Multi-Objective Optimal Capacity Configuration of PV–ESS–Charging Integrated Systems in Highway Service Areas Based on the VIKOR Criterion

With the rapid growth of electric vehicles, charging demand at highway service areas has increased sharply, while insufficient charging facilities have intensified the mismatch between supply and demand. Existing studies on photovoltaic–energy storage–charging systems mainly focus on urban scenarios and rarely consider the spatiotemporal characteristics of long-distance highway travel. To address this gap, this study proposes a capacity planning method for photovoltaic–energy storage–charging systems in highway service areas. EV charging load is simulated using a Monte Carlo approach considering travel characteristics and state of charge, while an M/M/c queuing model is used to quantify user waiting time. A multi-objective optimization model considering system costs and waiting-time costs is solved using a multi-objective genetic algorithm, and the Pareto solutions are ranked by VIKOR. Under the normal-load scenario, the optimized configuration yields a weighted average waiting time of 5.06 min and reduces the maximum waiting time from 52 min to 11.83 min, with a construction and maintenance cost of RMB 2.5758 million. Under the high-load scenario, the corresponding values are 5.35 min, 12.12 min, and RMB 3.3078 million, respectively. The results show that the proposed method can adapt system capacity to different traffic demand levels while maintaining charging service quality.