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Note: This page contains sample records for the topic "module forecasts future" from the National Library of EnergyBeta (NLEBeta).
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1

Time Series Prediction Forecasting the Future and ...  

Science Conference Proceedings (OSTI)

Time Series Prediction Forecasting the Future and Understanding the Past Santa Fe Institute Proceedings on the Studies in the Sciences of ...

2012-10-01T23:59:59.000Z

2

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

3

Using Customers' Reported Forecasts to Predict Future Sales  

E-Print Network (OSTI)

Using Customers' Reported Forecasts to Predict Future Sales Nihat Altintas , Alan Montgomery orders using forecasts provided by their customers. Our goal is to improve the supplier's operations through a better un- derstanding of the customers's forecast behavior. Unfortunately, customer forecasts

Murphy, Robert F.

4

Model documentation: electricity market module. [15 year forecasts  

SciTech Connect

This report documents the electricity market model. This model is a component of the Intermediate Future Forecasting System (IFFS), the energy market model used to provide projections of energy markets up to 15 years into the future. The electricity market model was developed by the Supply Analysis and Integration Branch as part of building the larger system. This report is written for an audience consisting of mathematical economists, statisticians, operations research analysts, and utility planners. This report contains an overview and a mathematical specification of the electricity market module. It includes a description of the model logic and the individual subroutines in the computer code. A companion document Intermediate Future Forecasting System: Executive Summary (DOE/EIA-430) provides an overview of the components in IFFS and their linkages. 22 figures, 2 tables.

Sanders, R.C.; Murphy, F.H.

1984-12-01T23:59:59.000Z

5

Optimal Updating of Forecasts for the Timing of Future Events  

Science Conference Proceedings (OSTI)

A major problem in forecasting is estimating the time of some future event. traditionally, forecasts are designed to minimize an error cost function that is evaluated once, possibly when the event occurs and forecast accuracy can be determined. However, ... Keywords: Air Transportation, Dynamic Programming Applications, Forecasting

Juhwen Hwang; Medini R. Singh; W. J. Hurley; Robert A. Shumsky

1998-03-01T23:59:59.000Z

6

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

7

Mathematical and computer modelling reports: Modeling and forecasting energy markets with the intermediate future forecasting system  

Science Conference Proceedings (OSTI)

This paper describes the Intermediate Future Forecasting System (IFFS), which is the model used to forecast integrated energy markets by the U.S. Energy Information Administration. The model contains representations of supply and demand for all of the ...

Frederic H. Murphy; John J. Conti; Susan H. Shaw; Reginald Sanders

1989-09-01T23:59:59.000Z

8

Expert Panel: Forecast Future Demand for Medical Isotopes  

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

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

9

Solar future: 1978. [Market forecast to 1992  

SciTech Connect

The growth in sales of solar heating equipment is discussed. Some forecasts are made for the continued market growth of collectors, pool systems, and photovoltaics. (MOW)

Butt, S.H.

1978-03-01T23:59:59.000Z

10

Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

forecasts (or any other forecast, for that matter) in makingcase natural gas price forecast, but to also examine a wideAEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

Bolinger, Mark A.

2010-01-01T23:59:59.000Z

11

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

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

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

12

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

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

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

13

Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

AEO 2009 Natural Gas Price Forecast to NYMEX Futures Priceslong-term natural gas price forecasts from the AEO series toAEO reference-case gas price forecast compares to the NYMEX

Bolinger, Mark

2009-01-01T23:59:59.000Z

14

Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

longer-term market-based forecasts that can be used to more-AEO 2008 Natural Gas Price Forecast to NYMEX Futures Priceslong-term natural gas price forecasts from the AEO series to

Bolinger, Mark

2008-01-01T23:59:59.000Z

15

Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

a portion of the gas price forecast – through 2010 – can beAEO 2006 reference case forecast to conduct a 25-yearAEO 2006 Natural Gas Price Forecast to NYMEX Futures Prices

Bolinger, Mark; Wiser, Ryan

2005-01-01T23:59:59.000Z

16

Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

9: Two Alternative Price Forecasts (denoted by open circlesAEO 2007 Natural Gas Price Forecast to NYMEX Futures Priceslong-term natural gas price forecasts from the AEO series to

Bolinger, Mark; Wiser, Ryan

2006-01-01T23:59:59.000Z

17

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

18

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

E-Print Network (OSTI)

to the EIA’s natural gas price forecasts in AEO 2004 and AEOon the AEO 2005 natural gas price forecasts will likely onceof AEO 2005 Natural Gas Price Forecast to NYMEX Futures

Bolinger, Mark; Wiser, Ryan

2004-01-01T23:59:59.000Z

19

September 2000Forecasting Future Variance from Option Prices  

E-Print Network (OSTI)

Although it is widely believed that option prices provide the best possible forecasts of the future variance of the assets which underlie them, a large body of empirical evidence concludes that option prices consistently yield biased forecasts of future variance. The prevailing interpretation of these findings is that option investors may be forming unbiased forecasts of the future variance of underlying assets but that these unbiased forecasts fail to get impounded into option prices because of either (1) the difficulty of carrying out the necessary arbitrage strategies that would force the prices to their proper levels, or (2) the availability to market makers of lucrative alternative strategies in which they simply profit from the large bid-ask spreads in the options markets. This interpretation has significant consequences for nearly the entire range of option pricing research, since it implies that non-continuous trading, bid-ask spreads, and other market imperfections substantially influence option prices. This implication is important, both because incorporating these types of market imperfections into option pricing models is much more difficult than, for example, altering the dynamics of the underlying asset and also because it suggests that researchers cannot learn about option investor expectations by filtering option

Allen M. Poteshman; Mark R. Manfredo; Allen M. Poteshman; Allen M. Poteshman; Champaign Helpful; Jegadeesh Narasimhan

2000-01-01T23:59:59.000Z

20

Assessment of the possibility of forecasting future natural gas curtailments  

Science Conference Proceedings (OSTI)

This study provides a preliminary assessment of the potential for determining probabilities of future natural-gas-supply interruptions by combining long-range weather forecasts and natural-gas supply/demand projections. An illustrative example which measures the probability of occurrence of heating-season natural-gas curtailments for industrial users in the southeastern US is analyzed. Based on the information on existing long-range weather forecasting techniques and natural gas supply/demand projections enumerated above, especially the high uncertainties involved in weather forecasting and the unavailability of adequate, reliable natural-gas projections that take account of seasonal weather variations and uncertainties in the nation's energy-economic system, it must be concluded that there is little possibility, at the present time, of combining the two to yield useful, believable probabilities of heating-season gas curtailments in a form useful for corporate and government decision makers and planners. Possible remedial actions are suggested that might render such data more useful for the desired purpose in the future. The task may simply require the adequate incorporation of uncertainty and seasonal weather trends into modeling systems and the courage to report projected data, so that realistic natural gas supply/demand scenarios and the probabilities of their occurrence will be available to decision makers during a time when such information is greatly needed.

Lemont, S.

1980-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "module forecasts future" 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

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

E-Print Network (OSTI)

AEO 2005 reference case oil price forecast and NYMEX oi lthan the reference case oil price forecast for that year. Inoil futures case” where oil prices are based on the NYMEX

Bolinger, Mark; Wiser, Ryan

2004-01-01T23:59:59.000Z

22

Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

this “hybrid” NYMEX-EIA gas price projection still does notonly a portion of the gas price forecast – through 2010 –of AEO 2006 Natural Gas Price Forecast to NYMEX Futures

Bolinger, Mark; Wiser, Ryan

2005-01-01T23:59:59.000Z

23

Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

late January 2008, extend its natural gas futures strip anComparison of AEO 2008 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts from

Bolinger, Mark

2008-01-01T23:59:59.000Z

24

Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

Figure 9: Two Alternative Price Forecasts (denoted by openComparison of AEO 2007 Natural Gas Price Forecast toNYMEX Futures Prices Date: December 6, 2006 Introduction On

Bolinger, Mark; Wiser, Ryan

2006-01-01T23:59:59.000Z

25

Forecasting the Bayes factor of a future observation  

E-Print Network (OSTI)

I present a new procedure to forecast the Bayes factor of a future observation by computing the Predictive Posterior Odds Distribution (PPOD). This can assess the power of future experiments to answer model selection questions and the probability of the outcome, and can be helpful in the context of experiment design. As an illustration, I consider a central quantity for our understanding of the cosmological concordance model, namely the scalar spectral index of primordial perturbations, n_S. I show that the Planck satellite has over 90% probability of gathering strong evidence against n_S = 1, thus conclusively disproving a scale-invariant spectrum. This result is robust with respect to a wide range of choices for the prior on n_S.

Roberto Trotta

2007-03-05T23:59:59.000Z

26

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

27

Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

range of different plausible price projections, using eitherthat renewables can provide price certainty over even longerof AEO 2009 Natural Gas Price Forecast to NYMEX Futures

Bolinger, Mark

2009-01-01T23:59:59.000Z

28

Energy forecasting: the troubled past of looking the future  

SciTech Connect

Energy forecasts have hardly been distinguished by their accuracy. Why forecasts go awry, and the impact these prominent tools have, is explored. A brief review of the record is given. Because of their allure, their popularity in he media, and their usefulness as tools in political battles, forecasts have played a significant role so far. The danger is that they represent and enhance a fix 'em up, tinkering approach, to the detriment of more efficient free-market policies.

Kutler, E.

1986-01-01T23:59:59.000Z

29

Future world oil prices: modeling methodologies and summary of recent forecasts  

SciTech Connect

This paper has three main objectives. First, the various methodologies that have been developed to explain historical oil price changes and forecast future price trends are reviewed and summarized. Second, the paper summarizes recent world oil price forecasts, and, then possible, discusses the methodologies used in formulating those forecasts. Third, utilizing conclusions from the reviews of the modeling methodologies and the recent price forecasts, in combination with an assessment of recent and projected oil market trends, oil price projections are given for the time period 1987 to 2022. The paper argues that modeling methodologies have undergone significant evolution during the past decade as modelers increasingly recognize the complex and constantly changing structure of the world oil market. Unfortunately, at this point in time a consensus about the appropriate methodology to use in formulating oil price forecasts is yet to be reached. There is, however, a general movement toward the opinion that both economic and political factors should be considered when making price projections. Likewise, there is no consensus about future oil price trends. Forecasts differ widely. However, in general, forecasts have been adjusted downwardly in recent years. Further, an overall assessment of the forecasts and recent oil market trends suggests that oil prices will remain constant in real terms for the remainder of the 1980s. Real oil prices are expected to increase by between 2 and 3% during the 1990s and beyond. Forecasters are quick to point out, however, that all forecasts are subject to significant uncertainty. 69 references, 3 figures, 10 tables.

Curlee, T.R.

1985-04-01T23:59:59.000Z

30

A Hybrid ARCH-M and BP Neural Network Model For GSCI Futures Price Forecasting  

Science Conference Proceedings (OSTI)

As a versatile investment tool in energy markets for speculators and hedgers, the Goldman Sachs Commodity Index (GSCI) futures are quite well known. Therefore, this paper proposes a hybrid model incorporating ARCH family models and ANN model to forecast ... Keywords: ANN, ARCH-M, Commodity Index, Forecasting, GSCI

Wen Bo; Wang Shouyang; K. K. Lai

2007-05-01T23:59:59.000Z

31

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

index.html. Appendix A.1 Natural Gas Price Data for FuturesError STEO Error A.1 Natural Gas Price Data for Futuresof forecasts for natural gas prices as reported by the

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

2005-01-01T23:59:59.000Z

32

On The MSC Forecasters Forums and the Future Role of the Human Forecaster  

Science Conference Proceedings (OSTI)

The Meteorological Service of Canada held a series of three Forecasters Forum meetings between 2003 and 2005 to seek input from the meteorological community on the best ways to implement a restructuring strategy and to develop a common vision ...

David M. L. Sills

2009-05-01T23:59:59.000Z

33

Integration of Variable Generation Forecasting into System Operations: Current Practices and Future Requirements  

Science Conference Proceedings (OSTI)

This project update provides the first output of the EPRI Bulk Renewable Integration Program Project P173-010, “Integration of Variable Generation Forecasts into System Operations.” This project, begun in 2013, aims to improve existing methods utilities/independent system operators (ISOs) use to integrate forecasts into system operations and develop new methods. This year’s goal was to identify current practices and future requirements. This was done by interacting with a wide ...

2013-12-11T23:59:59.000Z

34

Quantile Forecasting of Commodity Futures' Returns: Are Implied Volatility Factors Informative?  

E-Print Network (OSTI)

This study develops a multi-period log-return quantile forecasting procedure to evaluate the performance of eleven nearby commodity futures contracts (NCFC) using a sample of 897 daily price observations and at-the-money (ATM) put and call implied volatilities of the corresponding prices for the period from 1/16/2008 to 7/29/2011. The statistical approach employs dynamic log-returns quantile regression models to forecast price densities using implied volatilities (IVs) and factors estimated through principal component analysis (PCA) from the IVs, pooled IVs and lagged returns. Extensive in-sample and out-of-sample analyses are conducted, including assessment of excess trading returns, and evaluations of several combinations of quantiles, model specifications, and NCFC's. The results suggest that the IV-PCA-factors, particularly pooled return-IV-PCA-factors, improve quantile forecasting power relative to models using only individual IV information. The ratio of the put-IV to the call-IV is also found to improve quantile forecasting performance of log returns. Improvements in quantile forecasting performance are found to be better in the tails of the distribution than in the center. Trading performance based on quantile forecasts from the models above generated significant excess returns. Finally, the fact that the single IV forecasts were outperformed by their quantile regression (QR) counterparts suggests that the conditional distribution of the log-returns is not normal.

Dorta, Miguel

2012-05-01T23:59:59.000Z

35

Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices  

SciTech Connect

On December 14, 2009, the reference-case projections from Annual Energy Outlook 2010 were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in itigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings.

Bolinger, Mark A.; Wiser, Ryan H.

2010-01-04T23:59:59.000Z

36

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

37

Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX FuturesPrices  

SciTech Connect

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

Bolinger, Mark; Wiser, Ryan

2005-12-19T23:59:59.000Z

38

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

SciTech Connect

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

Bolinger, Mark; Wiser, Ryan

2004-12-13T23:59:59.000Z

39

Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX FuturesPrices  

DOE Green Energy (OSTI)

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

Bolinger, Mark; Wiser, Ryan

2005-12-19T23:59:59.000Z

40

Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX FuturesPrices  

Science Conference Proceedings (OSTI)

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

Bolinger, Mark; Wiser, Ryan

2006-12-06T23:59:59.000Z

Note: This page contains sample records for the topic "module forecasts future" 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

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

DOE Green Energy (OSTI)

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

Bolinger, Mark; Wiser, Ryan

2004-12-13T23:59:59.000Z

42

Forecasting the Locations of Future Large Earthquakes: An Analysis and Verification  

E-Print Network (OSTI)

its uses in earthquake forecasting, Pure Appl. Geophys. 162,D.L. (2005), Earthquake forecasting and its veri?ca- tion,hazard assessment and forecasting, Pure Appl. Geophys. 157,

Shcherbakov, Robert; Turcotte, Donald L.; Rundle, John B.; Tiampo, Kristy F.; Holliday, James R.

2010-01-01T23:59:59.000Z

43

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

E-Print Network (OSTI)

revisions to the EIA’s natural gas price forecasts in AEOon the AEO 2005 natural gas price forecasts will likely onceComparison of AEO 2005 Natural Gas Price Forecast to NYMEX

Bolinger, Mark; Wiser, Ryan

2004-01-01T23:59:59.000Z

44

Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

to estimate the base-case natural gas price forecast, but toComparison of AEO 2010 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from the AEO

Bolinger, Mark A.

2010-01-01T23:59:59.000Z

45

Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

the base-case natural gas price forecast, but to alsoof AEO 2010 Natural Gas Price Forecast to NYMEX Futurescase long-term natural gas price forecasts from the AEO

Bolinger, Mark A.

2010-01-01T23:59:59.000Z

46

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

E-Print Network (OSTI)

revisions to the EIA’s natural gas price forecasts in AEOsolely on the AEO 2005 natural gas price forecasts willComparison of AEO 2005 Natural Gas Price Forecast to NYMEX

Bolinger, Mark; Wiser, Ryan

2004-01-01T23:59:59.000Z

47

Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

to estimate the base-case natural gas price forecast, but toComparison of AEO 2010 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts from

Bolinger, Mark A.

2010-01-01T23:59:59.000Z

48

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

the forecast. In 1978 the Natural Gas Policy Act was passedof Other Natural Gas Price Forecasts Researchers and policyresearchers and policy makers who utilize natural gas prices

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

2005-01-01T23:59:59.000Z

49

Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

Comparison of AEO 2006 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

Bolinger, Mark; Wiser, Ryan

2005-01-01T23:59:59.000Z

50

Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

Comparison of AEO 2008 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

Bolinger, Mark

2008-01-01T23:59:59.000Z

51

Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

Comparison of AEO 2007 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

Bolinger, Mark; Wiser, Ryan

2006-01-01T23:59:59.000Z

52

Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

Comparison of AEO 2009 Natural Gas Price Forecast to NYMEXcase long-term natural gas price forecasts from theto contemporaneous natural gas prices that can be locked in

Bolinger, Mark

2009-01-01T23:59:59.000Z

53

Comparing Price Forecast Accuracy of Natural Gas Models andFutures Markets  

SciTech Connect

The purpose of this article is to compare the accuracy of forecasts for natural gas prices as reported by the Energy Information Administration's Short-Term Energy Outlook (STEO) and the futures market for the period from 1998 to 2003. The analysis tabulates the existing data and develops a statistical comparison of the error between STEO and U.S. wellhead natural gas prices and between Henry Hub and U.S. wellhead spot prices. The results indicate that, on average, Henry Hub is a better predictor of natural gas prices with an average error of 0.23 and a standard deviation of 1.22 than STEO with an average error of -0.52 and a standard deviation of 1.36. This analysis suggests that as the futures market continues to report longer forward prices (currently out to five years), it may be of interest to economic modelers to compare the accuracy of their models to the futures market. The authors would especially like to thank Doug Hale of the Energy Information Administration for supporting and reviewing this work.

