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


1

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

2

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

3

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

4

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

5

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

6

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

7

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

E-Print Network (OSTI)

the accuracy of two methods to forecast natural gas prices:forecasting models along with the AEO forecast. Appendix ATable 1. Forecast Year AEO Predicted Price from 1996-2003

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

2005-01-01T23:59:59.000Z

8

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

9

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...

10

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

11

Forecasting Natural Gas Prices Using Time Series Models .  

E-Print Network (OSTI)

??The objective of this thesis is to estimate the natural gas component of the All Urban Consumer Price Index (CP-U) using time series forecasting models.… (more)

Berg, Andrew

2006-01-01T23:59:59.000Z

12

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

13

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

14

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

15

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

16

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

17

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

18

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

19

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

20

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

Note: This page contains sample records for the topic "base forecast natural" 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)

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

22

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

23

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

24

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

25

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

26

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

27

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

28

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

29

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

30

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

31

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

32

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

33

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

34

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

35

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

36

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

37

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

38

Compatibility of Stand Basal Area Predictions Based on Forecast Combination  

E-Print Network (OSTI)

Compatibility of Stand Basal Area Predictions Based on Forecast Combination Xiongqing Zhang Carr.) in Beijing, forecast combination was used to adjust predicted stand basal areas from these three types of models. The forecast combination method combines information and disperses errors from

Cao, Quang V.

39

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

40

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

Note: This page contains sample records for the topic "base forecast natural" 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 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

42

Bayesian Study and Naturalness in MSSM Forecast for the LHC  

E-Print Network (OSTI)

We perform a forecast of the CMSSM for the LHC based in an improved Bayesian analysis taking into account the present theoretical and experimental wisdom about the model. In this way we obtain a map of the preferred regions of the CMSSM parameter space and show that fine-tuning penalization arises from the Bayesian analysis itself when the experimental value of Mz is considered. The results are remarkable stable when using different priors

Maria Eugenia Cabrera

2010-05-14T23:59:59.000Z

43

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

Science Conference Proceedings (OSTI)

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

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-08-13T23:59:59.000Z

44

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

45

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

46

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

47

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

48

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

49

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

50

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

51

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

52

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

53

Operational forecasting based on a modified Weather Research and Forecasting model  

DOE Green Energy (OSTI)

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

Lundquist, J; Glascoe, L; Obrecht, J

2010-03-18T23:59:59.000Z

54

PROBCAST: A Web-Based Portal to Mesoscale Probabilistic Forecasts  

Science Conference Proceedings (OSTI)

This paper describes the University of Washington Probability Forecast (PROBCAST), a Web-based portal to probabilistic weather predictions over the Pacific Northwest. PROBCAST products are derived from the output of a mesoscale ensemble system ...

Clifford Mass; Jeff Baars; Susan Joslyn; John Pyle; Patrick Tewson; David Jones; Tilmann Gneiting; Adrian Raftery; J. M. Sloughter; Chris Fraley

2009-07-01T23:59:59.000Z

55

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

DOE Green Energy (OSTI)

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

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-08-13T23:59:59.000Z

56

Weather-based forecasts of California crop yields  

SciTech Connect

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

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

2005-09-26T23:59:59.000Z

57

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

58

Injection season forecast for natural gas storage - Today in ...  

U.S. Energy Information Administration (EIA)

This Week in Petroleum › Weekly Petroleum Status Report › Weekly Natural Gas Storage Report › Natural Gas Weekly Update ...

59

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

60

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

Note: This page contains sample records for the topic "base forecast natural" 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 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

62

How regulators should use natural gas price forecasts  

Science Conference Proceedings (OSTI)

Natural gas prices are critical to a range of regulatory decisions covering both electric and gas utilities. Natural gas prices are often a crucial variable in electric generation capacity planning and in the benefit-cost relationship for energy-efficiency programs. High natural gas prices can make coal generation the most economical new source, while low prices can make natural gas generation the most economical. (author)

Costello, Ken

2010-08-15T23:59:59.000Z

63

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

64

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

65

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

66

A Degeneracy in Cross-Validated Skill in Regression-based Forecasts  

Science Conference Proceedings (OSTI)

Highly negative skill scores may occur in regression-based experimental forecast trials in which the data being forecast are withheld in turn from a fixed sample, and the remaining data are used to develop regression relationships-that is, ...

Anthony G. Barnston; Huug M. van den Dool

1993-05-01T23:59:59.000Z

67

A new method for crude oil price forecasting based on support vector machines  

Science Conference Proceedings (OSTI)

This paper proposes a new method for crude oil price forecasting based on support vector machine (SVM). The procedure of developing a support vector machine model for time series forecasting involves data sampling, sample preprocessing, training & ...

Wen Xie; Lean Yu; Shanying Xu; Shouyang Wang

2006-05-01T23:59:59.000Z

68

CFSv2-Based Seasonal Hydroclimatic Forecasts over the Conterminous United States  

Science Conference Proceedings (OSTI)

There is a long history of debate on the usefulness of climate model–based seasonal hydroclimatic forecasts as compared to ensemble streamflow prediction (ESP). In this study, the authors use NCEP's operational forecast system, the Climate ...

Xing Yuan; Eric F. Wood; Joshua K. Roundy; Ming Pan

2013-07-01T23:59:59.000Z

69

Comments on “An Operational Ingredients-Based Methodology for Forecasting Midlatitude Winter Season Precipitation”  

Science Conference Proceedings (OSTI)

Wetzel and Martin present an ingredients-based methodology for forecasting winter season precipitation. Although they are to be commended for offering a framework for winter-weather forecasting, disagreements arise with some of their specific ...

David M. Schultz; John V. Cortinas Jr.; Charles A. Doswell III

2002-02-01T23:59:59.000Z

70

High-Resolution GFS-Based MOS Quantitative Precipitation Forecasts on a 4-km Grid  

Science Conference Proceedings (OSTI)

The Meteorological Development Laboratory (MDL) of the National Weather Service (NWS) has developed high-resolution Global Forecast System (GFS)-based model output statistics (MOS) 6- and 12-h quantitative precipitation forecast (QPF) guidance on ...

Jerome P. Charba; Frederick G. Samplatsky

2011-01-01T23:59:59.000Z

71

Probabilistic Quantitative Precipitation Forecasts Based on Reforecast Analogs: Theory and Application  

Science Conference Proceedings (OSTI)

A general theory is proposed for the statistical correction of weather forecasts based on observed analogs. An estimate is sought for the probability density function (pdf) of the observed state, given today’s numerical forecast. Assume that an ...

Thomas M. Hamill; Jeffrey S. Whitaker

2006-11-01T23:59:59.000Z

72

Shootout-89, A Comparative Evaluation of Knowledge-based Systems That Forecast Severe Weather  

Science Conference Proceedings (OSTI)

During the summer of 1989, the Forecast Systems Laboratory of the National Oceanic and Atmospheric Administration sponsored an evaluation of artificial-intelligence-based systems that forecast severe convective storms. The evaluation experiment, ...

W. R. Moninger; C. Lusk; W. F. Roberts; J. Bullas; Bde Lorenzis; J. C. McLeod; E. Ellison; J. Flueck; P. D. Lampru; K. C. Young; J. Weaver; R. S. Philips; R. Shaw; T. R. Stewart; S. M. Zubrick

1991-09-01T23:59:59.000Z

73

Stock Price and Index Forecasting by Arbitrage Pricing Theory-Based Gaussian TFA Learning  

E-Print Network (OSTI)

Stock Price and Index Forecasting by Arbitrage Pricing Theory-Based Gaussian TFA Learning Kai Chun take advantage of those models. In literature, forecasting of stock prices within the framework Xu, (2002) "Stock price and index forecasting by arbitrage pricing theory-based gaussian TFA learning

Xu, Lei

74

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

E-Print Network (OSTI)

Natural Gas Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Natural Gas Prices . . . . . . . . . . . . . . . . . . . . . . . . . .versus AEO and Henry Hub Natural Gas Prices . . . . . .

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

2005-01-01T23:59:59.000Z

75

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

76

Multimodel Approach Based on Evidence Theory for Forecasting Tropical Cyclone Tracks  

Science Conference Proceedings (OSTI)

In this paper a new multimodel approach for forecasting tropical cyclone tracks is presented. The approach is based on the Dempster–Shafer theory of evidence. At each forecast period, the multimodel forecast is given as an area where the tropical ...

Svetlana V. Poroseva; Nathan Lay; M. Yousuff Hussaini

2010-02-01T23:59:59.000Z

77

Crude Oil Price Forecasting: A Transfer Learning Based Analog Complexing Model  

Science Conference Proceedings (OSTI)

Most of the existing models for oil price forecasting only use the data in the forecasted time series itself. This study proposes a transfer learning based analog complexing model (TLAC). It first transfers some related time series in source domain to ... Keywords: transfer learning method, analog complexing model, genetic algorithm, crude oil price forecasting

Jin Xiao; Changzheng He; Shouyang Wang

2012-08-01T23:59:59.000Z

78

The stock index forecast based on dynamic recurrent neural network trained with GA  

E-Print Network (OSTI)

neural networks applied in forecasting stock price, at present, the most widely used neural network is BPThe stock index forecast based on dynamic recurrent neural network trained with GA Fang Yixian1In order to forecast the stock market more accurately, according to the dynamic property for the stock

79

ANN-based Short-Term Load Forecasting in Electricity Markets  

E-Print Network (OSTI)

ANN-based Short-Term Load Forecasting in Electricity Markets Hong Chen Claudio A. Ca~nizares Ajit forecasting technique that considers electricity price as one of the main characteristics of the system load. B. Makram, "A Hybrid Wavelet- Kalman Filter Method for Load Forecasting," Electric Power Systems

Cañizares, Claudio A.

80

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 "base forecast natural" 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

Forecasting Solar Radiation -- Preliminary Evaluation of an Approach Based upon the National Forecast Database  

DOE Green Energy (OSTI)

Our objective is to develop, and undertake a preliminary evaluation of a simple solar radiation forecast model using sky cover predictions from the National Digital Forecast Database as an input. This report describes the model and presents a limited evaluation of its performance against ground-measured and satellite-derived irradiances in Albany, New York.

Perez, R.; Moore, K.; Wilcox, S.; Renne, D.; Zelenka, A.

2007-01-01T23:59:59.000Z

82

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

E-Print Network (OSTI)

Natural Gas Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .> History of Natural Gas Regulation The natural gas marketto oversee the regulation of natural gas sales by regulating

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

2005-01-01T23:59:59.000Z

83

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

E-Print Network (OSTI)

coal supply. The natural gas supply covers six categories:renewables, oil supply, natural gas supply, natural gasnation-wide natural gas market, equalizing supply with

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

2005-01-01T23:59:59.000Z

84

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

85

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

E-Print Network (OSTI)

underestimate natural gas prices. The trends changed afterestimate natural gas prices. These trends suggest that

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

2005-01-01T23:59:59.000Z

86

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

E-Print Network (OSTI)

History of Natural Gas Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .pdf/table13.pdf> History of Natural Gas Regulation The

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

2005-01-01T23:59:59.000Z

87

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

Science Conference Proceedings (OSTI)

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

Antony Millner

2008-10-01T23:59:59.000Z

88

Short-term wind speed forecasting based on a hybrid model  

Science Conference Proceedings (OSTI)

Wind power is currently one of the types of renewable energy with a large generation capacity. However, operation of wind power generation is very challenging because of the intermittent and stochastic nature of the wind speed. Wind speed forecasting ... Keywords: Forecasting, RBF neural networks, Seasonal adjustment, Wavelet transform, Wind speed

Wenyu Zhang, Jujie Wang, Jianzhou Wang, Zengbao Zhao, Meng Tian

2013-07-01T23:59:59.000Z

89

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

90

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

91

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

E-Print Network (OSTI)

1 1.1 History of Natural Gaspdf/table13.pdf> History of Natural Gas Regulation TheUnderstanding the history of the natural gas market helps to

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

2005-01-01T23:59:59.000Z

92

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

E-Print Network (OSTI)

1 1.1 History of Natural Gas8 4.1 U.S. Wellhead and AEO Natural Gas8 4.2 U.S. Wellhead and Henry Hub Natural Gas

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

2005-01-01T23:59:59.000Z

93

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

E-Print Network (OSTI)

is on the rise, natural gas demand is expected to grow 2.4%has resulted in higher natural gas demand and volatility andelectricity and natural gas markets, demand-side management

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

2005-01-01T23:59:59.000Z

94

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

E-Print Network (OSTI)

Gas Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Gas Prices . . . . . . . . . . . . . . . . . . . . . . . . . .versus AEO and Henry Hub Natural Gas Prices . . . . . .

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

2005-01-01T23:59:59.000Z

95

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

96

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

E-Print Network (OSTI)

2003). Balancing Natural Gas Policy - Fueling the Demands ofThis lead to the Natural Gas Policy Act (NGPA) in 1978 whichnatural gas markets, demand-side management programs, development of renewable sources, and environmental policies. ”

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

2005-01-01T23:59:59.000Z

97

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

98

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

Science Conference Proceedings (OSTI)

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

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

2011-08-01T23:59:59.000Z

99

ANN-based residential water end-use demand forecasting model  

Science Conference Proceedings (OSTI)

Bottom-up urban water demand forecasting based on empirical data for individual water end uses or micro-components (e.g., toilet, shower, etc.) for different households of varying characteristics is undoubtedly superior to top-down estimates originating ... Keywords: Artificial neural network, Residential water demand forecasting, Water demand management, Water end use, Water micro-component

Christopher Bennett; Rodney A. Stewart; Cara D. Beal

2013-03-01T23:59:59.000Z

100

Application of Object-Based Verification Techniques to Ensemble Precipitation Forecasts  

Science Conference Proceedings (OSTI)

Both the Method for Object-based Diagnostic Evaluation (MODE) and contiguous rain area (CRA) object-based verification techniques have been used to analyze precipitation forecasts from two sets of ensembles to determine if spread-skill behavior ...

William A. Gallus Jr.

2010-02-01T23:59:59.000Z

Note: This page contains sample records for the topic "base forecast natural" 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

Application of dynamic linear regression to improve the skill of ensemble-based deterministic ozone forecasts  

SciTech Connect

Forecasts from seven air quality models and surface ozone data collected over the eastern USA and southern Canada during July and August 2004 provide a unique opportunity to assess benefits of ensemble-based ozone forecasting and devise methods to improve ozone forecasts. In this investigation, past forecasts from the ensemble of models and hourly surface ozone measurements at over 350 sites are used to issue deterministic 24-h forecasts using a method based on dynamic linear regression. Forecasts of hourly ozone concentrations as well as maximum daily 8-h and 1-h averaged concentrations are considered. It is shown that the forecasts issued with the application of this method have reduced bias and root mean square error and better overall performance scores than any of the ensemble members and the ensemble average. Performance of the method is similar to another method based on linear regression described previously by Pagowski et al., but unlike the latter, the current method does not require measurements from multiple monitors since it operates on individual time series. Improvement in the forecasts can be easily implemented and requires minimal computational cost.

