2005 Peak Demand Forecast ......................... 2

310

Operational Forecaster Uncertainty Needs and Future Roles  

Science Conference Proceedings (OSTI)

Key results of a comprehensive survey of U.S. National Weather Service operational forecast managers concerning the assessment and communication of forecast uncertainty are presented and discussed. The survey results revealed that forecasters are ...

David R. Novak; David R. Bright; Michael J. Brennan

2008-12-01T23:59:59.000Z

311

Calibration of Probabilistic Forecasts of Binary Events  

Science Conference Proceedings (OSTI)

Probabilistic forecasts of atmospheric variables are often given as relative frequencies obtained from ensembles of deterministic forecasts. The detrimental effects of imperfect models and initial conditions on the quality of such forecasts can ...

Cristina Primo; Christopher A. T. Ferro; Ian T. Jolliffe; David B. Stephenson

2009-03-01T23:59:59.000Z

312

CORPORATE GOVERNANCE AND MANAGEMENT EARNINGS FORECAST  

E-Print Network (OSTI)

1 CORPORATE GOVERNANCE AND MANAGEMENT EARNINGS FORECAST QUALITY: EVIDENCE FROM FRENCH IPOS Anis attributes, ownership retained, auditor quality, and underwriter reputation and management earnings forecast quality measured by management earnings forecast accuracy and bias. Using 117 French IPOs, we find

Paris-Sud XI, Université de

313

Forecasting women's apparel sales using mathematical  

E-Print Network (OSTI)

Forecasting women's apparel sales using mathematical modeling Celia Frank and Ashish Garg, USA Les Sztandera Philadelphia University, Philadelphia, PA, USA Keywords Apparel, Forecasting average (MA), auto- regression (AR), or combinations of them are used for forecasting sales. Since

Raheja, Amar

314

Diagnosing Forecast Errors in Tropical Cyclone Motion  

Science Conference Proceedings (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

315

Forecasting Electric Vehicle Costs with Experience Curves  

E-Print Network (OSTI)

April, 5. R 2~1. Dino. "Forecasting the Price Evolution of 1ElectromcProducts," Ioumal of Forecasting, ¥oL4, No I, 1985.costs and a set of forecasting tools that can be refined as

Lipman, Timonthy E.; Sperling, Daniel

2001-01-01T23:59:59.000Z

316

Calibration of Probabilistic Quantitative Precipitation Forecasts  

Science Conference Proceedings (OSTI)

From 1 August 1990 to 31 July 1995, the Weather Service Forecast Office in Pittsburgh prepared 6159 probabilistic quantitative precipitation forecasts. Forecasts were made twice a day for 24-h periods beginning at 0000 and 1200 UTC for two river ...

Roman Krzysztofowicz; Ashley A. Sigrest

1999-06-01T23:59:59.000Z

317

Evaluating Probabilistic Forecasts Using Information Theory  

Science Conference Proceedings (OSTI)

The problem of assessing the quality of an operational forecasting system that produces probabilistic forecasts is addressed using information theory. A measure of the quality of the forecasting scheme, based on the amount of a data compression ...

Mark S. Roulston; Leonard A. Smith

2002-06-01T23:59:59.000Z

318

Virtual Floe Ice Drift Forecast Model Intercomparison  

Science Conference Proceedings (OSTI)

Both sea ice forecast models and methods to measure their skill are needed for operational sea ice forecasting. Two simple sea ice models are described and tested here. Four different measures of skill are also tested. The forecasts from the ...

Robert W. Grumbine

1998-09-01T23:59:59.000Z

319

SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2003 THRU FY2046 VERSION 2003.1 VOLUME 2 [SEC 1 & 2  

Science Conference Proceedings (OSTI)

This report includes data requested on September 10, 2002 and includes radioactive solid waste forecasting updates through December 31, 2002. The FY2003.0 request is the primary forecast for fiscal year FY 2003.

BARCOT, R.A.

2003-12-01T23:59:59.000Z

320

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty  

SciTech Connect

This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.

2013-12-18T23:59:59.000Z

Note: This page contains sample records for the topic "include monthly forecasts" 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

The evolution of consensus in macroeconomic forecasting  

E-Print Network (OSTI)

When professional forecasters repeatedly forecast macroeconomic variables, their forecasts may converge over time towards a consensus. The evolution of consensus is analyzed with Blue Chip data under a parametric polynomial decay function that permits flexibility in the decay path. For the most part, this specification fits the data. We test whether forecast differences decay to zero at the same point in time for a panel of forecasters, and discuss possible explanations for this, along with its implications for studies using panels of forecasters.

Allan W. Gregory; James Yetman; Jel Codes C E; Robert Eggert; Fred Joutz

2004-01-01T23:59:59.000Z

322

Monthly energy review, January 1996  

SciTech Connect

This document presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum,natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal metric conversion factors.

1996-01-01T23:59:59.000Z

323

Monthly energy review, April 1997  

Science Conference Proceedings (OSTI)

This report presents an overview of monthly energy statistics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. International energy and thermal metric conversion factors are included.

NONE

1997-04-01T23:59:59.000Z

324

Monthly energy review, November 1993  

SciTech Connect

The Monthly Energy Review gives information on production, distribution, and consumption for various energy sources, e.g. petroleum, natural gas, oil, coal, electricity, and nuclear energy. Some data is also included on international energy sources and supplies, the import of petroleum products into the US and pricing and reserves data (as applicable) for the various sources of energy listed above.

Not Available

1993-11-24T23:59:59.000Z

325

Natural gas monthly, July 1990  

Science Conference Proceedings (OSTI)

This report highlights activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry. Volume and price data are presented each month for natural gas production, distribution, consumption, and interstate pipeline activities. Producer-related activities and underground storage data are also reported. A glossary is included. 7 figs., 33 tabs.

Not Available

1990-10-03T23:59:59.000Z

326

Monthly energy review, July 1996  

Science Conference Proceedings (OSTI)

This document presents an overview of the recent monthly energy statistics from the Energy Information Administration (EIA). Statistical data covers activities of U.S. production, consumption, trade, stocks, and prices for fossil fuels , nuclear energy, and electricity. Also included are international energy and thermal and metric conversion factors.

NONE

1996-07-01T23:59:59.000Z

327

Monthly energy review, December 1993  

SciTech Connect

This document provides data on monthly energy use and fossil fuels. The following sections are included: Highlights: Emissions of greenhouse gases in the United States 1985--1990; Highlights: assessment of energy use in multibuilding facilities; energy overview; energy consumption; petroleum; natural gas; oil and gas resource development; coal; electricity; nuclear energy; energy prices; and international energy.

Not Available

1993-12-22T23:59:59.000Z

328

Electric power monthly, March 1995  

SciTech Connect

This report for March 1995, presents monthly electricity statistics for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead.

1995-03-20T23:59:59.000Z

329

Monthly energy review, June 1990  

SciTech Connect

The Monthly Energy Review presents current data on production, consumption, stocks, imports, exports, and prices of the principal energy commodities in the United States. Also included are data on international production of crude oil, consumption of petroleum products, petroleum stocks, and production of electricity from nuclear-powered facilities.

1990-09-26T23:59:59.000Z

330

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

331

Monthly load data report, fiscal year 1984  

SciTech Connect

Monthly tables are given for TVA megawatt demands and related information by customer class, at point of measurement (generation). Peak day profile graphs are also included. (DLC)

1984-01-01T23:59:59.000Z

332

Monthly Biodiesel Production Report - Energy Information ...  

U.S. Energy Information Administration (EIA)

Revisions – The July 2013 Monthly Biodiesel Report includes revised data for 2012. ... response to section 1508 of the Energy Policy Act of 2005 which directed EIA ...

333

Background pollution forecast over bulgaria  

Science Conference Proceedings (OSTI)

Both, the current level of air pollution studies and social needs in the country, are in a stage mature enough for creating Bulgarian Chemical Weather Forecasting and Information System The system is foreseen to provide in real time forecast of the spatial/temporal ...

