The expansion plan of urban electric vehicle charging stations considering traffic flow

Traditional methods often suffer from three key shortcomings: imprecise traffic flow predictions, inadequate charging station coverage, and prolonged average wait times for charging. To overcome these issues, an expansion plan method of urban electric vehicle charging stations considering traffic flow is proposed. Input urban traffic data into the urban traffic flow prediction model to obtain the prediction results. The objective function of electric vehicle charging station expansion planning was designed with the goal of minimizing costs. After determining the constraints, a charging station expansion planning model was built. The differential evolution-particle swarm optimization algorithm was used to solve the model and obtain the optimal planning solution. Through experiments, it has been proven that the maximum accuracy of the proposed method for predicting traffic flow is 97.68%, the maximum coverage rate of charging station areas is 85.73%, and the minimum average waiting time for charging is 5.69 minutes.