Optimization of Electric Vehicle Charging and Swapping Loads Based on Dynamic Time-of-Use Electricity Pricing Guidance Strategy

The rapid growth of electric vehicles (EVs) has increased power grid pressure due to stochastic charging loads, often coinciding with peak residential demand. This paper proposes an optimization method for EV charging and swapping loads using dynamic time-of-use electricity pricing, emphasizing battery swapping stations. Models for user travel, EV charging, and battery swapping are established to analyze the adverse effects of uncoordinated charging. Using the Particle Swarm Optimization (PSO) algorithm, the method optimizes charging loads, highlighting the advantages of integrated charging-swapping stations. Simulation results show reduced peak-to-valley differences, improved load utilization, and lower charging costs, promoting EV market growth.