Stability Improvement of Sulbagsel Electricity System Integrated Wind Power Plant Using SVC-PSS3C Based on Improved Mayfly Algorithm

This study thoroughly investigates the enhancement of power system stability through the coordinated design of Static VAR Compensator (SVC) and Multi-Band Power System Stabilizer type 3C (MB-PSS3C). An Improved Mayfly Algorithm (IMA) is employed to optimize the placement and tuning of SVC and MB-PSS3C within the Southern Sulawesi (Sulbagsel) integrated Wind Power Plant (WPP) electricity system. Mayfly intelligence is inspired by the mating and flight behaviors of adult mayflies. In its standard form, this algorithm cannot be applied to high-dimensional, nonlinear, and complex space problems. This study proposes an Exponent Decreasing Inertia Weight (EDIW) strategy to enhance the performance of the standard Mayfly Algorithm (MA). The IMA demonstrates superior performance compared to other methods, achieving a minimum fitness function value of 80.0582 and converging rapidly by 8th iteration. For SVC, the optimization analysis involved reviewing the voltage profile at each bus and analyzing Optimal Power Flow (OPF). For MB-PSS3C, the optimization focused on evaluating system stability through damping analysis, time-domain simulations, and eigenvalue visualization. The application of IMA-based SVC improved reactive power management in transmission systems, resulting in enhanced voltage profiles, OPF, and reduced transmission losses. Specifically, transmission losses decreased by 3.12% in the normal system case study and by 2.88% in the N-1 contingency case study. Meanwhile, the IMA-based MB-PSS3C enhanced system stability by increasing system damping, reducing generator oscillation overshoot, and improving system eigenvalues. The implementation of MB-PSS3C using IMA across 14 generators achieved the highest damping ratio of 0.7375, compared to 0.7274 for MB-PSS3C with MA.