无模型自适应控制在海上漂浮风电机组中的实现与优化

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振动与冲击 ›› 2025, Vol. 44 ›› Issue (13) : 131-138.

振动理论与交叉研究

无模型自适应控制在海上漂浮风电机组中的实现与优化

袁嘉旺 1, 2, 何山*1, 2, 杜新 3

作者信息 +

Implementation and optimization of model-free adaptive control in offshore floating wind turbines

YUAN Jiawang1,2, HE Shan*1,2, DU Xin3

Author information +

文章历史 +

摘要

随着风电机组叶片尺寸的不断增大，非对称载荷逐渐成为影响风电机组运行稳定性和安全性的关键因素。非对称载荷具有周期性特征，长期运行中可能引起部件的反复疲劳，进而增加维护成本，甚至可能导致部件损坏或风机倾覆的风险。针对这一挑战，本研究提出了一种基于贝叶斯优化的无模型自适应独立变桨距控制方法，通过高斯过程模型捕捉目标函数与控制参数之间的关系，实现对控制器参数的优化，利用风机仿真软件FAST软件对15MW海上风电机组的模拟评估，表明该方法能够有效缓解非对称载荷引起的周期性振动，并显著减少载荷波动，提高风电机组的运行稳定性和安全性，降低维护成本。

Abstract

As the size of wind turbine blades continues to increase, asymmetric loads have gradually become a key factor affecting the operational stability and safety of wind turbines. These asymmetric loads exhibit periodic characteristics, and over long-term operation, they can lead to repeated fatigue of components, increasing maintenance costs and potentially causing component failure or even turbine overturning. To address this challenge, this study proposes a model-free adaptive independent pitch control method based on Bayesian optimization. By using a Gaussian process model, the relationship between the objective function and control parameters is captured, enabling the optimization of controller parameters. Simulations using the FAST software on a 15 MW offshore wind turbine indicate that this method can effectively mitigate the periodic vibrations induced by asymmetric loads, significantly reduce load fluctuations, enhance the operational stability and safety of the wind turbine, and lower maintenance costs.

导出引用

袁嘉旺 1, 2, 何山 1, 2, 杜新 3. 无模型自适应控制在海上漂浮风电机组中的实现与优化[J]. 振动与冲击, 2025, 44(13): 131-138

YUAN Jiawang1, 2, HE Shan1, 2, DU Xin3. Implementation and optimization of model-free adaptive control in offshore floating wind turbines[J]. Journal of Vibration and Shock, 2025, 44(13): 131-138

