Scenario-based sizing and siting of battery swapping stations for electric buses using realistic demand modeling on distribution network

Large-scale electrification of public transport using battery swapping stations (BSS) has major implications for the stability of distribution networks due to high-power charging loads. In this regard, this paper presents a new comprehensive planning framework that minimizes the load smoothing index (SI). The proposed approach addresses the optimal design and operation of BSS for electric buses (EBs), in particular by determining the optimal location, minimum storage battery capacity, and smart charging schedule. The method is performed in three innovative steps. First, a high-fidelity physics-based simulation is performed that integrates the technical specifications of EBs, stochastic operating schedules, and a physical energy consumption model to generate realistic battery swapping demands for the EB fleet under three distinct battery capacity scenarios (150, 200, and 250 kWh). Second, the optimal number of storage batteries required for uninterrupted service is determined. Third, a hybrid metaheuristic optimization algorithm is employed to identify the optimal 24-h charging schedule that smoothes the load curve of the entire network. Finally, the technical feasibility of this solution is validated by applying the optimized BSS load to the IEEE 69-nodes standard test system. The results show that the proposed method is very effective at reducing network stress, lowering the SI from a maximum of 1.59 (in the uncoordinated case) to an optimal value of about 1.13. This research provides a robust model for transforming BSS into a strategic asset for network load management.