Research on Subway Harmonic Compensation Control Method Based on SSA Optimized Adaline Algorithm

Abstract

To avoid a large number of harmonics generated by the subway train in the process of operation on the power grid security, the theoretical analysis and simulation experiments on the harmonics of the subway traction power supply system are carried out. Aiming at the problem of severe distortion and fluctuation of network side current at the early stage of train startup, a harmonic analysis and compensation control method based on the Sparrow Search Algorithm (SSA) optimized Adaline Algorithm is proposed, which can be employed to carry out real-time adaptive detection and suppression of harmonics generated by the subway traction power supply system. This method can form a closed-loop training loop with the subway system, and the sparrow search algorithm is used to optimize the initial weight value and learning rate hyperparameters of the Adaline model. Simulation results show that the proposed compensating control can reduce harmonics from 15.12% to 2.89% and the current distortion rate by up to 80.8%. Four error evaluation indexes were used to evaluate the errors before and after the optimization. This method is highly adaptive and can be employed to analyze and compensate system harmonics efficiently.