Optimal bidding strategies for gencos in day ahead power market using pso based hybrid algorithms

Abstract

The main objective of this research is to develop improved newlinestochastic techniques namely Cauchy Mutated Memetic Particle Swarm newlineOptimization CMMPSO and MultiObjective Particle Swarm Optimization newlineDynamic Crowding Distance MOPSODCD for solving various scheduling newlineproblems faced by the Generator Companies Gencos in a dayahead newlinederegulated market newlineThe popularity of Particle Swarm Optimization PSO is due to its newlinesignificant property of dealing with optimization problems without any newlinerestrictions on the structure or type of the function to be optimized and due to newlinethe ease of computation However the critical drawbacks of the PSO are the newlinepremature convergence and high computation time required to obtain the newlinenear global optimum Thus an amendment in the classical PSO technique is newlineincorporated using Cauchy Mutation CM and local search for obtaining a newlinefaster but not premature convergence This improved technique is pertinently newlinetermed as CMMPSO newline newline