Improvement and Implementation of Electric Vehicle Charging Optimization Strategy Based on Multi-body Dynamics

Abstract

The charging time and location of electric vehicles have certain randomness and uncertainty. The disordered charging will bring new challenges to the power grid, affect the stability of the power system, and reduce the power quality. Therefore, it is particularly important to study the charging optimization strategy of electric vehicles. The purpose of this paper is to study the improvement and realization of electric vehicle charging optimization strategy which depends on multi-body dynamics. This paper establishes a charging load model for electric vehicles. Combined with the vehicle travel statistics released by the Transport Development Research Institute, the charge demand of electric vehicles is simulated using the Monte Carlo method. It is found that it is not conducive to the economic and stable operation of the distribution network, and the higher the share of electric vehicles, the more significant the adverse impact. Genetic algorithm is used to solve the optimization model. The peak and valley periods are subdivided by the membership function. The response model of electric vehicle is established through price elasticity matrix, and the optimized peak valley time of use price is finally solved by using genetic algorithm. Finally, the multi-body dynamics model is used for simulation.