Optimized Siting and Sizing of Urban Fast-Charging Stations with Land-Use Constraints Using Spatiotemporal PSO

The rapid popularity of electric vehicles (EVs) has exacerbated the unbalanced layout of fast charging stations (FCS) due to insufficient planning frameworks. Existing optimization models often overlook critical real-world constraints such as land use restrictions and spatiotemporal demand fluctuations, leading to suboptimal resource allocation. This study develops a comprehensive FCS layout model that minimizes total social costs while integrating practical land use considerations. The model employs the Analytic Hierarchy Process (AHP) to weight five key cost components: construction, operation, user electricity expenses, waiting time, and travel time. Queuing theory (M/M/k model) determines optimal charging capacity, while an improved Particle Swarm Optimization (PSO) algorithm solves the location problem. Voronoi diagrams visualize service area divisions. Applied to Nantong Economic Development Zone, the model identifies 6 optimal FCS locations with 20–35 charging piles each, balancing charging demand and cost efficiency. This framework provides actionable insights for urban EV infrastructure planning.