Modified Hybrid Grey Wolf-Cuckoo Search Algorithm for Optimum Tuning of the PI Controller for Controlling the Transients of the Doubly-Fed Induction Generator

Abstract

Double-fed induction generators play an important role in the wind energy sector due to their ability to operate at variable speeds, superior efficiency, and compatibility with the grid. The optimal controller design for a doubly-fed induction generator ensures efficient power conversion, stable operation, and fault tolerance in wind turbines. To maintain stability and control active and reactive power, this article suggests the design of a PI controller. This article suggests the design of a new PI controller to control the stability and active and reactive power of a doubly-fed induction generator. The PI controller gains are tuned in such a way that they control the operation of the doubly-fed induction generator. PI controller parameter tuning is done by a novel modified hybrid grey wolf cuckoo search algorithm. Furthermore, this work applied a modified Grey Wolf Cuckoo search algorithm for the tuning of PI controller parameters. In this work, the proposed controller has been tested for a 2 MW DFIG wind power system. The results obtained from the proposed controller are compared with the results of the Jaya optimization and Whale optimization algorithms. The results show that the proposed method tuned PI controller parameters accurately, hence improving the stability and efficiency of the DFIG model.