Pagowski, M O; Grell, G A; Devenyi, D; Peckham, S E; McKeen, S A; Gong, W; Monache, L D; McHenry, J N; McQueen, J; Lee, P

2006-02-02T23:59:59.000Z

102

Information-Based Skill Scores for Probabilistic Forecasts  

Science Conference Proceedings (OSTI)

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

Bodo Ahrens; André Walser

2008-01-01T23:59:59.000Z

103

Flash Flood Forecasting: An Ingredients-Based Methodology  

Science Conference Proceedings (OSTI)

An approach to forecasting the potential for flash flood-producing storms is developed, using the notion of basic ingredients. Heavy precipitation is the result of sustained high rainfall rates. In turn, high rainfall rates involve the rapid ...

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

1996-12-01T23:59:59.000Z

104

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

105

Bidding Strategy with Forecast Technology Based on Support Vector Machine in Electrcity Market  

E-Print Network (OSTI)

The participants of the electricity market concern very much the market price evolution. Various technologies have been developed for price forecast. SVM (Support Vector Machine) has shown its good performance in market price forecast. Two approaches for forming the market bidding strategies based on SVM are proposed. One is based on the price forecast accuracy, with which the being rejected risk is defined. The other takes into account the impact of the producer's own bid. The risks associated with the bidding are controlled by the parameters setting. The proposed approaches have been tested on a numerical example.

Gao, C; Napoli, R; Wan, Q

2007-01-01T23:59:59.000Z

106

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.

107

Crude Oil Price Forecasting with an Improved Model Based on Wavelet Transform and RBF Neural Network  

Science Conference Proceedings (OSTI)

The fluctuation of oil price decides the security of energy and economics. So the crude oil price forecasting performs importantly. In the paper, we apply the improved model based on Wavelet Transform and Radial Basis Function (RBF) neural network to ...

Wu Qunli; Hao Ge; Cheng Xiaodong

2009-05-01T23:59:59.000Z

108

FUTURA: Hybrid System for Electric Load Forecasting by Using Case-Based Reasoning and Expert System  

Science Conference Proceedings (OSTI)

The results of combining a numeric extrapolation of data with the methodology of case-based reasoning and expert systems in order to improve the electric load forecasting are presented in this contribution. Registers of power consumption are stored as ...

Raúl Vilcahuamán; Joaquim Meléndez; Josep Lluis de la Rosa

2002-10-01T23:59:59.000Z

109

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

110

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

111

Monthly streamflow forecasting based on improved support vector machine model  

Science Conference Proceedings (OSTI)

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

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

2011-09-01T23:59:59.000Z

112

Wavelet-based multi-resolution analysis and artificial neural networks for forecasting temperature and thermal power consumption  

E-Print Network (OSTI)

a novel technique for electric load forecasting based on neural weather compensation. They proposed in the context of short or long-term load forecasting and power utilities management. The complex and nonlinear-term load forecasting. They concluded that the just-mentioned tools can be good candidates

Paris-Sud XI, Université de

113

Real Time Runoff Forecasts for Two Hydroelectric Stations Based on Satellite Snow Cover Monitoring  

E-Print Network (OSTI)

Seasonal and short-term runoff forecasts for two hydroelectric stations in the upper Rhine basin are carried out in real time based on snow cover monitoring by Landsat and SPOT satellites. Evaluation of snow reserves on 1 April 1993 from satellite data reveals uncertainties in estimates using point measurements on the ground as index. Runoff is computed by the SRM model with snow covered areas as well as temperature and precipitation forecasts as input variables. A SRM menu system has been installed for operational data acquisition and management. The runoff forecasts can be exploited, among other purposes, for optimizing the hydropower production and for timely decisions on the electricity market.

Klaus Seidel; Walter Brüsch; Charlotte Steinmeier; Jaroslav Martinec; Jürg Wiedemeier; Klaus Seidel Walter Br Usch; J Urg Wiedemeier

1995-01-01T23:59:59.000Z

114

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

115

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

116

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

E-Print Network (OSTI)

Traditional scheduling tools like Gantt Charts and CPM while useful in planning and execution of complex construction projects with multiple interdependent activities haven?t been of much help in implementing effective control systems for the same projects in case of deviation from their desired or assumed behavior. Further, in case of such deviations project managers in most cases make decisions which might be guided either by the prospects of short term gains or the intension of forcing the project to follow the original schedule or plan, inadvertently increasing the overall project cost. Many deterministic project control methods have been proposed by various researchers for calculating optimal resource schedules considering the time-cost as well as the time-cost-quality trade-off analysis. But the need is for a project control system which optimizes the effort or cost required for controlling the project by incorporating the stochastic dynamic nature of the construction-production process. Further, such a system must include a method for updating and revising the beliefs or models used for representing the dynamics of the project using the actual progress data of the project. This research develops such an optimal project control method using Kalman Filter forecasting method for updating and using the assumed project dynamics model for forecasting the Estimated Cost at Completion (EAC) and the Estimated Duration at Completion (EDAC) taking into account the inherent uncertainties in the project progress and progress measurements. The controller is then formulated for iteratively calculating the optimal resource allocation schedule that minimizes either the EAC or both the EAC and EDAC together using the evolutionary optimization algorithm Covariance Matrix Adaption Evolution Strategy (CMA-ES). The implementation of the developed framework is used with a hypothetical project and tested for its robustness in updating the assumed initial project dynamics model and yielding the optimal control policy considering some hypothetical cases of uncertainties in the project progress and progress measurements. Based on the tests and demonstrations firstly it is concluded that a project dynamics model based on the project Gantt chart for spatial interdependencies of sub-tasks with triangular progress rates is a good representation of a typical construction project; and secondly, it is shown that the use of CMA-ES in conjunction with the Kalman Filter estimation and forecasting method provides a robust framework that can be implemented for any kind of complex construction process for yielding the optimal control policies.

Bondugula, Srikant

2009-05-01T23:59:59.000Z

117

Tradeoff between Investments in Infrastructure and Forecasting when Facing Natural Disaster Risk  

E-Print Network (OSTI)

Hurricane Katrina of 2005 was responsible for at least 81 billion dollars of property damage. In planning for such emergencies, society must decide whether to invest in the ability to evacuate more speedily or in improved forecasting technology to better predict the timing and intensity of the critical event. To address this need, we use dynamic programming and Markov processes to model the interaction between the emergency response system and the emergency forecasting system. Simulating changes in the speed of evacuation and in the accuracy of forecasting allows the determination of an optimal mix of these two investments. The model shows that the evacuation improvement and the forecast improvement give different patterns of impact to their benefit. In addition, it shows that the optimal investment decision changes by the budget and the feasible range of improvement.

Kim, Seong D.

2009-05-01T23:59:59.000Z

118

ANN-Based Short-Term Load Forecasting in Electricity Markets  

E-Print Network (OSTI)

Abstract—This paper proposes an Artificial Neural Network (ANN)-based short-term load forecasting technique that considers electricity price as one of the main characteristics of the system load, demonstrating the importance of considering pricing when predicting loading in today’s electricity markets. Historical load data from the Ontario Hydro system as well as pricing information from the neighboring system are used for testing, showing the good performance of the proposed method. Keywords: Short-term load forecasting, electricity markets, spot prices, Artificial Neural Networks (ANN)

Hong Chen; Claudio A. Cañizares; Ajit Singh

2001-01-01T23:59:59.000Z

119

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

120

Analog Sky Condition Forecasting Based on a k-nn Algorithm  

Science Conference Proceedings (OSTI)

Very short-range, cloudy–clear sky condition forecasts are important for a variety of military, civil, and commercial activities. In this investigation, an approach based on a k-nearest neighbors (k-nn) algorithm was developed and implemented to ...

Timothy J. Hall; Rachel N. Thessin; Greg J. Bloy; Carl N. Mutchler

2010-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "base forecast natural" 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

Oil Price Forecasting with an EMD-Based Multiscale Neural Network Learning Paradigm  

Science Conference Proceedings (OSTI)

In this study, a multiscale neural network learning paradigm based on empirical mode decomposition (EMD) is proposed for crude oil price prediction. In this learning paradigm, the original price series are first decomposed into various independent intrinsic ... Keywords: Crude oil price forecasting, artificial neural networks, empirical mode decomposition, multiscale learning paradigm

Lean Yu; Kin Keung Lai; Shouyang Wang; Kaijian He

2007-05-01T23:59:59.000Z

122

Probabilistic Forecast Guidance for Severe Thunderstorms Based on the Identification of Extreme Phenomena in Convection-Allowing Model Forecasts  

Science Conference Proceedings (OSTI)

With the advent of convection-allowing NWP models (CAMs) comes the potential for new forms of forecast guidance. While CAMs lack the required resolution to simulate many severe phenomena associated with convection (e.g., large hail, downburst ...

Ryan A. Sobash; John S. Kain; David R. Bright; Andrew R. Dean; Michael C. Coniglio; Steven J. Weiss

2011-10-01T23:59:59.000Z

123

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

information about natural gas supply and demand. As amarket Calibrating natural gas supply and demand conditionsnation-wide natural gas market, equalizing supply with

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

2005-01-01T23:59:59.000Z

124

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

about natural gas supply and demand. As a result, someCalibrating natural gas supply and demand conditions withelectricity and natural gas markets, demand-side management

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

2005-01-01T23:59:59.000Z

125

To forecast short-term load in electric power system based on FNN  

Science Conference Proceedings (OSTI)

Electric power system load forecasting plays an important part in the Energy Management System (EMS), which has a great effect on the operating, controlling and planning of power system. Accurate load forecasting, especially short-term load forecasting, ...

Yueli Hu; Huijie Ji; Xiaolong Song

2009-08-01T23:59:59.000Z

126

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

127

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

128

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

129

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

130

Ensemble-Based Exigent Analysis. Part I: Estimating Worst-Case Weather-Related Forecast Damage Scenarios  

Science Conference Proceedings (OSTI)

Exigent analysis supplements an ensemble forecast of weather-related damage with a map of the worst-case scenario (WCS), a multivariate confidence bound of the damage. For multivariate Gaussian ensembles, ensemble-based exigent analysis uses a ...

Daniel Gombos; Ross N. Hoffman

2013-06-01T23:59:59.000Z

131

Performance of Observation-Based Prediction Algorithms for Very Short-Range, Probabilistic Clear-Sky Condition Forecasting  

Science Conference Proceedings (OSTI)

Very short-range sky condition forecasts are produced to support a variety of military, civil, and commercial activities. In this investigation, six advanced, observation (obs)-based prediction algorithms were developed and tested that generated ...

Timothy J. Hall; Carl N. Mutchler; Greg J. Bloy; Rachel N. Thessin; Stephanie K. Gaffney; Jonathan J. Lareau

2011-01-01T23:59:59.000Z

132

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

133

Comparison of AEO 2010 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 prices. Figure 1 shows the daily price history

Bolinger, Mark A.

2010-01-01T23:59:59.000Z

134

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

135

Comparison of AEO 2009 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 prices. Figure 1 shows the daily price history

Bolinger, Mark

2009-01-01T23:59:59.000Z

136

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

137

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

and imports U.S. electricity and gas markets includingrepresentation of electricity and natural gas markets,initially to conduct electricity restructuring analysis in

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

2005-01-01T23:59:59.000Z

138

Verification of Ensemble-Based Uncertainty Circles around Tropical Cyclone Track Forecasts  

Science Conference Proceedings (OSTI)

Several tropical cyclone forecasting centers issue uncertainty information with regard to their official track forecasts, generally using the climatological distribution of position error. However, such methods are not able to convey information ...

Thierry Dupont; Matthieu Plu; Philippe Caroff; Ghislain Faure

2011-10-01T23:59:59.000Z

139

The Role of Latent Heat Release in Explosive Cyclogenesis: Three Examples Based on ECMWF Operational Forecasts  

Science Conference Proceedings (OSTI)

Operational forecasts from the European Centre for Medium Range Weather Forecasts of three cases of explosive cyclogenesis of large magnitude that occurred in the North Atlantic during a 1-week period in January 1986 are presented, and results of ...

Richard J. Reed; Mark D. Albright; Adrian J. Sammons; Per Undén

1988-09-01T23:59:59.000Z

140

Neural networks based multiplex forecasting system of the end-point of copper blow period  

Science Conference Proceedings (OSTI)

The neural network and the experiential evaluation method are introduced into the industrial converting process forecast, and a multiplex forecast system is proposed at the end-point of copper blow period in a matte converting process. The fuzzy clustering ...

Lihua Xue; Hongzhong Huang; Yaohua Hu; Zhangming Shi

2005-05-01T23:59:59.000Z

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


141

Statistical Forecasts Based on the National Meteorological Center's Numerical Weather Prediction System  

Science Conference Proceedings (OSTI)

The production of interpretive weather element forecasts from dynamical model output variables is now an integral part of the centralized guidance systems of weather services throughout the world. The statistical forecasting system in the United ...

Gary M. Carter; J. Paul Dallavalle; Harry R. Glahn

1989-09-01T23:59:59.000Z

142

Assessment and Forecasting Natural Gas Reserve Appreciation in the Gulf Coast Basin  

SciTech Connect

Reserve appreciation, also called reserve growth, is the increase in the estimated ultimate recovery (the sum of year end reserves and cumulative production) from fields subsequent to discovery from extensions, infield drilling, improved recovery of in-place resources, new pools, and intrapool completions. In recent years, reserve appreciation has become a major component of total U.S. annual natural gas reserve additions. Over the past 15 years, reserve appreciation has accounted for more than 80 percent of all annual natural gas reserve additions in the U.S. lower 48 states (Figure 1). The rise of natural gas reserve appreciation basically came with the judgment that reservoirs were much more geologically complex than generally thought, and they hold substantial quantities of natural gas in conventionally movable states that are not recovered by typical well spacing and vertical completion practices. Considerable evidence indicates that many reservoirs show significant geological variations and compartmentalization, and that uniform spacing, unless very dense, does not efficiently tap and drain a sizable volume of the reservoir (Figure 2). Further, by adding reserves within existing infrastructure and commonly by inexpensive recompletion technology in existing wells, reserve appreciation has become the dominant factor in ample, low-cost natural gas supply. Although there is a wide range in natural gas reserve appreciation potential by play and that potential is a function of drilling and technology applied, current natural gas reserve appreciation studies are gross, averaging wide ranges, disaggregated by broad natural gas provinces, and calculated mainly as a function of time. A much more detailed analysis of natural gas reserve appreciation aimed at assessing long-term sustainability, technological amenability, and economic factors, however, is necessary. The key to such analysis is a disaggregation to the play level. Plays are the geologically homogeneous subdivision of the universe of hydrocarbon pools within a basin. Typically, fields within a play share common hydrocarbon type, reservoir genesis, trapping mechanism, and source. Plays provide the comprehensive reference needed to more efficiently develop reservoirs, to extend field limits, and to better assess opportunities for intrafield exploration and development in mature natural gas provinces. Play disaggregation reveals current production trends and highlights areas for further exploration by identifying and emphasizing areas for potential reserve appreciation.

