Dynamic coordinated charging strategy and positive effects in regional power system

This paper presents a multi-scale dynamic optimizing method to improve the load characteristics of the regional power system based on the particle swarm optimization (PSO) algorithm. The optimizing strategy is operated as minimizing the peak-valley gap, load variance, and load fluctuation to be objective functions, respectively, and the scale of charging station and the demands of customers to be constraints. The customers´ travel performance is simulated by the stochastic method of probability distribution. And EV loads of coordinated and uncoordinated charging are integrated into a typical regional power system. Further, the results of the three objectives are contrasted. The conclusion shows that the dynamic coordinated charging strategy, especially the one for load gap, takes the most positive effect in characteristics of regional power system load in this dynamic process.