参考文献

[1] 王同光, 田琳琳, 钟伟, 等. 风能利用中的空气动力学研究进展 Ⅰ: 风力机气动特性[J]. 空气动力学学报, 2022, 40(4): 1-21.
Wang Tongguang, Tian Linlin, Zhong Wei, et al. Advances in Aerodynamic Research in Wind Energy Utilization I: Aerodynamic Characteristics of Wind Turbines [J]. Acta Aerodynamica Sinica, 2022, 40(4): 1-21.
[2] 程建东,赵浩然,韩明哲.市场机制下推动风电参与电力市场的实践总结与启示[J].电网技术, 2022(007):046.
Cheng Jiandong, Zhao Haoran, Han Mingzhe. Practice Summary and Insights on Promoting Wind Power Participation in the Electricity Market under Market Mechanisms [J]. Power System Technology, 2022(007):046.
[3] Li H, Soares C G. Assessment of failure rates and reliability of floating offshore wind turbines[J]. Reliability Engineering & System Safety, 2022, 228: 108777.
[4] Jahani K, Langlois R G, Afagh F F. Structural dynamics of offshore Wind Turbines: A review[J]. Ocean Engineering, 2022, 251: 111136.
[5] 王诗琪, 杜雪松, 朱才朝, 等. 海上浮式风电机组变桨距自抗扰控制策略研究[J]. 重庆大学学报, 2022, 45(10): 25-37.
Wang Shiqi, Du Xuesong, Zhu Caichao, et al. Research on Active Disturbance Rejection Control Strategy for Pitch Regulation of Offshore Floating Wind Turbines [J]. Journal of Chongqing University, 2022, 45(10): 25-37.
[6] 余万, 丁勤卫, **春, 等. 海上浮式风力机变桨距控制研究[J]. 太阳能学报, 2021, 42(1): 143.
Yu Wan, Ding Qinwei, **Chun, et al. Research on Pitch Control of Offshore Floating Wind Turbines [J]. Acta Energiae Solaris Sinica, 2021, 42(1): 143.
[7] 苑晨阳, 李静, 陈健云, 等. 大型风电机组变桨距 ABC-PID 控制研究[J]. 太阳能学报, 2019, 40(10): 3002-3008.
Yuan Chenyang, Li Jing, Chen Jianyun, et al. Research on ABC-PID Pitch Control for Large Wind Turbines [J]. Acta Energiae Solaris Sinica, 2019, 40(10): 3002-3008.
[8] Lara M, Garrido J, van Wingerden J W, et al. Optimization with genetic algorithms of individual pitch control design with and without azimuth offset for wind turbines in the full load region[J]. IFAC-PapersOnLine, 2023, 56(2): 342-347.
[9] Liu Y, Patton R J, Shi S. Actuator fault tolerant offshore wind turbine load mitigation control[J]. Renewable Energy, 2023, 205: 432-446.
[10] 姚兴佳,刘玥,郭庆鼎.基于前馈补偿方位角权系数的分程独立变桨距控制研究[J].太阳能学报, 2012, 33(4):8.
Yao Xingjia, Liu Yue, Guo Qingding. Research on Multi-Segment Independent Pitch Control Based on Feedforward Compensation Azimuth Weight Coefficient [J]. Acta Energiae Solaris Sinica, 2012, 33(4): 8.
[11] Mousavi Y, Bevan G, Kucukdemiral I B. Fault-tolerant optimal pitch control of wind turbines using dynamic weighted parallel firefly algorithm[J]. ISA transactions, 2022, 128: 301-317.
[12] Yuan Y, Chen X, Tang J. Multivariable robust blade pitch control design to reject periodic loads on wind turbines[J]. Renewable Energy, 2020, 146: 329-341.
[13]任建华,赵凯龙,刘欣宜.模糊控制理论在风电机组变桨控制系统中的应用[J].现代电子技术,2019,42(23):130-134.
Ren Jianhua, Zhao Kailong, Liu Xinyi. Application of Fuzzy Control Theory in the Pitch Control System of Wind Turbines [J]. Modern Electronics Technique, 2019, 42(23): 130-134.
[14] 何胜华,黄弘,范必双,等.带自适应模糊神经网络补偿的自耦合PI在风力机变桨控制中的应用[J].可再生能源,2023,41(05):618-624.
He Shenghua, Huang Hong, Fan Bishuang, et al. Application of Self-Coupling PI with Adaptive Fuzzy Neural Network Compensation in Wind Turbine Pitch Control [J]. Renewable Energy, 2023, 41(05): 618-624.
[15] 张前,何山,黄嵩,等.基于DDPG算法的风力发电机变桨距控制研究[J].科学技术与工程,2023,23(18):7764-7771.
Zhang Qian, He Shan, Huang Song, et al. Research on Wind Turbine Pitch Control Based on DDPG Algorithm [J]. Science Technology and Engineering, 2023, 23(18): 7764-7771.
[16] Wang X, Jiang Z, Lu H, et al. Independent pitch control strategy and simulation for reducing unbalanced load of wind turbine[C]//2020 Chinese Control And Decision Conference (CCDC). IEEE, 2020: 5535-5539.
[17] Santoni C, Khosronejad A, Seiler P, et al. Toward control co-design of utility-scale wind turbines: Collective vs. individual blade pitch control[J]. Energy Reports, 2023, 9: 793-806.
[18] Liu Y, Patton R J, Shi S. Monte Carlo analysis of Bayesian optimization-based pitch controller with pitch fault compensation for offshore wind turbine[J]. IFAC-PapersOnLine, 2022, 55(6): 384-389.
[19] 侯忠生,金尚泰.无模型自适应控制[M].科学出版社,2013.
Hou Zhongsheng, Jin Shangtai. Model-Free Adaptive Control [M]. Science Press, 2013.
[20] 李中奇,周靓,杨辉.高速动车组数据驱动无模型自适应控制方法[J].自动化学报, 2023, 49(2).
Li Zhongqi, Zhou Liang, Yang Hui. Data-Driven Model-Free Adaptive Control Method for High-Speed Trains [J]. Acta Automatica Sinica, 2023, 49(2).
[21] Li J, Wang S, Li Y. A model-free adaptive controller with tracking error differential for collective pitching of wind turbines[J]. Renewable energy, 2020, 161: 435-447.
[22] Abbas N J, Zalkind D S, Pao L, et al. A reference open-source controller for fixed and floating offshore wind turbines[J]. Wind Energy Science, 2022, 7(1): 53-73.
[23] 毛明轩,冯心营,陈思宇,等.基于贝叶斯优化卷积神经网络的路面光伏阵列最大功率点电压预测方法[J].中国电机工程学报, 2024, 44(2):620-630.
Mao Mingxuan, Feng Xinying, Chen Siyu, et al. Voltage Prediction Method for Maximum Power Point of Road Photovoltaic Arrays Based on Bayesian Optimization and Convolutional Neural Networks [J]. Proceedings of the CSEE, 2024, 44(2): 620-630.
[24] Allen, Christopher, Viscelli, Anthony, Dagher, Habib, Goupee, Andrew, Gaertner, Evan, Abbas, Nikhar, Hall, Matthew, and Barter, Garrett. Definition of the UMaine VolturnUS-S Reference Platform Developed for the IEA Wind 15-Megawatt Offshore Reference Wind Turbine. United States: N. p., 2020. Web. doi:10.2172/1660012