Research on Adaptive Suppression of LCL Converter Resonance Grid-Connected System

Abstract

LCL-type converters are widely used in grid-connected systems due to their small size and good filtering performance. However, the resonance suppression problem brought by the LCL filter cannot be ignored. The capacitive current feedback is a commonly used resonance suppression method. In applications, the grid impedance can cause LCL filter resonance. Thus, this paper presents an adaptive resonance suppression method based on the RBF network optimized by particle swarm optimization. This method optimizes the initial parameters of the RBF network through particle swarm optimization, identifies the parameters of the PI controller by RBF neural network’s own identification capability, and updates the active damping coefficient based on constraints such as stability margin, thereby realizing the LCL-type inverter to maintain the system stability when the grid impedance changes. The effectiveness of the method is verified by experiments.