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

2005-06-30T23:59:59.000Z

54

Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

of AEO 2008 Natural Gas Price Forecast to NYMEX Futurescase long-term natural gas price forecasts from the AEOto contemporaneous natural gas prices that can be locked in

Bolinger, Mark

2008-01-01T23:59:59.000Z

55

Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

of AEO 2007 Natural Gas Price Forecast to NYMEX Futurescase long-term natural gas price forecasts from the AEOto contemporaneous natural gas prices that can be locked in

Bolinger, Mark; Wiser, Ryan

2006-01-01T23:59:59.000Z

56

Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

of AEO 2009 Natural Gas Price Forecast to NYMEX Futurescase long-term natural gas price forecasts from the AEOto contemporaneous natural gas prices that can be locked in

Bolinger, Mark

2009-01-01T23:59:59.000Z

57

Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

Comparison of AEO 2006 Natural Gas Price Forecast to NYMEXs reference case long-term natural gas price forecasts fromAEO series to contemporaneous natural gas prices that can be

Bolinger, Mark; Wiser, Ryan

2005-01-01T23:59:59.000Z

58

Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

Comparison of AEO 2009 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts fromAEO series to contemporaneous natural gas prices that can be

Bolinger, Mark

2009-01-01T23:59:59.000Z

59

Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

Comparison of AEO 2007 Natural Gas Price Forecast to NYMEXs reference case long-term natural gas price forecasts fromAEO series to contemporaneous natural gas prices that can be

Bolinger, Mark; Wiser, Ryan

2006-01-01T23:59:59.000Z

60

Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

approach to evaluating price risk would be to use suchthe base-case natural gas price forecast, but to alsorange of different plausible price projections, using either

Bolinger, Mark A.

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "module forecasts future" 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

Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

this “hybrid” NYMEX-EIA gas price projection still does notcomparison with fixed- price renewable generation (becauseonly a portion of the gas price forecast – through 2010 –

Bolinger, Mark; Wiser, Ryan

2005-01-01T23:59:59.000Z

62

Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices  

SciTech Connect

On December 17, 2008, the reference-case projections from Annual Energy Outlook 2009 (AEO 2009) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof), differences in capital costs and O&M expenses, or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired or nuclear generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers; and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal, uranium, and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

Bolinger, Mark; Wiser, Ryan

2009-01-28T23:59:59.000Z

63

Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices  

Science Conference Proceedings (OSTI)

On December 12, 2007, the reference-case projections from Annual Energy Outlook 2008 (AEO 2008) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof) or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers (though its appeal has diminished somewhat as prices have increased); and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

Bolinger, Mark A; Bolinger, Mark; Wiser, Ryan

2008-01-07T23:59:59.000Z

64

From: Mark Bolinger and Ryan Wiser, Berkeley Lab (LBNL) Subject: Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices Date: January 4, 2010 1. Introduction, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better

65

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 “naďve method”), or highly complex such as neural nets and econometric systems of simultaneous equations. The

Rob J Hyndman

2009-01-01T23:59:59.000Z

66

Using artificial neural networks to forecast the futures prices of crude oil  

Science Conference Proceedings (OSTI)

Crude oil is the commodity de jour and its pricing is of paramount importance to the layperson as well as to any responsible government. However, one of the main challenges facing econometric pricing models is the forecasting accuracy. ...

Hassan A. Khazem / A. K. Mazouz

2008-01-01T23:59:59.000Z

67

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

E-Print Network (OSTI)

to the EIA’s natural gas price forecasts in AEO 2004 and AEOcost comparisons of fixed-price renewable generationwith variable price gas-fired generation that are based

Bolinger, Mark; Wiser, Ryan

2004-01-01T23:59:59.000Z

68

Predicting daily streamflow using rainfall forecasts, a simple loss module and unit hydrographs: Two Brazilian catchments  

Science Conference Proceedings (OSTI)

The performance of a simple, spatially-lumped, rainfall-streamflow model is compared with that of a more complex, spatially-distributed model. In terms of two model-fit statistics it is shown that for two catchments in Brazil (about 30,000km^2 and 34,000km^2) ... Keywords: Brazil, Hydropower, Rainfall forecasts, River Paraná, Streamflow forecasts, Unit hydrographs

I. G. Littlewood; R. T. Clarke; W. Collischonn; B. F. W. Croke

2007-09-01T23:59:59.000Z

69

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Energy futures markets are ‘hubs’ that price and marketenergy price fluctuations. In theory, futures market pricesenergy prices, including most prominently, energy futures markets.

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

2005-01-01T23:59:59.000Z

70

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

energy price fluctuations. In theory, futures market prices summarize privately available informationEnergy; Brookhaven National Laboratory Canadian Energy Research Institute U.S. Energy Information Administration Energy Marketsinformation about future energy prices, including most prominently, energy futures markets.

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

2005-01-01T23:59:59.000Z

71

Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

Daily price history of 1st-nearby NYMEX natural gas futuresNatural Gas Futures Prices Figure 1 focuses on the historythe daily history of the average 5-year natural gas futures

Bolinger, Mark; Wiser, Ryan

2006-01-01T23:59:59.000Z

72

Successive Modulation of ENSO to the Future Greenhouse Warming  

Science Conference Proceedings (OSTI)

The multidecadal modulation of the El Nińo–Southern Oscillation (ENSO) due to greenhouse warming has been analyzed herein by means of diagnostics of Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) coupled general ...

Soon-Il An; Jong-Seong Kug; Yoo-Geun Ham; In-Sik Kang

2008-01-01T23:59:59.000Z

73

Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

Daily price history of 1st-nearby NYMEX natural gas futuresthe daily history of the average 5-year natural gas futuresNatural Gas Futures Prices F igure 1 focuses on the history

Bolinger, Mark

2008-01-01T23:59:59.000Z

74

Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network (OSTI)

Daily price history of 1st-nearby NYMEX natural gas futuresNatural Gas Futures Prices F igure 1 focuses on the historynatural gas prices. Figure 1 shows the daily price history

Bolinger, Mark; Wiser, Ryan

2005-01-01T23:59:59.000Z

75

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Appendix A.1 Natural Gas Price Data for Futures Market andSTEO Error A.1 Natural Gas Price Data for Futures Market andforecasts for natural gas prices as reported by the Energy

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

2005-01-01T23:59:59.000Z

76

Constraints on primordial non-Gaussianity from WMAP7 and luminous red galaxies power spectrum and forecast for future surveys  

Science Conference Proceedings (OSTI)

We place new constraints on the primordial local non-Gaussianity parameter f{sub NL} using recent cosmic microwave background anisotropy and galaxy clustering data. We model the galaxy power spectrum according to the halo model, accounting for a scale-dependent bias correction proportional to f{sub NL}/k{sup 2}. We first constrain f{sub NL} in a full 13 parameters analysis that includes 5 parameters of the halo model and 7 cosmological parameters. Using the WMAP7 CMB data and the SDSS DR4 galaxy power spectrum, we find f{sub NL}=171{sub -139}{sup +140} at 68% C.L. and -69forecast the constraints on f{sub NL} from future surveys as EUCLID and from CMB missions as Planck showing that their combined analysis could detect f{sub NL{approx}}5.

De Bernardis, Francesco [Physics Department and INFN, Universita di Roma 'La Sapienza', Ple Aldo Moro 2, 00185, Rome (Italy); Center for Cosmology, Department of Physics and Astronomy, University of California Irvine, Irvine, California 92697 (United States); Serra, Paolo; Cooray, Asantha [Center for Cosmology, Department of Physics and Astronomy, University of California Irvine, Irvine, California 92697 (United States); Melchiorri, Alessandro [Physics Department and INFN, Universita di Roma 'La Sapienza', Ple Aldo Moro 2, 00185, Rome (Italy)

2010-10-15T23:59:59.000Z

77

A model for forecasting future air travel demand on the North Atlantic  

E-Print Network (OSTI)

Introduction: One of the key problems in the analysis and planning of any transport properties and facilities is estimating the future volume of traffic that may be expected to use these properties and facilities. Estimates ...

Taneja, Nawal K.

1971-01-01T23:59:59.000Z

78

Forecasting future economic growth : the term structure of interest rates, volatility and inflation as leading indicators  

E-Print Network (OSTI)

The broad literature documents the empirical regularity that slope of the term structure of interest rates is a reliable predictor of future real economic activity. Steeper slopes presage increasing growth, and downward ...

Khait, Maria

2012-01-01T23:59:59.000Z

79

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Update on Petroleum, Natural Gas, Heating Oil and Gasoline.of the Market for Natural Gas Futures. Energy Journal 16 (Modeling Forum. 2003. Natural Gas, Fuel Diversity and North

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

2005-01-01T23:59:59.000Z

80

Forecast constraints on cosmic strings from future CMB, pulsar timing and gravitational wave direct detection experiments  

E-Print Network (OSTI)

We study future observational constraints on cosmic string parameters from various types of next-generation experiments: direct detection of gravitational waves (GWs), pulsar timing array, and the cosmic microwave background (CMB). We consider both GW burst and stochastic GW background searches by ground- and space-based interferometers as well as GW background detection in pulsar timing experiments. We also consider cosmic string contributions to the CMB temperature and polarization anisotropies. These different types of observations offer independent probes of cosmic strings and may enable us to investigate cosmic string properties if the signature is detected. In this paper, we evaluate the power of future experiments to constrain cosmic string parameters, such as the string tension Gmu, the initial loop size alpha, and the reconnection probability p, by performing Fisher information matrix calculations. We find that combining the information from the different types of observations breaks parameter degeneracies and provides more stringent constraints on the parameters. We also find future space-borne interferometers independently provide a highly precise determination of the parameters.

Sachiko Kuroyanagi; Koichi Miyamoto; Toyokazu Sekiguchi; Keitaro Takahashi; Joseph Silk

2012-10-10T23:59:59.000Z

Note: This page contains sample records for the topic "module forecasts future" 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

Constructive episodic simulation: temporal distance and detail of past and future events modulate hippocampal engagement  

E-Print Network (OSTI)

ABSTRACT: Behavioral, lesion and neuroimaging evidence show striking commonalities between remembering past events and imagining future events. In a recent event-related fMRI study, we instructed participants to construct a past or future event in response to a cue. Once an event was in mind, participants made a button press, then generated details (elaboration) and rated them. The elaboration of past and future events recruited a common neural network. However, regions within this network may respond differentially to event characteristics, such as the amount of detail generated and temporal distance, depending on whether the event is in the past or future. To investigate this further, we conducted parametric modulation analyses, with temporal distance and detail as covariates, and focused on the medial temporal lobes and frontopolar cortex. The analysis of detail (independent of temporal distance) showed that the left posterior hippocampus was responsive to the amount of detail comprising both past and future events. In contrast, the left anterior hippocampus responded differentially to the amount of detail comprising future events, possibly reflecting the recombination of details into a novel future event. The analysis of temporal distance revealed that the increasing recency of past events correlated with activity in the right parahippocampus gyrus (Brodmann area (BA) 35/36), while activity in the bilateral hippocampus was significantly correlated with the increasing remoteness of future events. We propose that the hippocampal response to the distance of future events reflects the increasing disparateness of details likely included in remote future events, and the intensive relational processing required for integrating such details into a coherent episodic simulation of the future. These findings provide further support for the constructive episodic simulation hypothesis (Schacter and Addis (2007) Philos Trans R Soc Lond B Biol Sci 362:773–786) and highlight the involvement of the hippocampus in relational processing during elaboration of future events. VC 2007 Wiley-Liss, Inc. KEY WORDS: episodic; autobiographical memory; future; fMRI; parametric modulation

Donna Rose Addis; Daniel L. Schacter

2008-01-01T23:59:59.000Z

82

FORECASTING COSMOLOGICAL PARAMETER CONSTRAINTS FROM NEAR-FUTURE SPACE-BASED GALAXY SURVEYS  

Science Conference Proceedings (OSTI)

The next generation of space-based galaxy surveys is expected to measure the growth rate of structure to a level of about one percent over a range of redshifts. The rate of growth of structure as a function of redshift depends on the behavior of dark energy and so can be used to constrain parameters of dark energy models. In this work, we investigate how well these future data will be able to constrain the time dependence of the dark energy density. We consider parameterizations of the dark energy equation of state, such as XCDM and {omega}CDM, as well as a consistent physical model of time-evolving scalar field dark energy, {phi}CDM. We show that if the standard, specially flat cosmological model is taken as a fiducial model of the universe, these near-future measurements of structure growth will be able to constrain the time dependence of scalar field dark energy density to a precision of about 10%, which is almost an order of magnitude better than what can be achieved from a compilation of currently available data sets.

Pavlov, Anatoly; Ratra, Bharat [Department of Physics, Kansas State University, 116 Cardwell Hall, Manhattan, KS 66506 (United States); Samushia, Lado, E-mail: pavlov@phys.ksu.edu, E-mail: ratra@phys.ksu.edu, E-mail: lado.samushia@port.ac.uk [Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Portsmouth PO1 3FX (United Kingdom)

2012-11-20T23:59:59.000Z

83

Forecasting technology costs via the Learning Curve - Myth or Magic?  

E-Print Network (OSTI)

is generally considered to be traditional fossil fuel power stations, hence making a further assumption that such a value for cost can be forecasted). In situations where niche markets exist (for example solar PV electricity for remote areas or hand held... Solar PV provides a good example of the use and dangers of using experience curves to forecast future costs of an energy technology. It is a good example since solar PV modules are generally accessed by an international market allowing for worldwide...

Alberth, Stephan

84

Economic Value of Seasonal Climate Forecasts for Agriculture: Review of Ex-Ante Assessments and Recommendations for Future Research  

Science Conference Proceedings (OSTI)

Advanced information in the form of seasonal climate forecasts has the potential to improve farmers’ decision making, leading to increases in farm profits. Interdisciplinary initiatives seeking to understand and exploit the potential benefits of ...

Francisco J. Meza; James W. Hansen; Daniel Osgood

2008-05-01T23:59:59.000Z

85

Orphan drugs : future viability of current forecasting models, in light of impending changes to influential market factors  

E-Print Network (OSTI)

Interviews were conducted to establish a baseline for how orphan drug forecasting is currently undertaken by financial market and industry analysts with the intention of understanding the variables typically accounted for ...

Gottlieb, Joshua

2011-01-01T23:59:59.000Z

86

Synoptic Forecasting of the Oceanic Mixed Layer Using the Navy's Operational Environmental Data Base: Present Capabilities and Future Applications  

Science Conference Proceedings (OSTI)

A synoptic forecast model of the oceanic mixed layer has been developed for operational use at the U.S. Navy's Fleet Numerical Oceanography Center (FNOC), Monterey, Calif. The potential success of this model depends critically on the quality of ...

R. Michael Clancy; Paul J. Martin

1981-06-01T23:59:59.000Z

87

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

88

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

89

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

90

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...

91

Quasi-Biweekly Mode and Its Modulation on the Diurnal Rainfall in Taiwan Forecasted by the CFS  

Science Conference Proceedings (OSTI)

The occurrence of diurnal afternoon convection in Taiwan undergoes substantial modulation from tropical intraseasonal oscillations in the western North Pacific, including the quasi-biweekly (QBW) mode. By analyzing surface station observations and ...

Shih-Yu Wang; Hsin-Hsing Chia; Robert R. Gillies; Xianan Jiang

2013-08-01T23:59:59.000Z

92

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

93

Forecasting exurban development to evaluate the influence of land-use policies on wildland and farmland conservation  

E-Print Network (OSTI)

Planning Vol 1 (2005) 40—57 Forecasting exurban developmentof general plans for forecasting future development can be

Merenlender, Adina M.; Brooks, Colin; Shabazian, David; Gao, Shengyi; Johnston, Robert A.

2005-01-01T23:59:59.000Z

94

Uses and Applications of Climate Forecasts for Power Utilities  

Science Conference Proceedings (OSTI)

The uses and potential applications of climate forecasts for electric and gas utilities were assessed 1) to discern needs for improving climate forecasts and guiding future research, and 2) to assist utilities in making wise use of forecasts. In-...

Stanley A. Changnon; Joyce M. Changnon; David Changnon

1995-05-01T23:59:59.000Z

95

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

96

Future Power Systems 20: The Smart Enterprise, its Objective...  

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

0: The Smart Enterprise, its Objective and Forecasting. Future Power Systems 20: The Smart Enterprise, its Objective and Forecasting. Future Power Systems 20: The Smart Enterprise,...

97

Uncertainties in forecasting future climate  

SciTech Connect

The increasing atmospheric concentrations of carbon dioxide, methane, chlorofluorocarbons, and other trace gases (collectively, greenhouse gases) pose a three-part challenge: (1) What the changes to atmospheric composition and the climate system will be; (2) What impacts (both detrimental and beneficial) these changes will induce on the biosphere and natural and societal resources; and (3) What the appropriate response, if any, might be when considering the changes themselves, the resulting impacts, and the benefits and other impacts of the activities generating the emissions. This brief summary will address only areas of agreement and areas of uncertainty related to the first challenge.

MacCracken, M.C.

1990-11-01T23:59:59.000Z

98

EUROCONTROL EUROCONTROL Long-Term Forecast: IFR Flight Movements 2010-2030  

E-Print Network (OSTI)

published in September 2010 (Ref.1). This forecast replaces the EUROCONTROL Long-Term Forecast issued in November 2008. The forecast uses four scenarios to explore the future of the aviation and the risks that lie

Flight Movements

2010-01-01T23:59:59.000Z

99

State-of-the art of freight forecast modeling: lessons learned and the road ahead  

E-Print Network (OSTI)

of-the art of freight forecast modeling: lessons learned andof goods as well as to forecast the expected future truckused for the short-term forecasts of freight volumes on

Chow, Joseph Y.; Yang, Choon Heon; Regan, Amelia C.