D. Syrakov; K. Ganev; M. Prodanova; N. Miloshev; G. Jordanov; E. Katragkou; D. Melas; A. Poupkou; K. Markakis

2009-06-01T23:59:59.000Z

334

Frequency Dependence in Forecast Skill  

Science Conference Proceedings (OSTI)

A method is proposed to calculate measures of forecast skill for high, medium and low temporal frequency variations in the atmosphere. This method is applied to a series of 128 consecutive 1 to 10-day forecasts produced at NMC with their ...

H. M. van Den Dool; Suranjana Saha

1990-01-01T23:59:59.000Z

335

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

336

Improving Forecasting: A plea for historical retrospectives  

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

Improving Forecasting: A plea for historical retrospectives Title Improving Forecasting: A plea for historical retrospectives Publication Type Journal Article Year of Publication...

337

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

338

Radiation fog forecasting using a 1-dimensional model  

E-Print Network (OSTI)

The importance of fog forecasting to the aviation community, to road transportation and to the public at large is irrefutable. The deadliest aviation accident in history was in fact partly a result of fog back on 27 March 1977. This has, along with numerous less dramatic examples, helped focus many meteorological efforts into trying to forecast this phenomenon as accurately as possible. Until recently, methods of fog forecasting have relied primarily on the forecaster's ability to recognize surface weather patterns known to be favorable for producing fog and once it has formed, to state that it will persist unless the pattern changes. Unfortunately, while such methods have shown some success, many times they have led weather forecasters astray with regards to the onset and dissipation of the phenomenon. Fortunately, now with computers becoming ever-increasingly powerful, numerical models have been utilized to attempt to more accurately deal with the fog forecasting problem. This study uses a 1 dimensional model called COBEL to simulate several past fog cases in the hopes of mimicking its actual occurrence and determining what weather parameters the fog is most sensitive to. The goal is to create a technique where the weather forecaster will be able to run several fog forecasts with the model each time with different initial conditions representing the uncertain weather conditions. In this way, the forecaster will be able to use his expertise to choose the most likely scenario. Results indicate that COBEL is able to simulate the fog cases quite well. Issues remain with the model's handling of the gravitational settling rate, the fact that it currently does not include any vegetation, and its coupling process with the soil model. Nevertheless, simulations and sensitivity tests indicate that soil temperature, soil moisture, low-level winds, initial relative humidity, dew deposition and surface emissivity are the weather parameters that affect fog the most. These parameters will be prime candidates for the 1 dimensional ensemble (ODEP) technique described above.

Peyraud, Lionel

2001-01-01T23:59:59.000Z

339

Monthly Energy Review - October 2007  

Gasoline and Diesel Fuel Update (EIA)

0) 0) October 2007 Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2), that: "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

340

Monthly Energy Review - November 2007  

Gasoline and Diesel Fuel Update (EIA)

1) 1) November 2007 Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2), that: "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

Note: This page contains sample records for the topic "include monthly forecasts" 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

Electric power monthly, July 1993  

Science Conference Proceedings (OSTI)

The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.

Not Available

1993-07-29T23:59:59.000Z

342

Monthly Energy Review - January 2008  

Gasoline and Diesel Fuel Update (EIA)

1) 1) January 2008 Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2), that: "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

343

Monthly Energy Review - September 2007  

Gasoline and Diesel Fuel Update (EIA)

09) 09) September 2007 Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2), that: "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

344

Monthly Energy Review - February 2008  

Gasoline and Diesel Fuel Update (EIA)

2) 2) February 2008 Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2), that: "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

345

Electric power monthly, June 1994  

Science Conference Proceedings (OSTI)

The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.

Not Available

1994-06-01T23:59:59.000Z

346

Electric power monthly, August 1994  

Science Conference Proceedings (OSTI)

The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.

Not Available

1994-08-24T23:59:59.000Z

347

Monthly energy review, June 1999  

Science Conference Proceedings (OSTI)

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the MER and in other EIA publications. 37 figs., 61 tabs.

NONE

1999-06-01T23:59:59.000Z

348

Monthly energy review, July 1999  

Science Conference Proceedings (OSTI)

The Monthly Energy Review (MER) presents an overview of the Energy Information Administration`s recent monthly energy statistics. The statistics cover the major activities of US production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the MER and in other EIA publications. 37 figs., 75 tabs.

NONE

1999-07-01T23:59:59.000Z

349

Development and testing of improved statistical wind power forecasting methods.  

DOE Green Energy (OSTI)

Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

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

2011-12-06T23:59:59.000Z

350

Monthly Energy Review, August 1998  

Gasoline and Diesel Fuel Update (EIA)

August August 25, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/ multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/08) Distribution Category UC-950 Monthly Energy Review

351

Monthly Energy Review - December 1998  

Gasoline and Diesel Fuel Update (EIA)

December December 22, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/ multi.htm * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at: ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/12) Distribution Category UC-950 Monthly Energy

352

Monthly Energy Review - July 2004  

Gasoline and Diesel Fuel Update (EIA)

4 4 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: July 27, 2004 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's primary report of recent energy statistics. Included are

353

Monthly Energy Review - May 2004  

Gasoline and Diesel Fuel Update (EIA)

4 4 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: May 26, 2004 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's primary report of recent energy statistics. Included are

354

Monthly Energy Review - February 2006  

Gasoline and Diesel Fuel Update (EIA)

6 6 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: February 23, 2006 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

355

Monthly Energy Review - May 1999  

Gasoline and Diesel Fuel Update (EIA)

May May 25, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website. Go to http://www.eia.doe.gov and click on "Energy Overview." Data are available in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/emeu/mer/contents.html) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. DOE/EIA-0035(99/05) Monthly Energy Review May 1999 Energy Information Administration Office

356

Monthly Energy Review, October 1998  

Gasoline and Diesel Fuel Update (EIA)

October October 27, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/ multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/10) Distribution Category UC-950 Monthly Energy

357

Monthly Energy Review - November 2000  

Gasoline and Diesel Fuel Update (EIA)

November 2000 November 2000 www.eia.doe.gov Energy Information Administration On the Web at: www.eia.doe.gov/mer Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics. The statisti cs cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are international energy and ther- mal and metric conversion factors. Publication of this report is in keeping with responsibilities given to the Energy Information Administration (EIA) in Public Law 95-91 (Department of Energy Organization Act), which states, in part, in Section 205(a)(2), that: The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes

358

Monthly Energy Review - July 2000  

Gasoline and Diesel Fuel Update (EIA)

July July 26, 2000 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/mer) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Cover Image: Optical glass fibers, though

359

Monthly Energy Review, July 1998  

Gasoline and Diesel Fuel Update (EIA)

July July 28, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/ multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/07) Distribution Category UC-950 Monthly Energy Review

360

Monthly Energy Review - October 2002  

Gasoline and Diesel Fuel Update (EIA)

2 2 E n e r g y P l u g : W i n t e r F u e l s O u t l o o k Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statis- tics. The statistics cover the major activities of U.S. production, consumption, trade, stocks, and prices for petroleum, natural gas, coal, electricity, and nuclear energy. Also included are interna- tional energy and thermal and metric conversion factors. Publication of this report is in keeping with responsibilities given to the Energy Information Administration (EIA) in Public Law 95-91 (Department of Energy Organization Act), which states, in part, in Section 205(a)(2), that: The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the MER and in other EIA

Note: This page contains sample records for the topic "include monthly forecasts" 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

Monthly Energy Review, September 1998  

Gasoline and Diesel Fuel Update (EIA)

September September 25, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/ multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/09) Distribution Category UC-950 Monthly Energy

362

Monthly Energy Review - October 2005  

Gasoline and Diesel Fuel Update (EIA)

5 5 E n e r g y P l u g : W i n t e r F u e l s O u t l o o k Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: October 26, 2005 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

363

Monthly Energy Review - March 2006  

Gasoline and Diesel Fuel Update (EIA)

6 6 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: March 27, 2006 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

364

Monthly Energy Review - November 2004  

Gasoline and Diesel Fuel Update (EIA)

4 4 E n e r g y P l u g : O i l M a r k e t B a s i c s Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: November 23, 2004 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

365

Monthly Energy Review - February 1999  

Gasoline and Diesel Fuel Update (EIA)

