Parameter Identification of a PMSG Using a PSO Algorithm Based on Experimental Tests

Abstract

An accurate model for a permanent magnet synchronous generator (PMSG) is important for the design of a high-performance PMSG control system. The performance of such control systems is influenced by PMSG parameter variations under real operation conditions. In this paper, the electrical parameters of a PMSG (the phase resistance, the phase inductance and the rotor permanent magnet (PM) flux linkage) are identified by a particle swarm optimisation (PSO) algorithm based on experimental tests. The advantages of adopting the PSO algorithm in this research include easy implementation, a high computational efficiency and stable convergence characteristics. For PMSG parameter identification, the normalised root mean square error (NRMSE) between the measured and simulated data is calculated and minimised using PSO.

Keywords

• Parameter identification
• permanent magnet synchronous generator (PMSG)
• particle swarm optimisation (PSO)
• modelling
• dSPACE