2010-01-01T23:59:59.000Z

100

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

Note: This page contains sample records for the topic "module forecasts future" 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

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

102

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

103

> 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

104

Energy conservation and official UK energy forecasts  

SciTech Connect

Behind the latest United Kingdom (UK) official forecasts of energy demand are implicit assumptions about future energy-price elasticities. Mr. Pearce examines the basis of the forecasts and finds that the long-term energy-price elasticities that they imply are two or three times too low. The official forecasts substantially understate the responsiveness of demand to energy price rises. If more-realistic price elasticities were assumed, the official forecasts would imply a zero primary energy-demand growth to 2000. This raises the interesting possibility of a low energy future being brought about entirely by market forces. 15 references, 3 tables.

Pearce, D.

1980-09-01T23:59:59.000Z

105

Extended-Range Probability Forecasts Based on Dynamical Model Output  

Science Conference Proceedings (OSTI)

A probability forecast has advantages over a deterministic forecast as the former offers information about the probabilities of various possible future states of the atmosphere. As physics-based numerical models find their success in modern ...

Jianfu Pan; Huug van den Dool

1998-12-01T23:59:59.000Z

106

A web-based Hong Kong tourism demand forecasting system  

Science Conference Proceedings (OSTI)

Accurate predictions of future business activities are important for business decision-making. As a consequence, powerful and simple forecasting processes are urgently pursued by decision-makers. This study presents a tourism demand forecasting system ...

Haiyan Song; Zixuan Gao; Xinyan Zhang; Shanshan Lin

2012-04-01T23:59:59.000Z

107

Potential Economic Value of Ensemble-Based Surface Weather Forecasts  

Science Conference Proceedings (OSTI)

The possible economic value of the quantification of uncertainty in future ensemble-based surface weather forecasts is investigated using a formal, idealized decision model. Current, or baseline, weather forecasts are represented by probabilistic ...

Daniel S. Wilks; Thomas M. Hamill

1995-12-01T23:59:59.000Z

108

A Review of Quantitative Precipitation Forecasts and Their Use in Short- to Medium-Range Streamflow Forecasting  

Science Conference Proceedings (OSTI)

Unknown future precipitation is the dominant source of uncertainty for many streamflow forecasts. Numerical weather prediction (NWP) models can be used to generate quantitative precipitation forecasts (QPF) to reduce this uncertainty. The ...

Lan Cuo; Thomas C. Pagano; Q. J. Wang

2011-10-01T23:59:59.000Z

109

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

110

Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

111

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

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

112

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

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

113

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

114

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

115

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

116

Draft Forecast of Electricity Demand for the 5th  

E-Print Network (OSTI)

products has been below the medium-low. Future natural gas prices are expected to be higher in this power's draft natural gas price forecasts. The medium natural gas price forecast for this plan in 2015 is about Council Document 2001-23, sited above. #12;DRAFT DRAFT DRAFT 11 Table 1 Natural Gas Price Forecasts

117

Earnings forecast bias -a statistical analysis Franois Dossou  

E-Print Network (OSTI)

Earnings forecast bias - a statistical analysis François Dossou Sandrine Lardic** Karine Michalon' earnings forecasts is an important aspect of research for different reasons: Many empirical studies employ analysts' consensus forecasts as a proxy for the market's expectations of future earnings in order

Paris-Sud XI, Université de

118

Distribution Based Data Filtering for Financial Time Series Forecasting  

E-Print Network (OSTI)

of stock prices, which aims to forecast the future values of the price of a stock, in order to obtain/selling strategies to gain competitive advantage. Classic and popular methods for stock price forecasting [3Distribution Based Data Filtering for Financial Time Series Forecasting Goce Ristanoski1 , James

Bailey, James

119

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 ...

Męuser Valença; Teresa Ludermir; Anelle Valença

2005-12-01T23:59:59.000Z

120

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

Note: This page contains sample records for the topic "module forecasts future" 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

Renewable Fuels Module  

Reports and Publications (EIA)

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the Annual Energy Outlook forecasts.

Chris Namovicz

2013-07-03T23:59:59.000Z

122

Maintaining the Role of Humans in the Forecast Process: Analyzing the Psyche of Expert Forecasters  

Science Conference Proceedings (OSTI)

The Second Forum on the Future Role of the Human in the Forecast Process occurred on 2–3 August 2005 at the American Meteorological Society's Weather Analysis and Forecasting Conference in Washington, D.C. The forum consisted of three sessions. ...

Neil A. Stuart; David M. Schultz; Gary Klein

2007-12-01T23:59:59.000Z

123

Mercury emissions from municipal solid waste combustors. An assessment of the current situation in the United States and forecast of future emissions  

Science Conference Proceedings (OSTI)

This report examines emissions of mercury (Hg) from municipal solid waste (MSW) combustion in the United States (US). It is projected that total annual nationwide MSW combustor emissions of mercury could decrease from about 97 tonnes (1989 baseline uncontrolled emissions) to less than about 4 tonnes in the year 2000. This represents approximately a 95 percent reduction in the amount of mercury emitted from combusted MSW compared to the 1989 mercury emissions baseline. The likelihood that routinely achievable mercury emissions removal efficiencies of about 80 percent or more can be assured; it is estimated that MSW combustors in the US could prove to be a comparatively minor source of mercury emissions after about 1995. This forecast assumes that diligent measures to control mercury emissions, such as via use of supplemental control technologies (e.g., carbon adsorption), are generally employed at that time. However, no present consensus was found that such emissions control measures can be implemented industry-wide in the US within this time frame. Although the availability of technology is apparently not a limiting factor, practical implementation of necessary control technology may be limited by administrative constraints and other considerations (e.g., planning, budgeting, regulatory compliance requirements, etc.). These projections assume that: (a) about 80 percent mercury emissions reduction control efficiency is achieved with air pollution control equipment likely to be employed by that time; (b) most cylinder-shaped mercury-zinc (CSMZ) batteries used in hospital applications can be prevented from being disposed into the MSW stream or are replaced with alternative batteries that do not contain mercury; and (c) either the amount of mercury used in fluorescent lamps is decreased to an industry-wide average of about 27 milligrams of mercury per lamp or extensive diversion from the MSW stream of fluorescent lamps that contain mercury is accomplished.

Not Available

1993-05-01T23:59:59.000Z

124

Impact of Early Forecast Information Sharing on Manufacturers with Capacity Uncertainty  

E-Print Network (OSTI)

251 Impact of Early Forecast Information Sharing on Manufacturers with Capacity Uncertainty of future demand. Advanced forecast information sharing between buyer and seller about these demand patterns) manufacturers receive an early rough forecast with a deterministic due date, however, forecast revisions

Chinnam, Ratna Babu

125

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

126

Assumptions to the Annual Energy Outlook 1999 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

127

Assumptions to the Annual Energy Outlook 2000 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

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

128

Assumptions to the Annual Energy Outlook 2002 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and

129

Assumptions to the Annual Energy Outlook 2001 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and

130

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...

131

A short-range forecasting and inventory strategy for new product launches  

E-Print Network (OSTI)

Companies like Procter & Gamble that operate on a make-to-stock strategy use forecasts to drive their manufacturing, selling, and buying processes. Because forecasting future demand is not an exact science, inventory ...

Cheung, Christine

2005-01-01T23:59:59.000Z

132

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

133

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

134

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 ...

135

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

136

A non-parametric data-based approach for probabilistic flood forecasting in support of uncertainty communication  

Science Conference Proceedings (OSTI)

In addition to structural measures, governmental authorities have set up flood forecasting systems to be used as early warning systems, to minimize the damage of future floods. These flood forecasting systems make use of hydrological and hydrodynamic ... Keywords: Non parametric approach, Operational flood forecasting, Probabilistic forecasting, Uncertainty estimation

N. Van Steenbergen; J. Ronsyn; P. Willems

2012-07-01T23:59:59.000Z

137

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

138

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 Sřrensen

2003-01-01T23:59:59.000Z

139

Annual Energy Outlook Forecast Evaluation 2005  

Gasoline and Diesel Fuel Update (EIA)

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

140

Dynamic Algorithm for Space Weather Forecasting System  

E-Print Network (OSTI)

We propose to develop a dynamic algorithm that intelligently analyzes existing solar weather data and constructs an increasingly more accurate equation/algorithm for predicting solar weather accurately in real time. This dynamic algorithm analyzes a wealth of data derived from scientific research and provides increasingly accurate solar forecasts. As the database of information grows over time, this algorithm perfects itself and reduces forecast uncertainties. This will provide a vastly more effective way of processing existing data for practical use in the public and private sectors. Specifically, we created an algorithm that stores data from several sources in a way that is useable, we created the ?dynamic algorithm? used for creating accurate/effective forecasts, and we have performed preliminary benchmarks on this algorithm. The preliminary benchmarks yield surprisingly effective results thus far?forecasts have been made 8-16 hours into the future with significant magnitude and trend accuracy, which is a vast improvement over current methods employed.

Fischer, Luke D.

2010-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "module forecasts future" 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.
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to obtain the most current and comprehensive results.


141

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

4 4 The commercial module forecasts consumption by fuel 15 at the Census division level using prices from the NEMS energy supply modules, and macroeconomic variables from the NEMS Macroeconomic Activity Module (MAM), as well as external data sources (technology characterizations, for example). Energy demands are forecast for ten end-use services 16 for eleven building categories 17 in each of the nine Census divisions (see Figure 5). The model begins by developing forecasts of floorspace for the 99 building category and Census division combinations. Next, the ten end-use service demands required for the projected floorspace are developed. The electricity generation and water and space heating supplied by distributed generation and combined heat and power technologies are projected. Technologies are then

142

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

143

Microsoft PowerPoint - FinalModule6.ppt  

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

6: Metrics, Performance 6: Metrics, Performance Measurements and Forecasting Prepared by: Module 6 - Metrics, Performance Measures and Forecasting 2 Prepared by: Booz Allen Hamilton Module 6: Metrics, Performance Measurements and Forecasting Welcome to Module 6. The objective of this module is to introduce you to the Metrics and Performance Measurement tools used, along with Forecasting, in Earned Value Management. The Topics that will be addressed in this Module include: * Define Cost and Schedule Variances * Define Cost and Schedule Performance Indices * Define Estimate to Complete (ETC) * Define Estimate at Completion (EAC) and Latest Revised Estimate (LRE) Module 6 - Metrics, Performance Measures and Forecasting 3 Prepared by: Booz Allen Hamilton Review of Previous Modules Let's quickly review what has been covered in the previous modules.

144

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

145

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

146

Large-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random Fields  

E-Print Network (OSTI)

pricing. Although it is known that probabilistic forecasts (which give a distribution over possible futureLarge-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random Fields Matt Wytock and J. Zico Kolter Abstract-- Short-term forecasting is a ubiquitous practice

Kolter, J. Zico

147

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

148

Adaptive sampling and forecasting with mobile sensor networks  

E-Print Network (OSTI)

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

Choi, Han-Lim

2009-01-01T23:59:59.000Z

149

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

150

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

151

Neural-wavelet Methodology for Load Forecasting  

Science Conference Proceedings (OSTI)

Intelligent demand-side management represents a future trend of power system regulation. A key issue in intelligent demand-side management is accurate prediction of load within a local area grid (LAG), which is defined as a set of customers with an appropriate ... Keywords: load forecasting, load identification, neural-wavelet

Rong Gao; Lefteri H. Tsoukalas

2001-05-01T23:59:59.000Z

152

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

153

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

154

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...

155

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

156

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

157

A RELM earthquake forecast based on pattern informatics  

E-Print Network (OSTI)

We present a RELM forecast of future earthquakes in California that is primarily based on the pattern informatics (PI) method. This method identifies regions that have systematic fluctuations in seismicity, and it has been demonstrated to be successful. A PI forecast map originally published on 19 February 2002 for southern California successfully forecast the locations of sixteen of eighteen M>5 earthquakes during the past three years. The method has also been successfully applied to Japan and on a worldwide basis. An alternative approach to earthquake forecasting is the relative intensity (RI) method. The RI forecast map is based on recent levels of seismic activity of small earthquakes. Recent advances in the PI method show considerable improvement, particularly when compared with the RI method using relative operating characteristic (ROC) diagrams for binary forecasts. The RELM application requires a probability for each location for a number of magnitude bins over a five year period. We have therefore co...

Holliday, J R; Donnelan, A; Rundle, J B; Tiampo, K F; Turcotte, D L; Chen, Chien-chih; Donnelan, Andrea; Holliday, James R.; Rundle, John B.; Tiampo, Kristy F.; Turcotte, Donald L.

2005-01-01T23:59:59.000Z

158

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

159

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

160

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

Note: This page contains sample records for the topic "module forecasts future" 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

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

162

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

163

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

164

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

165

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

Gasoline and Diesel Fuel Update (EIA)

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

166

Future risks of satellite-based tracking  

Science Conference Proceedings (OSTI)

This study finds out if in the future, some special risks concerning satellite-based tracking and navigation occur. To find out possible future risks, future research methods such as scenarios were being used. Forecasting the future is impossible, but ... Keywords: future research, risk management, satellite-base tracking, satellite-based navigation, tracking

Miikka Ohisalo; Otto Tiuri; Tatu Urpila; Jyri Rajamäki

2011-03-01T23:59:59.000Z

167

Forecasting photovoltaic array power production subject to mismatch losses  

Science Conference Proceedings (OSTI)

The development of photovoltaic (PV) energy throughout the world this last decade has brought to light the presence of module mismatch losses in most PV applications. Such power losses, mainly occasioned by partial shading of arrays and differences in PV modules, can be reduced by changing module interconnections of a solar array. This paper presents a novel method to forecast existing PV array production in diverse environmental conditions. In this approach, field measurement data is used to identify module parameters once and for all. The proposed method simulates PV arrays with adaptable module interconnection schemes in order to reduce mismatch losses. The model has been validated by experimental results taken on a 2.2 kW{sub p} plant, with three different interconnection schemes, which show reliable power production forecast precision in both partially shaded and normal operating conditions. Field measurements show interest in using alternative plant configurations in PV systems for decreasing module mismatch losses. (author)

Picault, D.; Raison, B.; Bacha, S. [Grenoble Electrical Engineering Laboratory (G2Elab), 961, rue Houille Blanche BP 46, 38402 St Martin d'Heres (France); de la Casa, J.; Aguilera, J. [Grupo de Investigacion IDEA, Departamento de Electronica, Escuela Politecnica Superior, Universidad de Jaen, Campus Las Lagunillas, 23071 Jaen (Spain)

2010-07-15T23:59:59.000Z

168

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

169

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

170

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 Sřrensen

2011-01-01T23:59:59.000Z

171

Wind Speed Forecasting for Power System Operation  

E-Print Network (OSTI)

In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system operation in terms of the efficiency of the system. The goal of this dissertation is to develop advanced statistical wind speed predictive models to reduce the uncertainties in wind, especially the short-term future wind speed. Moreover, a criterion is proposed to evaluate the performance of models. Cost reduction in power system operation, as proposed, is more realistic than prevalent criteria, such as, root mean square error (RMSE) and absolute mean error (MAE). Two advanced space-time statistical models are introduced for short-term wind speed forecasting. One is a modified regime-switching, space-time wind speed fore- casting model, which allows the forecast regimes to vary according to the dominant wind direction and seasons. Thus, it avoids a subjective choice of regimes. The other one is a novel model that incorporates a new variable, geostrophic wind, which has strong influence on the surface wind, into one of the advanced space-time statistical forecasting models. This model is motivated by the lack of improvement in forecast accuracy when using air pressure and temperature directly. Using geostrophic wind in the model is not only critical, it also has a meaningful geophysical interpretation. The importance of model evaluation is emphasized in the dissertation as well. Rather than using RMSE or MAE, the performance of both wind forecasting models mentioned above are assessed by economic benefits with real wind farm data from Pacific Northwest of the U.S and West Texas. Wind forecasts are incorporated into power system economic dispatch models, and the power system operation cost is used as a loss measure for the performance of the forecasting models. From another perspective, the new criterion leads to cost-effective scheduling of system-wide wind generation with potential economic benefits arising from the system-wide generation of cost savings and ancillary services cost savings. As an illustration, the integrated forecasts and economic dispatch framework are applied to the Electric Reliability Council of Texas (ERCOT) equivalent 24- bus system. Compared with persistence and autoregressive models, the first model suggests that cost savings from integration of wind power could be on the scale of tens of millions of dollars. For the second model, numerical simulations suggest that the overall generation cost can be reduced by up to 6.6% using look-ahead dispatch coupled with spatio-temporal wind forecast as compared with dispatch with persistent wind forecast model.

Zhu, Xinxin

2013-08-01T23:59:59.000Z

172

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

173

Commercial Sector Demand Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Kevin Jarzomski

2012-11-15T23:59:59.000Z

174

Commercial Sector Demand Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Kevin Jarzomski

2013-10-10T23:59:59.000Z

175

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

176

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

177

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

178

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.

179

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

180

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...

Note: This page contains sample records for the topic "module forecasts future" 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

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

182

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

183

Comparison of Wind Power and Load Forecasting Error Distributions: Preprint  

DOE Green Energy (OSTI)

The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent System Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.

Hodge, B. M.; Florita, A.; Orwig, K.; Lew, D.; Milligan, M.

2012-07-01T23:59:59.000Z

184

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 12 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS 27 data.

185

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

186

Forecasting the Impact of the Irregular Events with DIPA Methodology  

Science Conference Proceedings (OSTI)

The impact of the irregular events on oil futures markets is so great that it is even superior to the variation tendency of the time series itself. In order to forecast the influence of the irregular events on oil futures price, based on the thorough ...

Jinrong Zhu

2008-01-01T23:59:59.000Z

187

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

188

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

189

Forecasting Cosmological Constraints from Redshift Surveys  

E-Print Network (OSTI)

Observations of redshift-space distortions in spectroscopic galaxy surveys offer an attractive method for observing the build-up of cosmological structure, which depends both on the expansion rate of the Universe and our theory of gravity. In this paper we present a formalism for forecasting the constraints on the growth of structure which would arise in an idealized survey. This Fisher matrix based formalism can be used to study the power and aid in the design of future surveys.

