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

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.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability
Published
2025-03-17
DOI
https://doi.org/10.1177/1748006x251323690
Citations
21
Primary Topic
Power System Reliability and Maintenance
Type
article
Field-Weighted Citation Impact
27.37
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article

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

Fuxi Zhang, Yu Cao, Oleg Gaidai, Fang Wang et al.
21 citations
Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability
Power System Reliability and Maintenance
27.37
article

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

Fuxi Zhang, Yu Cao, Oleg Gaidai, Fang Wang, Yan Zhu, Zirui Liu, Jinlu Sheng
article en
21 citations

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.

Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and ReliabilityVol. 239(6)
Jiangsu University of Science and Technology (CN), Shanghai Ocean University (CN), Chongqing Jiaotong University (CN)
Openalex Percentile: Top 0%
Power System Reliability and Maintenance
27.37
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