February February 26, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website. Go to http://www.eia.doe.gov and click on "Energy Overview." Data are available in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/emeu/mer/contents.html) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. DOE/EIA-0035(99/02) Monthly Energy Review February 1999 Energy Information Administration

366

Monthly Energy Review - April 2006  

Gasoline and Diesel Fuel Update (EIA)

6 6 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: April 25, 2006 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

367

Monthly Energy Review, November 1998  

Gasoline and Diesel Fuel Update (EIA)

November November 24, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/ multi.htm * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at: ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/11) Distribution Category UC-950 Monthly Energy

368

Monthly Energy Review, June 1998  

Gasoline and Diesel Fuel Update (EIA)

June June 25, 1998 Electronic Access Monthly Energy Review (MER) data are also avail- able through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/con- tents.html * A portable document format (pdf) file of the com- plete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.over- view/monthly.energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM con- tains over 200 reports, databases, and models. DOE/EIA-0035(98/06) Distribution Category UC-950 Monthly Energy Review

369

Monthly Energy Review - January 1999  

Gasoline and Diesel Fuel Update (EIA)

January January 26, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website. Go to http://www.eia.doe.gov and click on "Energy Overview." Data are available in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/emeu/mer/contents.html) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. DOE/EIA-0035(99/01) Distribution Category UC-950 Monthly Energy Review January 1999 Energy

370

Monthly Energy Review April 1999  

Gasoline and Diesel Fuel Update (EIA)

April April 27, 1999 Electronic Access The Monthly Energy Review is available on the Energy Information Administration's website. Go to http://www.eia.doe.gov and click on "Energy Overview." Data are available in a variety of formats: * ASCII text, Lotus (wk1), and Excel (XLS) versions of the data tables (http://www.eia.doe.gov/emeu/mer/contents.html) * A portable document format (pdf) file of the entire report including text, tables, and graphs (http://www.eia.doe.gov/bookshelf/multi.html) * ASCII comma delimited files (previously available on diskettes) (ftp://ftp.eia.doe.gov/pub/energy.overview/ monthly.energy/current.mer) For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. DOE/EIA-0035(99/04) Monthly Energy Review April 1999 Energy Information Administration Office

371

Electric power monthly, May 1994  

Science Conference Proceedings (OSTI)

The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. This publication provides monthly statistics for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Statistics by company and plant are published on the capability of new generating units, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fossil fuels.

Not Available

1994-05-01T23:59:59.000Z

372

Monthly Energy Review - January 2006  

Gasoline and Diesel Fuel Update (EIA)

6 6 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: January 25, 2006 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

373

Monthly Energy Review - July 2006  

Gasoline and Diesel Fuel Update (EIA)

6 6 Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: July 26, 2006 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Admin- istration's (EIA) primary report of recent energy statistics. Included

374

Geographic Area Month  

Gasoline and Diesel Fuel Update (EIA)

Fuels by PAD District and State (Cents per Gallon Excluding Taxes) - Continued Geographic Area Month No. 1 Distillate No. 2 Distillate a No. 4 Fuel b Sales to End Users Sales for...

375

December Natural Gas Monthly  

Annual Energy Outlook 2012 (EIA)

DOEEIA-0130(9712) Distribution CategoryUC-950 Natural Gas Monthly December 1997 Energy Information Administration Office of Oil and Gas U.S. Department of Energy Washington, DC...

376

National Women's History Month  

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

During Women's History Month, we recall that the pioneering legacy of our grandmothers and great-grandmothers is revealed not only in our museums and history books, but also in the fierce...

377

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: August 2011 The U.S. has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at...

378

Black History Month  

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

During National African American History Month, we pay tribute to the contributions of past generations and reaffirm our commitment to keeping the American dream alive for the next generation.  In...

379

Petroleum Supply Monthly  

U.S. Energy Information Administration (EIA)

Energy Information Administration/Petroleum Supply Monthly, October 2011 11 Table 4. U.S. Year-to-Date Daily Average Supply and Disposition of Crude Oil and Petroleum ...

380

MonthlyReportAll  

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

MonthlyReportAllFleet Summary Report - Hymotion Prius (Kvaser 1 2102010 4:19:25 PM Vehicle Technologies Program 30 Notes: 1 - 9. Please see http:avt.inel.govphevreportnotes...

Note: This page contains sample records for the topic "include monthly forecasts" 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

Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price Forecast  

E-Print Network (OSTI)

Forecast Introduction................................................................... 16 The Base Case Forecast..................................................................... 16 Base Case Price Forecast

382

Petroleum supply monthly, June 1993  

SciTech Connect

Data presented in the Petroleum Supply Monthly (PSM) describe the supply and disposition of petroleum products in the United States and major US geographic regions. The data series describe production, imports and exports, inter-Petroleum Administration for Defense (PAD) District movements, and inventories by the primary suppliers of petroleum products in the United States (50 States and the District of Columbia). The reporting universe includes those petroleum sectors in primary supply. Included are: petroleum refiners, motor gasoline blenders, operators of natural gas processing plants and fractionators, inter-PAD transporters, importers, and major inventory holders of petroleum products and crude oil. When aggregated, the data reported by these sectors approximately represent the consumption of petroleum products in the United States. Data presented in the PSM are divided into two sections: Summary Statistics and Detailed Statistics. The tables and figures ih the Summary Statistics section of the PSM present a time series of selected petroleum data on a US level. Most time series include preliminary estimates for one month based on the Weekly Petroleum Supply Reporting System; statistics based on the most recent data from the Monthly Petroleum Supply Reporting System (MPSRS); and statistics published in prior issues of the PSM and PSA. The Detailed Statistics tables of the PSM present statistics for the most current month available as well as year-to-date. In most cases, the statistics are presented for several geographic areas - - the United States (50 States and the District of Columbia), five PAD Districts, and 12 Refining Districts. At the US and PAD District level, the total volume and the daily rate of activities are presented. The statistics are developed from monthly survey forms submitted by respondents to the EIA and from data provided firom other sources.

Not Available

1993-06-28T23:59:59.000Z

383

Monthly Energy Review, August 1997  

Annual Energy Outlook 2012 (EIA)

Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics. The statistics cover the...

384

Monthly Energy Review, October 1997  

Annual Energy Outlook 2012 (EIA)

Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the Energy Information Administration's recent monthly energy statistics. The statistics cover the...

385

Windpower Monthly | Open Energy Information  

Open Energy Info (EERE)

Windpower Monthly Jump to: navigation, search Name Windpower Monthly Place Knebel, Denmark Zip DK-8420 Knebe Sector Wind energy Product Windpower Monthly is a energy news magazine....

386

Quantitative Precipitation Forecast Techniques for Use in Hydrologic Forecasting  

Science Conference Proceedings (OSTI)

Quantitative hydrologic forecasting usually requires knowledge of the spatial and temporal distribution of precipitation. First, it is important to accurately measure the precipitation falling over a particular watershed of interest. Second, ...

Konstantine P. Georgakakos; Michael D. Hudlow

1984-11-01T23:59:59.000Z

387

Comparison of Ensemble Kalman Filter–Based Forecasts to Traditional Ensemble and Deterministic Forecasts for a Case Study of Banded Snow  

Science Conference Proceedings (OSTI)

The ensemble Kalman filter (EnKF) technique is compared to other modeling approaches for a case study of banded snow. The forecasts include a 12- and 3-km grid-spaced deterministic forecast (D12 and D3), a 12-km 30-member ensemble (E12), and a 12-...

Astrid Suarez; Heather Dawn Reeves; Dustan Wheatley; Michael Coniglio

2012-02-01T23:59:59.000Z

388

Load Forecast For use in Resource Adequacy  

E-Print Network (OSTI)

Load Forecast 2019 For use in Resource Adequacy Massoud Jourabchi #12;In today's presentation d l­ Load forecast methodology ­ Drivers of the forecast f i­ Treatment of conservation ­ Incorporating impact of weather ­ Forecast for 2019 #12;Regional Loads (MWA and MW)Regional Loads (MWA and MW

389

Forecast Technical Document Felling and Removals  

E-Print Network (OSTI)

Forecast Technical Document Felling and Removals Forecasts A document describing how volume fellings and removals are handled in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Felling and removals forecasts Background A fellings and removals

390

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

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

391

Combining forecast weights: Why and how?  

