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Wake redirection control for offshore wind farm power and fatigue multi-objective optimisation based on a wind turbine load indicator

Author

Listed:
  • Sun, Jili
  • Yang, Jingqing
  • Jiang, Zezhong
  • Xu, JinFeng
  • Meng, Xiaofei
  • Feng, Xiaoguang
  • Si, Yulin
  • Zhang, Dahai

Abstract

Wake effects within offshore wind farms not only impact the overall energy output but also increase the structural fatigue loads of wind turbines. In this work, we propose a wake redirection control (WRC) strategy for power and fatigue multi-objective optimisation. In particular, the steady-state engineering wake model is further augmented by incorporating a load assessment feature, so that evaluating both power and fatigue behaviours in WRC design becomes possible. More specifically, a steady-state aerodynamic wake model is used to evaluate the power output, while the wind turbine fatigue behaviour is predicted by a load indicator derived from aero-elastic simulations covering a wide range of waked inflow and yaw-offset conditions. Based on the wake model and the load indicator, multi-objective particle swarm optimisation is then used to locate the optimal wind farm yaw settings for both power optimisation and load mitigation. In order to demonstrate the effectiveness of the proposed strategy, WRC design is performed for a 3 × 3 offshore wind farm, and the results have been verified against the state-of-the-art multi-physics engineering tool FAST.Farm. It is shown that the proposed multi-objective WRC strategy could achieve a 7.49% overall power increase and a 2.15% tower-bottom fatigue load reduction, while suppressing the growth of blade-root fatigue load at the same time, over-performing the other WRC designs with different control objectives. This study provides an efficient way of structural fatigue evaluation under combined wake interactions and yaw-misalignment, enabling power and fatigue multi-objective optimisation for offshore wind farm WRC design.

Suggested Citation

  • Sun, Jili & Yang, Jingqing & Jiang, Zezhong & Xu, JinFeng & Meng, Xiaofei & Feng, Xiaoguang & Si, Yulin & Zhang, Dahai, 2024. "Wake redirection control for offshore wind farm power and fatigue multi-objective optimisation based on a wind turbine load indicator," Energy, Elsevier, vol. 313(C).
    • Handle: RePEc:eee:energy:v:313:y:2024:i:c:s0360544224036715
    DOI: 10.1016/j.energy.2024.133893
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    References listed on IDEAS

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    2. Xu, Zongyuan & Gao, Xiaoxia & Zhang, Huanqiang & Lu, Hongkun & Han, Zhonghe & Zhu, Xiaoxun & Wang, Yu & Zhao, Wensheng, 2025. "Coupled effects of 3D wake expansion and terrain anisotropy on downstream wind turbine power performance and fatigue load," Energy, Elsevier, vol. 334(C).
    3. Li, Pei-hang & Jia, Rong & Cao, Ge & Ming, Bo & Guo, Yi & Wang, Song-kai & Li, Wei, 2025. "A novel perspective for equivalent aggregation of wind farm: Measuring the dynamic similarity between output time-series," Applied Energy, Elsevier, vol. 392(C).
    4. Wasilczuk, Filip & Kasprzak, Piotr & Rybiński, Michał & Flaszyński, Paweł & Dzierwa, Piotr & Ziędalska, Klaudia & Kowalczyk, Sebastian & Taler, Dawid, 2025. "Positive effect of wind farm control on energy production and revenue in European markets," Energy, Elsevier, vol. 326(C).
    5. Xiaomei Ma & Mengxue Li & Wenquan Li & Yongqian Liu, 2025. "Overview of Offshore Wind Power Technologies," Sustainability, MDPI, vol. 17(2), pages 1-16, January.

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