Parameter Identification of Permanent-Magnetic Synchronous Generator -Wind Turbine based on Particle Swarm Optimization

This paper presents a parameter identification method for the permanent-magnetic synchronous generator (PSMG)-wind turbines based on particle swarm optimization. The method utilizes the particle swarm algorithm to approximate the actual equipment’s frequency response characteristics, requiring only disturbance application and output measurement at the point of common coupling (PCC) for parameter identification. Firstly, the operational principles and mathematical models of the PMSG-wind turbines are analyzed. Corresponding transfer functions are established to analyze their frequency response characteristics. Building upon this analysis, an optimization model for parameter identification of the PMSG-wind turbines is constructed. Furthermore, a parameter identification method based on the particle swarm algorithm is proposed. Simulation results demonstrate the maximum error of proposed method is not more than 2.6%.