Bidding Strategy Considering Risk by Generating Companies in an Open Electricity Market Using Particle Swarm Optimization

K. Edukondalu; D. M. Vinod Kumar; J. Vijaya Kumar
This paper presents a novel methodology based on Particle Swarm Optimization (PSO) for the preparation of optimal bidding strategies by power suppliers in a competitive electricity market. The gaming by participants in a competitive electricity market causes electricity market more an oligopoly than a competitive market. In general, Competition implies the opportunities for Generation Companies (Gencos) to get more profit and, in the mean time, the risk of not being dispatched. In this paper each participant can increase their own profit by optimally selecting the bidding parameters using PSO. The proposed method is numerically verified through computer simulations on IEEE 30-bus system consist of six suppliers and two large consumers. The results are compared with Genetic Algorithm (GA) and Monte Carlo method. The Test results indicate that the proposed algorithm maximize profit, converge much faster and more reliable than GA and Monte Carlo method.
Market Clearing Price; Optimal Bidding Strategy; Fuzzy Inference; Risk Analysis; Particle Swarm Optimization
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