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Predictive control of wind turbine yaw system model based on reinforcement learning
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Shengang SANG1, Guipeng LI1, Xiangwei WANG1, Yi LIU1, Sen WANG1, Xiangrong SHEN2
Thermal Power Generation | 2025, 54(9) : 86 - 94
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Thermal Power Generation | 2025, 54(9): 86-94
• Special topic on low carbon power technology •
Predictive control of wind turbine yaw system model based on reinforcement learning
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Shengang SANG1, Guipeng LI1, Xiangwei WANG1, Yi LIU1, Sen WANG1, Xiangrong SHEN2
Affiliations
  • 1.Huaneng New Energy Co., Ltd. Hebei Branch, Shijiazhuang 050011, China
  • 2.Department of Automation, North China Electric Power University, Baoding 071003, China
Published: 2025-09-25 doi: 10.19666/j.rlfd.202501006
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It is crucial to improve the dynamic performance of the yaw system of wind turbines in multiple operating scenarios. Therefore, a predictive control strategy for wind turbine yaw system model based on reinforcement learning is proposed, which achieves multi-objective parameter dynamic optimization through the dual-delay depth deterministic policy gradient (TD3) algorithm. Firstly, a multi-step model predictive controller for the yaw system (YMPC) is established to address the conflicting control objectives of power loss rate and yaw actuator utilization rate. Secondly, based on the optimization objectives and wind conditions of the yaw system, a dual-delay depth deterministic strategy gradient (TD3) intelligent agent is designed to determine the input state, action, and reward mechanism of the YMPC. The TD3 intelligent agent is then used to tune the weight coefficients and control step size of the YMPC. Finally, the effectiveness of this method was validated using typical daily data from wind farms in northern China. The results indicate that the proposed strategy significantly improves the overall performance of the yaw system compared with the YMPC with fixed control parameters.

wind turbines  /  yaw system  /  reinforcement learning  /  control parameter
Shengang SANG, Guipeng LI, Xiangwei WANG, Yi LIU, Sen WANG, Xiangrong SHEN. Predictive control of wind turbine yaw system model based on reinforcement learning[J]. Thermal Power Generation, 2025 , 54 (9) : 86 -94 . DOI: 10.19666/j.rlfd.202501006
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  • Science and Technology Project of China Huanneng Group Co., Ltd.(HNKJ22-HF69)
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Year 2025 volume 54 Issue 9
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102
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Article Info
doi: 10.19666/j.rlfd.202501006
  • Receive Date：2025-01-22
  • Online Date：2026-03-05
  • Published：2025-09-25
Article Data
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History
  • Received：2025-01-22
Funding
Science and Technology Project of China Huanneng Group Co., Ltd.(HNKJ22-HF69)
Affiliations
    1.Huaneng New Energy Co., Ltd. Hebei Branch, Shijiazhuang 050011, China
    2.Department of Automation, North China Electric Power University, Baoding 071003, China
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https://castjournals.cast.org.cn/joweb/rlfd/EN/10.19666/j.rlfd.202501006
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