Prediction of Electric Vehicle Charging Load Considering Climatic Factors under Faults

A load prediction method for electric vehicles(EV) considering climatic factors under fault is proposed. Firstly, establishing a road network model, and a road network coupling model based on graph theory is constructed. Secondly, the EV is divided into three categories: private car, taxi and public car. Introducing Dijkstra algorithm to determine the starting and ending points and driving paths of EVs. On this basis, the driving process and charging behavior model are established respectively. Then, correction of EV charging load based on user psychology, and the queuing time and the’ mileage anxiety ’ efficiency in the case of failure are comprehensively considered to establish a multi-source information EV charging load forecasting framework. Finally, the simulation analysis obtained the spatiotemporal distribution of EV charging load, verifying the effectiveness of the proposed method.