TY - GEN
T1 - Improving the Frequency Response of Microgrid Using GA-Optimized PI Controllers
AU - Sihombing, Sandi
AU - Fitri, Ismi Rosyiana
AU - Husnayain, Faiz
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The addition of sources of clean electricity, such as wind, photovoltaic (PV), even hydroelectric power, is posing issues for frequency regulation in electrical grids. The intermittent nature of environmental factors like wind and sunlight introduces uncertainty in renewable energy generation, intensifying frequency management challenges as wind and PV penetration increases. To address these issues, advanced control strategies are essential for managing power system operations under diverse conditions. This study proposes using a Genetic Algorithm (GA) for optimizing the Proportional-Integral (PI) controllers, enhancing frequency stability, particularly under fault conditions. The approach seeks to reduce the Integral of Time Absolute Error (ITAE) to identify the ideal parameters for the controller used for the PI. Numerical simulations are used to validate the proposed method and show that the optimization approach improves the performance of the Load Frequency Control (LFC).
AB - The addition of sources of clean electricity, such as wind, photovoltaic (PV), even hydroelectric power, is posing issues for frequency regulation in electrical grids. The intermittent nature of environmental factors like wind and sunlight introduces uncertainty in renewable energy generation, intensifying frequency management challenges as wind and PV penetration increases. To address these issues, advanced control strategies are essential for managing power system operations under diverse conditions. This study proposes using a Genetic Algorithm (GA) for optimizing the Proportional-Integral (PI) controllers, enhancing frequency stability, particularly under fault conditions. The approach seeks to reduce the Integral of Time Absolute Error (ITAE) to identify the ideal parameters for the controller used for the PI. Numerical simulations are used to validate the proposed method and show that the optimization approach improves the performance of the Load Frequency Control (LFC).
KW - Frequency Control
KW - Genetic Algorithm (GA)
KW - PI controller optimization
KW - Power system stability
KW - Renewable Energy Integration
UR - http://www.scopus.com/inward/record.url?scp=105004408947&partnerID=8YFLogxK
U2 - 10.1109/ISRITI64779.2024.10963497
DO - 10.1109/ISRITI64779.2024.10963497
M3 - Conference contribution
AN - SCOPUS:105004408947
T3 - 7th International Seminar on Research of Information Technology and Intelligent Systems: Advanced Intelligent Systems in Contemporary Society, ISRITI 2024 - Proceedings
SP - 329
EP - 333
BT - 7th International Seminar on Research of Information Technology and Intelligent Systems
A2 - Wibowo, Ferry Wahyu
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2024
Y2 - 11 December 2024
ER -
