Aiming at the problems of the negative sequence governance and regenerative braking energy utilization of electrified railways, a layered compensation optimization strategy considering the power flow of energy storage systems was proposed based on the railway power conditioner. The paper introduces the topology of the energy storage type railway power conditioner, and analyzes its negative sequence compensation and regenerative braking energy utilization mechanism. Considering the influence of equipment capacity and power flow of the energy storage system on railway power conditioner compensation effect, the objective function and constraint conditions of the layered compensation optimization of the energy storage type railway power conditioner were constructed, and the sequential quadratic programming method was used to solve the problem. The feasibility of the proposed strategy is verified by a multi-condition simulation test. The results show that the proposed optimization compensation strategy can realize negative sequence compensation and regenerative braking energy utilization, improve the power factor of traction substations when the system equipment capacity is limited, and it also has good real-time performance.

In order to achieve energy savings and promote on-site integration of photovoltaic energy in electrified railways, a topology structure is proposed for the integration of photovoltaic (PV) and the energy storage system (ESS) into the traction power supply system (TPSS) based on a railway power conditioner (RPC). This paper analyzes the composition and operation principles of this structure. To assess the economic benefits brought by the integration of photovoltaic and energy storage systems, a bilevel optimization model is established, with the objectives of optimizing energy storage capacity configuration and photovoltaic energy integration. The KKT (Karush–Kuhn–Tucker) method is employed to transform the model into a single-layer mixed-integer linear programming model, which is then solved using the CPLEX solver in MATLAB. The research findings indicate that, with the configuration of the ESS, the optimal PV consumption rate achieved is 96.8749%. Compared to a 100% PV consumption rate, the ESS capacity configuration is reduced by 13.14%, and the overall operational cost of the TPSS is at its lowest. The study suggests that the proposed bilevel optimization algorithm can more effectively consider PV consumption, leading to enhanced economic performance of the TPSS operation.