Martin White; Yong-Seon Song; Will J. Percival

2008-10-08T23:59:59.000Z

190

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

191

Decision support for financial forecasting  

SciTech Connect

A primary mission of the Budget Management Division of the Air Force is fiscal analysis. This involves formulating, justifying, and tracking financial data during budget preparation and execution. An essential requirement of this process is the ready availability and easy manipulation of past and current budget data. This necessitates the decentralization of the data. A prototypical system, BAFS (Budget Analysis and Forecasting System), that provides such a capability is presented. In its current state, the system is designed to be a decision support tool. A brief report of the budget decisions and activities is presented. The system structure and its major components are discussed. An insight into the implementation strategies and the tool used is provided. The paper concludes with a discussion of future enhancements and the system's evolution into an expert system. 4 refs., 3 figs.

Jairam, B.N.; Morris, J.D.; Emrich, M.L.; Hardee, H.K.

1988-10-01T23:59:59.000Z

192

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

193

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

194

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

195

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

196

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

197

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

198

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

199

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

200

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.

Note: This page contains sample records for the topic "module forecasts future" 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

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

202

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

203

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

204

Forecasting world oil prices: the evolution of modeling methodologies and summary of recent projections  

SciTech Connect

This paper has three main objectives: (1) to review and summarize the varios methodologies that have been developed to explain historical oil price changes and forecast future price trends, (2) to summarize recent world oil price forecasts, and, when possible, discuss the methodologies used in formulating those forecasts, and (3) utilizing conclusions from the reviews of the modeling methodologies and the recent price forecasts, in combination with an assessment of recent and projected oil market trends, to give oil price projections for the time period 1987 to 2022. The paper argues that modeling methodologies have undergone significant evolution during the past decade as modelers increasingly recognize the complex and constantly changing structure of the world oil market. Unfortunately, a consensus about the appropriate methodology to use in formulating oil price forecasts is yet to be reached. There is, however, a general movement toward the opinion that both economic and political factors should be considered when making price projections. Likewise, there is no consensus about future oil price trends. Forecasts differ widely. However, in general, forecasts have been adjusted downwardly in recent years. Further, an overall assessment of the forecasts and recent oil market trends suggests that oil prices will remain constant in real terms for the remainder of the 1980s. Real oil prices are expected to increase by between 2 and 3% during the 1990s and beyond. Forecasters are quick to point out, however, that all forecasts are subject to significant uncertainty. 68 references, 1 figure, 6 tables.

Curlee, T.R.

1985-01-01T23:59:59.000Z

205

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,

206

Context-aware parameter estimation for forecast models in the energy domain  

Science Conference Proceedings (OSTI)

Continuous balancing of energy demand and supply is a fundamental prerequisite for the stability and efficiency of energy grids. This balancing task requires accurate forecasts of future electricity consumption and production at any point in time. For ... Keywords: energy, forecasting, maintenance, parameter estimation

Lars Dannecker; Robert Schulze; Matthias Böhm; Wolfgang Lehner; Gregor Hackenbroich

2011-07-01T23:59:59.000Z

207

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect

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

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

2005-07-01T23:59:59.000Z

208

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

209

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

210

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

211

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

212

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.

213

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

SciTech Connect

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

NONE

1995-02-01T23:59:59.000Z

214

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

215

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

E-Print Network (OSTI)

Comparisons are made of energy forecasts using results from the Industrial module of the National Energy Modeling System (NEMS) and an industrial economic-engineering model called the Industrial Technology and Energy Modeling System (ITEMS), a model developed for industrial energy analysis at the Pacific Northwest National Laboratory. Although the results are mixed, generally ITEMS show greater penetration of energy efficient technologies and thus lower energy use, even though the business as usual forecasts for ITEMS uses a higher discount rate than NEMS uses.

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

2000-04-01T23:59:59.000Z

216

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

217

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

218

Free World energy survey: historical overview and long-term forecast  

SciTech Connect

This report gives a historical overview of international energy markets from the 1950s to date, and an analysis of future energy prices, economic growth, and potential supply instabilities. Forecasts of energy demand by region and fuel type are provided.

1983-01-01T23:59:59.000Z

219

On the Use of Mesoscale and Cloud-Scale Models in Operational Forecasting  

Science Conference Proceedings (OSTI)

In the near future, the technological capability will be available to use mesoscale and cloud-scale numerical models for forecasting convective weather in operational meteorology. We address some of the issues concerning effective utilization of ...

Harold E. Brooks; Charles A. Doswell III; Robert A. Maddox

1992-03-01T23:59:59.000Z

220

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 ...

Męuser Valença; Teresa Ludermir

2002-11-01T23:59:59.000Z

Note: This page contains sample records for the topic "module forecasts future" 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

Representing Serial Correlation of Meteorological Events and Forecasts in Dynamic Decision–Analytic Models  

Science Conference Proceedings (OSTI)

A recursive solution for optimal sequences of decisions given uncertainty in future weather events, and forecasts of those events, is presented. The formulation incorporates a representation of the autocorrelation that is typically exhibited. The ...

Daniel S. Wilks

1991-07-01T23:59:59.000Z

222

WRF-Fire: Coupled Weather–Wildland Fire Modeling with the Weather Research and Forecasting Model  

Science Conference Proceedings (OSTI)

A wildland fire-behavior module, named WRF-Fire, was integrated into the Weather Research and Forecasting (WRF) public domain numerical weather prediction model. The fire module is a surface fire-behavior model that is two-way coupled with the ...

Janice L. Coen; Marques Cameron; John Michalakes; Edward G. Patton; Philip J. Riggan; Kara M. Yedinak

2013-01-01T23:59:59.000Z

223

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

224

TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY  

E-Print Network (OSTI)

of future contributions from various emerging transportation fuels and technologies is unknown. PotentiallyCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY AND TRANSPORTATION DIVISION B. B. Blevins Executive Director DISCLAIMER This report was prepared by a California

225

Application of Polynomial Neural Networks to Exchange Rate Forecasting  

Science Conference Proceedings (OSTI)

This research investigates the use of Ridge Polynomial Neural Network (RPNN) as non-linear prediction model to forecast the future trends of financial time series. The network was used for the prediction of one step ahead and five steps ahead of two ... Keywords: Dynamic Ridge Polynomial Neural Network, Financial time series, Multilayer Perceptron, Ridge Polynomial Neural Network

R. Ghazali; A. J. Hussain; M. N. Mohd. Salleh

2008-11-01T23:59:59.000Z

226

Building simulation weather forecast files for predictive control strategies  

Science Conference Proceedings (OSTI)

Model-Based Predictive Control (MPC) has received significant attention in recent years as a tool for load management in buildings. MPC is based on predicting the response of a system based on knowledge of future inputs, such as weather and occupancy. ... Keywords: EPW files, building simulation, predictive control, weather forecast

José. A. Candanedo; Éric Paradis; Meli Stylianou

2013-04-01T23:59:59.000Z

227

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

228

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

229

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

230

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

231

Residential Sector Demand Module 1998, Model Documentation  

Reports and Publications (EIA)

This is the fourth edition of the Model Documentation Report: Residential Sector DemandModule of the National Energy Modeling System (NEMS). It reflects changes made to themodule over the past year for the Annual Energy Outlook 1998. Since last year, severalnew end-use services were added to the module, including: Clothes washers,dishwashers, furnace fans, color televisions, and personal computers. Also, as with allNEMS modules, the forecast horizon has been extended to the year 2020.

John H. Cymbalsky

1998-01-01T23:59:59.000Z

232

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

233

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

234

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

235

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

236

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

237

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

238

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

239

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

240

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 "module forecasts future" 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

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

242

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, ĄoL4, 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

243

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

244

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

245

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

246

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

247

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

248

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

249

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

250

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

251

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

252

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

253

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

254

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

255

Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets  

Science Conference Proceedings (OSTI)

This paper evaluates the accuracy of two methods to forecast natural gas prices: using the Energy Information Administration's ''Annual Energy Outlook'' forecasted price (AEO) and the ''Henry Hub'' compared to U.S. Wellhead futures price. A statistical analysis is performed to determine the relative accuracy of the two measures in the recent past. A statistical analysis suggests that the Henry Hub futures price provides a more accurate average forecast of natural gas prices than the AEO. For example, the Henry Hub futures price underestimated the natural gas price by 35 cents per thousand cubic feet (11.5 percent) between 1996 and 2003 and the AEO underestimated by 71 cents per thousand cubic feet (23.4 percent). Upon closer inspection, a liner regression analysis reveals that two distinct time periods exist, the period between 1996 to 1999 and the period between 2000 to 2003. For the time period between 1996 to 1999, AEO showed a weak negative correlation (R-square = 0.19) between forecast price by actual U.S. Wellhead natural gas price versus the Henry Hub with a weak positive correlation (R-square = 0.20) between forecasted price and U.S. Wellhead natural gas price. During the time period between 2000 to 2003, AEO shows a moderate positive correlation (R-square = 0.37) between forecasted natural gas price and U.S. Wellhead natural gas price versus the Henry Hub that show a moderate positive correlation (R-square = 0.36) between forecast price and U.S. Wellhead natural gas price. These results suggest that agencies forecasting natural gas prices should consider incorporating the Henry Hub natural gas futures price into their forecasting models along with the AEO forecast. Our analysis is very preliminary and is based on a very small data set. Naturally the results of the analysis may change, as more data is made available.

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

2005-02-09T23:59:59.000Z

256

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

257

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

258

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

259

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

260

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...

Note: This page contains sample records for the topic "module forecasts future" 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

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

262

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

263

Forecasts for CMB ?- and i-type spectral distortion constraints on the primordial power spectrum on scales 8 < k < 10^4 Mpc^-1 with the future Pixie-like experiments  

E-Print Network (OSTI)

Silk damping at redshifts 1.5 x 10^4 < z < 2 x 10^6 erases CMB anisotropies on scales corresponding to the comoving wavenumbers 8 < k < 10^4 Mpc^-1 (10^5 < \\ell < 10^8). This dissipated energy is gained by the CMB monopole, creating distortions from a blackbody in the CMB spectrum of the \\mu-type and the i-type. We study, using Fisher matrices, the constraints we can get from measurements of these spectral distortions on the primordial power spectrum from future experiments such as Pixie, and how these constraints change as we change the frequency resolution and the sensitivity of the experiment. We show that the additional information in the shape of the $i$-type distortions, in combination with the \\mu-type distortions, allows us to break the degeneracy between the amplitude and the spectral index of the power spectrum on these scales and leads to much tighter constraints. We quantify the information contained in both the \\mu-type distortions and the i-type distortions taking into account the partial degeneracy with the y-type distortions and the temperature of the blackbody part of the CMB. We also calculate the constraints possible on the primordial power spectrum when the spectral distortion information is combined with the CMB anisotropies measured by the WMAP, SPT, ACT and Planck experiments.

Rishi Khatri; Rashid A. Sunyaev

2013-03-28T23:59:59.000Z

264

Assumptions to the Annual Energy Outlook - Household Expenditures Module  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module Assumption to the Annual Energy Outlook Household Expenditures Module Figure 5. United States Census Divisions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and demographic characteristics, and consumption and expenditures for fuels for various end-uses. These data are combined with NEMS forecasts of household disposable income, fuel consumption, and fuel expenditures by end-use and household type. The HEM disaggregation algorithm uses these combined results to forecast household fuel consumption and expenditures by income quintile and Census Division (see

265

Load transfer coupling regression curve fitting for distribution load forecasting  

SciTech Connect

The planning of distribution facilities requires forecasts of future substation and feeder loads. Extrapolation based on a curve fit to past annual peak loads is currently the most popular manner of accomplishing this forecast. Curve fitting suffers badly from data shifts caused by switching as loads are routinely moved from one substation to another during the course of utility operations. This switching contaminates the data, reducing forecast accuracy. A new regression application reduces error due to these transfers by over an order of magnitude. A key to the usefulness of this method is that the amount of the transfer, and its direction (whether it was to or from a substation), is not a required input. The new technique, aspects of computer implementation of it, and a series of tests showing its advantage over normal multiple regression methods are given.

Willis, H.L.; Powell, R.W.

1984-05-01T23:59:59.000Z

266

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

267

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

268

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

269

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

270

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

271

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

272

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

273

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

274

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

275

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

276

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

277

Accurate Short Term Load Forecasting for an ESKOM Major Distribution Region in South Africa: An Application of EPRI ANNSTLF  

Science Conference Proceedings (OSTI)

ANNSTLF (Artificial Neural Network Short-term Load Forecaster), developed by EPRI, is a Microsoft Windows-based neural-network load forecasting software that uses historical load and weather parameters to predict future load values. The software requires customization for each utility. This project involved customizing ANNSTLF for the Eastern Region of the South African energy company ESKOM.

2005-09-27T23:59:59.000Z

278

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":""}]}

279

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

280

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

Note: This page contains sample records for the topic "module forecasts future" 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

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

282

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

283

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

284

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

285

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

286

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

287

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

288

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

289

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

290

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

291

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

292

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

293

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

294

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect

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

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

2005-07-01T23:59:59.000Z

295

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...

296

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

297

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

298

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

299

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

300

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

Note: This page contains sample records for the topic "module forecasts future" 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

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

302

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

303

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

304

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

305

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

306

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...

307

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

308

A Kalman-filter bias correction of ozone deterministic, ensemble-averaged, and probabilistic forecasts  

SciTech Connect

Kalman filtering (KF) is used to postprocess numerical-model output to estimate systematic errors in surface ozone forecasts. It is implemented with a recursive algorithm that updates its estimate of future ozone-concentration bias by using past forecasts and observations. KF performance is tested for three types of ozone forecasts: deterministic, ensemble-averaged, and probabilistic forecasts. Eight photochemical models were run for 56 days during summer 2004 over northeastern USA and southern Canada as part of the International Consortium for Atmospheric Research on Transport and Transformation New England Air Quality (AQ) Study. The raw and KF-corrected predictions are compared with ozone measurements from the Aerometric Information Retrieval Now data set, which includes roughly 360 surface stations. The completeness of the data set allowed a thorough sensitivity test of key KF parameters. It is found that the KF improves forecasts of ozone-concentration magnitude and the ability to predict rare events, both for deterministic and ensemble-averaged forecasts. It also improves the ability to predict the daily maximum ozone concentration, and reduces the time lag between the forecast and observed maxima. For this case study, KF considerably improves the predictive skill of probabilistic forecasts of ozone concentration greater than thresholds of 10 to 50 ppbv, but it degrades it for thresholds of 70 to 90 ppbv. Moreover, KF considerably reduces probabilistic forecast bias. The significance of KF postprocessing and ensemble-averaging is that they are both effective for real-time AQ forecasting. KF reduces systematic errors, whereas ensemble-averaging reduces random errors. When combined they produce the best overall forecast.

Monache, L D; Grell, G A; McKeen, S; Wilczak, J; Pagowski, M O; Peckham, S; Stull, R; McHenry, J; McQueen, J

2006-03-20T23:59:59.000Z

309

U.S. Department of Energy Workshop Report: Solar Resources and Forecasting  

DOE Green Energy (OSTI)

This report summarizes the technical presentations, outlines the core research recommendations, and augments the information of the Solar Resources and Forecasting Workshop held June 20-22, 2011, in Golden, Colorado. The workshop brought together notable specialists in atmospheric science, solar resource assessment, solar energy conversion, and various stakeholders from industry and academia to review recent developments and provide input for planning future research in solar resource characterization, including measurement, modeling, and forecasting.

Stoffel, T.

2012-06-01T23:59:59.000Z

310

Uncertainty Representation: Estimating Process Parameters for Forward Price Forecasting  

Science Conference Proceedings (OSTI)

Market prices set the value of electric power assets and contracts, yet forward prices are unavailable for time horizons relevant to most valuations. Price forecasts are inherently uncertain because the drivers of prices are uncertain, but equilibrating market forces also work to reduce the growth of uncertainty over time. Consequently, quantifying the degree of future price uncertainty is difficult, but has tremendous strategic potential for power companies seeking to value real options and invest in fl...

1999-12-10T23:59:59.000Z

311

California Regional Wind Energy Forecasting System Development, Vol. 3  

Science Conference Proceedings (OSTI)

The rated capacity of wind generation in California is expected to grow rapidly in the future beyond the approximately 2100 MW in place at the end of 2005. The main drivers are the state's 20 percent Renewable Portfolio Standard requirement in 2010 and the low cost of wind energy relative to other renewable energy sources. As wind is an intermittent generation resource and weather changes can cause large and rapid changes in output, system operators will need accurate and robust wind energy forecasting ...

2006-11-15T23:59:59.000Z

312

Mining big data: current status, and forecast to the future  

Science Conference Proceedings (OSTI)

Big Data is a new term used to identify datasets that we can not manage with current methodologies or data mining software tools due to their large size and complexity. Big Data mining is the capability of extracting useful information ...

Wei Fan; Albert Bifet

2013-04-01T23:59:59.000Z

313

Stock returns and the dispersion in earnings forecasts,” Working Paper No  

E-Print Network (OSTI)

Abstract: The efficient market hypothesis based on homogeneous expectations implies that future stock returns are unpredictable. However, the forecastability of stock returns has been well documented in a substantial literature. This paper introduces a new forecasting variable, dispersion in analysts ’ earnings forecasts. The implication from this finding is not only that we have another piece of evidence that stock returns are predictable, but also that alternative models should be used to explain movements of stock prices. Hence, this paper derives a relation between the dispersion in forecasts and future stock returns based on Harrison and Kreps (1978) and shows that the dispersion in forecasts exerts its own positive effect on demand in the market. Furthermore, this paper shows empirically that the dispersion in expectations has particularly strong predictive power for future stock returns at intermediate horizons (between 24 months and 43 months) and that it contains information about future stock returns aside from the information contained in other variables. In addition, the direction of predictive power from the dispersion for future stock returns is consistent with the derived relation from Harrison and Kreps (1978). This paper also shows that most of the movements in dispersion cannot be explained by other variables, such as common financial indicators, macroeconomic variables, market volatility, or non-economic events. Finally, Monte Carlo simulation shows that finite sample biases in long-horizon regressions using the dispersion do not seem so serious.

