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State-of-the-art multivariate lifetime assessment methodology for offshore renewable energy systems, utilizing novel deconvolution extrapolation scheme

Author

Listed:
  • Oleg Gaidai
  • Fang Wang
  • Jinlu Sheng
  • Yan Zhu
  • Zirui Liu
  • Zhang Fuxi
  • Yu Cao

Abstract

Green, renewable energy attracts growing popularity as global attention shifts toward carbon-neutral technologies. One such viable alternative is offshore wind power, harvested by FOWTs (Floating Offshore Wind Turbines). In the contemporary offshore wind energy business, FOWTs play a key role, generating industrial volumes of renewable clean electricity. Accurate operational life assessment of the FOWT structure is a critical design and technical safety concern, since excessive environmental loads may lead to structural damage. Utilizing OpenFAST (Fatigue, Aerodynamics, Structures and Turbulence) aeroelastic simulator, FOWT nonlinear structural reactions could be modelled accurately. The current study introduces a state-of-the-art reliability structural lifetime assessment approach, intended to serve designers when evaluating FOWT operational risks, given in-situ environmental loading patterns. The primary benefits of the recommended structural lifetime assessment approach lie within its capacity to address dynamic systems’ high-dimensionality, along with complex cross-correlations between the system’s critical components. A novel deconvolution extrapolation scheme has been employed to obtain conservative design values. The primary advantage of deconvolution extrapolation above existing parametric extrapolation methods, widely used in reliability studies, is a non-parametric feature, that increases the accuracy of forecasts.

Suggested Citation

  • Oleg Gaidai & Fang Wang & Jinlu Sheng & Yan Zhu & Zirui Liu & Zhang Fuxi & Yu Cao, 2025. "State-of-the-art multivariate lifetime assessment methodology for offshore renewable energy systems, utilizing novel deconvolution extrapolation scheme," Journal of Risk and Reliability, , vol. 239(6), pages 1496-1504, December.
  • Handle: RePEc:sae:risrel:v:239:y:2025:i:6:p:1496-1504
    DOI: 10.1177/1748006X251323690
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    References listed on IDEAS

    as
    1. Oleg Gaidai & Vladimir Yakimov & Fang Wang & Jiayao Sun & Kelin Wang, 2024. "Bivariate reliability analysis for floating wind turbines," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 19, pages 55-64.
    2. Baptiste Poujol & Anne Prieur‐Vernat & Jean Dubranna & Romain Besseau & Isabelle Blanc & Paula Pérez‐López, 2020. "Site‐specific life cycle assessment of a pilot floating offshore wind farm based on suppliers’ data and geo‐located wind data," Journal of Industrial Ecology, Yale University, vol. 24(1), pages 248-262, February.
    3. Oleg Gaidai & Fang Wang & Yu Cao & Zirui Liu, 2024. "4400 TEU cargo ship dynamic analysis by Gaidai reliability method," Journal of Shipping and Trade, Springer, vol. 9(1), pages 1-16, December.
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