Frequency control strategy for offshore wind-storage system based on artificial neural network-model predictive control
WU Junjie1, HU Ke2
1. Nanjing Dongbo Smart Energy Research Institute Co., Ltd, Nanjing 210000; 2. School of Electronic Engineering, Nanjing Xiaozhuang University, Nanjing 210000
Abstract：The rapid development of offshore wind power has put forward higher requirements for the frequency stability of the power grid. To improve the frequency regulation performance of offshore wind-storage system, this paper proposes a frequency regulation control strategy based on artificial neural network (ANN)-model predictive control (MPC). Firstly, considering the power characteristics of offshore wind power and energy storage equipment, a frequency control model for wind-storage system is constructed. Then, based on traditional MPC, ANN are used to replace the original rolling optimization process, in order to improve its computational efficiency and control performance. Finally, through simulation examples, the transient frequency fluctuations and response time of the system are optimized by the proposed method, and it still has good control performance under wind power fluctuations, providing a feasible solution for efficient frequency regulation control of offshore wind-storage system.
吴俊杰, 胡可. 基于人工神经网络-模型预测控制的海上风储系统调频控制策略[J]. 电气技术, 2025, 26(12): 24-28.
WU Junjie, HU Ke. Frequency control strategy for offshore wind-storage system based on artificial neural network-model predictive control. Electrical Engineering, 2025, 26(12): 24-28.
2025, Vol. 26 