Science Conference Proceedings (OSTI)

This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions

Yip Chee Yin; Ng Kok-Haur; Lim Hock-Eam

2012-01-01T23:59:59.000Z

392

PROBLEMS OF FORECAST1 Dmitry KUCHARAVY  

E-Print Network (OSTI)

1 PROBLEMS OF FORECAST1 Dmitry KUCHARAVY dmitry.kucharavy@insa-strasbourg.fr Roland DE GUIO roland for the purpose of Innovative Design. First, a brief analysis of problems for existing forecasting methods of the forecast errors. Second, using a contradiction analysis, a set of problems related to technology forecast

Paris-Sud XI, Université de

393

Using reforecasts for probabilistic forecast calibration  

E-Print Network (OSTI)

1 Using reforecasts for probabilistic forecast calibration Tom Hamill NOAA Earth System Research that is currently operational. #12;3 Why compute reforecasts? · For many forecast problems, such as long-lead forecasts or high-precipitation events, a few past forecasts may be insufficient for calibrating

Hamill, Tom

394

Assessing Forecast Accuracy Measures Department of Economics  

E-Print Network (OSTI)

Assessing Forecast Accuracy Measures Zhuo Chen Department of Economics Heady Hall 260 Iowa State forecast accuracy measures. In the theoretical direction, for comparing two forecasters, only when the errors are stochastically ordered, the ranking of the forecasts is basically independent of the form

395

Current status of ForecastCurrent status of Forecast 2005 EPACT is in the model  

E-Print Network (OSTI)

1 1 Current status of ForecastCurrent status of Forecast 2005 EPACT is in the model 2007 Federal prices are being inputted into the model 2 Sales forecast Select yearsSales forecast Select years --Draft 0.53% Irrigation 2.76% Annual Growth Rates Preliminary Electricity ForecastAnnual Growth Rates

396

Petroleum marketing monthly, July 1994  

Science Conference Proceedings (OSTI)

The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. Monthly statistics on purchases of crude oil and sales of petroleum products are presented in five sections: summary statistics; crude oil prices; prices of petroleum products; volumes of petroleum products; and prime supplier sales volumes of petroleum products for local consumption. 7 figs., 50 tabs.

Not Available

1994-07-01T23:59:59.000Z

397

Petroleum marketing monthly, August 1994  

SciTech Connect

The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Refined petroleum product Sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data in the Petroleum Marketing Monthly.

Not Available

1994-08-15T23:59:59.000Z

398

Petroleum marketing monthly, September 1994  

SciTech Connect

The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum product sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. The Petroleum Marketing Division, Office of Oil and Gas, Energy Information Administration ensures the accuracy, quality, and confidentiality of the published data in the Petroleum Marketing Monthly.

Not Available

1994-09-01T23:59:59.000Z

399

Petroleum marketing monthly, June 1994  

SciTech Connect

The Petroleum Marketing Monthly (PMM) provides information and statistical data on a variety of crude oils and refined petroleum products. The publication presents statistics on crude oil costs and refined petroleum products sales for use by industry, government, private sector analysts, educational institutions, and consumers. Data on crude oil include the domestic first purchase price, the f.o.b. and landed cost of imported crude oil, and the refiners` acquisition cost of crude oil. Refined petroleum product sales data include motor gasoline, distillates, residuals, aviation fuels, kerosene, and propane. Monthly statistics on purchases of crude oil and sales of petroleum products are presented in five sections: Summary Statistics; Crude Oil Prices; Prices of Petroleum Products; Volumes of Petroleum Products; and Prime Supplier Sales Volumes of Petroleum Products for Local Consumption. The feature article is entitled ``The Second Oxygenated Gasoline Season.`` 7 figs., 50 tabs.

Not Available

1994-06-01T23:59:59.000Z

400

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electric Power Sector Coal Stocks: November 2011 Electric Power Sector Coal Stocks: November 2011 Stocks As discussed in this month's feature story, electric power sector coal stocks continued to replenish after the summer burn in November, though stockpile levels remain below 2010 and 2009 levels. All coal stockpile levels declined from November 2010, with bituminous coal stockpile levels 9 percent lower than the same month of 2010. Days of Burn Days of burn Coal capacity The average number of days of burn held at electric power plants is a forward looking estimate of coal supply given a power plantâ€(tm)s current stockpile and past consumption patterns. The average number of days of burn held on hand at electric power plants dropped slightly from last month and remained below levels seen in November of 2010 or 2009. While

Note: This page contains sample records for the topic "include monthly forecasts" 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

Monthly Energy Statistics  

Gasoline and Diesel Fuel Update (EIA)

July July 2003 E n e r g y P l u g : R e s i d e n t i a l E n e r g y C o n s u m p t i o n Cover Image: Optical glass fibers, though many times thinner than a human hair, carry vastly greater quantities of data than metallic wires, occupy less space, and are more secure. First introduced in the 1970s, high-purity optical fibers are capable of transmitting data over long distances and have replaced wires in many telecommunications, computing, and electronics applications. Timing of release: MER data are normally released in the afternoon of the third-to-last workday of each month and are usually available electronically the following day. Released for Printing: July 28, 2003 Printed with soy ink on recycled paper. Monthly Energy Review The Monthly Energy Review (MER) presents an overview of the

402

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: March 2012 Regional Wholesale Markets: March 2012 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the Nation. The range of daily prices and demand data is shown for the report month and for the year ending with the report month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest

403

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

404

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

405

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

406

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

407

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electric Power Sector Coal Stocks: March 2012 Electric Power Sector Coal Stocks: March 2012 Stocks The seasonal winter drawdown of coal stocks was totally negated during the winter months this year due to low natural gas prices and unseasonably warm temperatures throughout the continental United States. In fact, March 2012 was the seventh straight month that coal stockpiles at power plants increased from the previous month. The largest driver of increasing stockpiles has been declining consumption of coal due to unseasonably warm weather and declining natural gas prices. Because much of the coal supplied to electric generators is purchased through long-term contracts, increasing coal stockpiles have proven difficult for electric power plant operators to handle. Some operators have inventories so high that they are refusing

408

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electric Power Sector Coal Stocks: October 2013 Electric Power Sector Coal Stocks: October 2013 Stocks In October 2013, total coal stocks increased 0.8 percent from the previous month. This follows the normal seasonal pattern for this time of year as the country begins to build up coal stocks to be consumed during the winter months. Compared to last October, coal stocks decreased 17.7 percent. This occurred because coal stocks in October 2012 were at an extremely high level. Days of Burn Days of burn Coal capacity The average number of days of burn held at electric power plants is a forward looking estimate of coal supply given a power plant's current stockpile and past consumption patterns. The total bituminous supply decreased from 85 days the previous month to 78 days in October 2013, while the total subbituminous supply decreased from 63 days in September 2013 to

409

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

410

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

411

monthly | OpenEI  

Open Energy Info (EERE)

714 714 Varnish cache server Browse Upload data GDR 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2142280714 Varnish cache server monthly Dataset Summary Description The Florida Geological Survey is where data related to oil, gas, and geothermal resources for the state of Florida are made public. This dataset contains monthly oil and gas production data for January and February of 2011. The dataset is in .xls format, and displays well status, well production, and cumulative data. Source Florida Geological Survey Date Released February 28th, 2011 (3 years ago) Date Updated Unknown Keywords data Florida gas monthly oil production Data application/vnd.ms-excel icon February 2011 oil and gas production data (xls, 33.8 KiB)

412

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: November 2011 Regional Wholesale Markets: November 2011 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the U.S. The range of daily prices and demand data is shown for the report month and for the year ending with the report month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest

413

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

414

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: December 2011 Regional Wholesale Markets: December 2011 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the nation. The range of daily prices and demand data is shown for the report month and for the year ending with the report month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest

415

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

416

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Methodology and Documentation Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S. Energy Information Administration (EIA), U.S. Department of Energy. Data published in the Electricity Monthly Update are compiled from the following sources: U.S. Energy Information Administration, Form EIA-826,"Monthly Electric Utility Sales and Revenues with State Distributions Report," U.S. Energy Information Administration, Form EIA-923, "Power Plant Operations Report," fuel spot prices from Bloomberg Energy, electric power prices from SNL Energy, electric system demand data from Ventyx Energy Velocity Suite, and weather data and imagery from the National Oceanic and Atmospheric