Kim, E.M.; Fisher, W.L.

1997-10-01T23:59:59.000Z

143

A review of agent-based models for forecasting the deployment of distributed generation in energy systems  

Science Conference Proceedings (OSTI)

Agent-based models are seeing increasing use in the study of distributed generation (DG) deployment. Researchers and decision makers involved in the implementation of DG have been lacking a concise overview of why they should consider using agent-based ... Keywords: agent-based modeling, consumer behavior, distributed generation, energy forecasting, product deployment

Jason G. Veneman; M. A. Oey; L. J. Kortmann; F. M. Brazier; L. J. de Vries

2011-06-01T23:59:59.000Z

144

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

145

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

146

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...

147

Research on Short-term Load Forecasting of the Thermoelectric Boiler Based on a Dynamic RBF Neural Network  

E-Print Network (OSTI)

As thermal inertia is the key factor for the lag of thermoelectric utility regulation, it becomes very important to forecast its short-term load according to running parameters. In this paper, dynamic radial basis function (RBF) neural network is proposed based on the RBF neural network with the associated parameters of sample deviation and partial sample deviation, which are defined for the purpose of effective judgment of new samples. Also, in order to forecast the load of sample with large deviation, sensitivity coefficients of input layer is given in this paper. To validate this model, an experiment is performed on a thermoelectric plant, and the experimental result indicates that the network can be put into extensive use for short-term load forecasting of thermoelectric utility.

Dai, W.; Zou, P.; Yan, C.

2006-01-01T23:59:59.000Z

148

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

149

Building-level occupancy data to improve ARIMA-based electricity use forecasts  

Science Conference Proceedings (OSTI)

The energy use of an office building is likely to correlate with the number of occupants, and thus knowing occupancy levels should improve energy use forecasts. To gather data related to total building occupancy, wireless sensors were installed in a ... Keywords: energy forecast, occupancy, office buildings, sensors

Guy R. Newsham; Benjamin J. Birt

2010-11-01T23:59:59.000Z

150

Object-Based Evaluation of the Impact of Horizontal Grid Spacing on Convection-Allowing Forecasts  

Science Conference Proceedings (OSTI)

Forecasts generated by the Center for Analysis and Prediction of Storms with 1- and 4-km grid spacing using the Advanced Research Weather Research and Forecasting Model (ARW-WRF; ARW1 and ARW4, respectively) for the 2009–11 NOAA Hazardous Weather ...

Aaron Johnson; Xuguang Wang; Fanyou Kong; Ming Xue

2013-10-01T23:59:59.000Z

151

Performance evaluation of competing forecasting models: A multidimensional framework based on MCDA  

Science Conference Proceedings (OSTI)

So far, competing forecasting models are compared to each other using a single criterion at a time, which often leads to different rankings for different criteria - a situation where one cannot make an informed decision as to which model performs best ... Keywords: Crude oil prices, Forecasting models, Multi-Criteria Decision Analysis, Performance evaluation

Bing Xu; Jamal Ouenniche

2012-07-01T23:59:59.000Z

152

Research on Requirement Forecasting of Raw Materials for Boiler Manufacturing Enterprise Based on Exponential Smoothing Method  

Science Conference Proceedings (OSTI)

The best purchases of raw materials of manufacturing enterprises can be determined by accurate requirement forecasting to decide order quantities. According to the characteristics of the boiler manufacturers, the weighted coefficients and initial values ... Keywords: manufacturing enterprises, raw materials, requirement forecasting, exponential smoothing, weighting coefficients

Du Yanwei

2010-01-01T23:59:59.000Z

153

The complex fuzzy system forecasting model based on triangular fuzzy robust wavelet ?-support vector machine  

Science Conference Proceedings (OSTI)

This paper presents a new version of fuzzy wavelet support vector regression machine to forecast the nonlinear fuzzy system with multi-dimensional input variables. The input and output variables of the proposed model are described as triangular fuzzy ... Keywords: Fuzzy ?-support vector machine, Fuzzy system forecasting, Particle swarm optimization, Wavelet kernel function

Qi Wu

2011-11-01T23:59:59.000Z

154

A Displacement-Based Error Measure Applied in a Regional Ensemble Forecasting System  

Science Conference Proceedings (OSTI)

Errors in regional forecasts often take the form of phase errors, where a forecasted weather system is displaced in space or time. For such errors, a direct measure of the displacement is likely to be more valuable than traditional measures. A ...

Christian Keil; George C. Craig

2007-09-01T23:59:59.000Z

155

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

156

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

Science Conference Proceedings (OSTI)

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

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

2012-02-01T23:59:59.000Z

157

A Bias in Skill in Forecasts Based on Analogues and Antilogues  

Science Conference Proceedings (OSTI)

A bias in skill may exist in statistical forecast methods in which the verification datum is withheld from the developmental data (cross-validation methods). Under certain circumstances this bias in skill can become troublesome. By way of example,...

H. M. van den Dool

1987-09-01T23:59:59.000Z

158

A Fuzzy Logic–Based Analog Forecasting System for Ceiling and Visibility  

Science Conference Proceedings (OSTI)

WIND-3 is an application for aviation weather forecasting that uses the analog method to produce deterministic predictions of cloud ceiling height and horizontal visibility at airports. For data, it uses historical and current airport ...

Bjarne Hansen

2007-12-01T23:59:59.000Z

159

Climate Index Weighting Schemes for NWS ESP-Based Seasonal Volume Forecasts  

Science Conference Proceedings (OSTI)

This study compares methods to incorporate climate information into the National Weather Service River Forecast System (NWSRFS). Three small-to-medium river subbasins following roughly along a longitude in the Colorado River basin with different ...

Kevin Werner; David Brandon; Martyn Clark; Subhrendu Gangopadhyay

2004-12-01T23:59:59.000Z

160

Use of Seasonal Climate Forecasts in Rangeland-Based Livestock Operations in West Texas  

Science Conference Proceedings (OSTI)

The potential for west Texas ranchers to increase the profitability of their enterprises by becoming more proactive in their management practices by using seasonal climate forecasts is investigated using a focus group and ecological–economic ...

Kristi G. Jochec; James W. Mjelde; Andrew C. Lee; J. Richard Conner

2001-09-01T23:59:59.000Z

Note: This page contains sample records for the topic "base forecast natural" 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

Accounting for Model Error in Ensemble-Based State Estimation and Forecasting  

Science Conference Proceedings (OSTI)

Accurate forecasts require accurate initial conditions. For systems of interest, even given a perfect model and an infinitely long time series of observations, it is impossible to determine a system's exact initial state. This motivates a ...

James A. Hansen

2002-10-01T23:59:59.000Z

162

Other States Natural Gas Coalbed Methane, Reserves Based Production...  

Gasoline and Diesel Fuel Update (EIA)

Other States Natural Gas Coalbed Methane, Reserves Based Production (Billion Cubic Feet) Other States Natural Gas Coalbed Methane, Reserves Based Production (Billion Cubic Feet)...

163

Community-Based Forest (Natural) Resource Management: A Path...  

Open Energy Info (EERE)

Based Forest (Natural) Resource Management: A Path to Sustainable Environment and Development Jump to: navigation, search Name Community-Based Forest (Natural) Resource Management:...

164

Alaska Natural Gas in Underground Storage (Base Gas) (Million...  

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

Date: 9302013 Next Release Date: 10312013 Referring Pages: Underground Base Natural Gas in Storage - All Operators Alaska Underground Natural Gas Storage - All Operators Base...

165

Forecasting overview  

E-Print Network (OSTI)

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

Rob J Hyndman

2009-01-01T23:59:59.000Z

166

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

167

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

168

VBR MPEG Video Traffic Dynamic Prediction Based on the Modeling and Forecast of Time Series  

Science Conference Proceedings (OSTI)

The variable-bit-rate traffic characteristic brings a large complication to the utilization of network resources, especially bandwidth. To solve this problem, this paper proposes a dynamic prediction scheme of MPEG video traffic. We first advance an ... Keywords: MPEG, video trace, forecast, time series, ARMA

Jun Dai; Jun Li

2009-08-01T23:59:59.000Z

169

On Summary Measures of Skill in Rare Event Forecasting Based on Contingency Tables  

Science Conference Proceedings (OSTI)

The so-called True Skill Statistic (TSS) and the Heidke Skill Score (S), as used in the context of the contingency, table approach to forecast verification, are compared. It is shown that the TSS approaches the Probability of Detection (POD) ...

Charles A. Doswell III; Robert Davies-Jones; David L. Keller

1990-12-01T23:59:59.000Z

170

Fuzzy rule-based methodology for residential load behaviour forecasting during power systems restoration  

Science Conference Proceedings (OSTI)

Inadequate load pickup during power system restoration can lead to overload and underfrequency conditions, and even restart the blackout process, due to thermal energy losses. Thus, load behaviour estimation during restoration is desirable to avoid inadequate ... Keywords: artificial intelligence, energy management systems, fuzzy logic, load behaviour estimation, power system distribution, power system restoration, residential load forecasting, thermostatically controlled loads

Lia Toledo Moreira Mota; Alexandre Assis Mota; Andre Luiz Morelato Franca

2005-04-01T23:59:59.000Z

171

Chaotic Time Series Forecasting Base on Fuzzy Adaptive PSO for Feedforward Neural Network Training  

Science Conference Proceedings (OSTI)

Short-term electricity demand forecasting for the next hour to several days out is one of the most important tools by which an electric utility plans and dispatches the loading of generating units in order to meet system demand. But there exists chaos ... Keywords: Particle Swarm Optimization (PSO), chaotic time Series, fuzzy system, feedforward neural network

Wenyu Zhang; Jinzhao Liang; Jianzhou Wang; Jinxing Che

2008-11-01T23:59:59.000Z

172

A GA-weighted ANFIS model based on multiple stock market volatility causality for TAIEX forecasting  

Science Conference Proceedings (OSTI)

Stock market forecasting is important and interesting, because the successful prediction of stock prices may promise attractive benefits. The economy of Taiwan relies on international trade deeply, and the fluctuations of international stock markets ... Keywords: ANFIS, Genetic algorithm, Neural network, Weighted rule

Liang-Ying Wei

2013-02-01T23:59:59.000Z

173

Development of Wind Speed Forecasting Model Based on the Weibull Probability Distribution  

Science Conference Proceedings (OSTI)

Wind is a variable energy source. The power output of a wind turbine generator (WTG) unit, therefore, fluctuates with wind speed variations. Accurate models reflecting the variability of wind speed is hence required in both reliability evaluation of ... Keywords: Wind Energy, Wind Speed Forecasting Model, Weibull Distribution, Maximum Likelihood Method, Time Series Model

Ruigang Wang; Wenyi Li; B. Bagen

2011-02-01T23:59:59.000Z

174

Support vector regression with chaos-based firefly algorithm for stock market price forecasting  

Science Conference Proceedings (OSTI)

Due to the inherent non-linearity and non-stationary characteristics of financial stock market price time series, conventional modeling techniques such as the Box-Jenkins autoregressive integrated moving average (ARIMA) are not adequate for stock market ... Keywords: Chaotic mapping, Firefly algorithm, Stock market price forecasting, Support vector regression

Ahmad Kazem; Ebrahim Sharifi; Farookh Khadeer Hussain; Morteza Saberi; Omar Khadeer Hussain

2013-02-01T23:59:59.000Z

175

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

E-Print Network (OSTI)

supply contracts and natural gas storage. As shown below insupply contracts and natural gas storage. As shown below in

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

176

Wavelet-Based Nonlinear Multiscale Decomposition Model for Electricity Load Forecasting  

E-Print Network (OSTI)

ABSTRACT: We propose a wavelet multiscale decomposition based autoregressive approach for the prediction of one-hour ahead ahead load based on historical electricity load data. This approach is based on a multiple resolution decomposition of the signal using the non-decimated or redundant Haar à trous wavelet transform whose advantage is taking into account the asymmetric nature of the time-varying data. There is an additional computational advantage in that there is no need to recompute the wavelet transform (wavelet coefficients) of the full signal if the electricity data (time series) is regularly updated. We assess results produced by this multiscale autoregressive (MAR) method, in both linear and non-linear variants, with single resolution autoregression (AR), multilayer perceptron (MLP), Elman recurrent neural network (ERN) and the general regression neural network (GRNN) models. Results are based on the New South Wales (Australia) electricity load data that is provided by the National Electricity Market

D. Benaouda; F. Murtagh; J. L. Starck; O. Renaud; Universiti Tenaga Nasional; Jalan Kajang-puchong

2005-01-01T23:59:59.000Z

177

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

178

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

179

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

E-Print Network (OSTI)

CEC). 2002. Natural Gas Supply and Infrastructureincluded a long-term natural gas supply deal for years 2004fixed-price gas supply contracts and natural gas storage. As

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

180

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

E-Print Network (OSTI)

Associates, citing NYMEX natural gas bid-offer spreadAnalysis of the Market for Natural Gas Futures. ” The EnergyProfiles of Renewable and Natural Gas Electricity Contracts:

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "base forecast natural" 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

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

E-Print Network (OSTI)

supply contracts and natural gas storage. As shown below insupply contracts and natural gas storage. As shown below inWe find that natural gas options and storage are not

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

182

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

E-Print Network (OSTI)

Hedge Against Natural Gas Price Movements. ” http://Downward Pressure on Natural Gas Prices: The Impact ofTheis. 2001. “Which way the natural gas price: an attempt to

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

183

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

E-Print Network (OSTI)

solar, and hydro power are often sold on a fixed-pricesolar, and hydro power, which by their nature are immune to natural gas fuel price

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

184

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

E-Print Network (OSTI)

Which way the natural gas price: an attempt to predict theas a Hedge Against Gas Price Movement. ” Public UtilitiesHedge Against Natural Gas Price Movements. ” http://

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

185

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

186

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

187

Miscellaneous States Natural Gas Plant Liquids, Reserves Based...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Miscellaneous States Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

188

Oklahoma Natural Gas Liquids Lease Condensate, Reserves Based...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Oklahoma Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

189

Colorado Natural Gas Liquids Lease Condensate, Reserves Based...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Colorado Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

190

Kansas Natural Gas Liquids Lease Condensate, Reserves Based Production...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Kansas Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

191

Arkansas Natural Gas Liquids Lease Condensate, Reserves Based...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Arkansas Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

192

Wyoming Natural Gas Liquids Lease Condensate, Reserves Based...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Wyoming Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

193

Michigan Natural Gas Liquids Lease Condensate, Reserves Based...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Michigan Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

194

New Mexico Natural Gas Liquids Lease Condensate, Reserves Based...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) New Mexico Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

195

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...

