With the gradual increase in the application of renewable energy in railroad traction systems, how to rationally configure photovoltaic (PV) and energy storage systems in order to reduce the cost of electricity has become a key issue to be solved. In this paper, a cooperative optimization model of PV and energy storage system based on particle swarm optimization algorithm (PSO) is proposed, aiming to maximize the economic benefits of the system by coordinating PV power generation, lithium battery energy storage and flywheel energy storage. The objective of the model is to minimize the total power cost, including equipment investment, operation and maintenance cost, and grid power purchase cost. The system optimization model was constructed and simulated by analyzing a number of data such as load data, light intensity profiles, and roof area of the two stations. Finally, the simulation results show the configured capacity of the optimized energy storage system, the power curve of each energy source, and the comparison of grid power before and after optimization, which provide a scientific basis for practical application.