A Fuzzy Bilevel Model and a PSO-Based Algorithm for Day-Ahead Electricity Market Strategy Making

Authors:
Guangquan Zhang;Guoli Zhang;Ya Gao;Jie Lu
Affiliations:
Faculty of Engineering & Information Technology, University of Technology, Sydney, Australia 2007;Department of Mathematics and Physics, North China Electric Power University, Baoding, Hebei, P.R. China 071003;Faculty of Engineering & Information Technology, University of Technology, Sydney, Australia 2007;Faculty of Engineering & Information Technology, University of Technology, Sydney, Australia 2007
Venue:
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part II
Year:
2009

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Abstract

This paper applies bilevel optimization techniques and fuzzy set theory to model and support bidding strategy making in electricity markets. By analyzing the strategic bidding behavior of generating companies, we build up a fuzzy bilevel optimization model for day-ahead electricity market strategy making. In this model, each generating company chooses the bids to maximize the individual profit. A market operator solves an optimization problem based on the minimization purchase electricity fare to determine the output power for each unit and uniform marginal price. Then, a particle swarm optimization (PSO)-based algorithm is developed for solving problems defined by this model.