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| 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 |
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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.
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Received: 18 June 2025
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| Cite this article: |
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WU Junjie,HU Ke. Frequency control strategy for offshore wind-storage system based on artificial neural network-model predictive control[J]. Electrical Engineering, 2025, 26(12): 24-28.
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| URL: |
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https://dqjs.cesmedia.cn/EN/Y2025/V26/I12/24
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[1] 胡博, 谢开贵, 邵常政, 等. 双碳目标下新型电力系统风险评述: 特征、指标及评估方法[J]. 电力系统自动化, 2023, 47(5): 1-15.
[2] 李可心, 安军, 石岩, 等. 基于可用调频能量的风电机组综合虚拟惯性控制参数整定[J]. 电工技术学报, 2025, 40(5): 1382-1394.
[3] 黄冬梅, 牟宗凯, 时帅, 等. 考虑复杂海洋状况下的深远海风电场并网系统可靠性评估[J]. 电力科学与技术学报, 2024, 39(6): 174-183.
[4] 杨德健, 王鑫, 严干贵, 等. 计及调频死区的柔性风储联合频率控制策略[J]. 电工技术学报, 2023, 38(17): 4646-4656.
[5] 王威, 谢丽蓉, 张琦, 等. 基于优化赋权模型预测控制的风储协调策略研究[J]. 太阳能学报, 2024, 45(5): 260-266.
[6] 刘传斌, 矫文书, 吴秋伟, 等. 基于模型预测控制的风储联合电场参与电网二次调频策略[J]. 上海交通大学学报, 2024, 58(1): 91-101.
[7] 王育飞, 张文韬, 杨铭诚, 等. 考虑虚拟控制参数调节的风储联合调频优化模型预测控制[J]. 电力系统保护与控制, 2024, 52(16): 37-48.
[8] 谢珍建, 孙文涛, 韩杏宁, 等. 计及海上风电调频能力的新型电力系统频率态势分析[J]. 可再生能源, 2023, 41(9): 1232-1238.
[9] 胡石阳, 刘国荣. 基于虚拟同步机的新能源并网智能控制研究[J]. 电气技术, 2022, 23(10): 10-17.
[10] 王宏东, 邓桂瑶. 基于荷电状态的多储能微电网改进下垂控制策略[J]. 电气技术, 2025, 26(4): 29-36.
[11] ZHANG Yonghui, HUANGFU Yigeng, TAN Bo, et al.A virtual MPC-based artificial neural network controller for PMSM drives in aircraft electric propulsion system[C]//2022 IEEE Industry Appli- cations Society Annual Meeting (IAS), Detroit, MI, USA, 2022. |
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2025, Vol. 26 
