A novel Multi-objective Fuzzy Adaptive Chaotic PSO algorithm for Optimal Operation Management of distribution network with regard to fuel cell power plants

摘要

A new Multi-objective Fuzzy Adaptive Chaotic particle swarm optimization (MFACPSO) evolutionarynalgorithm for the Multi-objective daily Optimal Operation Management (MOOM) problem with regard tonfuel cell power plants (FCPPs) in distribution system is presented in this paper. The purposes of the MOOMnproblem are to minimize the total electrical energy losses, the total electrical energy cost, and the totalnpollutant emission produced by sources. Conventional algorithms for solving the multi-objective optimizationnproblems convert the multiple objectives into a single objective using a vector of the user-predefinednweights. This conversion has several defects. For instance, the final solution of the algorithms greatlyndepends on the values of the weights and it also loses some information in the conversion and this strategy isnnot expected to provide a robust solution. The proposed algorithm maintains a finite-sized repository of nondominatednsolutions which gets iteratively updated in the presence of new solutions. Since the objectivenfunctions are non-commensurable, a fuzzy clustering technique is used to control the size of the repositorynwithin the limits. The proposed algorithm is tested on two distribution test feeders and the resultsndemonstrate the capabilities of the proposed approach to generate a set of well-distributed Pareto-optimalnnon-dominated solutions of the MOOM problem. The comparison with the different reported techniquesndemonstrates the superiority of the proposed MFACPSO in terms of the diversity of the Pareto-optimalnsolutions obtained. In addition, the results confirm the potential of the proposed technique to solve thenMOOMproblem and produce high-quality non-dominated solutions. Copyright#2010 JohnWiley&Sons,nLtd.