Application of particle swarm optimization for auction based dispatch in deregulated environment

This paper presents an intuitive solution to the auction based dispatch problem in the deregulated power system based on swarm intelligence optimization. The formulated expressions effectively substitute the seller's bidden cost function in the production cost including market strategy. The auction methodology for maximum thermal capacity of every line of the system is completed using the calculated values of power flows in each line and Locational Marginal Price (LMP). The cost of transmitting a specific amount of electrical power through each line is calculated through auction (in MW) and substituted in the same system to minimize the production cost of generators through particle swarm optimization (PSO) algorithm with satisfying constraints like balance of supply, demand constraint and the capacity limit. Triumph of the developed algorithm is demonstrated using two test systems (3 sellers and 8 sellers). Detailed results such as the cost convergence characteristics, parameter selection for PSO algorithm and sellers contracted demands illustrate the competent performance and merits of the proposed algorithm.