A Dynamic Traffic Flow-Based Simulation Method for Charging Demands of EVs Considering Various Uncertainties

With the large-scale application of electric vehicles (EVs), the stable operation of power grid is significantly affected by the increasing of uneven charging demand distribution. Considering the real-world traffic conditions under time-varying multiple uncertainties, this paper proposes a dynamic traffic flow charging load simulation method to analyze the variable charging demands. First, the characteristics of multiple uncertainties are depicted by the probability models, including the link capacity, travel demand and EV operation states. Then, the dynamic traffic flow assignment problem under multiple uncertainties is established by considering the congestion effect of EVs. The optimal path generation model is used to construct the available path sets. Finally, the effectiveness of the proposed method is verified by the simulation results in case studies.