A novel chaotic chimp sine cosine algorithm part-II: Automatic generation control of complex power system

Abstract

This is part II of two-paper set deals with the application of the designed algorithm in automatic generation control (AGC) problem of different structures, such as conventional and isolated. The companion paper (i.e., Part I) describes the designed algorithm in detail and shows the validation of the results in support of the proposed algorithm in a systematic manner. The main focus of this study is to apply and validate the algorithm for automatic generation control (AGC) in power systems. Specifically, the algorithm is tested on various AGC models, including a conventional four-area interconnected power system, deregulated power system and an isolated power system model withchange in operating conditions. The employed controller is a proportional-integral-derivative (PID) controller, and its parameters are tuned using the chimp optimization algorithm (CHOA), chaotic chimp optimization algorithm (C-CHOA), and chaotic chimp sine cosine optimization algorithm (C-CHOA-SC).The objective of this study is to assess the effectiveness of the proposed C-CHOA-SC optimization method in tuning the PID controller parameters for AGC in the considered power system models. Through simulations, the study evaluates the performance of the algorithm in terms of AGC efficiency and the ability to maintain dynamic responses within acceptable limits.The simulation results demonstrate that the proposed algorithm outperforms alternative methods in all the tested AGC models. It showcases superior performance while ensuring the desired dynamic response characteristics are maintained.