Spatio‐Temporal Load Simulation of Integrated Electric Vehicle Charging and Battery Swapping Station

ABSTRACT Traditional load simulation methods are difficult to capture EVs dynamic behaviours. In this paper, a spatio‐temporal load simulation model is proposed for integrated EV charging and battery swapping stations (ICSSs) based on dynamic characteristics of both road traffic and EVs. A dynamic traffic flow model and EV queuing model are developed to characterise EVs route choice, charging decisions and queuing states. By simulating individual EV trajectories, the model captures short time scale dynamics in traffic flow, travel time and EV queuing conditions, rather than relying on steady‐state or purely aggregate assumptions. The proposed method is implemented in MATLAB and tested on an improved 12‐node transportation network using real‐world traffic data. Results show that dynamic traffic conditions significantly affect EV route choice and charging demand distribution. ICSSs charging demand exhibits strong spatial‐temporal heterogeneity. Benchmark comparisons indicate that neglecting station queuing feedback leads to higher EV arrivals and more concentrated local traffic flow. In addition, ICSSs siting has a significant impact on traffic redistribution, while charger deployment creates a clear tradeoff between service quality and infrastructure utilisation. The results show that the traffic flow of the representative branch can be reduced by 48.3% and 62.5% under a more suitable chargers deployment scheme.