196

Standardized Software for Wind Load Forecast Error Analyses and Predictions Based on Wavelet-ARIMA Models - Applications at Multiple Geographically Distributed Wind Farms  

Science Conference Proceedings (OSTI)

Given the multi-scale variability and uncertainty of wind generation and forecast errors, it is a natural choice to use time-frequency representation (TFR) as a view of the corresponding time series represented over both time and frequency. Here we use wavelet transform (WT) to expand the signal in terms of wavelet functions which are localized in both time and frequency. Each WT component is more stationary and has consistent auto-correlation pattern. We combined wavelet analyses with time series forecast approaches such as ARIMA, and tested the approach at three different wind farms located far away from each other. The prediction capability is satisfactory -- the day-ahead prediction of errors match the original error values very well, including the patterns. The observations are well located within the predictive intervals. Integrating our wavelet-ARIMA (‘stochastic’) model with the weather forecast model (‘deterministic’) will improve our ability significantly to predict wind power generation and reduce predictive uncertainty.

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

2013-03-19T23:59:59.000Z

197

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

E-Print Network (OSTI)

and Policy Options of California’s Reliance on Natural Gas. ”policy is often formulated with ratepayers in mind. 2) Second, long-term fixed-price natural gas

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

198

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

E-Print Network (OSTI)

biomass in particular – are subject to fuel price risks ofbiomass, solar, and hydro power are often sold on a fixed-pricebiomass, solar, and hydro power, which by their nature are immune to natural gas fuel price

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

199

Biennial Assessment of the Fifth Power Plan Interim Report on Electric Price Forecasts  

E-Print Network (OSTI)

2012. This is because high natural gas prices result in a shift to wind and coal generation. Figure 2 the Aurora forecast was based on medium trend natural gas prices and average water conditions. The spike in electric prices during the fall and winter of 2005 are due to high natural gas prices following hurricanes

200

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

E-Print Network (OSTI)

history nevertheless does not lend ready support to the view that the EIA’s reference case natural gas

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "base forecast natural" 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

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

202

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

203

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

204

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

205

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

206

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

207

> 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

208

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

209

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

210

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

211

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

212

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

E-Print Network (OSTI)

natural gas combined-cycle and combustion turbine power plantsnatural gas combined-cycle and combustion turbine power plantsnatural gas has become the fuel of choice for new power plants

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

213

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

E-Print Network (OSTI)

energy resources such as wind power carry no natural gas fuel priceenergy resources such as wind, geothermal, biomass, solar, and hydro power are often sold on a fixed-price

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

214

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

215

A novel statistical time-series pattern based interval forecasting strategy for activity durations in workflow systems  

Science Conference Proceedings (OSTI)

Forecasting workflow activity durations is of great importance to support satisfactory QoS in workflow systems. Traditionally, a workflow system is often designed to facilitate the process automation in a specific application domain where activities ... Keywords: Activity duration, Interval forecasting, Statistical time series, Time-series patterns, Workflow system

Xiao Liu; Zhiwei Ni; Dong Yuan; Yuanchun Jiang; Zhangjun Wu; Jinjun Chen; Yun Yang

2011-03-01T23:59:59.000Z

216

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

217

Utah Natural Gas in Underground Storage (Base Gas) (Million Cubic...  

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

Base Gas) (Million Cubic Feet) Utah Natural Gas in Underground Storage (Base Gas) (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1990 46,944 46,944...

218

Utah and Wyoming Natural Gas Plant Liquids, Reserves Based Production...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Utah and Wyoming Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

219

Federal Offshore--Texas Natural Gas Plant Liquids, Reserves Based...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Federal Offshore--Texas Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

220

New Mexico Natural Gas Plant Liquids, Reserves Based Production...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) New Mexico Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

Note: This page contains sample records for the topic "base forecast natural" 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

Louisiana--North Natural Gas Plant Liquids, Reserves Based Production...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Louisiana--North Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

222

Wyoming Natural Gas Plant Liquids, Reserves Based Production...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Wyoming Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

223

Colorado Natural Gas Plant Liquids, Reserves Based Production...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Colorado Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

224

Kentucky Natural Gas Plant Liquids, Reserves Based Production...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Kentucky Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

225

Kansas Natural Gas Plant Liquids, Reserves Based Production ...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Kansas Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

226

Utah Natural Gas Plant Liquids, Reserves Based Production (Million...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Utah Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

227

Florida Natural Gas Plant Liquids, Reserves Based Production...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Florida Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

228

Montana Natural Gas Plant Liquids, Reserves Based Production...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Montana Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

229

North Dakota Natural Gas Plant Liquids, Reserves Based Production...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) North Dakota Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

230

Oklahoma Natural Gas Plant Liquids, Reserves Based Production...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Oklahoma Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

231

Michigan Natural Gas Plant Liquids, Reserves Based Production...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Michigan Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

232

Utah Natural Gas Liquids Lease Condensate, Reserves Based Production...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Utah Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

233

Arkansas Natural Gas Plant Liquids, Reserves Based Production...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Arkansas Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6...

234

Colorado Natural Gas in Underground Storage (Base Gas) (Million...  

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

Base Gas) (Million Cubic Feet) Colorado Natural Gas in Underground Storage (Base Gas) (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1990 39,062 39,062...

235

Illinois Natural Gas in Underground Storage (Base Gas) (Million...  

Gasoline and Diesel Fuel Update (EIA)

Base Gas) (Million Cubic Feet) Illinois Natural Gas in Underground Storage (Base Gas) (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1990 571,959 571,959...

236

New Mexico Natural Gas in Underground Storage (Base Gas) (Million...  

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

Base Gas) (Million Cubic Feet) New Mexico Natural Gas in Underground Storage (Base Gas) (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1990 20,204 20,204...

237

Texas--State Offshore Natural Gas Plant Liquids, Reserves Based...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Texas--State Offshore Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

238

Texas Natural Gas in Underground Storage (Base Gas) (Million...  

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

Base Gas) (Million Cubic Feet) Texas Natural Gas in Underground Storage (Base Gas) (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1990 134,707 134,707...

239

Biometric verification/identification based on hands natural layout  

Science Conference Proceedings (OSTI)

In this paper, a hand biometric system for verification and recognition purposes is presented. The method is based on three keys. Firstly, the system is based on using a Natural Reference System (NRS) defined on the hand's natural layout. Consequently, ... Keywords: Biometric systems, Hand geometry, Invariant features, Security, Similarity

Miguel Adán; Antonio Adán; Andrés S. Vázquez; Roberto Torres

2008-04-01T23:59:59.000Z

240

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

Note: This page contains sample records for the topic "base forecast natural" 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

International Energy Outlook - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas International Energy Outlook 2004 Natural Gas Natural gas is the fastest growing primary energy source in the IEO2004 forecast. Consumption of natural gas is projected...

242

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

243

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

244

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

245

An economic feasibility analysis of distributed electric power generation based upon the Natural Gas-Fired Fuel Cell: a model of the operations cost.  

DOE Green Energy (OSTI)

This model description establishes the revenues, expenses incentives and avoided costs of Operation of a Natural Gas-Fired Fuel Cell-Based. Fuel is the major element of the cost of operation of a natural gas-fired fuel cell. Forecasts of the change in the price of this commodity a re an important consideration in the ownership of an energy conversion system. Differences between forecasts, the interests of the forecaster or geographical areas can all have significant effects on imputed fuel costs. There is less effect on judgments made on the feasibility of an energy conversion system since changes in fuel price can affect the cost of operation of the alternatives to the fuel cell in a similar fashion. The forecasts used in this model are only intended to provide the potential owner or operator with the means to examine alternate future scenarios. The operations model computes operating costs of a system suitable for a large condominium complex or a residential institution such as a hotel, boarding school or prison. The user may also select large office buildings that are characterized by 12 to 16 hours per day of operation or industrial users with a steady demand for thermal and electrical energy around the clock.

Not Available

1993-06-30T23:59:59.000Z

246

The Natural Number of Forward Markets for Electricity  

E-Print Network (OSTI)

forecast test for the natural gas price and load forecast (Lag in days RMSE (b) Natural gas price forecast 2-day laggedinformation on the natural gas price and load level as well

Suenaga, Hiroaki; Williams, Jeffrey

2005-01-01T23:59:59.000Z

247

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

248

How natural is a natural interface? An evaluation procedure based on action breakdowns  

Science Conference Proceedings (OSTI)

This paper describes an issue-based method to evaluate the naturalness of an interface. The method consists of the execution of a series of tasks on that interface, which is subsequently systematically analyzed to identify breakdowns in the users' actions. ... Keywords: Action breakdown, Naturalness, Systematic video analysis, Usability

Luciano Gamberini; Anna Spagnolli; Lisa Prontu; Sarah Furlan; Francesco Martino; Beatriz Rey Solaz; Mariano Alcañiz; Josè Antonio Lozano

2013-01-01T23:59:59.000Z

249

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

250

The Effect of Spaceborne Microwave and Ground-Based Continuous Lightning Measurements on Forecasts of the 1998 Groundhog Day Storm  

Science Conference Proceedings (OSTI)

This study seeks to evaluate the impact of several newly available sources of meteorological data on mesoscale model forecasts of the extratropical cyclone that struck Florida on 2 February 1998. Intermittent measurements of precipitation and ...

Dong-Eon Chang; James A. Weinman; Carlos A. Morales; William S. Olson

2001-08-01T23:59:59.000Z

251

Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications  

Science Conference Proceedings (OSTI)

Current land surface schemes used for mesoscale weather forecast models use the Jarvis-type stomatal resistance formulations for representing the vegetation transpiration processes. The Jarvis scheme, however, despite its robustness, needs ...

Dev Niyogi; Kiran Alapaty; Sethu Raman; Fei Chen

2009-02-01T23:59:59.000Z

252

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

253

Contributions of Mixed Physics versus Perturbed Initial/Lateral Boundary Conditions to Ensemble-Based Precipitation Forecast Skill  

Science Conference Proceedings (OSTI)

An experiment is described that is designed to examine the contributions of model, initial condition (IC), and lateral boundary condition (LBC) errors to the spread and skill of precipitation forecasts from two regional eight-member 15-km grid-...

Adam J. Clark; William A. Gallus Jr.; Tsing-Chang Chen

2008-06-01T23:59:59.000Z

254

Base Natural Gas in Underground Storage (Summary)  

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

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period:

255

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

E-Print Network (OSTI)

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

Perez, Richard R.

256

A forecasting solution to the oil spill problem based on a hybrid intelligent system  

Science Conference Proceedings (OSTI)

Oil spills represent one of the most destructive environmental disasters. Predicting the possibility of finding oil slicks in a certain area after an oil spill can be critical in reducing environmental risks. The system presented here uses the Case-Based ... Keywords: Case-Based Reasoning, Ensembles, Fusion algorithms, Oil spill, Radial Basis Function, Self organizing memory

Bruno Baruque; Emilio Corchado; Aitor Mata; Juan M. Corchado

2010-05-01T23:59:59.000Z

257

General Decompositions of MSE-Based Skill Scores: Measures of Some Basic Aspects of Forecast Quality  

Science Conference Proceedings (OSTI)

Skill scores defined as measures of relative mean square error—and based on standards of reference representing climatology, persistence, or a linear combination of climatology and persistence—are decomposed. Two decompositions of each skill ...

Allan H. Murphy

1996-10-01T23:59:59.000Z

258

Comparison of Information-Based Measures of Forecast Uncertainty in Ensemble ENSO Prediction  

Science Conference Proceedings (OSTI)

In this study, ensemble predictions of the El Niño–Southern Oscillation (ENSO) were conducted for the period 1981–98 using two hybrid coupled models. Several recently proposed information-based measures of predictability, including relative ...

Youmin Tang; Richard Kleeman; Andrew M. Moore

2008-01-01T23:59:59.000Z

259

An Operational Ingredients-Based Methodology for Forecasting Midlatitude Winter Season Precipitation  

Science Conference Proceedings (OSTI)

An ingredients-based methodology (IM) for the operational analysis and prediction of midlatitude winter season precipitation is developed. Diagnostics for five fundamental physical ingredients involved in the production of precipitation—forcing ...

Suzanne W. Wetzel; Jonathan E. Martin

2001-02-01T23:59:59.000Z

260

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 "base forecast natural" 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

Florida Natural Gas Liquids Lease Condensate, Reserves Based...  

Gasoline and Diesel Fuel Update (EIA)

Florida Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 0...

262

Kentucky Natural Gas Liquids Lease Condensate, Reserves Based...  

Annual Energy Outlook 2012 (EIA)

Kentucky Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 0...

263

Montana Natural Gas Liquids Lease Condensate, Reserves Based...  

Annual Energy Outlook 2012 (EIA)

Montana Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 0...

264

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

265

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...

266

Original paper: Development of a web-based disease forecasting system for strawberries  

Science Conference Proceedings (OSTI)

Abstract: Florida produces about 16 million flats of strawberries every year, 15% of berries produced in the U.S. and virtually all the berries grown in the winter. Fungicides are applied on a weekly schedule to control Anthracnose and Botrytis fruit ... Keywords: Climate, Decision support system, Google Maps, Simulation modeling, Web-based interface

W. Pavan; C. W. Fraisse; N. A. Peres

2011-01-01T23:59:59.000Z

267

Classification of Commodity Price Forecast With Random Forests and Bayesian  

E-Print Network (OSTI)

Classification of Commodity Price Forecast Sentiment With Random Forests and Bayesian Optimization, Morgan Stanley or Merrill Lynch produce24 price forecasting and reports to predict the direction on the sentiment of price39 forecasts and reports for commodities such as gold, natural gas or most commonly oil

de Freitas, Nando

268

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

269

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

270

Genomics of Plant-based Biofuels in the Journal Nature  

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

3, 2008 3, 2008 DOE JGI Director Eddy Rubin Highlights the Genomics of Plant-based Biofuels in the Journal Nature WALNUT CREEK, CA-Genomics is accelerating improvements for converting plant biomass into biofuel-as an alternative to fossil fuel for the nation's transportation needs, reports Eddy Rubin, Director of the U.S. Department of Energy Joint Genome Institute (DOE JGI), in the August 14 edition of the journal Nature. In "Genomics of cellulosic biofuels," Rubin lays out a path forward for how emerging genomic technologies will contribute to a substantially different biofuels future as compared to the present corn-based ethanol industry-and in part mitigate the food-versus-fuel debate. The Nature Review is available for download (by subscription) at http://www.nature.com/.

