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Risk-based maintenance planning of offshore wind turbine farms

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  • Yeter, B.
  • Garbatov, Y.
  • Guedes Soares, C.

Abstract

A risk-based maintenance planning for offshore wind farm installations is developed. Initially, the optimal number of monopile offshore wind turbines to be installed in an offshore wind farm is estimated, targeting a minimum levelised cost of energy. To this end, a sufficient number of design combinations for monopile support structure is generated by the design of experiment technique and then analysed based on the fatigue limit state. Following the fatigue reliability analysis performed for the monopile designs, an analytical relation between manufacturing cost and the structural safety regarding fatigue is developed to be used in the life-cycle cost analysis. The offshore wind farm is considered here as a system consisting of correlated components. The system reliability is estimated by using Ditlevsen bounding technique, which uses a time-variant correlation matrix of offshore wind turbines. The event tree method is employed to assess the expected cost of failure to be included in the capital investment as the structural risk premium, and the total expected cost to be included in the operational cost. Furthermore, different inspection policies are studied, and the most cost-effective inspection and maintenance policy is found for each studied wind farm. The present study also develops a novel framework for inspection and maintenance planning that maximises the benefits of performing inspections for a multi-unit system. Finally, the developed framework is applied to an offshore wind farm with sixty installations, and the detailed description of the planned inspections are discussed.

Suggested Citation

  • Yeter, B. & Garbatov, Y. & Guedes Soares, C., 2020. "Risk-based maintenance planning of offshore wind turbine farms," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    • Handle: RePEc:eee:reensy:v:202:y:2020:i:c:s0951832020305639
    DOI: 10.1016/j.ress.2020.107062
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    References listed on IDEAS

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    1. Nielsen, Jannie Jessen & Sørensen, John Dalsgaard, 2011. "On risk-based operation and maintenance of offshore wind turbine components," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 218-229.
    2. Horn, Jan-Tore & Leira, Bernt J., 2019. "Fatigue reliability assessment of offshore wind turbines with stochastic availability," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    3. Shafiee, Mahmood & Sørensen, John Dalsgaard, 2019. "Maintenance optimization and inspection planning of wind energy assets: Models, methods and strategies," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    4. Blanco, María Isabel, 2009. "The economics of wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1372-1382, August.
    5. Dong, Wenbin & Moan, Torgeir & Gao, Zhen, 2012. "Fatigue reliability analysis of the jacket support structure for offshore wind turbine considering the effect of corrosion and inspection," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 11-27.
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    4. Wu, Xingguang & Huang, Huirong & Xie, Jianyu & Lu, Meixing & Wang, Shaobo & Li, Wang & Huang, Yixuan & Yu, Weichao & Sun, Xiaobo, 2023. "A novel dynamic risk assessment method for the petrochemical industry using bow-tie analysis and Bayesian network analysis method based on the methodological framework of ARAMIS project," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    5. Zou, Guang & Kolios, Athanasios, 2022. "Quantifying the value of negative inspection outcomes in fatigue maintenance planning: Cost reduction, risk mitigation and reliability growth," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    6. 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).
    7. Zhang, Chen & Hu, Di & Yang, Tao, 2022. "Anomaly detection and diagnosis for wind turbines using long short-term memory-based stacked denoising autoencoders and XGBoost," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    8. Shi, Yan & Lu, Zhenzhou & Huang, Hongzhong & Liu, Yu & Li, Yanfeng & Zio, Enrico & Zhou, Yicheng, 2022. "A new preventive maintenance strategy optimization model considering lifecycle safety," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    9. Chadha, Mayank & Ramancha, Mukesh K. & Vega, Manuel A. & Conte, Joel P. & Todd, Michael D., 2023. "The modeling of risk perception in the use of structural health monitoring information for optimal maintenance decisions," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    10. BULUT, Merve & ÖZCAN, Evrencan, 2021. "A new approach to determine maintenance periods of the most critical hydroelectric power plant equipment," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    11. Li, He & Guedes Soares, C, 2022. "Assessment of failure rates and reliability of floating offshore wind turbines," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    12. Kristjanpoller, Fredy & Cárdenas-Pantoja, Nicolás & Viveros, Pablo & Pascual, Rodrigo, 2023. "Wind farm life cycle cost modelling based on oversizing capacity under load sharing configuration," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    13. Afef Fekih & Hamed Habibi & Silvio Simani, 2022. "Fault Diagnosis and Fault Tolerant Control of Wind Turbines: An Overview," Energies, MDPI, vol. 15(19), pages 1-21, September.

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