DocumentCode
822152
Title
Trading wind generation in short term energy markets
Author
Bathurst, Graeme N. ; Weatherill, Jennie ; Strbac, Goran
Author_Institution
Centre for Electr. Eng., Univ. of Manchester Inst. of Sci. & Technol., UK
Volume
17
Issue
3
fYear
2002
fDate
8/1/2002 12:00:00 AM
Firstpage
782
Lastpage
789
Abstract
Even with state of the art forecasting methods, the short-term generation of wind farms cannot be predicted with a high degree of accuracy. In a market situation, these forecasting errors lead to commercial risk through imbalance costs when advance contracting. This situation is one that needs to be addressed due to the steady increase in the amount of grid connected wind generation, combined with the rise of deregulated, market orientated electricity systems. In the presence of imbalance prices and uncertain generation, a method is required to determine the optimum level of contract energy to be sold on the advance markets. Such a method is presented here using Markov probabilities for a wind farm and demonstrates substantial reductions in the imbalance costs. The effect of market closure delays and forecasting window lengths are also shown.
Keywords
Markov processes; electricity supply industry; wind power; wind power plants; Markov probabilities; Markov processes; NETA; advance contracting; advance markets; commercial risk; contract energy; deregulated market orientated electricity systems; forecasting errors; forecasting window lengths; grid connected wind generation; imbalance costs; imbalance prices; market closure delays; risk analysis; short-term generation; state of the art forecasting methods; uncertain generation; wind energy; wind farms; wind generation trading; Contracts; Costs; Delay effects; Economic forecasting; Electricity supply industry deregulation; Mesh generation; Power generation; Wind energy generation; Wind farms; Wind forecasting;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/TPWRS.2002.800950
Filename
1033726
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