Differential evolution algorithm based on PCA to determine the objective function to optimize the configuration of microgrid

Recently, microgrids are increasingly used in our lives. The purpose of this paper is to solve the uncertainties of multi-objective decision-making and the instability of algorithms in the optimal configuration of traditional microgrids. This paper proposed a differential evolution algorithm based on PCA to determine the objective function. Firstly, a multi-objective optimization model of the micro-grid was established on the basis of fully considering the economy, environmental protection and stability of the micro-grid. Next, the first principal component of the multi-objective was extracted based on PCA combining innovatively the Pareto optimal solution set, and the multi-objective optimization problem was transformed into a single-objective optimization problem. Finally, the experimental simulation result shows that the algorithm proposed in this paper can comprehensively consider the economy, environmental protection and stability of the microgrid on the basis of ensuring the efficiency and stability of the algorithm to realize the optimized configuration of the microgrid.