417

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: January 2012 Regional Wholesale Markets: January 2012 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the nation. The range of daily prices and demand data is shown for the report month and for the year ending with the report month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest

418

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: October 2011 Regional Wholesale Markets: October 2011 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the U.S. The range of daily prices and demand data is shown for the report month and for the year ending with the report month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest

419

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: February 2012 Regional Wholesale Markets: February 2012 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the Nation. The range of daily prices and demand data is shown for the report month and for the year ending with the report month. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest

420

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 technologies. This paper briefly discusses the observed patterns of the diffusion of new' technologies and the determinants (both sociological and economic) which have been proposed to explain the variation in the diffusion rates. Existing market penetration models are reviewed and their capability to forecast the use of conservation technologies is assessed using a set of criteria developed for this purpose. The reasoning behind the choice of criteria is discussed. The criteria includes the range of hypothesized influences to market penetration that are incorporated into the models and the applicability of the available parameter estimates. The attributes of our methodology and forecasting model choice (a behavioral lag equation developed by Mathtech, Inc.), are displayed using a list of the judgment criteria. This method was used to forecast the use of electricity conservation technologies in industries located in the Pacific Northwest for the Bonneville Power Administration.

Lang, K.

1982-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "include monthly forecasts" 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

Electric Power monthly, November 1996  

Science Conference Proceedings (OSTI)

This publication presents monthly electricity statistics for a wide audience including Congress, Federal and state agencies, the electric utility industry, and the general public. Purpose is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.

NONE

1996-11-01T23:59:59.000Z

422

Electric power monthly, May 1996  

Science Conference Proceedings (OSTI)

This publication presents monthly electricity statistics for a wide audience including Congress, Federal and Stage agencies, the electric utility industry, and the general public. Purpose is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. EIA collected the information to fulfill its data collection and dissemination responsibilities in Federal Energy Administration Act of 1974 (Public Law 93-275) as amended.

NONE

1996-05-01T23:59:59.000Z

423

Laser fusion monthly -- August 1980  

SciTech Connect

This report documents the monthly progress for the laser fusion research at Lawrence Livermore National Laboratory. First it gives facilities report for both the Shiva and Argus projects. Topics discussed include; laser system for the Nova Project; the fusion experiments analysis facility; optical/x-ray streak camera; Shiva Dante System temporal response; 2{omega}{sub 0} experiment; and planning for an ICF engineering test facility.

Ahlstrom, H.G. [ed.

1980-08-01T23:59:59.000Z

424

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":""}]}

425

Value of Wind Power Forecasting  

DOE Green Energy (OSTI)

This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

2011-04-01T23:59:59.000Z

426

Sampling Errors in Seasonal Forecasting  

Science Conference Proceedings (OSTI)

The limited numbers of start dates and ensemble sizes in seasonal forecasts lead to sampling errors in predictions. Defining the magnitude of these sampling errors would be useful for end users as well as informing decisions on resource ...

Stephen Cusack; Alberto Arribas

2009-03-01T23:59:59.000Z

427

Scoring Rules for Forecast Verification  

Science Conference Proceedings (OSTI)

The problem of probabilistic forecast verification is approached from a theoretical point of view starting from three basic desiderata: additivity, exclusive dependence on physical observations (“locality”), and strictly proper behavior. By ...

Riccardo Benedetti

2010-01-01T23:59:59.000Z

428

Wavelets and Field Forecast Verification  

Science Conference Proceedings (OSTI)

Current field forecast verification measures are inadequate, primarily because they compress the comparison between two complex spatial field processes into one number. Discrete wavelet transforms (DWTs) applied to analysis and contemporaneous ...

William M. Briggs; Richard A. Levine

1997-06-01T23:59:59.000Z

429

Richardson's Barotropic Forecast: A Reappraisal  

Science Conference Proceedings (OSTI)

To elucidate his numerical technique and to examine the effectiveness of geostrophic initial winds, Lewis Fry Richardson carried out an idealized forecast using the linear shallow-water equations and simple analytical pressure and velocity ...

Peter Lynch

1992-01-01T23:59:59.000Z

430

Downscaling Extended Weather Forecasts for Hydrologic Prediction  

SciTech Connect

Weather and climate forecasts are critical inputs to hydrologic forecasting systems. The National Center for Environmental Prediction (NCEP) issues 8-15 days outlook daily for the U.S. based on the Medium Range Forecast (MRF) model, which is a global model applied at about 2? spatial resolution. Because of the relatively coarse spatial resolution, weather forecasts produced by the MRF model cannot be applied directly to hydrologic forecasting models that require high spatial resolution to represent land surface hydrology. A mesoscale atmospheric model was used to dynamically downscale the 1-8 day extended global weather forecasts to test the feasibility of hydrologic forecasting through this model nesting approach. Atmospheric conditions of each 8-day forecast during the period 1990-2000 were used to provide initial and boundary conditions for the mesoscale model to produce an 8-day atmospheric forecast for the western U.S. at 30 km spatial resolution. To examine the impact of initialization of the land surface state on forecast skill, two sets of simulations were performed with the land surface state initialized based on the global forecasts versus land surface conditions from a continuous mesoscale simulation driven by the NCEP reanalysis. Comparison of the skill of the global and downscaled precipitation forecasts in the western U.S. showed higher skill for the downscaled forecasts at all precipitation thresholds and increasingly larger differences at the larger thresholds. Analyses of the surface temperature forecasts show that the mesoscale forecasts generally reduced the root-mean-square error by about 1.5 C compared to the global forecasts, because of the much better resolved topography at 30 km spatial resolution. In addition, initialization of the land surface states has large impacts on the temperature forecasts, but not the precipitation forecasts. The improvements in forecast skill using downscaling could be potentially significant for improving hydrologic forecasts for managing river basins.

Leung, Lai-Yung R.; Qian, Yun

2005-03-01T23:59:59.000Z

431

Application of DSM evaluation studies to utility forecasting and planning  

SciTech Connect

Utilities and their customers have made substantial investments in utility demand-side management (DSM) programs. These DSM programs also represent a substantial electricity resource. DSM program performance has been studied more systematically in recent years than over any previous period. DSM program evaluations are traditionally targeted to meet the program manager`s need for information on program costs and performance and, more recently, to verify savings to regulators for incentive awards and lost revenue recovery. Yet evaluations may also be used to produce results relevant to utility forecasting and planning. Applying evaluation results is especially important for utilities with substantial current and future commitments to acquiring demand-side resources. This report discusses the application of evaluation results to utility forecasting and planning. The report has three objectives. First, we identify what demand forecasters, DSM forecasters, and resource planners want to learn from evaluations. Second, we identify and describe the major obstacles and problems associated with applying evaluation results and illustrate many of these issues through a specific evaluation application exercise. Finally, we suggest approaches for addressing these major problems. The report summarizes results from interviews with utilities, regulators, and consultants to determine how the industry currently applies evaluation results in forecasting and planning. The report also includes results from case studies of Sacramento Municipal Utility District and Southern California Edison Company, utilities with large DSM programs and active evaluation efforts. Finally, we draw on a specific application exercise in which we used a set of impact evaluations to revise a utility DSM forecast.

Baxter, L.W.

1995-02-01T23:59:59.000Z

432

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-developed WATFORE model so that potential seasonal water use is calculated from a Fourier series fitted to seven-day weighted moving average values of daily maximum air temperature. A study is made comparing Kalman filtering and Box-Jenkins time series methods for automated model calibration. Although the Kalman filter method explains more of the time variation of the model parameters, the forecast accuracy of both methods is about the same. Box-Jenkins time series estimation algorithms specially designed for daily water use model parameter calibration, along with graphics and data editing routines, are implemented in WATCAL. A study is also made of the impact of conservation programs implemented in Austin and Corpus Christi, Texas during the dry summers of 1984 and 1985. Mandatory conservation programs reduced water use in Austin about 10% and in Corpus Christi about 30% of peak summer usage. The effects of an undesirable five-day cycle in Austin's water use (caused by a mandatory watering scheme where addresses ending in a specified pair of digits were allowed to water on a given day) were analyzed. An alternative address digit pairing devised as part Of this research eliminated the cycle during the summer Of 1986. A study of monthly and daily water use in five cities in Southern California shows that once water use data are made dimensionless, they follow a generic, weather-dependent pattern that is independent of city size and location within the region

Shaw, Douglas T.; Maidment, David R.

