Spatial-temporal Distribution Prediction of Charging Load for Electric Vehicle based on Dynamic Traffic Flow

Abstract

On the basis of velocity-flow-density relationship and traffic-energy consumption relationship, this paper proposes a prediction method of the spatial and temporal characteristic of electric vehicle charging load using the traffic data. By analyzing the residential travel data, a probability model was built to generate trip chains of a day, which contain destination and start time. Then vehicle transfer model was used to simulate driving vehicles on the roads and SOC could be calculated by the road condition and temperature. Drivers would charge vehicles when SOC is below the charging threshold. Finally, by using the Monte Carlo method, charging load of a real traffic model was calculated according to charging demand from all electric vehicles at different time and location during the area.