Research on EV Charging Scheduling Strategy Based on Multi-objective Optimization

The charging behavior of electric vehicles is random, and a large number of unordered charging loads will have a great impact on the planning and operation of the power grid. This paper analyzes the influence of electric vehicles on regional load under different access rates. Then, the optimal charging strategy is adopted to optimize the initial charging time as the control quantity, the minimum load fluctuation and the minimum distribution cost, and the optimal solution is obtained by using the multi-strategy improved artificial bee colony algorithm. In this paper, the load of a certain region is taken as an example, and the results show that the mode of unordered charging of electric vehicles will increase the regional load fluctuation. However, the control strategy proposed in this paper based on the improved artificial bee colony algorithm to optimize the charging time of electric vehicles has achieved good results, among which, it can effectively reduce the fluctuation of power grid load and reduce the maximum value while meeting the needs of users. The example proves that the proposed method can save 50 yuan and the maximum load fluctuation range can be reduced to less than 15% in distribution optimization cost.