1987-08-01T23:59:59.000Z

433

November 2010 monthly report  

Science Conference Proceedings (OSTI)

These viewgraphs are to be provided to NNSA to update the status of the B61 Life Extension Project work and activities. The viewgraphs cover such issues as budget, schedule, scope, and the like. They are part of the monthly reporting process.

Neff, Warren E [Los Alamos National Laboratory

2010-12-07T23:59:59.000Z

434

Natural gas monthly  

Science Conference Proceedings (OSTI)

Monthly highlights of activities, events, and analyses of interest to public and private sector organizations associated with the natural gas industry are presented. Feature articles for this issue are: Natural Gas Overview for Winter 1983-1984 by Karen A. Kelley; and an Analysis of Natural Gas Sales by John H. Herbert. (PSB)

Not Available

1983-11-01T23:59:59.000Z

435

One-Month Ahead Prediction of Wind Speed and Output Power Based on EMD and LSSVM  

Science Conference Proceedings (OSTI)

Wind speed is a kind of non-stationary time series, it is difficult to construct the model for accurate forecast. The way improving accuracy of the model for predicting wind speed up to one-month ahead has been investigated using measured data recorded ... Keywords: wind speed forecasting, empirical mode decomposition(EMD), least square support vector machine (LSSVM), intrinsic mode function(IFM), wind power

Wang Xiaolan; Li Hui

2009-10-01T23:59:59.000Z

436

The Potential Impact of Using Persistence as a Reference Forecast on Perceived Forecast Skill  

Science Conference Proceedings (OSTI)

Skill is defined as actual forecast performance relative to the performance of a reference forecast. It is shown that the choice of reference (e.g., random or persistence) can affect the perceived performance of the forecast system. Two scores, ...

Marion P. Mittermaier

2008-10-01T23:59:59.000Z

437

The Complex Relationship between Forecast Skill and Forecast Value: A Real-World Analysis  

Science Conference Proceedings (OSTI)

For routine forecasts of temperature and precipitation, the relative skill advantage of human forecasters with respect to the numerical–statistical guidance is small (and diminishing). Since the relationship between forecast skill and the value ...

Paul J. Roebber; Lance F. Bosart

1996-12-01T23:59:59.000Z

438

Evaluation of Wave Forecasts Consistent with Tropical Cyclone Warning Center Wind Forecasts  

Science Conference Proceedings (OSTI)

An algorithm to generate wave fields consistent with forecasts from the official U.S. tropical cyclone forecast centers has been made available in near–real time to forecasters since summer 2007. The algorithm removes the tropical cyclone from ...

Charles R. Sampson; Paul A. Wittmann; Efren A. Serra; Hendrik L. Tolman; Jessica Schauer; Timothy Marchok

2013-02-01T23:59:59.000Z

439

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

440

Ability to Forecast Regional Soil Moisture with a Distributed Hydrological Model Using ECMWF Rainfall Forecasts  

Science Conference Proceedings (OSTI)

This study mimics an online forecast system to provide nine day-ahead forecasts of regional soil moisture. It uses modified ensemble rainfall forecasts from the numerical weather prediction model of the European Centre for Medium-Range Weather ...

J. M. Schuurmans; M. F. P. Bierkens

2009-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "include monthly forecasts" 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

What Is a Good Forecast? An Essay on the Nature of Goodness in Weather Forecasting  

Science Conference Proceedings (OSTI)

Differences of opinion exist among forecasters—and between forecasters and users—regarding the meaning of the phrase “good (bad) weather forecasts.” These differences of opinion are fueled by a lack of clarity and/or understanding concerning the ...

Allan H. Murphy

1993-06-01T23:59:59.000Z

442

Quantification of Uncertainity in Fire-Weather Forecasts: Some Results of Operational and Experimental Forecasting Programs  

Science Conference Proceedings (OSTI)

Fire-weather forecasts (FWFs) prepared by National Weather Service (NWS) forecasters on an operational basis are traditionally expressed in categorical terms. However, to make rational and optimal use of such forecasts, fire managers need ...

Barbara G. Brown; Allan H. Murphy

1987-09-01T23:59:59.000Z

443

Petroleum supply monthly, February 1994  

Science Conference Proceedings (OSTI)

The Petroleum Supply Monthly presents data describing the supply and disposition of petroleum products in the United States and major US geographic regions. The data series describe production, imports and exports, inter-Petroleum Administration for Defense (PAD) District movements, and inventories by the primary suppliers of petroleum products in the US. The reporting universe includes those petroleum sectors in primary supply. Included are: petroleum refiners, motor gasoline blenders; operators of natural gas processing plants and fractionators, inter-PAD transporters, importers, and major inventory holders of petroleum products and crude oil. Data are divided into two sections: Summary statistics and Detailed statistics.

Not Available

1994-03-01T23:59:59.000Z

444

Petroleum supply monthly, April 1994  

Science Conference Proceedings (OSTI)

Data presented in the Petroleum Supply Monthly (PSM) describe the supply and disposition of petroleum products in the United States and major US geographical regions. The data series describe production, imports and exports, inter-Petroleum Administration for Defense (PAD) District movements, and inventories by the primary suppliers of petroleum products in the US. The reporting universe includes those petroleum sectors in primary supply. Included are: petroleum refiners, motor gasoline blenders, operators of natural gas processing plants and fractionators, inter-PAD transporters, importers, and major inventory holders of petroleum products and crude oil. When aggregated, the data reported by these sectors approximately represent the consumption of petroleum products in the US.

Not Available

1994-04-01T23:59:59.000Z

445

Light truck forecasts  

SciTech Connect

The recent dramatic increase in the number of light trucks (109% between 1963 and 1974) has prompted concern about the energy consequences of the growing popularity of the light truck. An estimate of the future number of light trucks is considered to be a reasonable first step in assessing the energy impact of these vehicles. The monograph contains forecasts based on two models and six scenarios. The coefficients for the models have been derived by ordinary least squares regression of national level time series data. The first model is a two stage model. The first stage estimates the number of light trucks and cars (together), and the second stage applies a share's submodel to determine the number of light trucks. The second model is a simultaneous equation model. The two models track one another remarkably well, within about 2%. The scenarios were chosen to be consistent with those used in the Lindsey-Kaufman study Projection of Light Truck Population to Year 2025. Except in the case of the most dismal economic scenario, the number of light trucks is expected to increase from the 1974 level of 0.09 light truck per person to about 0.12 light truck per person in 1995.

Liepins, G.E.

1979-09-01T23:59:59.000Z

446

Monthly Energy Review The Monthly Energy Review  

Gasoline and Diesel Fuel Update (EIA)

natural gas, natural gas, coal, electricity, and nuclear energy. Also included are international energy and thermal and metric conversion factors. Publication of this report is in keeping with responsibilities given to the Energy Information Administration (EIA) in Public Law 95-91 (Department of Energy Organization Act), which states, in part, in Section 205(a)(2) that: The MER is intended for use by Members of Congress, Federal and State agencies, energy analysts, and the general public. EIA welcomes suggestions from readers regarding data series in the MER and in other EIA publications. Related Publication: Readers of the MER may also be interested in EIA's Annual Energy Review, where many of the same data series are provided annually beginning with 1949. Contact our National Energy Information Center at 202-586-8800 for more information. Timing of Release: MER data

447

Annual Energy Outlook Forecast Evaluation-Table 1  

Annual Energy Outlook 2012 (EIA)

Annual Energy Outlook Forecast Evaluation > Table 1 Annual Energy Outlook Forecast Evaluation Table 1. Comparison of Absolute Percent Errors for AEO Forecast Evaluation, 1996 to...

