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