Enhanced Salp Swarm Algorithm for Multimodal Optimization and Fuzzy Based Grid Frequency Controller Design

Abstract

In the present study, an Enhanced SSA (ESSA) has been proposed where the parameter of the SSA technique, which balances the exploration and exploitation phases, has been modified. Additionally, the variable scaling factor is engaged to regulate the salp’s position during the search procedure to minimize the random movement of salps. To demonstrate the effectiveness of the enhanced SSA (ESSA), a set of multimodal test functions are engaged. The statistical outcomes demonstrate that ESSA profits from local optima evasion and quick convergence speed, which aids the proposed ESSA algorithm to outclass the standard SSA and other recent algorithms. The fair analysis displays that ESSA delivers very promising results and outclass current methods. Next, frequency control of power systems is executed by designing a Combined Fuzzy PID (CFPID) controller with the projected ESSA method. Next, a Partially Distributed CFPID (PD-CFPID) controller is designed for a distributed power system (DPS). It is shown that the ESSA method outclasses the SSA method in engineering problems. It is also noted that the ESSA-based PD-CFPID scheme has become more operative in monitoring the frequency than similar structured centralized fuzzy PID (CFPID) as well as PID controller. Finally, the outcomes of the PD-CFPID controller are equated with CFPID and PID for various uncertain situations to validate the benefit of the proposed control approach.