TY - JOUR
T1 - Performance Improvement of Sulselrabar System Using Single-Band Power System Stabilizer Based on Mayfly Algorithm Under Different Loading Condition
AU - Robandi, Imam
AU - Djalal, Muhammad Ruswandi
AU - Prakasa, Mohammad Almas
N1 - Publisher Copyright:
© (2024), (Intelligent Network and Systems Society). All Rights Reserved.
PY - 2024
Y1 - 2024
N2 - This study proposes the application of a single-band power system stabilizer type 1A (SB-PSS1A) to enhance the damping ratio in multimachine systems. The mayfly optimization algorithm (MOA) method is employed to optimize the performance of the SB-PSS1A. The South Sulawesi, Southeast Sulawesi, and West Sulawesi regions of the Sulselrabar system are covered by the proposed control plan. To evaluate the effectiveness of the proposed controller, frequency domain analysis and time domain simulation analysis with varying load changes are presented. The accuracy of the MOA method is compared to the swarm intelligence method based on particle swarm optimization (PSO) and firefly algorithm (FA). The analysis results indicate an improvement in system stability, as demonstrated by an increased damping ratio, reduced oscillation overshoot in generator speed and minimum rotor angle, and faster settling time. By implementing SB-PSS1A on 14 generators using the MOA optimization method, a damping ratio of 0.5868 was achieved.
AB - This study proposes the application of a single-band power system stabilizer type 1A (SB-PSS1A) to enhance the damping ratio in multimachine systems. The mayfly optimization algorithm (MOA) method is employed to optimize the performance of the SB-PSS1A. The South Sulawesi, Southeast Sulawesi, and West Sulawesi regions of the Sulselrabar system are covered by the proposed control plan. To evaluate the effectiveness of the proposed controller, frequency domain analysis and time domain simulation analysis with varying load changes are presented. The accuracy of the MOA method is compared to the swarm intelligence method based on particle swarm optimization (PSO) and firefly algorithm (FA). The analysis results indicate an improvement in system stability, as demonstrated by an increased damping ratio, reduced oscillation overshoot in generator speed and minimum rotor angle, and faster settling time. By implementing SB-PSS1A on 14 generators using the MOA optimization method, a damping ratio of 0.5868 was achieved.
KW - Damping
KW - Mayfly optimization algorithm
KW - Overshoot
KW - SB-PSS1A
KW - Sulselrabar
UR - http://www.scopus.com/inward/record.url?scp=85184173997&partnerID=8YFLogxK
U2 - 10.22266/ijies2024.0229.33
DO - 10.22266/ijies2024.0229.33
M3 - Article
AN - SCOPUS:85184173997
SN - 2185-310X
VL - 17
SP - 370
EP - 382
JO - International Journal of Intelligent Engineering and Systems
JF - International Journal of Intelligent Engineering and Systems
IS - 1
ER -