Research on Orderly Charging optimization of Electric Vehicle Based on Differential Evolution Algorithm

Abstract

Due to the performance characteristics of electric vehicles, there is a lot of room for development in the future. When too many vehicles are connected to the grid at the same time, it will exceed the capacity of the grid, which will damage both the user and the grid, and that needs to be studied and controlled. This article is from the perspective of electric vehicle users, supplemented by the safety of the distribution network, and establishes an objective function for the minimum user charging cost and the minimum grid load peak-valley difference, considering the conditions of initial battery capacity, charging time and grid rated power. It dispatches the charging period selected by users based on time-of-use (TOU) electricity price, adopts a differential evolution algorithm (DE) to optimize the orderly charging, and carries out an example simulation to obtain the orderly charging load curve. The daily random charging state is simulated by the Monte Carlo algorithm, and the disordered charging curve is generated. By comparing the disordered charging curve with the ordered charging curve, the effectiveness of DE in realizing ‘peak cutting and valley filling’ is verified.