Cheolbeom Park

2001-01-01T23:59:59.000Z

314

Solar Energy Market Forecast | Open Energy Information  

Open Energy Info (EERE)

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

315

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

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

316

A Cosmology Forecast Toolkit -- CosmoLib  

E-Print Network (OSTI)

The package CosmoLib is a combination of a cosmological Boltzmann code and a simulation toolkit to forecast the constraints on cosmological parameters from future observations. In this paper we describe the released linear-order part of the package. We discuss the stability and performance of the Boltzmann code. This is written in Newtonian gauge and including dark energy perturbations. In CosmoLib the integrator that computes the CMB angular power spectrum is optimized for a $\\ell$-by-$\\ell$ brute-force integration, which is useful for studying inflationary models predicting sharp features in the primordial power spectrum of metric fluctuations. The numerical code and its documentation are available at http://www.cita.utoronto.ca/~zqhuang/CosmoLib.

Zhiqi Huang

2012-01-28T23:59:59.000Z

317

PDSF Modules  

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

Modules Modules Modules Modules Approach to Managing The Environment Modules is a system which you can use to specify what software you want to use. If you want to use a particular software package loading its module will take care of the details of modifying your environment as necessary. The advantage of the modules approach is that the you are not required to explicitly specify paths for different executable versions and try to keep their related man paths and environment variables coordinated. Instead you simply "load" and "unload" specific modules to control your environment. Getting Started with Modules If you're using the standard startup files on PDSF then you're already setup for using modules. If the "module" command is not available, please

318

Annual Energy Outlook 2001-Appendix G: Major Assumptions for the Forecasts  

Gasoline and Diesel Fuel Update (EIA)

Forecasts Forecasts Summary of the AEO2001 Cases/ Scenarios - Appendix Table G1 bullet1.gif (843 bytes) Model Results (Formats - PDF, ZIP) - Appendix Tables - Reference Case - 1998 to 2020 bullet1.gif (843 bytes) Download Report - Entire AEO2001 (PDF) - AEO2001 by Chapters (PDF) bullet1.gif (843 bytes) Acronyms bullet1.gif (843 bytes) Contacts Related Links bullet1.gif (843 bytes) Assumptions to the AEO2001 bullet1.gif (843 bytes) Supplemental Data to the AEO2001 (Only available on the Web) - Regional and more detailed AEO 2001 Reference Case Results - 1998, 2000 to 2020 bullet1.gif (843 bytes) NEMS Conference bullet1.gif (843 bytes) Forecast Homepage bullet1.gif (843 bytes) EIA Homepage Appendix G Major Assumptions for the Forecasts Component Modules Major Assumptions for the Annual Energy Outlook 2001

319

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

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

320

A Review of Numerical Forecast Guidance for Hurricane Hugo  

Science Conference Proceedings (OSTI)

Numerical forecast guidance for Hurricane Hugo from the National Meteorological Center is examined, as well as forecasts from the European Center for Medium Range Forecasting and the United Kingdom Meteorological Office. No one forecast product ...

John H. Ward

1990-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "module forecasts future" 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

Short-Range Ensemble Forecasts of Precipitation Type  

Science Conference Proceedings (OSTI)

Short-range ensemble forecasting is extended to a critical winter weather problem: forecasting precipitation type. Forecast soundings from the operational NCEP Short-Range Ensemble Forecast system are combined with five precipitation-type ...

Matthew S. Wandishin; Michael E. Baldwin; Steven L. Mullen; John V. Cortinas Jr.

2005-08-01T23:59:59.000Z

322

Summary Verification Measures and Their Interpretation for Ensemble Forecasts  

Science Conference Proceedings (OSTI)

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

A. Allen Bradley; Stuart S. Schwartz

2011-09-01T23:59:59.000Z

323

The Automated Tropical Cyclone Forecasting System (ATCF)  

Science Conference Proceedings (OSTI)

The U.S. Navy Automated Tropical Cyclone Forecasting System (ATCF) is an IBM-AT compatible software package developed for the Joint Typhoon Warning Center (JTWC), Guam. ATCF is designed to assist forecasters with the process of making tropical ...

Ronald J. Miller; Ann J. Schrader; Charles R. Sampson; Ted L. Tsui

1990-12-01T23:59:59.000Z

324

Evaluation of LFM-2 Quantitative Precipitation Forecasts  

Science Conference Proceedings (OSTI)

The results of a near real time experiment designed to assess the state of the art of quantitative precipitation forecasting skill of the operational NMC LFM-2 are described. All available LFM-2 quantitative precipitation forecasts were verified ...

Lance F. Bosart

1980-08-01T23:59:59.000Z

325

Forecaster Workstation Design: Concepts and Issues  

Science Conference Proceedings (OSTI)

Some basic ideas about designing a meteorological workstation for operational weather forecasting are presented, in part as a complement to the recently published discussion of workstation design by R. R. Hoffman. Scientific weather forecasting ...

Charles A. Doswell III

1992-06-01T23:59:59.000Z

326

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

327

Local Forecast Communication In The Altiplano  

Science Conference Proceedings (OSTI)

Forecasts play an important role in planting decisions for Andean peasant producers. Predictions of the upcoming cropping season determine when, where, and what farmers will plant. This research looks at the sources of forecast information used ...

Jere L. Gilles; Corinne Valdivia

2009-01-01T23:59:59.000Z

328

Bayesian Model Verification of NWP Ensemble Forecasts  

Science Conference Proceedings (OSTI)

Forecasts of convective precipitation have large uncertainties. To consider the forecast uncertainties of convection-permitting models, a convection-permitting ensemble prediction system (EPS) based on the Consortium for Small-scale Modeling (...

Andreas Röpnack; Andreas Hense; Christoph Gebhardt; Detlev Majewski

2013-01-01T23:59:59.000Z

329

Economic and Statistical Measures of Forecast Accuracy  

E-Print Network (OSTI)

This paper argues in favour of a closer link between decision and forecast evaluation problems. Although the idea of using decision theory for forecast evaluation appears early in the dynamic stochastic programming literature, and has continued...

Granger, Clive W J; Pesaran, M Hashem

2004-06-16T23:59:59.000Z

330

2013 Midyear Economic Forecast Sponsorship Opportunity  

E-Print Network (OSTI)

2013 Midyear Economic Forecast Sponsorship Opportunity Thursday, April 18, 2013, ­ Hyatt Regency Irvine 11:30 a.m. ­ 1:30 p.m. Dr. Anil Puri presents his annual Midyear Economic Forecast addressing

de Lijser, Peter

331

Forecasting consumer products using prediction markets  

E-Print Network (OSTI)

Prediction Markets hold the promise of improving the forecasting process. Research has shown that Prediction Markets can develop more accurate forecasts than polls or experts. Our research concentrated on analyzing Prediction ...

Trepte, Kai

2009-01-01T23:59:59.000Z

332

Probabilistic Visibility Forecasting Using Bayesian Model Averaging  

Science Conference Proceedings (OSTI)

Bayesian model averaging (BMA) is a statistical postprocessing technique that has been used in probabilistic weather forecasting to calibrate forecast ensembles and generate predictive probability density functions (PDFs) for weather quantities. ...

Richard M. Chmielecki; Adrian E. Raftery

2011-05-01T23:59:59.000Z

333

Intercomparison of Spatial Forecast Verification Methods  

Science Conference Proceedings (OSTI)

Advancements in weather forecast models and their enhanced resolution have led to substantially improved and more realistic-appearing forecasts for some variables. However, traditional verification scores often indicate poor performance because ...

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

2009-10-01T23:59:59.000Z

334

Forecasting with Reference to a Specific Climatology  

Science Conference Proceedings (OSTI)

Seasonal forecasts are most commonly issued as anomalies with respect to some multiyear reference period. However, different seasonal forecasting centers use different reference periods. This paper shows that for near-surface temperature, ...

Emily Wallace; Alberto Arribas

2012-11-01T23:59:59.000Z

335

Probabilistic Quantitative Precipitation Forecasts for River Basins  

Science Conference Proceedings (OSTI)

A methodology has been formulated to aid a field forecaster in preparing probabilistic quantitative precipitation forecasts (QPFs) for river basins. The format of probabilistic QPF is designed to meet three requirements: (i) it is compatible with ...

Roman Krzysztofowicz; William J. Drzal; Theresa Rossi Drake; James C. Weyman; Louis A. Giordano

1993-12-01T23:59:59.000Z

336

A General Framework for Forecast Verification  

Science Conference Proceedings (OSTI)

A general framework for forecast verification based on the joint distribution of forecasts and observations is described. For further elaboration of the framework, two factorizations of the joint distribution are investigated: 1) the calibration-...

Allan H. Murphy; Robert L. Winkler

1987-07-01T23:59:59.000Z

337

Antarctic Satellite Meteorology: Applications for Weather Forecasting  

Science Conference Proceedings (OSTI)

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

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

2003-02-01T23:59:59.000Z

338

Value from Ambiguity in Ensemble Forecasts  

Science Conference Proceedings (OSTI)

This study explores the objective application of ambiguity information, that is, the uncertainty in forecast probability derived from an ensemble. One application approach, called uncertainty folding, merges ambiguity with forecast uncertainty ...

Mark S. Allen; F. Anthony Eckel

2012-02-01T23:59:59.000Z

339

Module Handbook Specialisation Wind Energy  

E-Print Network (OSTI)

of wind energy External costs Future price trends 3. Environmental Issues Environmental benefits of WT and Externalities Clculation methods Current plant costs Wind energy prices The value Module Handbook Specialisation Wind Energy 2nd Semester for the Master Programme

Habel, Annegret

340

Management of supply chain: an alternative modelling technique for forecasting  

E-Print Network (OSTI)

Forecasting is a necessity almost in any operation. However, the tools of forecasting are still primitive in view

Datta, Shoumen

2007-05-23T23:59:59.000Z

Note: This page contains sample records for the topic "module forecasts future" 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

Improving week two forecasts with multi-model re-forecast ensembles  

E-Print Network (OSTI)

Improving week two forecasts with multi-model re-forecast ensembles Jeffrey S. Whitaker and Xue Wei NOAA-CIRES Climate Diagnostics Center, Boulder, CO Fr´ed´eric Vitart Seasonal Forecasting Group, ECMWF dataset of ensemble 're-forecasts' from a single model can significantly improve the skill

Whitaker, Jeffrey S.

342

Weather forecast-based optimization of integrated energy systems.  

SciTech Connect

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

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

2009-03-01T23:59:59.000Z

343

Forecasting for energy and chemical decision analysis  

SciTech Connect

This paper focuses on uncertainty and bias in forecasts used for major energy and chemical investment decisions. Probability methods for characterizing uncertainty in the forecast are reviewed. Sources of forecasting bias are classified based on the results of relevant psychology research. Examples are drawn from the energy and chemical industry to illustrate the value of explicit characterization of uncertainty and reduction of bias in forecasts.

Cazalet, E.G.

1984-08-01T23:59:59.000Z

344

A Rank Approach to Equity Forecast Construction  

E-Print Network (OSTI)

that are fit for their purpose; for example, returningaggregate county and sector forecasts that are consistent by construction....

Satchell, Stephen E; Wright, Stephen M

2006-03-14T23:59:59.000Z

345

Forecasting Techniques Utilized by the Forecast Branch of the National Meteorological Center During a Major Convective Rainfall Event  

Science Conference Proceedings (OSTI)

Meteorologists within the Forecast Branch (FB) of the National Meteorological Center (NMC) produce operational quantitative precipitation forecasts (QPFs). These manual forecasts are prepared utilizing various forecasting techniques, which are ...

Theodore W. Funk

1991-12-01T23:59:59.000Z

346

Application of Forecast Verification Science to Operational River Forecasting in the U.S. National Weather Service  

Science Conference Proceedings (OSTI)

Forecast verification in operational hydrology has been very limited to date, mainly due to the complexity of verifying both forcing input forecasts and hydrologic forecasts on multiple space–time scales. However, forecast verification needs to ...

Julie Demargne; Mary Mullusky; Kevin Werner; Thomas Adams; Scott Lindsey; Noreen Schwein; William Marosi; Edwin Welles

2009-06-01T23:59:59.000Z

347

Freeway Short-Term Traffic Flow Forecasting by Considering Traffic Volatility Dynamics and Missing Data Situations  

E-Print Network (OSTI)

Short-term traffic flow forecasting is a critical function in advanced traffic management systems (ATMS) and advanced traveler information systems (ATIS). Accurate forecasting results are useful to indicate future traffic conditions and assist traffic managers in seeking solutions to congestion problems on urban freeways and surface streets. There is new research interest in short-term traffic flow forecasting due to recent developments in ITS technologies. Previous research involves technologies in multiple areas, and a significant number of forecasting methods exist in literature. However, forecasting reliability is not properly addressed in existing studies. Most forecasting methods only focus on the expected value of traffic flow, assuming constant variance when perform forecasting. This method does not consider the volatility nature of traffic flow data. This paper demonstrated that the variance part of traffic flow data is not constant, and dependency exists. A volatility model studies the dependency among the variance part of traffic flow data and provides a prediction range to indicate the reliability of traffic flow forecasting. We proposed an ARIMA-GARCH (Autoregressive Integrated Moving Average- AutoRegressive Conditional Heteroskedasticity) model to study the volatile nature of traffic flow data. Another problem of existing studies is that most methods have limited forecasting abilities when there is missing data in historical or current traffic flow data. We developed a General Regression Neural Network(GRNN) based multivariate forecasting method to deal with this issue. This method uses upstream information to predict traffic flow at the studied site. The study results indicate that the ARIMA-GARCH model outperforms other methods in non-missing data situations, while the GRNN model performs better in missing data situations.

Zhang, Yanru

2011-08-01T23:59:59.000Z

348

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

349

Consensus Coal Production And Price Forecast For  

E-Print Network (OSTI)

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

Mohaghegh, Shahab

350

Modeling and Forecasting Electric Daily Peak Loads  

E-Print Network (OSTI)

Forecast Update As part of the Mid Term Assessment, staff is preparing a long term wholesale electricity 29, 2012 Preliminary Results of the Electricity Price Forecast Update As part of the Mid Term Assessment, staff is preparing a long term wholesale electricity market price forecast. A summary of the work

Abdel-Aal, Radwan E.

351

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

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

352

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

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

353

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

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

354

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

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

355

Load forecast and treatment of conservation  

E-Print Network (OSTI)

Load forecast and treatment of conservation July 28th 2010 Resource Adequacy Technical Committee conservation is implicitly incorporated in the short-term demand forecast? #12;3 Incorporating conservation in the short-term model Our short-term model is an econometric model which can not explicitly forecast

356

FINAL STAFF FORECAST OF 2008 PEAK DEMAND  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION FINAL STAFF FORECAST OF 2008 PEAK DEMAND STAFFREPORT June 2007 CEC-200 of the information in this paper. #12;Abstract This document describes staff's final forecast of 2008 peak demand demand forecasts for the respective territories of the state's three investor-owned utilities (IOUs

357

STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES 2005 TO 2018 report, Staff Forecast: Retail Electricity Prices, 2005 to 2018, was prepared with contributions from the technical assistance provided by Greg Broeking of R.W. Beck, Inc. in preparing retail price forecasts

358

Blue Chip Consensus US GDP Forecast  

E-Print Network (OSTI)

and metro area from Moody’s Economy.com Equivalent to US-level Gross Domestic Product ? The GMP forecasts have a large impact on the peak load forecasts Rule of thumb: 1 % growth in RTO GMP ? approx. 1,000 MW growth in forecast RTO peak load

James F. Wilson

2007-01-01T23:59:59.000Z

359

5, 183218, 2008 A rainfall forecast  

E-Print Network (OSTI)

HESSD 5, 183­218, 2008 A rainfall forecast model using Artificial Neural Network N. Q. Hung et al An artificial neural network model for rainfall forecasting in Bangkok, Thailand N. Q. Hung, M. S. Babel, S Geosciences Union. 183 #12;HESSD 5, 183­218, 2008 A rainfall forecast model using Artificial Neural Network N

Paris-Sud XI, Université de

360

System Demonstration Multilingual Weather Forecast Generation System  

E-Print Network (OSTI)

System Demonstration Multilingual Weather Forecast Generation System Tianfang Yao DongmoZhang Qian (Multilingual Weather Forecasts Assistant) system will be demonstrated. It is developed to generate the multilingual text of the weather forecasts automatically. The raw data from the weather observation can be used

Note: This page contains sample records for the topic "module forecasts future" 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

(1) Ensemble forecast calibration & (2) using reforecasts  

E-Print Network (OSTI)

1 (1) Ensemble forecast calibration & (2) using reforecasts Tom Hamill NOAA Earth System Research · Calibration: ; the statistical adjustment of the (ensemble) forecast ­ Rationale 1: Infer large-sample probabilities from small ensemble. ­ Rationale 2: Remove bias, increase forecast reliability while preserving

Hamill, Tom

362

Forecasting Solar Wind Speeds  

E-Print Network (OSTI)

By explicitly taking into account effects of Alfven waves, I derive from a simple energetics argument a fundamental relation which predicts solar wind (SW) speeds in the vicinity of the earth from physical properties on the sun. Kojima et al. recently found from their observations that a ratio of surface magnetic field strength to an expansion factor of open magnetic flux tubes is a good indicator of the SW speed. I show by using the derived relation that this nice correlation is an evidence of the Alfven wave which accelerates SW in expanding flux tubes. The observations further require that fluctuation amplitudes of magnetic field lines at the surface should be almost universal in different coronal holes, which needs to be tested by future observations.

Takeru K. Suzuki

2006-02-03T23:59:59.000Z

363

Annual Energy Outlook Forecast Evaluation  

Gasoline and Diesel Fuel Update (EIA)

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

364

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

365

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.

