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Extreme structural response prediction and fatigue damage evaluation for large-scale monopile offshore wind turbines subject to typhoon conditions

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  • Qin, Mengfei
  • Shi, Wei
  • Chai, Wei
  • Fu, Xing
  • Li, Lin
  • Li, Xin

Abstract

Offshore wind is becoming the way forward for green energy harnessing worldwide. However, frequent typhoons are a major constraint for the development of offshore wind power for some regions in Asia and North America. Typhoons may pose a huge challenge to offshore wind farm development in southern China. In this paper, a fully-coupled analysis was carried out for a 10 MW large-scale monopile offshore wind turbine (OWT) using SIMO-Riflex-Aerodyn (SRA) code. The response characteristics of the OWTs in different typhoon regions are investigated based on the measured typhoon conditions in China. The effect of aerodynamic damping on the response and the load effect is analyzed in detail. Two different distribution methods are used to statistically extrapolate the response value and get the short-term extreme response. Cumulative linear fatigue damage is evaluated by the rain-flow counting method to explore the possible failure modes of large wind turbines during typhoons. The results show that aerodynamic loads play an important role in large monopile OWTs during high wind speeds in parked conditions. The extreme response and fatigue analyses from this study indicate that fatigue is a dominant failure mode for the large OWT tower during typhoons, while buckling is unlikely.

Suggested Citation

  • Qin, Mengfei & Shi, Wei & Chai, Wei & Fu, Xing & Li, Lin & Li, Xin, 2023. "Extreme structural response prediction and fatigue damage evaluation for large-scale monopile offshore wind turbines subject to typhoon conditions," Renewable Energy, Elsevier, vol. 208(C), pages 450-464.
    • Handle: RePEc:eee:renene:v:208:y:2023:i:c:p:450-464
    DOI: 10.1016/j.renene.2023.03.066
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    References listed on IDEAS

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    Cited by:

    1. Zeng, Xinmeng & Shao, Yanlin & Feng, Xingya & Xu, Kun & Jin, Ruijia & Li, Huajun, 2024. "Nonlinear hydrodynamics of floating offshore wind turbines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    2. Oh, So Young & Joung, Chanwoo & Lee, Seonghwan & Shim, Yoon-Bo & Lee, Dahun & Cho, Gyu-Eun & Jang, Juhyeong & Lee, In Yong & Park, Young-Bin, 2024. "Condition-based maintenance of wind turbine structures: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 204(C).
    3. Liu, Yingzhou & Li, Xin & Shi, Wei & Wang, Wenhua & Jiang, Zhiyu, 2024. "Vibration control of a monopile offshore wind turbines under recorded seismic waves," Renewable Energy, Elsevier, vol. 226(C).
    4. Yao, Qi & Tang, Jie & Ke, Yiming & Li, Li & Lu, Xiaoqin & Hu, Yang & Fang, Fang & Liu, Jizhen, 2024. "Anti-tropical cyclone load reduction control of wind turbines based on deep neural network yaw algorithm," Applied Energy, Elsevier, vol. 376(PB).
    5. Ren, Yajun & Shi, Wei & Venugopal, Vengatesan & Zhang, Lixian & Li, Xin, 2024. "Experimental study of tendon failure analysis for a TLP floating offshore wind turbine," Applied Energy, Elsevier, vol. 358(C).
    6. Liang, Jun & Fu, Yuhao & Wang, Ying & Ou, Jinping, 2024. "Identification of equivalent wind and wave loads for monopile-supported offshore wind turbines in operating condition," Renewable Energy, Elsevier, vol. 237(PA).

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