Design of Energy-Saving Optimization Algorithm for Power Electronic Devices in Railway Electrification System

With the continuous expansion of the scale of railway electrification systems, the proportion of power electronic devices in energy consumption has increased significantly, and effective energy-saving optimization strategies are urgently needed to improve the overall efficiency of the system. To address this problem, this paper designs an energy-saving optimization scheme based on a hybrid optimization algorithm. First, an energy consumption model of power electronic devices in railway electrification systems is established to accurately describe the energy conversion and loss mechanism of each component. Then, a hybrid optimization algorithm is developed by combining genetic algorithm (GA) and particle swarm optimization algorithm (PSO) to fully utilize the advantages of both in global search and local search. Finally, by introducing a multi-objective optimization method, the energy-saving effect and system stability are balanced to ensure that the various requirements of the optimization process are met. In the experimental conclusion, the optimized configuration saves a total of about 6594.1 kWh of electricity in a 24-hour operation cycle, with an average energy saving of about 270 kWh per hour. In addition, the optimized configuration performs well in terms of system reliability. However, the stability of the optimized configuration in terms of load fluctuation and voltage fluctuation is slightly reduced. In the above conclusions, the proposed hybrid optimization algorithm performs outstandingly in terms of energy saving and reliability, providing effective technical support for the optimization of railway electrification systems. However, further optimization is still needed in terms of system stability.