271

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

272

Computer Generation of Marine Weather Forecast Text  

Science Conference Proceedings (OSTI)

MARWORDS is a natural language text generation system which has been developed to synthesize marine forecasts for the Davis Strait area in Northern Canada. It uses standard manually produced predictions of wind speed, air temperature, and other ...

E. Goldberg; R. Kittredge; A. Polguère

1988-08-01T23:59:59.000Z

273

Irrigation water demand forecasting: a data pre-processing and data mining approach based on spatio-temporal data  

Science Conference Proceedings (OSTI)

World population is increasing at a fast rate resulting in huge pressure on limited water resources. Just about 3% of the earth's total water is freshwater that can be used for various applications including irrigation. Therefore, an efficient irrigation ... Keywords: data mining, data pre-processing, decision support system, decision tree, demand forecasting, water management

Mahmood A. Khan, Zahidul Islam, Mohsin Hafeez

2011-12-01T23:59:59.000Z

274

A Coherent Method of Stratification within a General Framework for Forecast Verification  

Science Conference Proceedings (OSTI)

The general framework for forecast verification described by Murphy and Winkler embodies a statistical approach to the problem of assessing the quality of forecasts. This framework is based on the joint distribution of forecasts and observations, ...

Allan H. Murphy

1995-05-01T23:59:59.000Z

275

An Objective Clear-Air Turbulence Forecasting Technique: Verification and Operational Use  

Science Conference Proceedings (OSTI)

An objective technique for forecasting clear-air turbulence (CAT) is described. An index is calculated based on the product of horizontal deformation and vertical wind shear derived from numerical model forecast winds aloft. The forecast ...

Gary P. Ellrod; David I. Knapp

1992-03-01T23:59:59.000Z

276

Revised Draft Fuel Price Forecasts for the Draft  

E-Print Network (OSTI)

Natural gas prices, as well as oil and coal prices, are forecast using an Excel spreadsheet model at this time, natural gas prices are forecast in more detail than oil and coal prices. Residential in the industrial boiler fuel market to help keep natural gas prices low. Continuing declines in coal prices coupled

277

DRAFT FUEL PRICE FORECASTS FOR THE 5TH  

E-Print Network (OSTI)

. Forecast Methods Natural gas prices, as well as oil and coal prices, are forecast using an Excel in more detail than oil and coal prices. Residential and commercial sector retail natural gas prices market to help keep natural gas prices low. Continuing declines in coal prices coupled with improved

278

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

279

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...

280

Building Energy Software Tools Directory: Energy Usage Forecasts  

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

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

Note: This page contains sample records for the topic "base forecast natural" 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

Early Warnings of Severe Weather from Ensemble Forecast Information  

Science Conference Proceedings (OSTI)

A system has been developed to give probabilistic warnings of severe-weather events for the United Kingdom (UK) on a regional and national basis, based on forecast output from the European Centre for Medium-Range Weather Forecasts (ECMWF) ...

T. P. Legg; K. R. Mylne

2004-10-01T23:59:59.000Z

282

The Effect of Probabilistic Information on Threshold Forecasts  

Science Conference Proceedings (OSTI)

The study reported here asks whether the use of probabilistic information indicating forecast uncertainty improves the quality of deterministic weather decisions. Participants made realistic wind speed forecasts based on historical information in ...

Susan Joslyn; Karla Pak; David Jones; John Pyles; Earl Hunt

2007-08-01T23:59:59.000Z

283

A Probability Model for Verifying Deterministic Forecasts of Extreme Events  

Science Conference Proceedings (OSTI)

This article proposes a method for verifying deterministic forecasts of rare, extreme events defined by exceedance above a high threshold. A probability model for the joint distribution of forecasts and observations, and based on extreme-value ...

Christopher A. T. Ferro

2007-10-01T23:59:59.000Z

284

Predictability and Information Theory. Part II: Imperfect Forecasts  

Science Conference Proceedings (OSTI)

This paper presents a framework for quantifying predictability based on the behavior of imperfect forecasts. The critical quantity in this framework is not the forecast distribution, as used in many other predictability studies, but the ...

Timothy DelSole

2005-09-01T23:59:59.000Z

285

Threshold Relative Humidity Duration Forecasts for Plant Disease Prediction  

Science Conference Proceedings (OSTI)

Duration of high relative humidity periods is an important component of many plant disease development models. Performance of forecasts of this quantity, based on the model output statistics 3-h temperature and dewpoint forecasts produced by the ...

Daniel S. Wilks; Karin W. Shen

1991-04-01T23:59:59.000Z

286

Comparative Forecast Evaluation: Graphical Gaussian Models and Sufficiency Relations  

Science Conference Proceedings (OSTI)

This paper deals with the comparative evaluation of categorical forecasts supposing that forecasts and observations are continuous variables and have a jointly normal distribution. An information content approach based on the well-established ...

Ulrich Callies

2000-06-01T23:59:59.000Z

287

How Essential is Hydrologic Model Calibration to Seasonal Streamflow Forecasting?  

Science Conference Proceedings (OSTI)

Hydrologic model calibration is usually a central element of streamflow forecasting based on the ensemble streamflow prediction (ESP) method. Evaluation measures of forecast errors such as root-mean-square error (RMSE) are heavily influenced by ...

Xiaogang Shi; Andrew W. Wood; Dennis P. Lettenmaier

2008-12-01T23:59:59.000Z

288

Empirical Correction of the NCEP Global Forecast System  

Science Conference Proceedings (OSTI)

This paper examines the extent to which an empirical correction method can improve forecasts of the National Centers for Environmental Prediction (NCEP) operational Global Forecast System. The empirical correction is based on adding a forcing ...

Xiaosong Yang; Timothy DelSole; Hua-Lu Pan

2008-12-01T23:59:59.000Z

289

On Peirce’s Motivation for Equitability in Forecast Verification  

Science Conference Proceedings (OSTI)

In 1884, Peirce proposed a new two-category score for deterministic forecasts. The score was motivated by the desire to estimate the number of correct forecasts based on sound reasoning, without being sensitive to the frequency distribution of any ...

Mark J. Rodwell

2011-11-01T23:59:59.000Z

290

Bayesian Approach to Decision Making Using Ensemble Weather Forecasts  

Science Conference Proceedings (OSTI)

The economic value of ensemble-based weather or climate forecasts is generally assessed by taking the ensembles at “face value.” That is, the forecast probability is estimated as the relative frequency of occurrence of an event among a limited ...

Richard W. Katz; Martin Ehrendorfer

2006-04-01T23:59:59.000Z

291

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

292

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

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

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

293

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

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

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

294

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

295

Forecast of the electricity consumption by aggregation of specialized experts; application to Slovakian and French  

E-Print Network (OSTI)

Forecast of the electricity consumption by aggregation of specialized experts; application-term forecast of electricity consumption based on ensemble methods. That is, we use several possibly independent base forecasters and design meta-forecasters which combine the base predictions that are output by them

296

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

297

ASSESSING AND FORECASTING, BY PLAY, NATURAL GAS ULTIMATE RECOVERY GROWTH AND QUANTIFYING THE ROLE OF TECHNOLOGY ADVANCEMENTS IN THE TEXAS GULF COAST BASIN AND EAST TEXAS  

SciTech Connect

A detailed natural gas ultimate recovery growth (URG) analysis of the Texas Gulf Coast Basin and East Texas has been undertaken. The key to such analysis was determined to be the disaggregation of the resource base to the play level. A play is defined as a conceptual geologic unit having one or more reservoirs that can be genetically related on the basis of depositional origin of the reservoir, structural or trap style, source rocks and hydrocarbon generation, migration mechanism, seals for entrapment, and type of hydrocarbon produced. Plays are the geologically homogeneous subdivision of the universe of petroleum pools within a basin. Therefore, individual plays have unique geological features that can be used as a conceptual model that incorporates geologic processes and depositional environments to explain the distribution of petroleum. Play disaggregation revealed important URG trends for the major natural gas fields in the Texas Gulf Coast Basin and East Texas. Although significant growth and future potential were observed for the major fields, important URG trends were masked by total, aggregated analysis based on a broad geological province. When disaggregated by plays, significant growth and future potential were displayed for plays that were associated with relatively recently discovered fields, deeper reservoir depths, high structural complexities due to fault compartmentalization, reservoirs designated as tight gas/low-permeability, and high initial reservoir pressures. Continued technology applications and advancements are crucial in achieving URG potential in these plays.

William L. Fisher; Eugene M. Kim

2000-12-01T23:59:59.000Z

298

EMAT based inspection of natural gas pipelines for SSC cracks  

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

EMAT-Based Inspection of Natural Gas EMAT-Based Inspection of Natural Gas Pipelines for Stress Corrosion Cracks FY2004 Report Venugopal K. Varma, Raymond W. Tucker, Jr., and Austin P. Albright Oak Ridge National Laboratory Oak Ridge, Tennessee 37831 1 This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name,

299

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.

300

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

Note: This page contains sample records for the topic "base forecast natural" 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

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

302

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 ...

303

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

304

A Distributed Modeling System for Short-Term to Seasonal Ensemble Streamflow Forecasting in Snowmelt Dominated Basins  

SciTech Connect

This paper describes a distributed modeling system for short-term to seasonal water supply forecasts with the ability to utilize remotely-sensed snow cover products and real-time streamflow measurements. Spatial variability in basin characteristics and meteorology is represented using a raster-based computational grid. Canopy interception, snow accumulation and melt, and simplified soil water movement are simulated in each computational unit. The model is run at a daily time step with surface runoff and subsurface flow aggregated at the basin scale. This approach allows the model to be updated with spatial snow cover and measured streamflow using an Ensemble Kalman-based data assimilation strategy that accounts for uncertainty in weather forecasts, model parameters, and observations used for updating. Model inflow forecasts for the Dworshak Reservoir in northern Idaho are compared to observations and to April-July volumetric forecasts issued by the Natural Resource Conservation Service (NRCS) for Water Years 2000 – 2006. October 1 volumetric forecasts are superior to those issued by the NRCS, while March 1 forecasts are comparable. The ensemble spread brackets the observed April-July volumetric inflows in all years. Short-term (one and three day) forecasts also show excellent agreement with observations.

Wigmosta, Mark S.; Gill, Muhammad K.; Coleman, Andre M.; Prasad, Rajiv; Vail, Lance W.

2007-12-01T23:59:59.000Z

305

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

306

The Skill of Extended-Range Extratropical Winter Dynamical Forecasts  

Science Conference Proceedings (OSTI)

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

M. Déquá; J. F. Royer

1992-11-01T23:59:59.000Z

307

FORECASTING SOLAR RADIATION PRELIMINARY EVALUATION OF AN APPROACH  

E-Print Network (OSTI)

FORECASTING SOLAR RADIATION -- PRELIMINARY EVALUATION OF AN APPROACH BASED UPON THE NATIONAL, and undertake a preliminary evaluation of, a simple solar radiation forecast model using sky cover predictions experimental product from the United States National Weather Service (NWS) providing gridded forecasted

Perez, Richard R.

308

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

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

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

309

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

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

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

310

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

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

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

311

Comparing the risk profiles of renewable and natural gas electricity contracts: A summary of the California Department of Water Resources contracts  

E-Print Network (OSTI)

Against Volatile Natural Gas Prices." Proceedings: ACEEEM W h . Appendix C. California Natural Gas Price ForecastScenarios California Natural Gas Price Forecast Scenarios

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

2003-01-01T23:59:59.000Z

312

The Rationality of EIA Forecasts under Symmetric and Asymmetric Loss  

E-Print Network (OSTI)

case and a high and low oil price case. These forecasts areNatural Gas Imports World Oil Prices Natural Gas Wellheadgas imports, world oil price, coal prices to electric

Auffhammer, Maximilian

2005-01-01T23:59:59.000Z

313

The Strategy of Professional Forecasting  

E-Print Network (OSTI)

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

Marco Ottaviani; Peter Norman Sørensen

2003-01-01T23:59:59.000Z

314

Lower 48 States Natural Gas Liquids Lease Condensate, Reserves Based  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Reserves Based Production (Million Barrels) Lower 48 States Natural Gas Liquids Lease Condensate, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 147 1980's 159 161 157 157 179 168 169 162 162 165 1990's 158 153 147 153 157 145 162 174 178 199 2000's 208 215 207 191 182 174 182 181 173 178 2010's 224 211 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 8/1/2013 Next Release Date: 8/1/2014 Referring Pages: Lease Condensate Estimated Production Lower 48 States Lease Condensate Proved Reserves, Reserve Changes, and Production Lease Condensate

315

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

316

Building Energy Software Tools Directory: Degree Day Forecasts  

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

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

317

Objective Debiasing for Improved Forecasting of Tropical Cyclone Intensity with a Global Circulation Model  

Science Conference Proceedings (OSTI)

The damage potential of a tropical cyclone is proportional to a power (generally greater than one) of intensity, which demands high accuracy in forecasting intensity for managing this natural disaster. However, the current skill in forecasting ...

P. Goswami; S. Mallick; K. C. Gouda

2011-08-01T23:59:59.000Z

318

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

319

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

320

Optimization of Value of Aerodrome Forecasts  

Science Conference Proceedings (OSTI)

Prediction of short-term variations of vital boundary layer conditions at airports, such as visibility and cloud base, is important to the safe and economic operation of airlines. Results of an experiment involving groups of forecasters at three ...

Ross Keith

2003-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "base forecast natural" 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 Term Hourly Load Forecasting Using Abductive Networks R. E. Abdel-Aal  

E-Print Network (OSTI)

--Congestion forecasting, price forecasting, wholesale power market, locational marginal price, load partitioning, convex for system planning.1 Many studies have focused on electricity price forecasting based on statistical tools distributed loads and DC-OPF system variable solutions was identified and applied to forecast congestion

Abdel-Aal, Radwan E.

322

Annual Energy Outlook Forecast Evaluation - Tables  

Gasoline and Diesel Fuel Update (EIA)

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

323

Mid-range energy-forecasting system: structure, forecasts, and critique  

SciTech Connect

The Mid-Range Energy Forecasting System (MEFS) is a large-scale, interdisciplinary model of the US energy system maintained by the US Department of Energy. MEFS provides long-run regional forecasts of delivered prices for electricity, coal, gasoline, residual, distillate, and natural gas. A number of sets of MEFS forecasts are usually issued, each set corresponding to a different scenario. Because it forecasts prices and since these forecasts are regularly disseminated, MEFS is of considerable practical interest. A critical guide of the model's output for potential users is provided in this paper. The model's logic is described, the latest forecasts from MEFS are presented, and the reasonableness of both the forecasts and the methodology are critically evaluated. The manner in which MEFS interfaces with the Oil Market Simulation Model, which forecasts crude oil price, is also discussed. The evaluation concludes that while there are serious problems with MEFS, selective use can prove very helpful. 17 references, 1 figure, 2 tables.

