Artificial Gorilla Troops Optimizer for Optimum Tuning of TID Based Power System Stabilizer

Abstract

The artificial gorilla troops optimization (GTO) is a recently-introduced metaheuristic optimization technique for non-linear, non-convex and non-smooth problems with multiple types of variables. This algorithm, which is a nature-based technique, has been inspired by the social intelligence of gorilla troops. This study delves into how optimal can a power system stabilizer (PSS) unit be tuned incorporating GTO algorithm. The Integral Time Square Error (ITSE) was utilized as a fitness function, which desirably should be minimized. Four different controllers are employed to investigate the model of a single-machine scheme as a model for the infinite bus. The tilt-integral-derivative (TID) shows a better performance response in comparison with the PID controller, lead-lag controller, as well as fractional-order PID controller (FOPID) investigated. The results have implied that the GTO algorithm has obtained faster convergence over the other compared optimization techniques, while it has superiority in not trapping in local optimum points. It has shown also a high level of precision.