The Prediction Model of Electric Vehicle Charging Demand in Cold Regions Considering Environmental Adaptability

Cold environments affect electric vehicle battery performance and hinder charging demand predictions using ordinary models. To improve forecasting accuracy of charging demand in cold regions, this paper constructs a model by analyzing the change of charging demand in low temperatures. The two-part model consists of one represented by electric buses and the other represented by social electric vehicles. Charging demand of electric buses is determined by fixed line and unit mileage power consumption, but charging demand of social electric vehicles is more complicated, making it necessary to consider their travel behavior, users’ charging preference, battery life, and related factors affecting fast and slow charging demand. Monte Carlo method is used to simulate trip and charging decision-making processes of electric vehicles to obtain time-space distribution of charging demand. Results can be superimposed to get the final cold area electric vehicle charging demand forecast. Validity is proved by example analysis.