Path Planning of Mobile Charging Vehicles Based on Improved Discrete Particle Swarm Optimization in Distribution System

Electric vehicles (EVs) are gaining widespread popularity; however, the driving range of vehicles and the coverage of basic charging infrastructure remain unsatisfactory. Mobile charging vehicles (MCVs), as a novel charging method, offer more flexible charging services and also act as energy storage equipment to assist the distribution system in peak frequency regulation. In this paper, an improved discrete particle swarm algorithm is proposed to optimize routes for MCVs. By incorporating the energy consumption model, considering practical application requirements, and comprehensively evaluating energy and time consumption during the dispatching process, it aims to plan energy-efficient and time-saving routes for MCVs. Simulation results demonstrate the effectiveness of the proposed algorithm in solving the path optimization problem in weighted graphs.