DocumentCode :
1239701
Title :
Management of price uncertainty in short-term generation planning
Author :
Shrestha, G.B. ; Pokharel, B.K. ; Lie, T.T. ; Fleten, S.-E.
Author_Institution :
Sch. of EEE, Nanyang Technol. Univ., Singapore
Volume :
2
Issue :
4
fYear :
2008
fDate :
7/1/2008 12:00:00 AM
Firstpage :
491
Lastpage :
504
Abstract :
Price uncertainty is faced by gencos in the scheduling of their units in competitive power markets. the proper way to deal with the uncertainty depends on the risk preference of the genco. two important means to manage the price uncertainty are (i) suitable flexible bids and (ii) the use of hedging tools such as forward contracts. the influence of these factors in the genco´s short-term generation planning and the corresponding profit performances is studied. the market price is represented by lognormal distribution, genco risk behaviour is represented by exponential utility functions, the bid functions are taken to be flexible and simple contracts for hedging are assumed available. the unit commitment problem is combined with the hedging problem to obtain the optimal solution. formulation of the problem to maximise profit in the spot market and its extension to incorporate the risk behaviour of the gencos and the forward contacts for hedging is presented. solution method based on genetic algorithms is implemented in matlab. it is observed through numerical examples that the flexible outputs and the forward contracts can be used to hedge against price risks to achieve desired profit performance according to gencos´ risk behaviour.
Keywords :
genetic algorithms; log normal distribution; power generation dispatch; power generation planning; power generation scheduling; power markets; power system management; pricing; risk analysis; Genco´s short-term generation planning; Gencos´ risk behaviour; MATLAB; bid function; exponential utility function; genetic algorithm; lognormal distribution; power market; price uncertainty management; unit commitment;
fLanguage :
English
Journal_Title :
Generation, Transmission & Distribution, IET
Publisher :
iet
ISSN :
1751-8687
Type :
jour
DOI :
10.1049/iet-gtd:20070177
Filename :
4537143
Link To Document :
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