| Abstract: |
The growing complexity of modern interconnected power systems has intensified the challenge of damping low-frequency oscillations, necessitating intelligent coordination between Power System Stabilizers (PSS) and Static Synchronous Series Compensators (SSSC). This paper presents an empirical investigation into the intelligent optimization of coordinated PSS–SSSC controller parameters using the Firefly Algorithm (FA). The primary objectives are to optimize PSS–SSSC controller parameters for enhanced oscillation damping and to evaluate FA's superiority over conventional metaheuristic approaches. A simulation-based methodology was adopted using the IEEE two-area four-machine benchmark system modelled in MATLAB/Simulink, where eigenvalue analysis and time-domain simulations were employed under multiple loading conditions. It is hypothesized that FA-based coordinated tuning yields significantly improved damping ratios, reduced settling times, and minimized overshoot compared to Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and uncoordinated designs. Results confirm that the FA-optimized coordinated PSS–SSSC controller achieved a minimum damping ratio of 0.3842, settling time of 3.12 seconds, and overshoot reduction of 38.6% over PSO-based designs. The discussion validates that FA's adaptive light-intensity mechanism ensures superior convergence and global optimality. It is concluded that FA-based PSS–SSSC coordination offers a robust, computationally efficient framework for power system stability enhancement. |