DeSouza, G.

1980-01-01T23:59:59.000Z

324

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

325

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

326

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...

327

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

328

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

329

California Natural Gas in Underground Storage (Base Gas) (Million Cubic  

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

Base Gas) (Million Cubic Feet) Base Gas) (Million Cubic Feet) California Natural Gas in Underground Storage (Base Gas) (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1990 243,944 243,944 243,944 243,944 243,944 243,944 243,944 243,944 243,944 243,944 243,944 243,944 1991 243,944 243,944 243,944 243,944 243,944 243,944 243,944 243,944 248,389 248,389 248,389 248,389 1992 248,389 248,389 248,389 248,389 248,389 248,389 248,389 248,389 248,389 248,389 248,389 250,206 1993 250,206 250,206 247,228 246,345 247,699 247,950 247,109 248,215 248,944 251,050 247,420 247,425 1994 251,384 251,384 251,384 251,384 251,384 251,384 251,384 251,384 247,435 247,435 247,435 247,435 1995 247,419 247,419 247,419 247,419 247,419 247,419 247,419 247,419 247,419 247,419 247,419 247,419

330

Pennsylvania Natural Gas in Underground Storage (Base Gas) (Million Cubic  

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

Base Gas) (Million Cubic Feet) Base Gas) (Million Cubic Feet) Pennsylvania Natural Gas in Underground Storage (Base Gas) (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1990 352,686 352,686 352,686 351,920 352,686 352,686 353,407 353,407 353,407 353,407 359,236 358,860 1991 349,459 348,204 334,029 335,229 353,405 349,188 350,902 352,314 353,617 354,010 353,179 355,754 1992 358,198 353,313 347,361 341,498 344,318 347,751 357,498 358,432 359,300 359,504 359,321 362,275 1993 362,222 358,438 351,469 354,164 360,814 359,349 359,455 359,510 359,530 361,433 360,977 360,971 1994 360,026 357,906 358,611 360,128 361,229 361,294 361,339 361,335 361,335 361,335 361,238 362,038 1995 357,538 357,538 357,538 356,900 357,006 356,909 357,848 357,895 357,967 357,994 357,994 358,094

331

Washington Natural Gas in Underground Storage (Base Gas) (Million Cubic  

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

Base Gas) (Million Cubic Feet) Base Gas) (Million Cubic Feet) Washington Natural Gas in Underground Storage (Base Gas) (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1990 21,300 21,300 21,300 21,300 0 21,300 21,300 21,300 21,300 21,300 21,300 1991 21,300 21,300 21,300 21,300 21,300 21,300 21,300 21,300 21,300 18,800 18,800 18,800 1992 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 1993 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 1994 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 1995 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 18,800 21,123

332

Mississippi Natural Gas in Underground Storage (Base Gas) (Million Cubic  

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

Base Gas) (Million Cubic Feet) Base Gas) (Million Cubic Feet) Mississippi Natural Gas in Underground Storage (Base Gas) (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1990 46,050 46,050 46,050 46,050 46,050 46,050 46,050 46,050 46,050 46,050 46,050 46,050 1991 47,530 47,483 47,483 47,483 47,483 47,868 48,150 48,150 48,150 48,150 48,150 48,150 1992 48,150 48,150 48,149 48,149 48,149 48,149 48,149 48,149 48,149 48,149 47,851 48,049 1993 48,039 48,049 48,049 48,049 47,792 48,049 48,049 48,049 48,049 49,038 70,555 70,688 1994 71,043 71,801 71,955 71,959 71,959 71,959 71,959 71,959 71,959 72,652 72,671 72,671 1995 74,188 75,551 75,551 75,551 75,551 75,551 75,551 75,551 75,551 75,551 75,551 77,682

333

Louisiana Natural Gas in Underground Storage (Base Gas) (Million Cubic  

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

Base Gas) (Million Cubic Feet) Base Gas) (Million Cubic Feet) Louisiana Natural Gas in Underground Storage (Base Gas) (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1990 262,136 262,136 262,136 262,136 262,136 262,136 262,136 262,136 262,136 262,136 262,136 1991 264,324 264,324 264,304 264,497 265,121 265,448 265,816 266,390 262,350 266,030 267,245 267,245 1992 267,245 267,245 265,296 262,230 262,454 263,788 266,852 260,660 257,627 258,575 259,879 262,144 1993 261,841 255,035 251,684 252,604 253,390 254,839 253,518 254,115 254,299 254,043 254,646 251,132 1994 263,981 263,749 263,836 264,541 265,702 266,435 266,702 266,702 266,702 266,702 266,702 266,702 1995 266,702 266,702 266,643 266,702 266,702 266,702 266,702 266,702 266,702 266,702 266,702 267,311

334

The Natural Number of Forward Markets for Electricity  

E-Print Network (OSTI)

test for the natural gas price and load forecast (a) LoadLag in days RMSE (b) Natural gas price forecast 2-day laggedlagged daily spot natural gas price, and (b) for k from 35

Suenaga, Hiroaki; Williams, Jeffrey

2005-01-01T23:59:59.000Z

335

The Natural Number of Forward Markets for Electricity  

E-Print Network (OSTI)

test for the natural gas price and load forecast (a) LoadLag in days RMSE (b) Natural gas price forecast 2-day laggedinformation on the natural gas price and load level as well

Suenaga, Hiroaki; Williams, Jeffrey

2005-01-01T23:59:59.000Z

336

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

337

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

338

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

339

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

340

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 "base forecast natural" 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

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

342

A neural network model based on the multi-stage optimization approach for short-term food price forecasting in China  

Science Conference Proceedings (OSTI)

Many studies have demonstrated that back-propagation neural network can be effectively used to uncover the nonlinearity in the financial markets. Unfortunately, back-propagation algorithm suffers the problems of slow convergence, inefficiency, and lack ... Keywords: Artificial neural network, Back-propagation, Food price forecasting, Multi-stage optimization approach, Time series forecasting

Zou Haofei; Xia Guoping; Yang Fangting; Yang Han

2007-08-01T23:59:59.000Z

343

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST  

E-Print Network (OSTI)

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

344

Annual Energy Outlook 2006 with Projections to 2030 - Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

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

345

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

346

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

347

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

348

Forecasters ’ Objectives and Strategies ?  

E-Print Network (OSTI)

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

Iván Marinovic; Marco Ottaviani; Peter Norman Sørensen

2011-01-01T23:59:59.000Z

349

Annual Energy Outlook with Projections to 2025-Forecast Comparisons  

Gasoline and Diesel Fuel Update (EIA)

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

350

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

351

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

352

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

353

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

354

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

355

CloudCast: Cloud Computing for Short-Term Weather Forecasts  

Science Conference Proceedings (OSTI)

CloudCast provides clients with personalized short-term weather forecasts based on their current location using cloud services

Dilip Kumar Krishnappa; David Irwin; Eric Lyons; Michael Zink

2013-01-01T23:59:59.000Z

356

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

357

Dynamical Properties of MOS Forecasts: Analysis of the ECMWF Operational Forecasting System  

Science Conference Proceedings (OSTI)

The dynamical properties of ECMWF operational forecasts corrected by a (linear) model output statistics (MOS) technique are investigated, in light of the analysis performed in the context of low-order chaotic systems. Based on the latter work, ...

S. Vannitsem

2008-10-01T23:59:59.000Z

358

Evaluation of the Added Value of Regional Ensemble Forecasts on Global Ensemble Forecasts  

Science Conference Proceedings (OSTI)

The regional single-model-based Aire Limitée Adaptation Dynamique Développement International–Limited Area Ensemble Forecasting (ALADIN-LAEF) ensemble prediction system (EPS) is evaluated and compared with the global ECMWF-EPS to investigate the ...

Yong Wang; Simona Tascu; Florian Weidle; Karin Schmeisser

2012-08-01T23:59:59.000Z

359

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

360

A Frequent-Updating Analysis System Based on Radar, Surface, and Mesoscale Model Data for the Beijing 2008 Forecast Demonstration Project  

Science Conference Proceedings (OSTI)

The Variational Doppler Radar Analysis System (VDRAS) was implemented in Beijing, China, and contributed to the Beijing 2008 Forecast Demonstration Project (B08FDP) in support of the Beijing Summer Olympics. VDRAS is a four-dimensional ...

Juanzhen Sun; Mingxuan Chen; Yingchun Wang

2010-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "base forecast natural" 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

Short-Range Direct and Diffuse Irradiance Forecasts for Solar Energy Applications Based on Aerosol Chemical Transport and Numerical Weather Modeling  

Science Conference Proceedings (OSTI)

This study examines 2–3-day solar irradiance forecasts with respect to their application in solar energy industries, such as yield prediction for the integration of the strongly fluctuating solar energy into the electricity grid. During cloud-...

Hanne Breitkreuz; Marion Schroedter-Homscheidt; Thomas Holzer-Popp; Stefan Dech

2009-09-01T23:59:59.000Z

362

The Value of Seasonal Climate Forecasts in Managing Energy Resources  

Science Conference Proceedings (OSTI)

Research and interviews with officials of the United States energy industry and a systems analysis of decision making in a natural gas utility lead to the conclusion that seasonal climate forecasts would only have limited value in fine tuning the ...

Edith Brown Weiss

1982-04-01T23:59:59.000Z

363

Probabilistic Seasonal Forecasting of African Drought by Dynamical Models  

Science Conference Proceedings (OSTI)

As a natural phenomenon, drought can have devastating impacts on local populations through food insecurity and famine in the developing world such as Africa. In this study, we have established a seasonal hydrologic forecasting system over Africa. ...

Xing Yuan; Eric F. Wood; Nathaniel W. Chaney; Justin Sheffield; Jonghun Kam; Miaoling Liang; Kaiyu Guan

364

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

365

Technology-Based Oil and Natural Gas Plays: Shale Shock! Could ...  

U.S. Energy Information Administration (EIA)

Technology-Based Oil and Natural Gas Plays: Shale Shock! Could There Be Billions in the Bakken? Through the use of technology, U.S. oil and natural gas operators are ...

366

Comparison of Model Forecast Skill of Sea Level Pressure along the East and West Coasts of the United States  

Science Conference Proceedings (OSTI)

Despite recent advances in numerical weather prediction, major errors in short-range forecasts still occur. To gain insight into the origin and nature of model forecast errors, error frequencies and magnitudes need to be documented for different ...

Garrett B. Wedam; Lynn A. McMurdie; Clifford F. Mass

2009-06-01T23:59:59.000Z

367

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...

368

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

369

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

370

Natural Gas Prices: Well Above  

Gasoline and Diesel Fuel Update (EIA)

context, defined as the average, +- 2 standard deviations). EIA's forecast has natural gas prices gradually declining after the winter heating season, but still remaining high...

371

GSI 3DVar-based Ensemble-Variational Hybrid Data Assimilation for NCEP Global Forecast System: Single Resolution Experiments  

Science Conference Proceedings (OSTI)

An ensemble Kalman filter-variational hybrid data assimilation system based on the grid point statistical interpolation (GSI) three dimensional variational (3DVar) system was developed. The performance of the system was investigated using the ...

Xuguang Wang; David Parrish; Daryl Kleist; Jeffrey Whitaker

372

Control method for mixed refrigerant based natural gas liquefier  

DOE Patents (OSTI)

In a natural gas liquefaction system having a refrigerant storage circuit, a refrigerant circulation circuit in fluid communication with the refrigerant storage circuit, and a natural gas liquefaction circuit in thermal communication with the refrigerant circulation circuit, a method for liquefaction of natural gas in which pressure in the refrigerant circulation circuit is adjusted to below about 175 psig by exchange of refrigerant with the refrigerant storage circuit. A variable speed motor is started whereby operation of a compressor is initiated. The compressor is operated at full discharge capacity. Operation of an expansion valve is initiated whereby suction pressure at the suction pressure port of the compressor is maintained below about 30 psig and discharge pressure at the discharge pressure port of the compressor is maintained below about 350 psig. Refrigerant vapor is introduced from the refrigerant holding tank into the refrigerant circulation circuit until the suction pressure is reduced to below about 15 psig, after which flow of the refrigerant vapor from the refrigerant holding tank is terminated. Natural gas is then introduced into a natural gas liquefier, resulting in liquefaction of the natural gas.

Kountz, Kenneth J. (Palatine, IL); Bishop, Patrick M. (Chicago, IL)

2003-01-01T23:59:59.000Z

373

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

E-Print Network (OSTI)

Fuel Price Risk: Using Forward Natural Gas Prices Insteadof Gas Price Forecasts to Compare Renewable to Natural Gas-2003. Natural Gas and Energy Price Volatility. Arlington,

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

2004-01-01T23:59:59.000Z

374

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

375

Value of Probabilistic Weather Forecasts: Assessment by Real-Time Optimization of Irrigation Scheduling  

SciTech Connect

This paper presents a modeling framework for real-time decision support for irrigation scheduling using the National Oceanic and Atmospheric Administration's (NOAA's) probabilistic rainfall forecasts. The forecasts and their probability distributions are incorporated into a simulation-optimization modeling framework. In this study, modeling irrigation is determined by a stochastic optimization program based on the simulated soil moisture and crop water-stress status and the forecasted rainfall for the next 1-7 days. The modeling framework is applied to irrigated corn in Mason County, Illinois. It is found that there is ample potential to improve current farmers practices by simply using the proposed simulation-optimization framework, which uses the present soil moisture and crop evapotranspiration information even without any forecasts. It is found that the values of the forecasts vary across dry, normal, and wet years. More significant economic gains are found in normal and wet years than in dry years under the various forecast horizons. To mitigate drought effect on crop yield through irrigation, medium- or long-term climate predictions likely play a more important role than short-term forecasts. NOAA's imperfect 1-week forecast is still valuable in terms of both profit gain and water saving. Compared with the no-rain forecast case, the short-term imperfect forecasts could lead to additional 2.4-8.5% gain in profit and 11.0-26.9% water saving. However, the performance of the imperfect forecast is only slightly better than the ensemble weather forecast based on historical data and slightly inferior to the perfect forecast. It seems that the 1-week forecast horizon is too limited to evaluate the role of the various forecast scenarios for irrigation scheduling, which is actually a seasonal decision issue. For irrigation scheduling, both the forecast quality and the length of forecast time horizon matter. Thus, longer forecasts might be necessary to evaluate the role of forecasts for irrigation scheduling in a more effective way.

