Load Frequency Control of Power System using Grey Wolf Optimization

Abstract

This article presents an effort to use the gray wolf optimization (GWO) approach to tackle the load frequency control (LFC) issue in an interconnected power system network equipped with a standard PI/PID controller. The suggested method is used to a networked two-area non-reheat thermal-thermal power system. Using a fitness function based on integral time multiplied absolute error (l TAE), the GWO algorithm optimizes the gains of the controller. The suggested GWO algorithm's performance has been compared to other comparable meta-heuristic optimization methods for comparable test systems that are available in the literature, including ensemble of mutation and crossover strategies and parameters in differential evolution (EPSDE), comprehensive learning particle swarm optimization (CLPSO), and others. Moreover, sensitivity analysis is carried out by adjusting the system characteristics and operating circumstances within a -+50% range in order to show the robustness of the suggested GWO method. The findings of the simulation demonstrate that GWO is more capable of tweaking than other comparable population-based optimization methods.