TY - GEN
T1 - Analysis of the performance of PID-based new-generation metaheuristic algorithms for automatic voltage regulation system
AU - Oladipo, Stephen
AU - Sun, Yanxia
N1 - Publisher Copyright:
© 2023 Owner/Author.
PY - 2023/12/8
Y1 - 2023/12/8
N2 - In recent decades, the expansion of industrial organizations in both scale and scope has necessitated dependable output voltage supplies. However, persistent oscillations in electromechanical devices can impede power efficiency and stability, underscoring the importance of reliable automatic generation regulation (AVR) systems and power system design in the manufacturing sector. To address this issue, this study presents a performance analysis of a proportional integral derivative (PID) controller based on new-generation metaheuristic algorithms (MAs) for the AVR system. Five recent and novel MAs were employed to optimize the PID controller for the AVR system, with the controllers' performances evaluated under five distinct performance metrics. The findings revealed that the Northern Goshawk Optimization (NGO) algorithm was the most effective optimization approach, exhibiting the lowest values of overshoot (33.2784%), peak time (0.2120 s), and objective value (0.0077). These results suggest that the NGO algorithm is a promising optimization method for improving AVR system performance in industrial settings.
AB - In recent decades, the expansion of industrial organizations in both scale and scope has necessitated dependable output voltage supplies. However, persistent oscillations in electromechanical devices can impede power efficiency and stability, underscoring the importance of reliable automatic generation regulation (AVR) systems and power system design in the manufacturing sector. To address this issue, this study presents a performance analysis of a proportional integral derivative (PID) controller based on new-generation metaheuristic algorithms (MAs) for the AVR system. Five recent and novel MAs were employed to optimize the PID controller for the AVR system, with the controllers' performances evaluated under five distinct performance metrics. The findings revealed that the Northern Goshawk Optimization (NGO) algorithm was the most effective optimization approach, exhibiting the lowest values of overshoot (33.2784%), peak time (0.2120 s), and objective value (0.0077). These results suggest that the NGO algorithm is a promising optimization method for improving AVR system performance in industrial settings.
KW - algorithm
KW - Automatic voltage regulation system
KW - metaheuristic
KW - northern goshawk optimization
KW - proportional integral derivative
UR - http://www.scopus.com/inward/record.url?scp=85188289116&partnerID=8YFLogxK
U2 - 10.1145/3638584.3638622
DO - 10.1145/3638584.3638622
M3 - Conference contribution
AN - SCOPUS:85188289116
T3 - ACM International Conference Proceeding Series
SP - 449
EP - 454
BT - CSAI 2023 - 2023 7th International Conference on Computer Science and Artificial Intelligence
PB - Association for Computing Machinery
T2 - 7th International Conference on Computer Science and Artificial Intelligence, CSAI 2023
Y2 - 8 December 2023 through 10 December 2023
ER -