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Experimental study on long-term performance of monopile-supported wind turbines (MWTs) in sand by using wind tunnel

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  • Lin, Kun
  • Xiao, Shaohui
  • Zhou, Annan
  • Liu, Hongjun

Abstract

Monopile is a dominate type of foundation for wind turbines in shallow water or inland wind farm. Long-term cyclic loads induced by wind, wave, and operation will influence the long-term dynamic characteristics and structural responses of monopile-supported wind turbines (MWTs). In this paper, wind tunnel tests which integrated accurate scaled model and well simulated loads were performed to study the long-term performance of MWTs. Similarity relation were discussed and a scaled MWT model was fabricated on the basis of NREL 5 MW wind turbine and installed in sand in a wind tunnel. The layouts of apparatus and the loading method for the wind tunnel tests were designed to study the long-term performance of wind turbines including dynamic characteristics, amplitude of structural responses, and accumulated deformation. The first order natural frequency and damping ratio were identified using stochastic subspace identification. Test results indicates that the natural frequency increases, while the damping ratio decreases slightly with the increase of load cycles. The amplitudes of structural responses increase significantly which may threaten the lifetimes of MWTs. Based on the wind tunnel test results, service life evaluation of MWT can be conducted in terms of natural frequency shifting and accumulated rotation at pile head.

Suggested Citation

  • Lin, Kun & Xiao, Shaohui & Zhou, Annan & Liu, Hongjun, 2020. "Experimental study on long-term performance of monopile-supported wind turbines (MWTs) in sand by using wind tunnel," Renewable Energy, Elsevier, vol. 159(C), pages 1199-1214.
    • Handle: RePEc:eee:renene:v:159:y:2020:i:c:p:1199-1214
    DOI: 10.1016/j.renene.2020.06.034
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    References listed on IDEAS

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    Cited by:

    1. Xiao, Shaohui & Lin, Kun & Liu, Hongjun & Zhou, Annan, 2021. "Performance analysis of monopile-supported wind turbines subjected to wind and operation loads," Renewable Energy, Elsevier, vol. 179(C), pages 842-858.
    2. Yang, Siyao & Lin, Kun & Zhou, Annan, 2024. "An ML-based wind turbine blade design method considering multi-objective aerodynamic similarity and its experimental validation," Renewable Energy, Elsevier, vol. 220(C).
    3. Charlton, T.S. & Rouainia, M., 2022. "Geotechnical fragility analysis of monopile foundations for offshore wind turbines in extreme storms," Renewable Energy, Elsevier, vol. 182(C), pages 1126-1140.

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