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Dynamic Performance of Monopile-Supported Wind Turbines (MWTs) under Different Operating and Ground Conditions

Author

Listed:
  • Shaohui Xiao

    (School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen 518055, China)

  • Hongjun Liu

    (School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen 518055, China)

  • Kun Lin

    (School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen 518055, China)

Abstract

A monopile is the most popular foundation type for wind turbines. However, the dynamic performance of monopile-supported wind turbines under different operating and ground conditions is not fully understood. In this study, an integrated monopile-supported wind turbine model in a wind tunnel was employed to jointly simulate the operating and ground conditions. A series of wind tunnel tests were designed and performed to investigate the dynamic performance of monopile-supported wind turbines. These tests included seven operating conditions (seven wind speeds and corresponding rotor speeds) and four ground conditions (one fixed ground condition and three deformable ground conditions with different soil relative densities). According to the test results, the structural responses and dynamic characteristics were analyzed and discussed. This shows that the assumption of fixed-base support significantly overestimates the natural frequency but underestimates the global damping ratio. With the increase in soil relative density, the natural frequency slightly increases, while the damping ratio decreases more significantly. With the increase in the wind speed and rotor speed, the increase in global damping is larger on softer ground. A regression analysis was performed to estimate the global damping ratio under different operating and ground conditions.

Suggested Citation

  • Shaohui Xiao & Hongjun Liu & Kun Lin, 2023. "Dynamic Performance of Monopile-Supported Wind Turbines (MWTs) under Different Operating and Ground Conditions," Energies, MDPI, vol. 17(1), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:17:y:2023:i:1:p:112-:d:1306794
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    References listed on IDEAS

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    1. Ozbek, Muammer & Rixen, Daniel J. & Erne, Oliver & Sanow, Gunter, 2010. "Feasibility of monitoring large wind turbines using photogrammetry," Energy, Elsevier, vol. 35(12), pages 4802-4811.
    2. Wang, Xuefei & Zeng, Xiangwu & Yang, Xu & Li, Jiale, 2019. "Seismic response of offshore wind turbine with hybrid monopile foundation based on centrifuge modelling," Applied Energy, Elsevier, vol. 235(C), pages 1335-1350.
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