NSGA-II-based load resource management for frequency and voltage support[J]. 全球能源互联网(英文), 2025,8(2).
Yaxin Wang, Zhihang Zhu, Zhihong Yu, et al. NSGA-II-based load resource management for frequency and voltage support[J]. Global energy interconnection, 2025, 8(2).
NSGA-II-based load resource management for frequency and voltage support[J]. 全球能源互联网(英文), 2025,8(2). DOI: 10.1016/j.gloei.2025.01.005.
Yaxin Wang, Zhihang Zhu, Zhihong Yu, et al. NSGA-II-based load resource management for frequency and voltage support[J]. Global energy interconnection, 2025, 8(2). DOI: 10.1016/j.gloei.2025.01.005.
NSGA-II-based load resource management for frequency and voltage support
Ensuring stable frequency and voltage has recently become increasingly challenging for modern power systems.This is primarily due to the fluctuating and intermittent nature of renewable energy sources and the uncertain electricity demand.To address these issues
this study proposes a load resource management (LRM) method to cope with the sudden power disturbances.The LRM method supports primary frequency and voltage regulation
and its integration with network dynamics minimizes the established disutility function caused by load participation.For better control performance
a non-dominated sorting genetic algorithm-II(NSGA-II)-based gain-tuning procedure was utilized for LRM
aiming to enhance the frequency/voltage nadir
reduce the frequency/voltage steady-state error
and minimize the total load control efforts.To validate the effectiveness of the proposed approach
comparative experiments were conducted with three load-resource management technologies for primary regulation auxiliary services in MATLAB/Simulink.Compared to the conventional optimal load control or using LRM alone
the improved NSGA-II-based LRM demonstrates superior performance.It achieves better frequency response