A PSO-Based Approach for Parameter Estimation in Synchronous Machines

Abstract

This study employs the particle swarm optimization (PSO) approach using Stand Still Frequency Responses Testing (SSFR) to identify the time constants (poles and zeros) of the operational inductances along the d and q axes, as well as the parameters of the equivalent circuits for the SSFR1, SSFR2, and SSFR3 synchronous machine models. The difference between the frequency responses of the identified and simulated models at a standstill is minimized using a quadratic criterion in this method. The SSFR3 model accurately represents the synchronous machine, and simulation results show that the PSO approach is effective in terms of convergence rate and offers ideal solutions.