Eigenvalues Optimization Method of Low Frequency Oscillation for Multi-machine System based on Genetic Algorithm

Abstract

This paper presents a method that simultaneously tunes the control parameters using genetic algorithms (GAs) to optimize the eigenvalues of multi-machine system, thereby achieving the effect of suppressing low frequency oscillation of the system. Due to the complexity and scale of the multi-machine system, it is necessary to rationally and efficiently optimize the algorithm for the parameter setting of this grid. In this article, the method of adjusting the population size and mutation rate and adopting several improved eigenvalues optimization objective functions is proposed to improve the performance of the genetic algorithm. These improvement measures are applied for control parameters tuning to the modified IEEE-39 system that contains DFIG-based wind farms and energy storage devices. The optimization results show that the efficiency and convergence of the genetic algorithm have indeed improved.