DocumentCode :
2577205
Title :
A bilevel optimization model and a PSO-based algorithm in day-ahead electricity markets
Author :
Zhang, Guoli ; Zhang, Guangquan ; Gao, Ya ; Lu, Jie
Author_Institution :
Dept. of Math. & Phys., North China Electr. Power Univ., Baoding, China
fYear :
2009
fDate :
11-14 Oct. 2009
Firstpage :
611
Lastpage :
616
Abstract :
Strategic bidding problems are becoming key issues in competitive electricity markets. This paper applies bilevel optimization theory to deal with this issue. We first analyze generating company strategic bidding behaviors and build a bilevel optimization model for a day-ahead electricity market. In this bilevel optimization model, each generating company will choose their bids in order to maximize their individual profits. A market operator will determine the output power for each unit and uniform marginal price based on the minimization purchase electricity fare. For solving this competitive strategic bidding problem described by the bilevel optimization model, a particle swarm optimization (PSO)-based algorithm is. Experiment results have demonstrated the validity of the PSO-based algorithm in solving the competitive strategic bidding problems for a day-ahead electricity market.
Keywords :
particle swarm optimisation; power markets; pricing; bilevel optimization model; competitive electricity markets; day-ahead electricity markets; minimization purchase electricity fare; particle swarm algorithm; strategic bidding problems; uniform marginal price; Constraint optimization; Cybernetics; Electricity supply industry; Energy management; Mathematical model; Nash equilibrium; Particle swarm optimization; Power generation; Power system modeling; USA Councils; bilevel programming; electricity market; optimization; particle swarm algorithm; strategic bidding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
ISSN :
1062-922X
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
Type :
conf
DOI :
10.1109/ICSMC.2009.5346635
Filename :
5346635
Link To Document :
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