Abstract

With the popularity of new energy electric vehicles, more and more EV charging stations have appeared in cities. In the face of the intermittent and random access of distributed power sources, it brings problems such as voltage fluctuation and network loss to the distribution network. This paper proposes a configuration method for multi-objective collaborative optimization of dis-tributed power generation under the premise that existing EV charging stations are connected to the distribution network. First, four typical wind-light operating scenarios and EV charging sta-tion working scenarios are constructed based on the K-means clustering algorithm. Secondly, based on the complementary evaluation mechanism to find the best ratio of wind and solar in-stallations, create multi-objective functions from the economic and technical aspects of distributed power planning, and establish the Pareto optimization evaluation mechanism. Finally, based on the IEEE-33 node example, the adaptive hybrid annealing particle swarm algorithm is used to solve the above model, and the Pareto optimal solution set is obtained to verify that the method pro-posed in this paper can reasonably plan the distributed power generation and improve the power quality of the distribution network.