366

How Do You Like Your Weather?: Using Weather Forecast Data to Improve Short-Term Load Forecasts  

Science Conference Proceedings (OSTI)

This document provides a quick overview of weather forecasts as a data issue in the development of electricity demand forecasts. These are three sections in this Brief: o reasons behind the rise in interest in using weather forecasts in electricity forecasting models, o an overview of what some utilities are doing to evaluate weather forecasts, and o a resource list of weather forecast providers.

2001-09-28T23:59:59.000Z

367

An Optimized Autoregressive Forecast Error Generator for Wind and Load Uncertainty Study  

SciTech Connect

This paper presents a first-order autoregressive algorithm to generate real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast errors. The methodology aims at producing random wind and load forecast time series reflecting the autocorrelation and cross-correlation of historical forecast data sets. Five statistical characteristics are considered: the means, standard deviations, autocorrelations, and cross-correlations. A stochastic optimization routine is developed to minimize the differences between the statistical characteristics of the generated time series and the targeted ones. An optimal set of parameters are obtained and used to produce the RT, HA, and DA forecasts in due order of succession. This method, although implemented as the first-order regressive random forecast error generator, can be extended to higher-order. Results show that the methodology produces random series with desired statistics derived from real data sets provided by the California Independent System Operator (CAISO). The wind and load forecast error generator is currently used in wind integration studies to generate wind and load inputs for stochastic planning processes. Our future studies will focus on reflecting the diurnal and seasonal differences of the wind and load statistics and implementing them in the random forecast generator.

De Mello, Phillip; Lu, Ning; Makarov, Yuri V.

2011-01-17T23:59:59.000Z

368

Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Residential Demand Module The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" (UEC) by appliance (in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type

369

Analysis and Synthesis of Load Forecasting Data for Renewable Integration Studies: Preprint  

SciTech Connect

As renewable energy constitutes greater portions of the generation fleet, the importance of modeling uncertainty as part of integration studies also increases. In pursuit of optimal system operations, it is important to capture not only the definitive behavior of power plants, but also the risks associated with systemwide interactions. This research examines the dependence of load forecast errors on external predictor variables such as temperature, day type, and time of day. The analysis was utilized to create statistically relevant instances of sequential load forecasts with only a time series of historic, measured load available. The creation of such load forecasts relies on Bayesian techniques for informing and updating the model, thus providing a basis for networked and adaptive load forecast models in future operational applications.

Steckler, N.; Florita, A.; Zhang, J.; Hodge, B. M.

2013-11-01T23:59:59.000Z

370

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

371

Critical Operating Constraint Forecasting (COCF)  

Science Conference Proceedings (OSTI)

This document represents the progress report and Task 1 letter report of the California Institute for Energy and Environment (CIEE) contract funded by the California Energy Commission (CEC), Critical Operating Constraint Forecasting (COCF) for California Independent System Operator (CAISO) Planning Phase. Task 1 was to accomplish the following items: Collect data from CAISO to set up the WECC power flow base case representing the CAISO system in the summer of 2006 Run TRACE for maximizing California Impo...

2006-06-30T23:59:59.000Z

372

Forecasting Techniques The Use of Hourly Model-Generated Soundings to Forecast Mesoscale Phenomena. Part I: Initial Assessment in Forecasting Warm-Season Phenomena  

Science Conference Proceedings (OSTI)

Since late 1995, NCEP has made available to forecasters hourly model guidance at selected sites in the form of vertical profiles of various forecast fields. These profiles provide forecasters with increased temporal resolution and greater ...

Robert E. Hart; Gregory S. Forbes; Richard H. Grumm

1998-12-01T23:59:59.000Z

373

Module Configuration  

SciTech Connect

A stand alone battery module including: (a) a mechanical configuration; (b) a thermal management configuration; (c) an electrical connection configuration; and (d) an electronics configuration. Such a module is fully interchangeable in a battery pack assembly, mechanically, from the thermal management point of view, and electrically. With the same hardware, the module can accommodate different cell sizes and, therefore, can easily have different capacities. The module structure is designed to accommodate the electronics monitoring, protection, and printed wiring assembly boards (PWAs), as well as to allow airflow through the module. A plurality of modules may easily be connected together to form a battery pack. The parts of the module are designed to facilitate their manufacture and assembly.

Oweis, Salah (Ellicott City, MD); D' Ussel, Louis (Bordeaux, FR); Chagnon, Guy (Cockeysville, MD); Zuhowski, Michael (Annapolis, MD); Sack, Tim (Cockeysville, MD); Laucournet, Gaullume (Paris, FR); Jackson, Edward J. (Taneytown, MD)

2002-06-04T23:59:59.000Z

374

Meese-Rogoff redux: Micro-based exchange-rate forecasting  

E-Print Network (OSTI)

Johnatban. "Exchange Rate Forecasting: The Errors We'veBased Exchange-Rate Forecasting By MARTIN D . D . EVANS ANDon longer-horizon forecasting, we examine forecasting over

Evans, MDD; Lyons, Richard K.

2005-01-01T23:59:59.000Z

375

The Past as Prologue? Business Cycles and Forecasting since the 1960s  

E-Print Network (OSTI)

Forecasters,” Journal of Forecasting, Vol. 28, No. 2, Mar,of Macroeconomic Forecasting” Journal of Macroeconomics,of Federal Reserve Forecasting,” Journal of Macroeconomics,

Bardhan, Ashok Deo; Hicks, Daniel; Kroll, Cynthia A.; Yu, Tiffany

2010-01-01T23:59:59.000Z

376

Material World: Forecasting Household Appliance Ownership in a Growing Global Economy  

E-Print Network (OSTI)

and V. Letschert (2005). Forecasting Electricity Demand in8364 Material World: Forecasting Household ApplianceMcNeil, 2008). Forecasting Diffusion Forecasting Variables

Letschert, Virginie

2010-01-01T23:59:59.000Z

377

Future gas consumption in the United States. [Monograph  

SciTech Connect

The ninth biennial market report on consumption and forecasts of future demand provides a planning tool for consumers and government officials as well as for the natural-gas industry. The report summarizes the actual 1980 consumption by market sector, notes changes in consumption patterns and market restrictions, and presents an operational forecast of sales to each sector through 1995 and in each of eleven regions surveyed by the Gas Requirements Committee. 9 references, 4 figures, 11 tables. (DCK)

1982-01-01T23:59:59.000Z

378

BMA Probabilistic Quantitative Precipitation Forecasting over the Huaihe Basin Using TIGGE Multi-model Ensemble Forecasts  

Science Conference Proceedings (OSTI)

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

Jianguo Liu; Zhenghui Xie

379

Using National Air Quality Forecast Guidance to Develop Local Air Quality Index Forecasts  

Science Conference Proceedings (OSTI)

The National Air Quality Forecast Capability (NAQFC) currently provides next-day forecasts of ozone concentrations over the contiguous United States. It was developed collaboratively by NOAA and Environmental Protection Agency (EPA) in order to ...

Brian Eder; Daiwen Kang; S. Trivikrama Rao; Rohit Mathur; Shaocai Yu; Tanya Otte; Ken Schere; Richard Wayland; Scott Jackson; Paula Davidson; Jeff McQueen; George Bridgers

2010-03-01T23:59:59.000Z

380

Role of Retrospective Forecasts of GCMs Forced with Persisted SST Anomalies in Operational Streamflow Forecasts Development  

Science Conference Proceedings (OSTI)

Seasonal streamflow forecasts contingent on climate information are essential for water resources planning and management as well as for setting up contingency measures during extreme years. In this study, operational streamflow forecasts are ...

A. Sankarasubramanian; Upmanu Lall; Susan Espinueva

2008-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "module forecasts future" 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

Evaluation of MJO Forecast Skill from Several Statistical and Dynamical Forecast Models  

Science Conference Proceedings (OSTI)

This work examines the performance of Madden–Julian oscillation (MJO) forecasts from NCEP’s coupled and uncoupled general circulation models (GCMs) and statistical models. The forecast skill from these methods is evaluated in near–real time. ...

Kyong-Hwan Seo; Wanqiu Wang; Jon Gottschalck; Qin Zhang; Jae-Kyung E. Schemm; Wayne R. Higgins; Arun Kumar

2009-05-01T23:59:59.000Z

382

A Probabilistic Forecast Contest and the Difficulty in Assessing Short-Range Forecast Uncertainty  

Science Conference Proceedings (OSTI)

Results are presented from a probability-based weather forecast contest. Rather than evaluating the absolute errors of nonprobabilistic temperature and precipitation forecasts, as is common in other contests, this contest evaluated the skill of ...

Thomas M. Hamill; Daniel S. Wilks

1995-09-01T23:59:59.000Z

383

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

Science Conference Proceedings (OSTI)

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

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

2010-01-01T23:59:59.000Z

384

Implications of Ensemble Quantitative Precipitation Forecast Errors on Distributed Streamflow Forecasting  

Science Conference Proceedings (OSTI)

Evaluating the propagation of errors associated with ensemble quantitative precipitation forecasts (QPFs) into the ensemble streamflow response is important to reduce uncertainty in operational flow forecasting. In this paper, a multifractal ...

Giuseppe Mascaro; Enrique R. Vivoni; Roberto Deidda

2010-02-01T23:59:59.000Z

385

Evaluation of Probabilistic Precipitation Forecasts Determined from Eta and AVN Forecasted Amounts  

Science Conference Proceedings (OSTI)

This note examines the connection between the probability of precipitation and forecasted amounts from the NCEP Eta (now known as the North American Mesoscale model) and Aviation (AVN; now known as the Global Forecast System) models run over a 2-...

William A. Gallus Jr.; Michael E. Baldwin; Kimberly L. Elmore

2007-02-01T23:59:59.000Z

386

Reliable Probabilistic Quantitative Precipitation Forecasts from a Short-Range Ensemble Forecasting System  

Science Conference Proceedings (OSTI)

A simple binning technique is developed to produce reliable 3-h probabilistic quantitative precipitation forecasts (PQPFs) from the National Centers for Environmental Prediction (NCEP) multimodel short-range ensemble forecasting system obtained ...

David J. Stensrud; Nusrat Yussouf

2007-02-01T23:59:59.000Z

387

The Impact of Writing Area Forecast Discussions on Student Forecaster Performance  

Science Conference Proceedings (OSTI)

A brief study is provided on the forecast performance of students who write a mock area forecast discussion (AFD) on a weekly basis. Student performance was tracked for one semester (11 weeks) during the University of Missouri—Columbia's local ...

Patrick S. Market

2006-02-01T23:59:59.000Z

388

An Operational Model for Forecasting Probability of Precipitation and Yes/No Forecast  

Science Conference Proceedings (OSTI)

An operational system for forecasting probability of precipitation (PoP) and yes/no forecast over 10 stations during monsoon season is developed. A perfect prog method (PPM) approach is followed for statistical interpretation of numerical weather ...

Ashok Kumar; Parvinder Maini; S. V. Singh

1999-02-01T23:59:59.000Z

389

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

390

Further Evaluation of the National Meterological Center's Medium-Range Forecast Model Precpitation Forecasts  

Science Conference Proceedings (OSTI)

Precipitation forecasts made by the National Meteorological Center's medium-range forecast (MRF) model are evaluated for the period, 1 March 1987 to 31 March 1989. As shown by Roads and Maisel, the MRF model wet bias was substantially alleviated ...

John O. Roads; T. Norman Maisal; Jordan Alpert

1991-12-01T23:59:59.000Z

391

R/ECON July 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON July 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF JULY 2000 NEW JERSEY of growth will decelerate over the forecast period. The R/ECON TM forecast for New Jersey in 2000 looks to decelerate over the course of the forecast. These forces will combine to push the unemployment rate to more

392

Increasing NOAA's computational capacity to improve global forecast modeling  

E-Print Network (OSTI)

1 Increasing NOAA's computational capacity to improve global forecast modeling A NOAA of the NWS's forecast products, even its regional forecast products, are constrained by the limitations of NOAA's global forecast model. Unfortunately, our global forecasts are less accurate than those from

Hamill, Tom

393

Forecasting Random Walks Under Drift Instability  

E-Print Network (OSTI)

Forecasting Random Walks Under Drift Instability? M. Hashem Pesaran University of Cambridge, CIMF, and USC Andreas Pick University of Cambridge, CIMF March 11, 2008 Abstract This paper considers forecast averaging when the same model is used... but estimation is carried out over different estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or more structural breaks. It is shown that compared to using forecasts based on a single...

Pesaran, M Hashem; Pick, Andreas

394

Forecast of California car and truck fuel demand  

Science Conference Proceedings (OSTI)

The purpose of this work is to forecast likely future car and truck fuel demand in California in light of recent and possible additional improvements in vehicle efficiency. Forecasts of gasoline and diesel fuel demand are made based on projections of primary economic, demographic, and transportation technology variables. Projections of car and light truck stock and new sales are based on regression equations developed from historical data. Feasible future vehicle fuel economies are determined from technical improvements possible with existing technology. Several different cases of market-induced efficiency improvement are presented. Anticipated fuel economy improvements induced by federal mileage standards and rising fuel costs will cause lower future fuel demand, even though vehicle miles traveled will continue to increase both on a per capita and total basis. If only relatively low-cost fuel economy improvements are adopted after about 1985, when federal standards require no further improvements, fuel demand will decrease from the 1982 level of 11.7 billion gallons (gasoline equivalent) to 10.6 billion gallons in 2002, about a 9% reduction. Higher fuel economy levels, based on further refinements in existing technology, can produce an additional 7% reduction in fuel demand by 2002.

Stamets, L.

1983-01-01T23:59:59.000Z

395

Forecasting market prices in a supply chain game q Christopher Kiekintveld a,*, Jason Miller b  

E-Print Network (OSTI)

), the simulation day, and the linear trend of selling prices from the previous ten days. For predicting future prices, we used the same set of features with the addition of the estimated customer demand trend (s). 4Forecasting market prices in a supply chain game q Christopher Kiekintveld a,*, Jason Miller b

Wellman, Michael P.

396

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

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

397

Geothermal wells: a forecast of drilling activity  

DOE Green Energy (OSTI)

Numbers and problems for geothermal wells expected to be drilled in the United States between 1981 and 2000 AD are forecasted. The 3800 wells forecasted for major electric power projects (totaling 6 GWe of capacity) are categorized by type (production, etc.), and by location (The Geysers, etc.). 6000 wells are forecasted for direct heat projects (totaling 0.02 Quads per year). Equations are developed for forecasting the number of wells, and data is presented. Drilling and completion problems in The Geysers, The Imperial Valley, Roosevelt Hot Springs, the Valles Caldera, northern Nevada, Klamath Falls, Reno, Alaska, and Pagosa Springs are discussed. Likely areas for near term direct heat projects are identified.

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

1981-07-01T23:59:59.000Z

398

Promotional forecasting in the grocery retail business  

E-Print Network (OSTI)

Predicting customer demand in the highly competitive grocery retail business has become extremely difficult, especially for promotional items. The difficulty in promotional forecasting has resulted from numerous internal ...

Koottatep, Pakawkul

2006-01-01T23:59:59.000Z

399

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...

400

Forecasting Prices andForecasting Prices and Congestion forCongestion for  

E-Print Network (OSTI)

Abstract--In deregulated electricity markets, short-term load forecasting is important for reliable power322 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 25, NO. 1, FEBRUARY 2010 Short-Term Load Forecasting presents a similar day-based wavelet neural network method to forecast tomorrow's load. The idea

Tesfatsion, Leigh

Note: This page contains sample records for the topic "module forecasts future" 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

Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations  

E-Print Network (OSTI)

Power Forecasting in Five U.S. Electricity Markets MISO NYISO PJM ERCOT CAISO Peak load 109,157 MW (7 ........................................................................................... 18 4 WIND POWER FORECASTING AND ELECTRICITY MARKET OPERATIONS............................................................ 18 4-1 Market Operation and Wind Power Forecasting in Five U.S. Electricity Markets .......... 21 #12

Kemner, Ken

402

Probabilistic Performance Forecasting for Unconventional Reservoirs With Stretched-Exponential Model  

E-Print Network (OSTI)

Reserves estimation in an unconventional-reservoir setting is a daunting task because of geologic uncertainty and complex flow patterns evolving in a long-stimulated horizontal well, among other variables. To tackle this complex problem, we present a reserves-evaluation workflow that couples the traditional decline-curve analysis with a probabilistic forecasting frame. The stretched-exponential production decline model (SEPD) underpins the production behavior. Our recovery appraisal workflow has two different applications: forecasting probabilistic future performance of wells that have production history; and forecasting production from new wells without production data. For the new field case, numerical model runs are made in accord with the statistical design of experiments for a range of design variables pertinent to the field of interest. In contrast, for the producing wells the early-time data often need adjustments owing to restimulation, installation of artificial-lift, etc. to focus on the decline trend. Thereafter, production data of either new or existing wells are grouped in accord with initial rates to obtain common SEPD parameters for similar wells. After determining the distribution of model parameters using well grouping, the methodology establishes a probabilistic forecast for individual wells. We present a probabilistic performance forecasting methodology in unconventional reservoirs for wells with and without production history. Unlike other probabilistic forecasting tools, grouping wells with similar production character allows estimation of self-consistent SEPD parameters and alleviates the burden of having to define uncertainties associated with reservoir and well-completion parameters.

Can, Bunyamin

2011-05-01T23:59:59.000Z

403

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

Gasoline and Diesel Fuel Update (EIA)

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

404

Forecasting during the Lake-ICE/SNOWBANDS Field Experiments  

Science Conference Proceedings (OSTI)

Despite improvements in numerical weather prediction models, statistical models, forecast decision trees, and forecasting rules of thumb, human interpretation of meteorological information for a particular forecast situation can still yield a ...

Peter J. Sousounis; Greg E. Mann; George S. Young; Richard B. Wagenmaker; Bradley D. Hoggatt; William J. Badini

1999-12-01T23:59:59.000Z

405

Experiments in Temperature and Precipitation Forecasting for Illinois  

Science Conference Proceedings (OSTI)

Six years of daily temperature and precipitation forecasting are studied for Urbana, Illinois. Minimum temperature forecast skills, measured against a climatological control, are 57%, 48%, 34% and 20% for the respective forecast ranges of one, ...

