Multiobjective Reactive Power Based on Improved Particle Swarm

This paper presents a multiobjective optimization algorithm based on Particle Swarm Optimizataion.This algorithm renews particles’individual optimization and global optimization by the Pareto dominance relationship,preserves the non-dominated solutions in the searching process by storage pool,cuts non-dominated solutions by clustering argorithm in order to maintain the distribution of solutions,and balances the particles’ local and global search capabilities by dynamic inertia weight.The algorithm has used in the multiobjective reactaive power optimization for the IEEE14 node system.