448

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007 INTEGRATED Table of Contents General Instructions for Demand Forecast Submittals.............................................................................. 4 Protocols for Submitted Demand Forecasts

449

Forecasting new product penetration with flexible substitution patterns  

E-Print Network (OSTI)

choice model for forecasting demand for alternative-fuel7511, Urban Travel Demand Forecasting Project, Institute of89 (1999) 109—129 Forecasting new product penetration with ?

Brownstone, David; Train, Kenneth

1999-01-01T23:59:59.000Z

450

Overestimation Reduction in Forecasting Telecommuting as a TDM Policy  

E-Print Network (OSTI)

M. , Ethics and advocacy in forecasting for public policy.change and social forecasting: the case of telecommuting asOverestimation Reduction in Forecasting Telecommuting as a

Tal, Gil

2008-01-01T23:59:59.000Z

451

Forecasting US CO2 Emissions Using State-Level Data  

E-Print Network (OSTI)

F. Hendry (eds), Economic Forecasting, Blackwell Publishing,W. : 2002, Macroeconomic forecasting using di?usion indexes,2003, Macroeconomic forecasting in the euro area: Country

Steinhauser, Ralf; Auffhammer, Maximilian

2005-01-01T23:59:59.000Z

452

NoVaS Transformations: Flexible Inference for Volatility Forecasting  

E-Print Network (OSTI)

and Correlation Forecasting” in G. Elliott, C.W.J.Handbook of Economic Forecasting, Amsterdam: North-Holland,Transformations”, forthcoming in Forecasting in the Presence

Politis, Dimitris N; Thomakos, Dimitrios D

2008-01-01T23:59:59.000Z

453

Forecasting new product penetration with flexible substitution patterns  

E-Print Network (OSTI)

7511, Urban Travel Demand Forecasting Project, Institute ofchoice model for forecasting demand for alternative-fuel89 (1999) 109—129 Forecasting new product penetration with

Brownstone, David; Train, Kenneth

1999-01-01T23:59:59.000Z

454

Earthquake Forecasting in Diverse Tectonic Zones of the Globe  

E-Print Network (OSTI)

Long-term probabilistic forecasting of earthquakes, J.2000), Probabilistic forecasting of earthquakes, Geophys. J.F.F. (2006), The EEPAS forecasting model and the probability

Kagan, Y. Y.; Jackson, D. D.

2010-01-01T23:59:59.000Z

455

Ensemble-based methods for forecasting census in hospital units  

E-Print Network (OSTI)

P, Fitzgerald G: Regression forecasting of patient admissionapproach to modeling and forecasting demand in the emergencySJ, Haug PJ, Snow GL: Forecasting daily patient volumes in

Koestler, Devin C; Ombao, Hernando; Bender, Jesse

2013-01-01T23:59:59.000Z

456

Forecasting Danerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures  

E-Print Network (OSTI)

costs could alter forecasting skill and the predictors thatForecasting Dangerous Inmate Misconduct: An Applications ofOn-Line Working Paper Series Forecasting Dangerous Inmate

Berk, Richard A.; Kriegler, Brian; Baek, John-Ho

2005-01-01T23:59:59.000Z

457

Developing a Practical Forecasting Screener for Domestic Violence Incidents  

E-Print Network (OSTI)

Developing a Practical Forecasting Screener for Domesticcomplicated did not improve forecasting skill. Taking thethe local costs of forecasting errors. It is also feasible

Richard A. Berk; Susan B. Sorenson; Yan He

2011-01-01T23:59:59.000Z

458

Forecasting with Dynamic Microsimulation: Design, Implementation, and Demonstration  

E-Print Network (OSTI)

Goulias Page 84 Forecasting with Dynamic Microsimulation:Goulias Page 80 Forecasting with Dynamic Microsimulation:L. Demographic Forecasting with a Dynamic Stochastic

Ravulaparthy, Srinath; Goulias, Konstadinos G.

2011-01-01T23:59:59.000Z

459

Electric power monthly, July 1994  

Science Conference Proceedings (OSTI)

The Electric Power Monthly (EPM) presents monthly electricity statistics. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead. Data in this report are presented for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. The EIA collected the information in this report to fulfill its data collection and dissemination responsibilities as specified in the Federal Energy Administration Act of 1974 (Public Law 93-275) as amended. The EPM is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the US, Census division, and State levels for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. Statistics by company and plant are published in the EPM on the capability of new generating units, net generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fossil fuels. Data on quantity, quality, and cost of fossil fuels lag data on net generation, fuel consumption, fuel stocks, electricity sales, and average revenue per kilowatthour by 1 month. This difference in reporting appears in the US, Census division, and State level tables. However, for purposes of comparison, plant-level data are presented for the earlier month.

Not Available

1994-07-01T23:59:59.000Z

460

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

Note: This page contains sample records for the topic "include monthly forecasts" 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

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

462

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

463

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

464

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Regional Wholesale Markets: September 2011 Regional Wholesale Markets: September 2011 The United States. has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale prices at selected pricing locations and daily peak demand for selected electricity systems in the U.S. The range of daily price and demand data is shown for the month of September 2011 and for the year ending on September 30, 2011. Prices and demand are shown for six Regional Transmission Operator (RTO) markets: ISO New England (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy), Southwest (Palo Verde) and

465

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

466

Project of the Month  

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

project-of-the-month Office of Environmental project-of-the-month Office of Environmental Management 1000 Independence Ave., SW Washington, DC 20585 202-586-7709 en One-of-a-Kind Facility Now in Safe Shutdown http://energy.gov/em/articles/one-kind-facility-now-safe-shutdown One-of-a-Kind Facility Now in Safe Shutdown

467

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

468

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

469

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Highlights: March 2012 Highlights: March 2012 Average natural gas prices at the Henry Hub declined for the eighth straight month leading to a nearly 40% increase in consumption for electricity during March 2012. The warmest March on record for much of the central U.S. drove a 5% decrease in residential retail sales when compared to March 2011. U.S. coal supplies as measured by days of burn were above 80 days for the third straight month in March as declining coal consumption drove coal stockpile increases. Key Indicators Mar 2012 % Change from Mar 2011 Total Net Generation (Thousand MWh) 309,709 -2.9% Residential Retail Price (cents/kWh) 11.76 1.5% Retail Sales (Thousand MWh) 282,453 -2.6% Heating Degree-Days 377 -36.4% Natural Gas Price, Henry Hub ($/MMBtu) 2.22 -45.7% Coal Stocks

470

End of Month Working  

Gasoline and Diesel Fuel Update (EIA)

The level of gas in storage at the end of the last heating season (March The level of gas in storage at the end of the last heating season (March 31, 2000) was 1,150 billion cubic feet (Bcf), just above the 1995-1999 average of 1,139 Bcf. Underground working gas storage levels are currently about 8-9 percent below year-ago levels. In large part, this is because injection rates since April 1 have been below average. Storage injections picked up recently due to warm weather in the last half of October. The month of November is generally the last month available in the year for injections into storage. A cold November would curtail net injections into storage. If net injections continue at average levels this winter, we project that storage levels will be low all winter, reaching a level of 818 Bcf at the end of March, the lowest level since 1996

471

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

March 2012 | Release Date: May 29, 2012 | Next March 2012 | Release Date: May 29, 2012 | Next Release Date: June 26, 2012 | Re-Release Date: November 28, 2012 (correction) Previous Issues Issue: November 2013 October 2013 September 2013 August 2013 July 2013 June 2013 May 2013 April 2013 March 2013 February 2013 January 2013 December 2012 November 2012 Previous issues Format: html xls Go Highlights: March 2012 Average natural gas prices at the Henry Hub declined for the eighth straight month leading to a nearly 40% increase in consumption for electricity during March 2012. The warmest March on record for much of the central U.S. drove a 5% decrease in residential retail sales when compared to March 2011. U.S. coal supplies as measured by days of burn were above 80 days for the third straight month in March as declining coal consumption drove

472

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

473

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electric Power Sector Coal Stocks: February 2012 Electric Power Sector Coal Stocks: February 2012 Stocks The unseasonably warm temperatures that the continental United States experienced throughout the winter, coupled with low natural gas prices, caused coal stocks at power plants to increase throughout the winter of 2011 - 2012. During this period, coal stocks usually see a seasonal decline due to the added need for electricity generation from coal plants for spacing heating load. However, it was the sixth straight month that coal stocks increased from the previous month, with this trend likely to continue as the country enters into spring. Days of Burn Days of burn Coal capacity The average number of days of burn held at electric power plants is a forward looking estimate of coal supply given a power plant's current

474

Electricity Monthly Update  

Gasoline and Diesel Fuel Update (EIA)

Electricity Monthly Update Explained Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains bulleted highlights at the top and key indicators in a table and graphics - data you might be interested in at a glance. The right column is used for navigation. End-Use: Retail Rates/Prices and Consumption The second section presents statistics on end-use: retail rates/prices and consumption of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general audience. The term rates/prices is used because charges for retail service are based primarily on set rates approved by State regulators. However, a number of

475

Electric power monthly  

SciTech Connect

The Electric Power Monthly is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the national, Census division, and State levels for net generation, fuel consumption, fuel stocks, quantity and quality of fuel, cost of fuel, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fuel are also displayed for the North American Electric Reliability Council (NERC) regions. Additionally, statistics by company and plant are published in the EPM on capability of new plants, new generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fuel.

