Optimal Energy Storage Siting and Capacity Configuration for Rail Transit Self-Consistent Systems Based on Cluster Division

With the expansion of rail transit mileage and the increase in service shifts in China, the demand for electricity has surged sharply, and both the braking power and the regenerative energy fed back into the power grid have grown significantly. In order to fully utilize regenerative braking energy, this paper proposes an energy storage siting and capacity configuration method for a rail transit self-coordinated system based on cluster division. First, a rail transit self-consistent system integrating photovoltaic and energy storage devices is constructed, and the Fast-Newman algorithm is then applied to partition the clusters. With the objective of minimizing the daily comprehensive cost, an optimization model for energy storage siting and capacity configuration is established to determine the optimal location and capacity of the energy storage devices. Case studies demonstrate that the proposed model not only reduces the system’s daily comprehensive cost but also effectively simplifies the planning and configuration process, thereby achieving a green energy supply for the self-coordinated rail transit system.