Cai, Ximing; Hejazi, Mohamad I.; Wang, Dingbao

2011-09-29T23:59:59.000Z

376

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

377

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

378

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

379

Wind and Load Forecast Error Model for Multiple Geographically Distributed Forecasts  

Science Conference Proceedings (OSTI)

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

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

2010-11-02T23:59:59.000Z

380

Patterns of Land Surface Errors and Biases in the Global Forecast System  

Science Conference Proceedings (OSTI)

One year’s worth of Global Forecast System (GFS) predictions of surface meteorological variables (wind speed, air temperature, dewpoint temperature, sea level pressure) are validated for land-based stations over the entire planet for forecasts ...

David Werth; Alfred Garrett

2011-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "base forecast natural" 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

Combining artificial neural networks and statistics for stock-market forecasting  

Science Conference Proceedings (OSTI)

We have developed a stock-market forecasting system based on artificial neural networks. The system has been trained with the Standard & Poor 500 composite indexes of past twenty years. Meanwhile, the system produces the forecasts and adjusts ...

Shaun-Inn Wu; Ruey-Pyng Lu

1993-03-01T23:59:59.000Z

382

Scientific Prerequisites to Comprehension of the Tropical Cyclone Forecast: Intensity, Track, and Size  

Science Conference Proceedings (OSTI)

The communication by forecasters of tropical cyclone (TC) descriptions and forecasts to user communities necessarily involves the transmission of information based in science to different classes of users composed primarily of nonscientists. ...

Lori Drake

2012-04-01T23:59:59.000Z

383

On the Level and Origin of Seasonal Forecast Skill in Northern Europe  

Science Conference Proceedings (OSTI)

This study examines the level and origin of seasonal forecast skill of surface air temperature in northern Europe. The forecasts are based on an empirical methodology, canonical correlation analysis (CCA), which is a method designed to find ...

Åke Johansson; Anthony Barnston; Suranjana Saha; Huug van den Dool

1998-01-01T23:59:59.000Z

384

Validation of Environment Canada and NOAA UV Index Forecasts with Brewer Measurements from Canada  

Science Conference Proceedings (OSTI)

Ground-based ultraviolet (UV) irradiance measurements by Brewer spectrophotometers at 10 sites across Canada are compared with UV index forecasts for the same locations from Environment Canada (EC) and NOAA. For the EC forecast validation, ...

Huixia He; Vitali E. Fioletov; David W. Tarasick; Thomas W. Mathews; Craig Long

2013-06-01T23:59:59.000Z

385

Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint  

Science Conference Proceedings (OSTI)

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

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

2013-10-01T23:59:59.000Z

386

Wind Power Forecasting Error Distributions: An International Comparison; Preprint  

DOE Green Energy (OSTI)

Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

Hodge, B. M.; Lew, D.; Milligan, M.; Holttinen, H.; Sillanpaa, S.; Gomez-Lazaro, E.; Scharff, R.; Soder, L.; Larsen, X. G.; Giebel, G.; Flynn, D.; Dobschinski, J.

2012-09-01T23:59:59.000Z

387

A Mixed Complementarity-Based Equilibrium Model of Natural Gas Markets  

Science Conference Proceedings (OSTI)

We present a new multiseasonal, multiyear, natural gas market equilibrium model based on the concept of a competitive equilibrium involving the market participants: producers, storage reservoir operators, peak gas operators, pipeline operators, marketers, ... Keywords: games/group decisions: noncooperative, industries: petroleum/natural gas, marketing: competitive strategy, natural resources: energy, programming: complementarity

Steven A. Gabriel; Supat Kiet; Jifang Zhuang

2005-09-01T23:59:59.000Z

388

Wood Pellets for UBC Boilers Replacing Natural Gas Based on LCA  

E-Print Network (OSTI)

Wood Pellets for UBC Boilers Replacing Natural Gas Based on LCA Submitted to Dr. Bi By Bernard Chan Pellets for UBC Boilers Replacing Natural Gas" By Bernard Chan, Brian Chan, and Christopher Young Abstract This report studies the feasibility of replacing natural gas with wood pellets for UBC boilers. A gasification

389

Validation of short and medium term operational solar radiation forecasts in the US  

SciTech Connect

This paper presents a validation of the short and medium term global irradiance forecasts that are produced as part of the US data set. The short term forecasts that extend up to 6-h ahead are based upon cloud motion derived from consecutive geostationary satellite images. The medium term forecasts extend up to 6-days-ahead and are modeled from gridded cloud cover forecasts from the US National Digital Forecast Database. The forecast algorithms are validated against ground measurements for seven climatically distinct locations in the United States for 1 year. An initial analysis of regional performance using satellite-derived irradiances as a benchmark reference is also presented. (author)

Perez, Richard; Kivalov, Sergey; Schlemmer, James; Hemker, Karl Jr. [ASRC, University at Albany, Albany, New York (United States); Renne, David [National Renewable Energy Laboratory, Golden, Colorado (United States); Hoff, Thomas E. [Clean Power Research, Napa, California (United States)

2010-12-15T23:59:59.000Z

390

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

391

U.S. Natural Gas Plant Liquids, Reserves Based Production (Million...  

Gasoline and Diesel Fuel Update (EIA)

Based Production (Million Barrels) U.S. Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

392

New Mexico--East Natural Gas Plant Liquids, Reserves Based Production...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) New Mexico--East Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

393

New Mexico--West Natural Gas Plant Liquids, Reserves Based Production...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) New Mexico--West Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5...

394

Texas--RRC District 6 Natural Gas Plant Liquids, Reserves Based...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Texas--RRC District 6 Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

395

Texas--RRC District 1 Natural Gas Plant Liquids, Reserves Based...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Texas--RRC District 1 Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

396

Texas--RRC District 5 Natural Gas Plant Liquids, Reserves Based...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Texas--RRC District 5 Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

397

Texas--RRC District 7C Natural Gas Plant Liquids, Reserves Based...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Texas--RRC District 7C Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

398

Texas--RRC District 7B Natural Gas Plant Liquids, Reserves Based...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Texas--RRC District 7B Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

399

Texas--RRC District 8A Natural Gas Plant Liquids, Reserves Based...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Texas--RRC District 8A Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

400

Texas--RRC District 10 Natural Gas Plant Liquids, Reserves Based...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Texas--RRC District 10 Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

Note: This page contains sample records for the topic "base forecast natural" 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

Texas--RRC District 8 Natural Gas Plant Liquids, Reserves Based...  

Annual Energy Outlook 2012 (EIA)

Reserves Based Production (Million Barrels) Texas--RRC District 8 Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

402

Texas--RRC District 9 Natural Gas Plant Liquids, Reserves Based...  

Gasoline and Diesel Fuel Update (EIA)

Reserves Based Production (Million Barrels) Texas--RRC District 9 Natural Gas Plant Liquids, Reserves Based Production (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4...

403

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

404

Improved Model Output Statistics Forecasts through Model Consensus  

Science Conference Proceedings (OSTI)

Consensus forecasts are computed by averaging model output statistics (MOS) forecasts based on the limited-area fine-mesh (LFM) model and the nested grid model (NGM) for the three-year period 1990–92. The test consists of four weather elements (...

Robert L. Vislocky; J. Michael Fritsch

1995-07-01T23:59:59.000Z

405

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

406

Final Report on California Regional Wind Energy Forecasting Project:Application of NARAC Wind Prediction System  

DOE Green Energy (OSTI)

Wind power is the fastest growing renewable energy technology and electric power source (AWEA, 2004a). This renewable energy has demonstrated its readiness to become a more significant contributor to the electricity supply in the western U.S. and help ease the power shortage (AWEA, 2000). The practical exercise of this alternative energy supply also showed its function in stabilizing electricity prices and reducing the emissions of pollution and greenhouse gases from other natural gas-fired power plants. According to the U.S. Department of Energy (DOE), the world's winds could theoretically supply the equivalent of 5800 quadrillion BTUs of energy each year, which is 15 times current world energy demand (AWEA, 2004b). Archer and Jacobson (2005) also reported an estimation of the global wind energy potential with the magnitude near half of DOE's quote. Wind energy has been widely used in Europe; it currently supplies 20% and 6% of Denmark's and Germany's electric power, respectively, while less than 1% of U.S. electricity is generated from wind (AWEA, 2004a). The production of wind energy in California ({approx}1.2% of total power) is slightly higher than the national average (CEC & EPRI, 2003). With the recently enacted Renewable Portfolio Standards calling for 20% of renewables in California's power generation mix by 2010, the growth of wind energy would become an important resource on the electricity network. Based on recent wind energy research (Roulston et al., 2003), accurate weather forecasting has been recognized as an important factor to further improve the wind energy forecast for effective power management. To this end, UC-Davis (UCD) and LLNL proposed a joint effort through the use of UCD's wind tunnel facility and LLNL's real-time weather forecasting capability to develop an improved regional wind energy forecasting system. The current effort of UC-Davis is aimed at developing a database of wind turbine power curves as a function of wind speed and direction, using its wind tunnel facility at the windmill farm at the Altamont Pass. The main objective of LLNL's involvement is to provide UC-Davis with improved wind forecasts to drive the parameterization scheme of turbine power curves developed from the wind tunnel facility. Another objective of LLNL's effort is to support the windmill farm operation with real-time wind forecasts for the effective energy management. The forecast skill in capturing the situation to meet the cut-in and cutout speed of given turbines would help reduce the operation cost in low and strong wind scenarios, respectively. The main focus of this report is to evaluate the wind forecast errors of LLNL's three-dimensional real-time weather forecast model at the location with the complex terrain. The assessment of weather forecast accuracy would help quantify the source of wind energy forecast errors from the atmospheric forecast model and/or wind-tunnel module for further improvement in the wind energy forecasting system.

Chin, H S

2005-07-26T23:59:59.000Z

407

Community-Based Forest (Natural) Resource Management: A Path to Sustainable  

Open Energy Info (EERE)

Community-Based Forest (Natural) Resource Management: A Path to Sustainable Community-Based Forest (Natural) Resource Management: A Path to Sustainable Environment and Development Jump to: navigation, search Name Community-Based Forest (Natural) Resource Management: A Path to Sustainable Environment and Development Agency/Company /Organization Regional Community Forestry Training Center for Asia and the Pacific Sector Land Focus Area Forestry Topics Implementation, Background analysis Resource Type Lessons learned/best practices Website http://recoftc.org/site/filead Country Philippines, Nepal UN Region South-Eastern Asia References Community-Based Forest (Natural) Resource Management: A Path to Sustainable Environment and Development[1] Community-Based Forest (Natural) Resource Management: A Path to Sustainable Environment and Development Screenshot

408

EIA - Forecasts and Analysis of Energy Data  

Gasoline and Diesel Fuel Update (EIA)

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

409

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

410

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

411

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

412

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

413

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

414

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

415

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.

416

Forecasting next-day price of electricity in the Spanish energy market using artificial neural networks  

Science Conference Proceedings (OSTI)

In this paper, next-day hourly forecasts are calculated for the energy price in the electricity production market of Spain. The methodology used to achieve these forecasts is based on artificial neural networks, which have been used successfully in recent ... Keywords: ART network, Backpropagation network, Box-Jenkins, Electricity market, Neural networks, Time series forecasting

Raúl Pino; José Parreno; Alberto Gomez; Paolo Priore

2008-02-01T23:59:59.000Z

417

Day-ahead electricity price forecasting by a new hybrid method  

Science Conference Proceedings (OSTI)

Electricity price forecasting has become necessary for power producers and consumers in the current deregulated electricity markets. Seeking for more accurate price forecasting techniques, this paper proposes a new hybrid method based on wavelet transform ... Keywords: ARIMA, Electricity price forecasting, LSSVM, PSO, WT

Jinliang Zhang; Zhongfu Tan; Shuxia Yang

2012-11-01T23:59:59.000Z

418

EVALUATION OF PV GENERATION CAPICITY CREDIT FORECAST ON DAY-AHEAD UTILITY MARKETS  

E-Print Network (OSTI)

EVALUATION OF PV GENERATION CAPICITY CREDIT FORECAST ON DAY-AHEAD UTILITY MARKETS Richard Perez of the NDFD-based solar radiation forecasts for several climatically distinct locations, the evaluation is now continued by testing the forecasts' end-use operational accuracy, focusing on their ability to accurately

Perez, Richard R.

419

Sixth Northwest Conservation & Electric Power Plan Draft Wholesale Power Price Forecasts  

E-Print Network (OSTI)

ANN-based Short-Term Load Forecasting in Electricity Markets Hong Chen Claudio A. Ca~nizares Ajit forecasting technique that considers electricity price as one of the main characteristics of the system load. B. Makram, "A Hybrid Wavelet- Kalman Filter Method for Load Forecasting," Electric Power Systems

420

Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint  

DOE Green Energy (OSTI)

One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

Zhang, J.; Hodge, B. M.; Gomez-Lazaro, E.; Lovholm, A. L.; Berge, E.; Miettinen, J.; Holttinen, H.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Dobschinski, J.

2013-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "base forecast natural" 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

Comparative Analysis of the Local Observation-Based (LOB) Method and the Nonparametric Regression-Based Method for Gridded Bias Correction in Mesoscale Weather Forecasting  

Science Conference Proceedings (OSTI)

The comparative analysis of three methods for objective grid-based bias removal in mesoscale numerical weather prediction models is considered. The first technique is the local observation-based (LOB) method that extends further the approaches of ...

Yulia R. Gel

2007-12-01T23:59:59.000Z

422

Natural  

Gasoline and Diesel Fuel Update (EIA)

Summary of U.S. Natural Gas Imports and Exports, 1992-1996 Table 1992 1993 1994 1995 1996 Imports Volume (million cubic feet) Pipeline Canada............................. 2,094,387 2,266,751 2,566,049 2,816,408 2,883,277 Mexico .............................. 0 1,678 7,013 6,722 13,862 Total Pipeline Imports....... 2,094,387 2,268,429 2,573,061 2,823,130 2,897,138 LNG Algeria .............................. 43,116 81,685 50,778 17,918 35,325 United Arab Emirates ....... 0 0 0 0 4,949 Total LNG Imports............. 43,116 81,685 50,778 17,918 40,274 Total Imports......................... 2,137,504 2,350,115 2,623,839 2,841,048 2,937,413 Average Price (dollars per thousand cubic feet) Pipeline Canada............................. 1.84 2.02 1.86 1.48 1.96 Mexico .............................. - 1.94 1.99 1.53 2.25 Total Pipeline Imports.......

