Urban electric vehicle charging station siting method considering road impedance based on improved WOA

The rational layout of urban electric vehicle charging stations (EVCSs) is critical to the operational planning of power systems. Incorporating charging demand into the siting process helps improve deployment rationality. However, existing methods inadequately integrate demand forecasting with siting optimization and often lack effective modeling of actual traffic conditions. To address this issue, this study proposes a siting method that incorporates both charging demand and road impedance. A road network model considering road impedance is first constructed using ArcGIS and open-map platforms to enhance the accuracy of load forecasting. Then, a multi-objective siting model is developed to maximize operator profit while ensuring user satisfaction and high station utilization. Data envelopment analysis (DEA) is introduced to balance these competing objectives. An improved whale optimization algorithm (WOA) is further proposed to solve the model efficiently. A case study based on a region in Lanzhou demonstrates that, compared with methods ignoring road impedance, the proposed approach improves operator profit and user satisfaction by 7.75% and 47.68%, respectively, and achieves a utilization rate of 79.3%, validating its effectiveness in optimizing EVCSs deployment.