Frequency domain parameter estimation of a synchronous generator using bi-objective genetic algorithms

This paper presents a way to obtain parameters of a direct-axis equivalent circuit of a synchronous generator from frequency response data using bi-objective genetic algorithms. The genetic algorithms is capable of finding a global minimum within a given search interval. The sum square error of magnitude and phase of the d-axis equivalent circuit transfer function to formulate a bi-objective optimization problem is minimized to best fit the measured data extracted from the frequency response test of the machine. As a result, exploitation of the bi-objective optimization based on Genetic Algorithms gives very good results than those of using either the magnitude or the phase as a single objective.