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Developing an Optimization Method for Bidding Strategies in an Open Electricity Market

Anagha Bhattacharya 1, Swapan Kr. Goswami 2, and Tanima Kole Bhowmik 3
1. NIT Mizoram EEE Dept., Aizawl, India
2. Jadavpur University EE Dept., Kolkata, India
3. CIEM, ECE Dept., Kolkata, India

Abstract—Deregulation of power sector has highly maximized competition of market by reforming conventionally integrated utility of power into competitive EM. Purpose of this research is to develop an optimization method by combining the genetic algorithm, adaptive metropolis search, particle swarm optimization and differential evolution methods for strategy of optimal bidding in an open electricity market. Maximum profit for power exchange and optimal result has been obtained with minimum convergence with the proposed algorithm. Developed algorithm gives much faster convergence of the optimal result Further the proposed algorithm can be expanded for complicated power system issue of optimization under deregulated environment.

Index Terms—particle swarm optimization, genetic algorithm, adaptive metropolis search, Electricity Market (EM), optimization method

Cite: Anagha Bhattacharya, Swapan Kr. Goswami, and Tanima Kole Bhowmik, "Developing an Optimization Method for Bidding Strategies in an Open Electricity Market," International Journal of Electrical Energy, Vol. 5, No. 1, pp. 71-75, June 2017. doi: 10.18178/ijoee.5.1.71-75

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