Multi objective optimization of microgrid based on Improved Multi-objective Particle Swarm Optimization

Abstract

In this paper, a multi-objective optimization mathematical model is established based on the comprehensive consideration of economy, environment and battery circulating power in the process of microgrid dispatching. Aiming at the shortcomings of the traditional multi-objective particle swarm optimization (MOPSO), this paper proposes a multi-objective particle swarm optimization algorithm based on fuzzy clustering (FCMOPSO), which introduces fuzzy clustering analysis in the iterative process to find the optimal cluster solution of each generation. Compared with MOPSO, FCMOPSO enhances the stability and global search ability of the algorithm, and makes the Pareto front distribution more uniform in the optimization results. After obtaining the Pareto optimal solution set, according to the importance of each target, the fuzzy model identification is used to find the optimal scheme under different conditions from the optimal solution set.