423

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,

424

Coal supply/demand, 1980 to 2000. Task 3. Resource applications industrialization system data base. Final review draft. [USA; forecasting 1980 to 2000; sector and regional analysis  

SciTech Connect

This report is a compilation of data and forecasts resulting from an analysis of the coal market and the factors influencing supply and demand. The analyses performed for the forecasts were made on an end-use-sector basis. The sectors analyzed are electric utility, industry demand for steam coal, industry demand for metallurgical coal, residential/commercial, coal demand for synfuel production, and exports. The purpose is to provide coal production and consumption forecasts that can be used to perform detailed, railroad company-specific coal transportation analyses. To make the data applicable for the subsequent transportation analyses, the forecasts have been made for each end-use sector on a regional basis. The supply regions are: Appalachia, East Interior, West Interior and Gulf, Northern Great Plains, and Mountain. The demand regions are the same as the nine Census Bureau regions. Coal production and consumption in the United States are projected to increase dramatically in the next 20 years due to increasing requirements for energy and the unavailability of other sources of energy to supply a substantial portion of this increase. Coal comprises 85 percent of the US recoverable fossil energy reserves and could be mined to supply the increasing energy demands of the US. The NTPSC study found that the additional traffic demands by 1985 may be met by the railways by the way of improved signalization, shorter block sections, centralized traffic control, and other modernization methods without providing for heavy line capacity works. But by 2000 the incremental traffic on some of the major corridors was projected to increase very significantly and is likely to call for special line capacity works involving heavy investment.

Fournier, W.M.; Hasson, V.

1980-10-10T23:59:59.000Z

425

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

426

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

427

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

428

Natural Gas - U.S. Energy Information Administration (EIA) - U ...  

U.S. Energy Information Administration (EIA)

In the News: EIA projects lower natural gas use this winter. The U.S. Energy Information Administration (EIA) forecasts that reduced natural gas consumption from ...

429

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.

430

Integration of Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

Science Conference Proceedings (OSTI)

In this paper, a new approach to evaluate the uncertainty ranges for the required generation performance envelope, including the balancing capacity, ramping capability and ramp duration is presented. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (CAISO) real life data have shown the effectiveness and efficiency of the proposed approach.

Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Chakrabarti, Bhujanga B.; Subbarao, Krishnappa; Loutan, Clyde; Guttromson, Ross T.

2010-04-20T23:59:59.000Z

431

A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size  

Science Conference Proceedings (OSTI)

An ensemble-based data assimilation approach is used to transform old ensemble forecast perturbations with more recent observations for the purpose of inexpensively increasing ensemble size. The impact of the transformations are propagated ...

Andrew R. Lawrence; James A. Hansen

2007-04-01T23:59:59.000Z

432

A statistical model for risk management of electric outage forecasts  

Science Conference Proceedings (OSTI)

Risk management of power outages caused by severe weather events, such as hurricanes, tornadoes, and thunderstorms, plays an important role in electric utility distribution operations. Damage prediction based on weather forecasts on an appropriate spatial ...

H. Li; L. A. Treinish; J. R. M. Hosking

2010-05-01T23:59:59.000Z

433

Comparing Probabilistic Forecasting Systems with the Brier Score  

Science Conference Proceedings (OSTI)

This article considers the Brier score for verifying ensemble-based probabilistic forecasts of binary events. New estimators for the effect of ensemble size on the expected Brier score, and associated confidence intervals, are proposed. An ...

Christopher A. T. Ferro

2007-10-01T23:59:59.000Z

434

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

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

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

435

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

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

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

436

Successful Hydrologic Forecasting for California Using an Information Theoretic Model  

Science Conference Proceedings (OSTI)

The Entropy Minimax technique from information theory has been applied to long-range, hydrologic forecasting in California. Based on 1852–1977 records, the technique exhibits a limited, but statistically significant, success for predictions one ...

R. A. Christensen; R. F. Eilbert; O. H. Lindgren; L. L. Rans

1981-06-01T23:59:59.000Z

437

Forecasting electricity demand by hybrid machine learning model  

Science Conference Proceedings (OSTI)

This paper proposes a hybrid machine learning model for electricity demand forecasting, based on Bayesian Clustering by Dynamics (BCD) and Support Vector Machine (SVM). In the proposed model, a BCD classifier is firstly applied to cluster the input data ...

Shu Fan; Chengxiong Mao; Jiadong Zhang; Luonan Chen

2006-10-01T23:59:59.000Z

438

A Multiseason Climate Forecast System at the National Meteorological Center  

Science Conference Proceedings (OSTI)

The Coupled Model Project was established at the National Meteorological Center(NMC)in January l991 to develop a multiseason forecast system based on coupled ocean atmosphere general circulation models. This provided a focus to combine expertise ...

Ming Ji; Arun Kumar; Ants Leetmaa

1994-04-01T23:59:59.000Z

439

Using Bayesian Model Averaging to Calibrate Forecast Ensembles  

Science Conference Proceedings (OSTI)

Ensembles used for probabilistic weather forecasting often exhibit a spread-error correlation, but they tend to be underdispersive. This paper proposes a statistical method for postprocessing ensembles based on Bayesian model averaging (BMA), ...

Adrian E. Raftery; Tilmann Gneiting; Fadoua Balabdaoui; Michael Polakowski

2005-05-01T23:59:59.000Z

440

Climate Forecasts for Corn Producer Decision-Making  

Science Conference Proceedings (OSTI)

Corn is the most widely grown crop in the Americas, with annual production in the US of approximately 332 million metric tons. Improved climate forecasts, together with climate-related decision-tools for corn producers based on these improved ...

Eugene S. Takle; Christopher J. Anderson; Jeffrey Andresen; James Angel; Roger W. Elmore; Benjamin M. Gramig; Patrick Guinan; Steven Hilberg; Doug Kluck; Raymond Massey; Dev Niyogi; Jeanne M. Schneider; Martha D. Shulski; Dennis Todey; Melissa Widhalm

Note: This page contains sample records for the topic "base forecast natural" 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

An Improved Modeling Scheme for Freezing Precipitation Forecasts  

Science Conference Proceedings (OSTI)

To improve forecasts of various weather elements (snow, rain, and freezing precipitation) in numerical weather prediction models, a new mixed-phase cloud scheme has been developed. The scheme is based on a single prognostic equation for total ...

André Tremblay; Anna Glazer

2000-05-01T23:59:59.000Z

442

Forecasting and strategic inventory placement for gas turbine aftermarket spares  

E-Print Network (OSTI)

This thesis addresses the problem of forecasting demand for Life Limited Parts (LLPs) in the gas turbine engine aftermarket industry. It is based on work performed at Pratt & Whitney, a major producer of turbine engines. ...

Simmons, Joshua T. (Joshua Thomas)

2007-01-01T23:59:59.000Z

443

A Bayesian Forecast Model of Australian Region Tropical Cyclone Formation  

Science Conference Proceedings (OSTI)

A new and potentially skillful seasonal forecast model of tropical cyclone formation [tropical cyclogenesis (TCG)] is developed for the Australian region. The model is based on Poisson regression using the Bayesian approach. Predictor combinations ...

Angelika Werner; Neil J. Holbrook

2011-12-01T23:59:59.000Z

444

Impact of PV forecasts uncertainty in batteries management in microgrids  

E-Print Network (OSTI)

Impact of PV forecasts uncertainty in batteries management in microgrids Andrea Michiorri Arthur-based battery schedule optimisation in microgrids in presence of network constraints. We examine a specific case

Recanati, Catherine

445

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

446

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

E-Print Network (OSTI)

ACEEE). 2003. Natural Gas Price Effects of Energy EfficiencyFuel Price Risk: Using Forward Natural Gas Prices Insteadof Gas Price Forecasts to Compare Renewable to Natural Gas-

Wiser, Ryan; Bolinger, Mark

2005-01-01T23:59:59.000Z

447

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

448

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

SciTech Connect

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

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

2013-12-18T23:59:59.000Z

449

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

450

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

451

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

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

Electricity Price Curve Modeling and Forecasting by Manifold Learning  

E-Print Network (OSTI)

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

Jie Chen; Shi-Jie Deng; Xiaoming Huo

2008-01-01T23:59:59.000Z

454

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

455

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

456

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

457

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

458

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

459

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

460

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

Note: This page contains sample records for the topic "base forecast natural" 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

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

462

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

463

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

464

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

465

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

466

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

467

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

468

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

469

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

470

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

471

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

472

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

473

Forecasting Electric Vehicle Costs with Experience Curves  

E-Print Network (OSTI)

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

Lipman, Timonthy E.; Sperling, Daniel

2001-01-01T23:59:59.000Z

474

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

475

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

476

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

E-Print Network (OSTI)

MOS), Numerical Weather Prediction (NWP), Solar Forecasting of numerical weather prediction for intra?day solar solar energy applications based on aerosol chemical transport and  numerical weather 

Mathiesen, Patrick; Kleissl, Jan

2011-01-01T23:59:59.000Z

477

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

478

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

479

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

480

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

Note: This page contains sample records for the topic "base forecast natural" 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

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...

482

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

483

Electricity price short-term forecasting using artificial neural networks  

Science Conference Proceedings (OSTI)

This paper presents the System Marginal Price (SMP) short-term forecasting implementation using the Artificial Neural Networks (ANN) computing technique. The described approach uses the three-layered ANN paradigm with back-propagation. The retrospective SMP real-world data, acquired from the deregulated Victorian power system, was used for training and testing the ANN. The results presented in this paper confirm considerable value of the ANN based approach in forecasting the SMP.

Szkuta, B.R.; Sanabria, L.A.; Dillon, T.S. [La Trobe Univ., Melbourne (Australia). Applied Computing Research Inst.

1999-08-01T23:59:59.000Z

484

Southern hemisphere tropical cyclone intensity forecast methods used at the Joint Typhoon Warning Center, Part II: statistical – dynamical forecasts  

E-Print Network (OSTI)

The development and performance of a statistical- dynamical tropical cyclone intensity forecast model, which was developed for the United States of America’s Joint Typhoon Warning Center (JTWC), is described. This model, called the Southern Hemisphere Statistical Typhoon Intensity Prediction Scheme (SH STIPS), mirrors similar capabilities created for use in the western North Pacific and North Indian Ocean tropical cyclone basins. The model is created by fitting an optimal combination of factors related to climatology and persistence, intensification potential, vertical wind shear, dynamic size/intensity forecasts and atmospheric stability. All of these factors except the climatology and persistence information are derived from global forecast model analyses and forecasts. In July 2005 the SH STIPS model began a real-time evaluation period. The forecasts from the SH STIPS model have outperformed the combined climatology and persistence based forecast and thus are skillful in independent testing since that time. Since October 2006, SH STIPS has been the primary member in an operational consensus forecast of tropical cyclone intensity change provided to the JTWC. Documentation

John A. Knaff; Charles R. Sampson

2008-01-01T23:59:59.000Z

485

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

486

Minding the Gap: Central Bank Estimates of the Unemployment Natural Rate  

Science Conference Proceedings (OSTI)

A time-varying parameter framework is suggested for use with real-time multiperiod forecast data to estimate implied forecast equations. The framework is applied to historical briefing forecasts prepared for the Federal Open Market Committee to estimate ... Keywords: FOMC Greenbook forecasts, the Great Iflation, time-varying natural rates

Sharon Kozicki; P. A. Tinsley

2006-05-01T23:59:59.000Z

487

The Feasibility of Natural Gas as a Fuel Source for Modern Land-Based Drilling Rigs  

E-Print Network (OSTI)

The purpose of this study is to determine the feasibility of replacing diesel with natural gas as a fuel source for modern drilling rigs. More specifically, this thesis (1) establishes a control baseline by examining operational characteristics (response, fuel usage, and cost) of an existing diesel-powered land rig during the drilling of a well in the Haynesville Shale; (2) estimates operational characteristics of a natural gas engine under identical conditions; and (3) draws a comparison between diesel and natural gas engines, determining the advantages and disadvantages of those fuel sources in drilling applications. Results suggest that diesel engines respond to transient loads very effectively because of their inherently higher torque, especially when compared with natural gas engines of a similar power rating. Regarding fuel consumption, the engines running on diesel for this study were more efficient than on natural gas. On a per-Btu basis, the natural gas engines consumed nearly twice as much energy in drilling the same well. However, because of the low price of natural gas, the total cost of fuel to drill the well was lowered by approximately 54%, or 37,000 USD. Based on the results, it is possible to infer that the use of natural gas engines in drilling environments is feasible, and in most cases, an economical and environmental advantage. First, when compared with diesel, natural gas is a cleaner fuel with less negative impact on the environment. Second, fuel cost can be reduced by approximately half with a natural gas engine. On the other hand, natural gas as a fuel becomes less practical because of challenges associated with transporting and storing a gas. In fact, this difficulty is the main obstacle for the use of natural gas in drilling environments. In conclusion, because of its minimal drawback on operations, it is recommended that in situations where natural gas is readily available near current market prices, natural gas engines should be utilized because of the cost savings and reduced environmental impact. In all other cases, particularly where transport and storage costs encroach on the cost benefit, it may still be advantageous to continue powering rigs with diesel because of its ease of use.

Nunn, Andrew Howard

2011-12-01T23:59:59.000Z

488

On the value of 3D seismic amplitude data to reduce uncertainty in the forecast of reservoir production  

E-Print Network (OSTI)

On the value of 3D seismic amplitude data to reduce uncertainty in the forecast of reservoir of this paper. We have approached the problem of assessing uncertainty in production forecasts by constructing the original distribution of petrophysical properties and to forecast oil production based on limited

Torres-Verdín, Carlos

489

Development and testing of improved statistical wind power forecasting methods.  

DOE Green Energy (OSTI)

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

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

2011-12-06T23:59:59.000Z

490

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

E-Print Network (OSTI)

Against Volatile Natural Gas Prices Mark Bolinger, Ryanwake of unprecedented natural gas price volatility duringyears) to a 10-year natural gas price forecast (i.e. , what

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

2002-01-01T23:59:59.000Z

491

Fuel Price Forecasts INTRODUCTION  

E-Print Network (OSTI)

Another important consideration in natural gas supply and cost is the capacity to transport the gas from.75 trillion cubic feet of natural gas from Canada; and 1.1 trillion cubic feet of that were imported through would mean a growing role for frontier supply areas and liquefied natural gas imports. High prices

492

Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory  

Gasoline and Diesel Fuel Update (EIA)

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

493

Short-Termed Integrated Forecasting System: 1993 Model documentation report  

Science Conference Proceedings (OSTI)

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

Not Available

1993-05-01T23:59:59.000Z

494

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

495

Short-Term World Oil Price Forecast  

Gasoline and Diesel Fuel Update (EIA)

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

496

OpenEI Community - energy data + forecasting  

Open Energy Info (EERE)

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

497

Solar Wind Forecasting with Coronal Holes  

E-Print Network (OSTI)

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

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

2007-01-09T23:59:59.000Z

498

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

499

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

500

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