John R. Gyakum

1986-06-01T23:59:59.000Z

406

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

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

407

The Economic Value Of Ensemble-Based Weather Forecasts  

Science Conference Proceedings (OSTI)

The potential economic benefit associated with the use of an ensemble of forecasts versus anequivalent or higher-resolution control forecast is discussed. Neither forecast systems are post-processed,except a simple calibration that is applied to ...

Yuejian Zhu; Zoltan Toth; Richard Wobus; David Richardson; Kenneth Mylne

2002-01-01T23:59:59.000Z

408

A Probabilistic Forecast Approach for Daily Precipitation Totals  

Science Conference Proceedings (OSTI)

Commonly, postprocessing techniques are employed to calibrate a model forecast. Here, a probabilistic postprocessor is presented that provides calibrated probability and quantile forecasts of precipitation on the local scale. The forecasts are ...

Petra Friederichs; Andreas Hense

2008-08-01T23:59:59.000Z

409

Precipitation and Temperature Forecast Performance at the Weather Prediction Center  

Science Conference Proceedings (OSTI)

The role of the human forecaster in improving upon the accuracy of numerical weather prediction is explored using multi-year verification of human-generated short-range precipitation forecasts and medium-range maximum temperature forecasts from ...

David R. Novak; Christopher Bailey; Keith Brill; Patrick Burke; Wallace Hogsett; Robert Rausch; Michael Schichtel

410

Forecasting and Verifying in a Field Research Project: DOPLIGHT '87  

Science Conference Proceedings (OSTI)

Verification of forecasts during research field experiments is discussed and exemplified using the DOPLIGHT '87 experiment. We stress the importance of forecast verification if forecasting is to be a serious component of the research. A direct ...

Charles A. Doswell III; John A. Flueck

1989-06-01T23:59:59.000Z

411

Diversity in Interpretations of Probability: Implications for Weather Forecasting  

Science Conference Proceedings (OSTI)

Over the last years, probability weather forecasts have become increasingly popular due in part to the development of ensemble forecast systems. Despite its widespread use in atmospheric sciences, probability forecasting remains a subtle and ...

Ramón de Elía; René Laprise

2005-05-01T23:59:59.000Z

412

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

413

On the Reliability and Calibration of Ensemble Forecasts  

Science Conference Proceedings (OSTI)

An important aspect of ensemble forecasting is that the resulting probabilities are reliable (i.e., the forecast probabilities match the observed frequencies). In the medium-range forecasting context, the literature tends to focus on the ...

Christine Johnson; Neill Bowler

2009-05-01T23:59:59.000Z

414

Scoring Probabilistic Forecasts: The Importance of Being Proper  

Science Conference Proceedings (OSTI)

Questions remain regarding how the skill of operational probabilistic forecasts is most usefully evaluated or compared, even though probability forecasts have been a long-standing aim in meteorological forecasting. This paper explains the ...

Jochen Bröcker; Leonard A. Smith

2007-04-01T23:59:59.000Z

415

Prediction of Consensus Tropical Cyclone Track Forecast Error  

Science Conference Proceedings (OSTI)

The extent to which the tropical cyclone (TC) track forecast error of a consensus model (CONU) routinely used by the forecasters at the National Hurricane Center can be predicted is determined. A number of predictors of consensus forecast error, ...

James S. Goerss

2007-05-01T23:59:59.000Z

416

An Experiment in Mesoscale Weather Forecasting in the Michigan Area  

Science Conference Proceedings (OSTI)

During an experiment in mesoscale weather forecasting in the Michigan area, consensus improved over NWS guidance in maximum/minimum temperature and probability of precipitation forecasts out to 24 hours. Forecasts were generally best in the ...

Dennis G. Baker

1986-12-01T23:59:59.000Z

417

forecasts  

U.S. Energy Information Administration (EIA)

Sheet3 Sheet2 Sheet1 Figure 106. Average annual minemouth coal prices by region, 1990-2040 (2011 dollars per million Btu) Appalachia Interior West US Average

418

Price and Load Forecasting in Volatile Energy Markets  

Science Conference Proceedings (OSTI)

With daily news stories about wildly fluctuating electricity prices and soaring natural gas prices, forecasters' responsibilities are expanding, visibility is increasing, and pressure exists to produce more frequent forecasts and more kinds of forecasts. The proceedings of EPRI's 13th Forecasting Symposium, held November 13-15 in Nashville, Tennessee, address current forecasting issues and developments, as well as explain the role that forecasters have played in recent events in energy markets.

2001-12-05T23:59:59.000Z

419

Module Handbook Specialisation Photovoltaics  

E-Print Network (OSTI)

#12;Specialisation Photovoltaics, University of Northumbria Module 1/Photovoltaics: PHOTOVOLTAIC CELL AND MODULE TECHNOLOGY Module name: PHOTOVOLTAIC CELL AND MODULE TECHNOLOGY Section EUREC · Chemistry · Physics Target learning outcomes The module Photovoltaic Cell and Module Technology teaches

Habel, Annegret

420

Future Healthcare  

E-Print Network (OSTI)

Patients want answers, not numbers. Evidence-based medicine must have numbers to generate answers. Therefore, analysis of numbers to provide answers is the Holy Grail of healthcare professionals and its future systems. ...

Datta, Shoumen

2010-12-15T23:59:59.000Z

Note: This page contains sample records for the topic "module forecasts future" 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

Future tense  

Science Conference Proceedings (OSTI)

Future Tense, one of the revolving features on this page, presents stories and essays from the intersection of computational science and technological speculation, their boundaries limited only by our ability to imagine what will and could be.

Rudy Rucker

2011-07-01T23:59:59.000Z

422

Blasting Vibration Forecast Base on Neural Network  

Science Conference Proceedings (OSTI)

The influence of blasting vibration to surroundings around the blasting area can not be ignored, in order to guarantee the safety of surroundings around blasting area, blasting vibration forecasting model based on neural network is established by improved ... Keywords: Blasting vibration, Neural network, Forecast

Haiwang Ye; Fang Liu; Jian Chang; Lin Feng; Yang Wang; Peng Yao; Kai Wu

2010-10-01T23:59:59.000Z

423

Evaluating the Skill of Categorical Forecasts  

Science Conference Proceedings (OSTI)

A generalized skill score is presented for evaluating forecasts in any number of categories. Each forecast in a sample is given a mark; the skill score for the sample is just the average mark. Each mark has an expected value of zero for an ...

Neil D. Gordon

1982-07-01T23:59:59.000Z

424

Forecasting demand of commodities after natural disasters  

Science Conference Proceedings (OSTI)

Demand forecasting after natural disasters is especially important in emergency management. However, since the time series of commodities demand after natural disasters usually has a great deal of nonlinearity and irregularity, it has poor prediction ... Keywords: ARIMA, Demand forecasting, EMD, Emergency management, Natural disaster

Xiaoyan Xu; Yuqing Qi; Zhongsheng Hua

2010-06-01T23:59:59.000Z

425

Time series forecasting with Qubit Neural Networks  

Science Conference Proceedings (OSTI)

This paper proposes a quantum learning scheme approach for time series forecasting, through the application of the new non-standard Qubit Neural Network (QNN) model. The QNN description was adapted in this work in order to resemble classical Artificial ... Keywords: artificial intelligence, artificial neural networks, quantum computing, qubit neural networks, time series forecasting

Carlos R. B. Azevedo; Tiago A. E. Ferreira

2007-08-01T23:59:59.000Z

426

Making Forecasts and Weather Normalization Work Together  

Science Conference Proceedings (OSTI)

Electric utility industry restructuring has changed the consistency between weather-normalized sales and energy forecasts. This Technology Review discusses the feasibility of integrating weather normalization and forecasting processes, and addresses whether the conflicting goal of obtaining greater consistency and accuracy with fewer staff resources can be met with more integrated approaches.

2000-09-11T23:59:59.000Z

427

A spatially distributed flash flood forecasting model  

Science Conference Proceedings (OSTI)

This paper presents a distributed model that is in operational use for forecasting flash floods in northern Austria. The main challenge in developing the model was parameter identification which was addressed by a modelling strategy that involved a model ... Keywords: Distributed modelling, Dominant processes concept, Floods, Forecasting, Kalman Filter, Model accuracy, Parameter identification, Stream routing

Günter Blöschl; Christian Reszler; Jürgen Komma

2008-04-01T23:59:59.000Z

428

The NCEP Climate Forecast System Version 2  

Science Conference Proceedings (OSTI)

The second version of the NCEP Climate Forecast System (CFSv2) was made operational at NCEP in March 2011. This version has upgrades to nearly all aspects of the data assimilation and forecast model components of the system. A coupled Reanalysis ...

Suranjana Saha; Shrinivas Moorthi; Xingren Wu; Jiande Wang; Sudhir Nadiga; Patrick Tripp; David Behringer; Yu-Tai Hou; Hui-ya Chuang; Mark Iredell; Michael Ek; Jesse Meng; Rongqian Yang; Malaquías Peńa Mendez; Huug van den Dool; Qin Zhang; Wanqiu Wang; Mingyue Chen; Emily Becker

429

Forecast of geothermal-drilling activity  

DOE Green Energy (OSTI)

The number of geothermal wells that will be drilled to support electric power production in the United States through 2000 A.D. are forecasted. Results of the forecast are presented by 5-year periods for the five most significant geothermal resources.

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

1982-07-01T23:59:59.000Z

430

Preemptive Forecasts Using an Ensemble Kalman Filter  

Science Conference Proceedings (OSTI)

An ensemble Kalman filter (EnKF) estimates the error statistics of a model forecast using an ensemble of model forecasts. One use of an EnKF is data assimilation, resulting in the creation of an increment to the first-guess field at the ...

Brian J. Etherton

2007-10-01T23:59:59.000Z

431

Incentives for Retailer Forecasting: Rebates vs. Returns  

Science Conference Proceedings (OSTI)

This paper studies a manufacturer that sells to a newsvendor retailer who can improve the quality of her demand information by exerting costly forecasting effort. In such a setting, contracts play two roles: providing incentives to influence the retailer's ... Keywords: endogenous adverse selection, forecasting, rebates, returns, supply chain contracting

Terry A. Taylor; Wenqiang Xiao

2009-10-01T23:59:59.000Z

432

Efficient forecasting for hierarchical time series  

Science Conference Proceedings (OSTI)

Forecasting is used as the basis for business planning in many application areas such as energy, sales and traffic management. Time series data used in these areas is often hierarchically organized and thus, aggregated along the hierarchy levels based ... Keywords: forecasting, hierarchies, optimization, time series

Lars Dannecker; Robert Lorenz; Philipp Rösch; Wolfgang Lehner; Gregor Hackenbroich

2013-10-01T23:59:59.000Z

433

Assumptions to the Annual Energy Outlook - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

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

434

Assumptions to the Annual Energy Outlook 2002 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 19). The Industrial Demand Module forecasts energy consumption at the four Census region levels; energy consumption at the Census Division level is allocated

435

Possibility of Skill Forecast Based on the Finite-Time Dominant Linear Solutions for a Primitive Equation Regional Forecast Model  

Science Conference Proceedings (OSTI)

The possibility of using forecast errors originating from the finite-time dominant linear modes for the prediction of forecast skill for a primitive equation regional forecast model is studied. This is similar to the method for skill prediction ...

Tomislava Vuki?evi?

1993-06-01T23:59:59.000Z

436

Evaluating the Cloud Cover Forecast of NCEP Global Forecast System with Satellite Observation  

E-Print Network (OSTI)

To assess the quality of daily cloud cover forecast generated by the operational global numeric model, the NCEP Global Forecast System (GFS), we compose a large sample with outputs from GFS model and satellite observations from the International Satellite Cloud Climatology Project (ISCCP) in the period of July 2004 to June 2008, to conduct a quantitative and systematic assessment of the performance of a cloud model that covers a relatively long range of time, basic cloud types, and in a global view. The evaluation has revealed the goodness of the model forecast, which further illustrates our completeness on understanding cloud generation mechanism. To quantity the result, we found a remarkably high correlation between the model forecasts and the satellite observations over the entire globe, with mean forecast error less than 15% in most areas. Considering a forecast within 30% difference to the observation to be a "good" one, we find that the probability for the GFS model to make good forecasts varies between...

Ye, Quanzhi

2011-01-01T23:59:59.000Z

437

SunShot Initiative: Forecasting and Influencing Technological...  

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

Forecasting and Influencing Technological Progress in Solar Energy to someone by E-mail Share SunShot Initiative: Forecasting and Influencing Technological Progress in Solar Energy...

438

New Climate Research Centers Forecast Changes and Challenges...  

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

Climate Research Centers Forecast Changes and Challenges New Climate Research Centers Forecast Changes and Challenges October 25, 2013 - 12:24pm Addthis This artist's rendering...

439

Exploiting Domain Knowledge to Forecast Heating Oil Consumption  

Science Conference Proceedings (OSTI)

The GasDay laboratory at Marquette University provides forecasts of energy consumption. One such service is the Heating Oil Forecaster

George F. Corliss; Tsuginosuke Sakauchi; Steven R. Vitullo; Ronald H. Brown

2011-01-01T23:59:59.000Z

440

Building Energy Software Tools Directory: Energy Usage Forecasts  

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

Alphabetically Tools by Platform PC Mac UNIX Internet Tools by Country Related Links Energy Usage Forecasts Energy Usage Forecasts Quick and easy web-based tool that provides...

Note: This page contains sample records for the topic "module forecasts future" 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

Primordial Helium Abundance from CMB: a constraint from recent observations and a forecast  

E-Print Network (OSTI)

We study a constraint on the primordial helium abundance $Y_p$ from current and future observations of CMB. Using the currently available data from WMAP, ACBAR, CBI and BOOMERANG, we obtained the constraint as $Y_p = 0.25 \\pm 0.10$ at 1$\\sigma$ level. We also provide a forecast for Planck using the Markov Chain Monte Carlo approach. In addition to forecasting the constraint on $Y_p$, we investigate how assumptions for $Y_p$ affect the constraints on the other cosmological parameters.

Ichikawa, Kazuhide; Takahashi, Tomo

2007-01-01T23:59:59.000Z

442

Primordial Helium Abundance from CMB: a constraint from recent observations and a forecast  

E-Print Network (OSTI)

We studied a constraint on the primordial helium abundance Y_p from current and future observations of CMB. Using the currently available data from WMAP, ACBAR, CBI and BOOMERANG, we obtained the constraint as Y_p = 0.25^{+0.10}_{-0.07} at 68% C.L. We also provide a forecast for the Planck experiment using the Markov chain Monte Carlo approach. In addition to forecasting the constraint on Y_p, we investigate how assumptions for Y_p affect constraints on the other cosmological parameters.

Kazuhide Ichikawa; Toyokazu Sekiguchi; Tomo Takahashi

2007-12-28T23:59:59.000Z

443

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

SciTech Connect

Recent forecasts of total electricity generating capacity and energy demand as well as for electricity produced from nuclear energy and hydroelectric power are presented in tables and graphs to the year 2000. A forecast of the distribution of type of fuel and energy source that will supply the future electricity demand is presented. Use of electricity by each major consuming sector is presented for 1975. Projected demands for electricity in the years 1985 and 2000, as allocated to consuming sectors, are derived and presented.

Lane, J.A.

1976-02-01T23:59:59.000Z

444

Assumptions to the Annual Energy Outlook 2001 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2001, DOE/EIA-M060(2001) January 2001. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves

445

Assumptions to the Annual Energy Outlook 2002 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2002, DOE/EIA-M060(2002) (Washington, DC, January 2002). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves

446

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

LBL-34045 UC-1600 Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting-uses include Heating, Ventilation and Air Conditioning (HVAC). Our analysis uses the modeling framework provided by the HVAC module in the Residential End-Use Energy Planning System (REEPS), which was developed

447

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

448

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

449

Electric demand growth: An uncertain future for uranium  

SciTech Connect

Broadly conceived, the demand for electricity depends upon three sets of variables: (i) the growths of the many individual demands for energy services; (ii) the competitiveness of electrically driven technologies in meeting these demands; and (iii) the energy-conversion efficiencies of installed electrical technologies. The first set of variables establishes the size of the potential market; the second, the market penetration of electrical equipment; and the third, the quantity of electricity required to operate the equipment. All forecasts of electricity consumption ultimately depend upon inferred or assumed relationships to describe the future behavior of these variables. In this paper, the authors review recent forecasts of electricity demand growth. They also examine, in a qualitative way, some of the causes for the systematic, downward revisions of these forecasts over recent years. Graphical presentations of data are extensively used in the discussions. In an important sense, forecasting, whatever the number of variables, remains a matter of ''curve fitting.''

Asbury, J.G.

1985-01-01T23:59:59.000Z

450

Construction Safety Forecast for ITER  

SciTech Connect

The International Thermonuclear Experimental Reactor (ITER) project is poised to begin its construction activity. This paper gives an estimate of construction safety as if the experiment was being built in the United States. This estimate of construction injuries and potential fatalities serves as a useful forecast of what can be expected for construction of such a major facility in any country. These data should be considered by the ITER International Team as it plans for safety during the construction phase. Based on average U.S. construction rates, ITER may expect a lost workday case rate of < 4.0 and a fatality count of 0.5 to 0.9 persons per year.

cadwallader, lee charles

2006-11-01T23:59:59.000Z

451

Earthquake Forecast via Neutrino Tomography  

E-Print Network (OSTI)

We discuss the possibility of forecasting earthquakes by means of (anti)neutrino tomography. Antineutrinos emitted from reactors are used as a probe. As the antineutrinos traverse through a region prone to earthquakes, observable variations in the matter effect on the antineutrino oscillation would provide a tomography of the vicinity of the region. In this preliminary work, we adopt a simplified model for the geometrical profile and matter density in a fault zone. We calculate the survival probability of electron antineutrinos for cases without and with an anomalous accumulation of electrons which can be considered as a clear signal of the coming earthquake, at the geological region with a fault zone, and find that the variation may reach as much as 3% for $\\bar \

Bin Wang; Ya-Zheng Chen; Xue-Qian Li

2010-01-17T23:59:59.000Z

452

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

453

A Buildings Module for the Stochastic Energy Deployment System  

SciTech Connect

The U.S. Department of Energy (USDOE) is building a new long-range (to 2050) forecasting model for use in budgetary and management applications called the Stochastic Energy Deployment System (SEDS), which explicitly incorporates uncertainty through its development within the Analytica(R) platform of Lumina Decision Systems. SEDS is designed to be a fast running (a few minutes), user-friendly model that analysts can readily run and modify in its entirety through a visual programming interface. Lawrence Berkeley National Laboratory is responsible for implementing the SEDS Buildings Module. The initial Lite version of the module is complete and integrated with a shared code library for modeling demand-side technology choice developed by the National Renewable Energy Laboratory (NREL) and Lumina. The module covers both commercial and residential buildings at the U.S. national level using an econometric forecast of floorspace requirement and a model of building stock turnover as the basis for forecasting overall demand for building services. Although the module is fundamentally an engineering-economic model with technology adoption decisions based on cost and energy performance characteristics of competing technologies, it differs from standard energy forecasting models by including considerations of passive building systems, interactions between technologies (such as internal heat gains), and on-site power generation.

