Performance Improvement Using GOA-Based Fuzzy-2D-PIDF Controller for AGC of Multi-Area Power System

Automatic generation control (AGC) is an automation scheme that regulates the output of several generators employed at different areas of an interconnected power system simultaneously in response to load variation in the most economical way. This article implements a fuzzy-two degree of freedom-PID controller considering derivative filter (F-2D-PIDF) optimally tuned through grasshopper optimization algorithms (GOA) for AGC of a three unequal area interconnected power system. Initially, comparative performance analysis is carried out for conventional PID controllers optimally designed by particle swarm optimization, teaching learning-based optimization and GOA techniques. After ensuring better performance from GOA based PID controller, the study extended to establish dominance of the proposed F-2D-PIDF controller over others like PID, PID with derivative filter (PIDF), two degree of freedom-PIDF, and fuzzy-PIDF for the same power system in presence and absence of nonlinearities with GOA framework. In all these above studies, a load perturbation of 0.01 p.u. is applied in area-1. Comparative performance analysis reveals that GOA based F-2D-PIDF controller outperforms other controllers in all aspects. Finally, robustness of the proposed controller verified by varying system parameters and loading condition.