Aggregation Model-Based Optimization for Electric Vehicle Charging Strategy

This paper presents an aggregation charging model for large numbers of electric vehicles (EVs). A genetic algorithm (GA) is employed to obtain the stochastic feature parameters of the aggregation model, and a charging strategy based on the aggregation model is developed to reduce the power fluctuation level caused by EV charging. In addition, an updatable optimization method is proposed to track the variation of the EV charging characteristics. The proposed charging strategy and optimization method are validated by the simulation results.