Lacommare, Kristina S H; Marnay, Chris; Stadler, Michael; Borgeson, Sam; Coffey, Brian; Komiyama, Ryoichi; Lai, Judy

2008-05-15T23:59:59.000Z

454

Model documentation: Electricity Market Module, Electricity Fuel Dispatch Submodule  

SciTech Connect

This report documents the objectives, analytical approach and development of the National Energy Modeling System Electricity Fuel Dispatch Submodule (EFD), a submodule of the Electricity Market Module (EMM). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Not Available

1994-04-08T23:59:59.000Z

455

Long range forecast of power demands on the Baltimore Gas and Electric Company system. Volume 1  

SciTech Connect

The report presents the results of an econometric forecast of peak and electric power demands for the Baltimore Gas and Electric Company (BGandE) through the year 2003. The report describes the methodology, the results of the econometric estimations and associated summary statistics, the forecast assumptions, and the calculated forecasts of energy usage and peak demand. Separate models were estimated for summer and winter residential electricity usage in both Baltimore city and the non-city portion of the BGandE service area. Equations were also estimated for commercial energy usage, industrial usage, streetlighting, and for losses plus Company use. Non-econometric techniques were used to estimate future energy use by Bethlehem Steel Corporation's Sparrows Point plant in Baltimore County, Conrail, and the Baltimore Mass Transit Administration underground rail system. Models of peak demand for summer and winter were also estimated.

Estomin, S.L.; Kahal, M.I.

1985-09-01T23:59:59.000Z

456

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

457

Forecast Bias Correction: A Second Order Method  

E-Print Network (OSTI)

The difference between a model forecast and actual observations is called forecast bias. This bias is due to either incomplete model assumptions and/or poorly known parameter values and initial/boundary conditions. In this paper we discuss a method for estimating corrections to parameters and initial conditions that would account for the forecast bias. A set of simple experiments with the logistic ordinary differential equation is performed using an iterative version of a first order version of our method to compare with the second order version of the method.

Crowell, Sean

2010-01-01T23:59:59.000Z

458

Industrial production index forecast: Methods comparison  

Science Conference Proceedings (OSTI)

The purpose of this work is to investigate the suitability of different methods as short term forecast tools. It is studied and compared the application of the Kalman filter method with other forecasting methods when applied to a set of qualitative and quantitative information. The work data set is made of qualitative surveys of conjunture and the industrial production index (IPI). The objective is the attainment of short term forecast models for the Portuguese IPI of the transforming industry. After the previous treatment of the data

M. Filomena Teodoro

2012-01-01T23:59:59.000Z

459

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

460

Short-term streamflow forecasting: ARIMA vs neural networks  

Science Conference Proceedings (OSTI)

Streamflow forecasting is very important for water resources management and flood defence. In this paper two forecasting methods are compared: ARIMA versus a multilayer perceptron neural network. This comparison is done by forecasting a streamflow of ... Keywords: artificial neural networks, auto regressive integrated moving average, forecasting, streamflow

Juan Frausto-Solis; Esmeralda Pita; Javier Lagunas

2008-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "module forecasts future" 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

Customization and Marketing of Monsoon Forecasts A CSIRCMMACS Synergy  

E-Print Network (OSTI)

Customization and Marketing of Monsoon Forecasts A CSIRCMMACS Synergy Criteria for Technical forecasts of monsoon can significantly aid many sectors like agriculture, power and production industries to the operational forecast, to develop and deliver customized monsoon forecasts based on user need is required

Swathi, P S

462

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

463

RESERVOIR INFLOW FORECASTING USING NEURAL NETWORKS CHANDRASHEKAR SUBRAMANIAN  

E-Print Network (OSTI)

or over predicting electricity demand due to poor weather forecasts is several hundred million dollars outages that many in the area experienced. Deep Thunder can also improve generation-side load forecasting by providing high-resolution weather forecast data for use in electricity demand forecast models. Integrating

Manry, Michael

464

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

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

465

R/ECON December 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON December 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF DECEMBER 1999 NEW and wage growth slow later in the forecast, income growth will average 5% a year between 2000 and 2004. Over the forecast period, population growth will average 0.5% a year. The population will rise from 8

466

R/ECON July 2001 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON July 2001 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF JULY 2001 NEW JERSEY each year. The R/ECONTM forecast for New Jersey looks for growth in real output of 2.6 percent years. Over the forecast period, both the construction and manufacturing sectors will lose jobs

467

R/ECON April 2001 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON April 2001 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF APRIL 2001 NEW JERSEY and 2005, and by an average of 43,000 thereafter (from 2005 to 2020). The R/ECONTM forecast for New Jersey.6 percent a year over the rest of the forecast period. Personal income will rise 5.6 percent this year, down

468

R/ECON October 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON October 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF OCTOBER 1999 NEW JERSEY the rate of inflation should remain under 3% a year. (See Table 1.) #12;Throughout the forecast period and wage growth slow later in the forecast period, income growth will average 4.8% a year between 2000

469

Does increasing model stratospheric resolution improve extended range forecast skill?  

E-Print Network (OSTI)

Does increasing model stratospheric resolution improve extended range forecast skill? Greg Roff,1 forecast skill at high Southern latitudes is explored. Ensemble forecasts are made for two model configurations that differ only in vertical resolution above 100 hPa. An ensemble of twelve 30day forecasts

470

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022  

E-Print Network (OSTI)

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

471

R/ECON December 1998 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON December 1998 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF DECEMBER 1998 NEW 1997 will continue-- though at a reduced rate--through the forecast period that ends in 2001. New inflation of about 1.5%. In 1998, R/ECONTM forecasts that employment will rise by 76,000 jobs, or 2

472

R/ECON October 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON October 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF OCTOBER 2000 NEW JERSEY and 2002, with 84,800 jobs being added over the two-year period. The R/ECON TM forecast for New Jersey the rest of the forecast period as foreign immigration declines and the population ages. In the next 10

473

R/ECON April 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON April 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF APRIL 1999 NEW JERSEY forecast for New Jersey is for a continuation of the current expansion but at a somewhat slower pace in employment through the forecast period will be in services and trade. We also expect considerable growth

474

R/ECON July 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON July 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF JULY 1999 NEW JERSEY forecast for New Jersey is for a continuing but slowing expansion. (See Table 1.) In 1998, employment rose increased by 0.7% in 1998. It will slow a bit over the forecast period as foreign immigration declines. #12

475

R/ECON April 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE  

E-Print Network (OSTI)

R/ECON April 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF APRIL 2000 NEW JERSEY to more inflation and higher interest rates. The R/ECON TM forecast for New Jersey looks for employment.6% a year over the forecast period. The services and trade sectors will provide 90% of the net increase

476

Atmospheric Lagrangian coherent structures considering unresolved turbulence and forecast uncertainty  

E-Print Network (OSTI)

Atmospheric Lagrangian coherent structures considering unresolved turbulence and forecast, the uncertainty of the forecast FTLE fields is analyzed using ensemble forecasting. Unavoidable errors of the forecast velocity data due to the chaotic dynamics of the atmosphere is the salient reason for errors

Ross, Shane

477

A New Measure of Earnings Forecast Uncertainty Xuguang Sheng  

E-Print Network (OSTI)

A New Measure of Earnings Forecast Uncertainty Xuguang Sheng American University Washington, D of earnings forecast uncertainty as the sum of dispersion among analysts and the variance of mean forecast available to analysts at the time they make their forecasts. Hence, it alleviates some of the limitations

Kim, Kiho

478

AN ANALYSIS OF FORECAST BASED REORDER POINT POLICIES : THE BENEFIT  

E-Print Network (OSTI)

AN ANALYSIS OF FORECAST BASED REORDER POINT POLICIES : THE BENEFIT OF USING FORECASTS Mohamed Zied Ch^atenay-Malabry Cedex, France Abstract: In this paper, we analyze forecast based inventory control policies for a non-stationary demand. We assume that forecasts and the associated uncertainties are given

Paris-Sud XI, Université de

479

Time dependent Directional Profit Model for Financial Time Series Forecasting  

E-Print Network (OSTI)

Time dependent Directional Profit Model for Financial Time Series Forecasting Jingtao YAO Chew Lim@comp.nus.edu.sg Abstract Goodness­of­fit is the most popular criterion for neural network time series forecasting. In the context of financial time series forecasting, we are not only concerned at how good the forecasts fit

Yao, JingTao

480

A Study on Training Criteria for Financial Time Series Forecasting  

E-Print Network (OSTI)

A Study on Training Criteria for Financial Time Series Forecasting JingTao YAO Dept of Information on goodness-of-fit which is also the most popular criterion forecasting. How ever, in the context of financial time series forecasting, we are not only concerned at how good the forecasts fit their target. In order

Yao, JingTao

Note: This page contains sample records for the topic "module forecasts future" 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

A new class of hybrid models for time series forecasting  

Science Conference Proceedings (OSTI)

Applying quantitative models for forecasting and assisting investment decision making has become more indispensable in business practices than ever before. Improving forecasting especially time series forecasting accuracy is an important yet often difficult ... Keywords: Artificial neural networks (ANNs), Auto-Regressive Integrated Moving Average (ARIMA), Hybrid models, Probabilistic neural networks (PNNs), Time series forecasting

Mehdi Khashei; Mehdi Bijari

2012-03-01T23:59:59.000Z

482

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

SciTech Connect

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

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

2011-10-01T23:59:59.000Z

483

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

DOE Green Energy (OSTI)

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

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

2013-10-01T23:59:59.000Z

484

Addressing an Uncertain Future Using Scenario Analysis  

Science Conference Proceedings (OSTI)

The Office of Energy Efficiency and Renewable Energy (EERE) has had a longstanding goal of introducing uncertainty into the analysis it routinely conducts in compliance with the Government Performance and Results Act (GPRA) and for strategic management purposes. The need to introduce some treatment of uncertainty arises both because it would be good general management practice, and because intuitively many of the technologies under development by EERE have a considerable advantage in an uncertain world. For example, an expected kWh output from a wind generator in a future year, which is not exposed to volatile and unpredictable fuel prices, should be truly worth more than an equivalent kWh from an alternative fossil fuel fired technology. Indeed, analysts have attempted to measure this value by comparing the prices observed in fixed-price natural gas contracts compared to ones in which buyers are exposed to market prices (see Bolinger, Wiser, and Golove and (2004)). In addition to the routine reasons for exploring uncertainty given above, the history of energy markets appears to have exhibited infrequent, but troubling, regime shifts, i.e., historic turning points at which the center of gravity or fundamental nature of the system appears to have abruptly shifted. Figure 1 below shows an estimate of how the history of natural gas fired generating costs has evolved over the last three decades. The costs shown incorporate both the well-head gas price and an estimate of how improving generation technology has gradually tended to lower costs. The purpose of this paper is to explore scenario analysis as a method for introducing uncertainty into EERE's forecasting in a manner consistent with the preceding observation. The two questions are how could it be done, and what is its academic basis, if any. Despite the interest in uncertainty methods, applying them poses some major hurdles because of the heavy reliance of EERE on forecasting tools that are deterministic in nature, such as the Energy Information Administration's (EIA's) National Energy Modeling System (NEMS). NEMS is the source of the influential Annual Energy Outlook whose business-as-usual (BAU) case, the Reference Case, forms the baseline for most of the U.S. energy policy discussion. NEMS is an optimizing model because: 1. it iterates to an equilibrium among modules representing the supply, demand, and energy conversion subsectors; and 2. several subsectoral models are individually solved using linear programs (LP). Consequently, it is deeply rooted in the recent past and any effort to simulate the consequences of a major regime shift as depicted in Figure 1 must come by applying an exogenously specified scenario. And, more generally, simulating futures that lie outside of our recent historic experience, even if they do not include regime switches suggest some form of scenario approach. At the same time, the statistical validity of scenarios that deviate significantly outside the ranges of historic inputs should be questioned.

Siddiqui, Afzal S.; Marnay, Chris

2006-12-15T23:59:59.000Z

485

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

DOE Green Energy (OSTI)

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

Lane, J.A.

1976-02-01T23:59:59.000Z

486

Comparisons of Short Term Load Forecasting using Artificial Neural Network and Regression Method  

E-Print Network (OSTI)

In power systems the next day’s power generation must be scheduled every day, day ahead short-term load forecasting (STLF) is a necessary daily task for power dispatch. Its accuracy affects the economic operation and reliability of the system greatly. Under prediction of STLF leads to insufficient reserve capacity preparation and in turn, increases the operating cost by using expensive peaking units. On the other hand, over prediction of STLF leads to the unnecessarily large reserve capacity, which is also related to high operating cost. the research work in this area is still a challenge to the electrical engineering scholars because of its high complexity. How to estimate the future load with the historical data has remained a difficulty up to now, especially for the load forecasting of holidays, days with extreme weather and other anomalous days. With the recent development of new mathematical, data mining and artificial intelligence tools, it is potentially possible to improve the forecasting result. This paper presents a new neural network based approach for short-term load forecasting that uses the most correlated weather data for training, validating and testing the neural network. Correlation analysis of weather data determines the input parameters of the neural networks. And its results compare to regression method. Index terms Load Forecasting, artificial neural network, short term

Mr. Rajesh Deshmukh; Dr. Amita Mahor

2011-01-01T23:59:59.000Z

487

New results in forecasting of photovoltaic systems output based on solar radiation forecasting  

Science Conference Proceedings (OSTI)

Accurate short term forecasting of photovoltaic (PV) systems output has a great significance for fast development of PV parks in South-East Europe

Laurentiu Fara

2013-01-01T23:59:59.000Z

488

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

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

489

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

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

490

Annual Energy Outlook Forecast Evaluation 2004  

Gasoline and Diesel Fuel Update (EIA)

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

491

Annual Energy Outlook 2001 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

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

492

energy data + forecasting | OpenEI Community  

Open Energy Info (EERE)

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

493

Artificial Skill and Validation in Meteorological Forecasting  

Science Conference Proceedings (OSTI)

The results of a simulation study of multiple regression prediction models for meteorological forecasting are reported. The effects of sample size, amount, and severity of nonrepresentative data in the population, inclusion of noninformative ...

Paul W. Mielke Jr.; Kenneth J. Berry; Christopher W. Landsea; William M. Gray

1996-06-01T23:59:59.000Z

494

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 Nińo-3.4 region of the tropical Pacific Ocean. Forecast data from ...

Michael K. Tippett; Anthony G. Barnston

2008-10-01T23:59:59.000Z

495

Assessing Forecast Skill through Cross Validation  

Science Conference Proceedings (OSTI)

This study explains the method of cross validation for assessing forecast skill of empirical prediction models. Cross validation provides a relatively accurate measure of an empirical procedure's ability to produce a useful prediction rule from a ...

J. B. Elsner; C. P. Schmertmann

1994-12-01T23:59:59.000Z

496

Ensemble Forecast of a Typhoon Flood Event  

Science Conference Proceedings (OSTI)

A high-resolution nested regional spectral model and an ensemble prediction system are combined to forecast the track, intensity, and flooding precipitation arising from Typhoon Winnie of August 1997, which eventually reached supertyphoon status. ...

Brian P. Mackey; T. N. Krishnamurti

2001-08-01T23:59:59.000Z

497

Potential Economic Value of Seasonal Hurricane Forecasts  

Science Conference Proceedings (OSTI)

This paper explores the potential utility of seasonal Atlantic hurricane forecasts to a hypothetical property insurance firm whose insured properties are broadly distributed along the U.S. Gulf and East Coasts. Using a recently developed hurricane ...

Kerry Emanuel; Fabian Fondriest; James Kossin

2012-04-01T23:59:59.000Z

498

Airborne Volcanic Ash Forecast Area Reliability  

Science Conference Proceedings (OSTI)

In support of aircraft flight safety operations, daily comparisons between modeled, hypothetical, volcanic ash plumes calculated with meteorological forecasts and analyses were made over a 1.5-yr period. The Hybrid Single-Particle Lagrangian ...

Barbara J. B. Stunder; Jerome L. Heffter; Roland R. Draxler

2007-10-01T23:59:59.000Z

499

Forecast verification: Its Complexity and Dimensionality  

Science Conference Proceedings (OSTI)

Two fundamental characteristics of forecast verification problems—complexity and dimensionality—are described. To develop quantitative definitions of these characteristics, a general framework for the problem of absolute verification (AV) is ...

Allan H. Murphy

1991-07-01T23:59:59.000Z

500

Consensus Forecasts of Modeled Wave Parameters  

Science Conference Proceedings (OSTI)

The use of numerical guidance has become integral to the process of modern weather forecasting. Using various techniques, postprocessing of numerical model output has been shown to mitigate some of the deficiencies of these models, producing more ...

Tom H. Durrant; Frank Woodcock; Diana J. M. Greenslade

2009-04-01T23:59:59.000Z