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Global sensitivity analysis of offshore wind turbine foundation fatigue loads

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  • Velarde, Joey
  • Kramhøft, Claus
  • Sørensen, John Dalsgaard

Abstract

The design and analysis of offshore wind turbine foundations are traditionally based on deterministic time-domain simulations of a numerical model. The wind turbine, support structure and environmental conditions are represented by a large number of input parameters, whose uncertainties are accounted by applying partial safety factors. In this paper, the sensitivity of fatigue loads with respect to primary structural, geotechnical and metocean parameters are investigated for a 5 MW offshore wind turbine installed on a gravity based foundation. Linear regression of Monte Carlo simulations and Morris screening are performed for three design load cases. Results show that parameter significance rankings vary according to which design load case is considered. In general, uncertainties in the fatigue loads are highly influenced by turbulence intensity and wave load uncertainties, while uncertainties in soil property suggest significant nonlinear or interactive effects. This work provides insights to foundation designers and wind turbine manufacturers on which parameters must be assessed in more detail in order to reduce uncertainties in load prediction.

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  • Velarde, Joey & Kramhøft, Claus & Sørensen, John Dalsgaard, 2019. "Global sensitivity analysis of offshore wind turbine foundation fatigue loads," Renewable Energy, Elsevier, vol. 140(C), pages 177-189.
    • Handle: RePEc:eee:renene:v:140:y:2019:i:c:p:177-189
    DOI: 10.1016/j.renene.2019.03.055
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    Cited by:

    1. Liao, Ding & Zhu, Shun-Peng & Correia, José A.F.O. & De Jesus, Abílio M.P. & Veljkovic, Milan & Berto, Filippo, 2022. "Fatigue reliability of wind turbines: historical perspectives, recent developments and future prospects," Renewable Energy, Elsevier, vol. 200(C), pages 724-742.
    2. Chen, Yisu & Wu, Di & Yu, Yuguo & Gao, Wei, 2021. "Do cyclone impacts really matter for the long-term performance of an offshore wind turbine?," Renewable Energy, Elsevier, vol. 178(C), pages 184-201.
    3. Liu, Zhenqing & Wang, Yize & Nyangi, Patrice & Zhu, Zhiwen & Hua, Xugang, 2021. "Proposal of a novel GPU-accelerated lifetime optimization method for onshore wind turbine dampers under real wind distribution," Renewable Energy, Elsevier, vol. 168(C), pages 516-543.
    4. Lu, Liang & Wu, Haijun & Wu, Jianzhong, 2021. "A case study for the optimization of moment-matching in wind turbine blade fatigue tests with a resonant type exciting approach," Renewable Energy, Elsevier, vol. 174(C), pages 769-785.
    5. Chen, Chao & Duffour, Philippe & Fromme, Paul & Hua, Xugang, 2021. "Numerically efficient fatigue life prediction of offshore wind turbines using aerodynamic decoupling," Renewable Energy, Elsevier, vol. 178(C), pages 1421-1434.
    6. Carta, José A. & Díaz, Santiago & Castañeda, Alberto, 2020. "A global sensitivity analysis method applied to wind farm power output estimation models," Applied Energy, Elsevier, vol. 280(C).
    7. Hübler, Clemens, 2020. "Global sensitivity analysis for medium-dimensional structural engineering problems using stochastic collocation," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    8. Shittu, Abdulhakim Adeoye & Mehmanparast, Ali & Hart, Phil & Kolios, Athanasios, 2021. "Comparative study between S-N and fracture mechanics approach on reliability assessment of offshore wind turbine jacket foundations," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    9. Okpokparoro, Salem & Sriramula, Srinivas, 2021. "Uncertainty modeling in reliability analysis of floating wind turbine support structures," Renewable Energy, Elsevier, vol. 165(P1), pages 88-108.

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