Assessment of failure rates and reliability of floating offshore wind turbines

• Published in: Reliability engineering & system safety Vol. 228; p. 108777
• Main Authors: Li, He, Guedes Soares, C
• Format: Journal Article
• Language: English
• Published: Barking Elsevier Ltd 01.12.2022; Elsevier BV
• Subjects: Bayesian analysis; Failure analysis; Failure rate assessment; Failure rate correction model; Failure rates; Floating offshore wind turbine; Mathematical models; Network reliability; Offshore; Offshore energy sources; Offshore structures; Reliability analysis; Reliability aspects; Reliability engineering; Turbines; Wind power; Wind turbines; Floating offshore wind turbine; Reliability analysis; Failure rate assessment; Failure rate correction model
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2022.108777

•A model is proposed to assess the failure rate of components of floating offshore wind turbines based on onshore turbine data.•A failure rate correction model is presented for the relations of failure between onshore and floating offshore wind turbines.•The results indicate that the failure rates of components of floating wind turbines are higher than those of onshore devices.•A Bayesian network is constructed to analyze the failure rate and reliability of the entire floating offshore wind turbine.•The performance of the proposed model is validated by a comprehensive comparison with the existing studies and models. A model is proposed to assess the failure rates of components of floating offshore wind turbines based on the knowledge of failure data of corresponding structures of onshore wind turbines with sufficient failure data. A failure rate correction model is first presented to map the relations of failure features between onshore and floating offshore wind turbines. Subsequently, a failure rate analogy model is established to infer the failure rates of elements of support structures that have no correspondence in onshore devices. The results indicate that the failure rates of components of floating offshore wind turbines are higher than those of onshore devices. Accordingly, a Bayesian network is constructed to analyze the failure rate and reliability of the entire floating offshore wind turbine. The uncertainty of the model is investigated to illustrate the factors that significantly affect the predicted failure rates and reliability. Moreover, the performance of the proposed model is validated by a comprehensive comparison with the existing studies and models. The model presented contributes to the risk, failure, and reliability analysis and assessment under insufficient data conditions.