Orderly Charging Strategy for Electric Vehicles Based on Elite Genetic Algorithm

The rapid growth of clean and efficient electric vehicles (EVs) is becoming an important flexibility resource. However, the scale of disorderly charging into the grid poses a challenge to the grid. Therefore, guiding the orderly charging of EVs is crucial to alleviate new energy fluctuations and stabilize grid load. Firstly, this paper establishes the system architecture for orderly charging of EVs. Then, it models the charging behavior of EVs in sub-functional areas and sets up multi-optimization objectives. Finally, it achieves the orderly charging scheduling of EVs through the use of the elite genetic algorithm for solving. The simulation results show that the orderly charging method for EVs proposed in this paper can effectively reduce the net load peakvalley difference rate, improve the new energy consumption rate, and reduce the charging cost; the elite genetic algorithm used has better optimal results and better convergence than the traditional genetic algorithm.