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• [P1030] A Bilevel Optimization Model and a PSO-based Algorithm in Day-ahead Electricity Markets
  Author(s): Guangquan Zhang, Jie Lu, Ya Gao, Guoli Zhang
  
  

  Abstract
  Strategic bidding problem is becoming a key issue 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 developed and implemented. Experiment results have demonstrated the validity of the PSO-based algorithm in solving the competitive strategic bidding problems for the day-ahead electricity market.

  
   

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