1992-05-01T23:59:59.000Z

476

Monthly Energy Review - August 2012  

Gasoline and Diesel Fuel Update (EIA)

U F U F A u g u s t 2 0 1 2 Mo n t h l y E n e r g y R e v i e w w w w K e i ~ K g o v L me r Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen-

477

Monthly Energy Review - March 2011  

Gasoline and Diesel Fuel Update (EIA)

r c h 2 0 1 1 r c h 2 0 1 1 D O E / E I A - 0 0 3 5 ( 2 0 1 1 / 0 3 ) Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

478

Monthly Energy Review - November 2013  

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

N N F N N F N o v e mb e r 2 0 1 3 Mo n t h l y E n e r g y R e v i e w w w w K e i ~ K g o v L me r Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen-

479

Monthly Energy review - September 2009  

Gasoline and Diesel Fuel Update (EIA)

9 9 September 2009 DOE/EIA-0035(2009/09) Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

480

Monthly Energy Review - October 2010  

Gasoline and Diesel Fuel Update (EIA)

O c t o b e r 2 0 1 0 O c t o b e r 2 0 1 0 D O E / E I A - 0 0 3 5 ( 2 0 1 0 / 1 0 ) Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

Note: This page contains sample records for the topic "include monthly forecasts" 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

Monthly Energy Review - November 2011  

Gasoline and Diesel Fuel Update (EIA)

N F N F N o v e mb e r 2 0 1 1 Mo n t h l y E n e r g y R e v i e w w w w K e i ~ K g o v L me r Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen-

482

Monthly Energy Review - April 2008  

Gasoline and Diesel Fuel Update (EIA)

4) 4) April 2008 Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2), that: "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu- ate, assemble, analyze, and disseminate data and information...."

483

Monthly Energy Review - June 2011  

Gasoline and Diesel Fuel Update (EIA)

J u n e 2 0 1 1 J u n e 2 0 1 1 D O E / E I A - 0 0 3 5 ( 2 0 1 1 / 0 6 ) Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

484

Monthly Energy Review - November 2010  

Gasoline and Diesel Fuel Update (EIA)

N o v e mb e r 2 0 1 0 N o v e mb e r 2 0 1 0 D O E / E I A - 0 0 3 5 ( 2 0 1 0 / 1 1 ) Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

485

Monthly Energy Review, November 1997  

Gasoline and Diesel Fuel Update (EIA)

November November 24, 1997 Electronic Access Monthly Energy Review (MER) data are also available through these electronic means: * ASCII text, Lotus (wk1), and Excel (xls) versions of the MER tables are available through EIA's Internet homepage at: http://www.eia.doe.gov/emeu/mer/contents.html * A portable document format (pdf) file of the complete MER including text, tables, and graphs can be downloaded via the homepage at: http://www.eia.doe.gov/bookshelf/multi.html * MER data series in ASCII comma delimited file format (previously available on diskettes) can be downloaded via EIA's ftp site at ftp://ftp.eia.doe.gov/pub/energy.overview/monthly .energy/current.mer * For information about the Energy Info Disc, call 1-800-STAT-USA. This CD-ROM contains over 200 reports, databases, and models. Timing of Release: MER data are normally released in the afternoon of the third-from-the-last

486

Monthly Energy Review - October 2009  

Gasoline and Diesel Fuel Update (EIA)

October 2009 October 2009 October 2009 DOE/EIA-0035(2009/10) Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

487

Monthly Energy Review - March 2008  

Gasoline and Diesel Fuel Update (EIA)

3) 3) March 2008 Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2), that: "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu- ate, assemble, analyze, and disseminate data and information...."

488

Monthly Energy Review - May 2008  

Gasoline and Diesel Fuel Update (EIA)

5) 5) May 2008 Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2), that: "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu- ate, assemble, analyze, and disseminate data and information...."

489

Monthly Energy Review - February 2011  

Gasoline and Diesel Fuel Update (EIA)

F e b r u a r y 2 0 1 1 F e b r u a r y 2 0 1 1 D O E / E I A - 0 0 3 5 ( 2 0 1 1 / 0 2 ) Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

490

Monthly Energy Review - November 2013  

Gasoline and Diesel Fuel Update (EIA)

N F N F N o v e mb e r 2 0 1 3 Mo n t h l y E n e r g y R e v i e w w w w K e i ~ K g o v L me r Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen-

491

Monthly Energy Review - July 2008  

Gasoline and Diesel Fuel Update (EIA)

7) 7) Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu- ate, assemble, analyze, and disseminate data and information...."

492

Monthly Energy Review - May 2011  

Gasoline and Diesel Fuel Update (EIA)

y 2 0 1 1 y 2 0 1 1 D O E / E I A - 0 0 3 5 ( 2 0 1 1 / 0 5 ) Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu-

493

Monthly Energy Review - March 2013  

Gasoline and Diesel Fuel Update (EIA)

P F P F Ma r c h 2 0 1 3 Mo n t h l y E n e r g y R e v i e w w w w K e i ~ K g o v L me r Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen-

494

Monthly Energy Review - September 2008  

Gasoline and Diesel Fuel Update (EIA)

9) 9) Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu- ate, assemble, analyze, and disseminate data and information...."

495

Monthly Energy Review - December 2011  

Gasoline and Diesel Fuel Update (EIA)

O F O F D e c e mb e r 2 0 1 1 Mo n t h l y E n e r g y R e v i e w w w w K e i ~ K g o v L me r Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen-

496

Monthly Energy Review - December 2008  

Gasoline and Diesel Fuel Update (EIA)

2) 2) Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu- ate, assemble, analyze, and disseminate data and information...."

497

Monthly Energy Review - November 2008  

Gasoline and Diesel Fuel Update (EIA)

1) 1) Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu- ate, assemble, analyze, and disseminate data and information...."

498

Monthly Energy Review - April 2013  

Gasoline and Diesel Fuel Update (EIA)

Q F Q F A p r i l 2 0 1 3 Mo n t h l y E n e r g y R e v i e w w w w K e i ~ K g o v L me r Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen-

499

Monthly Energy Review - August 2008  

Gasoline and Diesel Fuel Update (EIA)

8) 8) Monthly Energy Review The Monthly Energy Review (MER) is the Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen- sive, and unified energy data and information program which will collect, evalu- ate, assemble, analyze, and disseminate data and information...."

500

Monthly Energy Review - July 2013  

Gasoline and Diesel Fuel Update (EIA)

T F T F J u l y 2 0 1 3 Mo n t h l y E n e r g y R e v i e w w w w K e i ~ K g o v L me r Monthly Energy Review The Monthly Energy Review (MER) is the U.S. Energy Information Administration's (EIA) primary report of recent and historical energy statistics. Included are statistics on total energy production, consumption, trade, and energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, renewable energy, and international petroleum; carbon dioxide emissions; and data unit conversions. Release of the MER is in keeping with responsibilities given to EIA in Public Law 95-91 (Depart- ment of Energy Organization Act), which states, in part, in Section 205(a)(2): "The Administrator shall be responsible for carrying out a central, comprehen-