DocumentCode :
1080067
Title :
Trading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power
Author :
Pinson, Pierre ; Chevallier, Christophe ; Kariniotakis, George N.
Author_Institution :
Tech. Univ. of Denmark, Lyngby
Volume :
22
Issue :
3
fYear :
2007
Firstpage :
1148
Lastpage :
1156
Abstract :
Due to the fluctuating nature of the wind resource, a wind power producer participating in a liberalized electricity market is subject to penalties related to regulation costs. Accurate forecasts of wind generation are therefore paramount for reducing such penalties and thus maximizing revenue. Despite the fact that increasing accuracy in spot forecasts may reduce penalties, this paper shows that, if such forecasts are accompanied with information on their uncertainty, i.e., in the form of predictive distributions, then this can be the basis for defining advanced strategies for market participation. Such strategies permit to further increase revenues and thus enhance competitiveness of wind generation compared to other forms of dispatchable generation. This paper formulates a general methodology for deriving optimal bidding strategies based on probabilistic forecasts of wind generation, as well as on modeling of the sensitivity a wind power producer may have to regulation costs. The benefits resulting from the application of these strategies are clearly demonstrated on the test case of the participation of a multi-MW wind farm in the Dutch electricity market over a year.
Keywords :
costing; load forecasting; power generation economics; power markets; wind power plants; Dutch electricity market; liberalized electricity market; optimal bidding strategies; regulation costs; short-term probabilistic forecasts; wind farm; wind generation trading; Costs; Economic forecasting; Electricity supply industry; Power generation; Predictive models; Uncertainty; Wind energy; Wind energy generation; Wind forecasting; Wind power generation; Decision-making; energy markets; forecasting; uncertainty; wind energy;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2007.901117
Filename :
4282048
Link To Document :
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