Stability Improvement of Sulselrabar System With Integrated Wind Power Plant Using Multi-Band PSS3C Based Mayfly Optimization Algorithm

The introduction of additional controllers is essential in modern electric power systems to enhance their stability, particularly during disturbances. One effective method is the implementation of power system stabilizers (PSS). However, precise coordination of PSS equipment is necessary to determine the optimal locations and parameters. This study focuses on the optimal analysis of Multi-Band PSS3C (MB-PSS3C) coordination in integrated Wind Power Plant (WPP) systems in South, Southeast, and West Sulawesi (Sulselrabar). An artificial intelligence approach, utilizing the Mayfly Optimization Algorithm (MOA), is suggested for optimizing both the location and parameters of the PSS. Comparative investigations were conducted to assess the efficacy of MB-PSS3C in comparison with SB-PSS1A and MB-PSS2B, based on previous research. The performance analysis employed the time domain simulation method, reviewing the speed deviation response, field voltage response, PSS output voltage response, and rotor angle response for each generator. Eigenvalue analysis was performed for each control scheme. Load changes were applied to generators 1 (BAKARU) and 11 (WPP SIDRAP) to evaluate the performance of the system. The application of the MOA-based MB-PSS3C results in an increased damping ratio, improved speed response, and a more optimal rotor angle. MB-PSS3C provides a larger additional damping signal to the generator exciter, as indicated by the increase in the field voltage on the generator.