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Enhancing Reliability in Floating Offshore Wind Turbines through Digital Twin Technology: A Comprehensive Review

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  • Bai-Qiao Chen

    (School of Naval Architecture and Ocean Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China
    Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal)

  • Kun Liu

    (School of Naval Architecture and Ocean Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China)

  • Tongqiang Yu

    (School of Naval Architecture and Ocean Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China)

  • Ruoxuan Li

    (College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai 201306, China)

Abstract

This comprehensive review explores the application and impact of digital twin (DT) technology in bolstering the reliability of Floating Offshore Wind Turbines (FOWTs) and their supporting platforms. Within the burgeoning domain of offshore wind energy, this study contextualises the need for heightened reliability measures in FOWTs and elucidates how DT technology serves as a transformative tool to address these concerns. Analysing the existing scholarly literature, the review encompasses insights into the historical reliability landscape, DT deployment methodologies, and their influence on FOWT structures. Findings underscore the pivotal role of DT technology in enhancing FOWT reliability through real-time monitoring and predictive maintenance strategies, resulting in improved operational efficiency and reduced downtime. Highlighting the significance of DT technology as a potent mechanism for fortifying FOWT reliability, the review emphasises its potential to foster a robust operational framework while acknowledging the necessity for continued research to address technical intricacies and regulatory considerations in its integration within offshore wind energy systems. Challenges and opportunities related to the integration of DT technology in FOWTs are thoroughly analysed, providing valuable insights into the role of DTs in optimising FOWT reliability and performance, thereby offering a foundation for future research and industry implementation.

Suggested Citation

  • Bai-Qiao Chen & Kun Liu & Tongqiang Yu & Ruoxuan Li, 2024. "Enhancing Reliability in Floating Offshore Wind Turbines through Digital Twin Technology: A Comprehensive Review," Energies, MDPI, vol. 17(8), pages 1-23, April.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:8:p:1964-:d:1379574
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    References listed on IDEAS

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    1. Arcos Jiménez, Alfredo & Zhang, Long & Gómez Muñoz, Carlos Quiterio & García Márquez, Fausto Pedro, 2020. "Maintenance management based on Machine Learning and nonlinear features in wind turbines," Renewable Energy, Elsevier, vol. 146(C), pages 316-328.
    2. Snyder, Brian & Kaiser, Mark J., 2009. "Ecological and economic cost-benefit analysis of offshore wind energy," Renewable Energy, Elsevier, vol. 34(6), pages 1567-1578.
    3. Gentils, Theo & Wang, Lin & Kolios, Athanasios, 2017. "Integrated structural optimisation of offshore wind turbine support structures based on finite element analysis and genetic algorithm," Applied Energy, Elsevier, vol. 199(C), pages 187-204.
    4. Vincent T. Covello & Jeryl Mumpower, 1985. "Risk Analysis and Risk Management: An Historical Perspective," Risk Analysis, John Wiley & Sons, vol. 5(2), pages 103-120, June.
    5. Bhattacharya, Syamantak, 2012. "The effectiveness of the ISM Code: A qualitative enquiry," Marine Policy, Elsevier, vol. 36(2), pages 528-535.
    6. Kang, Jichuan & Sun, Liping & Guedes Soares, C., 2019. "Fault Tree Analysis of floating offshore wind turbines," Renewable Energy, Elsevier, vol. 133(C), pages 1455-1467.
    7. Tran, Thanh Toan & Kim, Dong-Hyun, 2016. "Fully coupled aero-hydrodynamic analysis of a semi-submersible FOWT using a dynamic fluid body interaction approach," Renewable Energy, Elsevier, vol. 92(C), pages 244-261.
    8. Saraygord Afshari, Sajad & Enayatollahi, Fatemeh & Xu, Xiangyang & Liang, Xihui, 2022. "Machine learning-based methods in structural reliability analysis: A review," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
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