Optimizing power system stability: A hybrid approach using manta ray foraging and Salp swarm optimization algorithms for electromechanical oscillation mitigation in multi-machine systems

Abstract

This paper emphasizes the significance of ensuring adequate damping of electromechanical oscillations in power systems to ensure stable operation. Power System Stabilizers (PSSs) are influential in enhancing system damping and refining dynamic characteristics during transient conditions. However, the efficacy of PSSs is notably contingent on parameter values, particularly in the case of lead-lag PSSs. In response to this challenge, the paper introduces a Tilt-Integral-Derivative (TID)-based PSS, optimized through a novel optimization algorithm called Hybrid Manta Ray Foraging and Salp Swarm Optimization Algorithms (MRFOSSA). The MRFOSSA algorithm demonstrates robustness and enhanced convergence, validated through benchmark function tests, and outperforms competing algorithms. These superior characteristics of MRFOSSA were employed in optimal tuning of TID-PSSs to uphold the stability of multi-machine power systems. The MRFOSSA algorithm demonstrates robustness and enhanced convergence, outperforms competing algorithms in the optimal tuning of TID-PSS within the Western System Coordinating Council (WSCC)-3-machines 9-bus test system. In summary, the proposed TID-PSS, coupled with the MRFOSSA algorithm, presents a promising avenue for enhancing power system stability.