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Health Monitoring and Safety Evaluation of the Offshore Wind Turbine Structure: A Review and Discussion of Future Development

Author

Listed:
  • Jijian Lian

    () (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China
    School of Civil Engineering, Tianjin University, Tianjin 300350, China)

  • Ou Cai

    () (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China
    School of Civil Engineering, Tianjin University, Tianjin 300350, China
    PowerChina Beijing Engineering Corporation Limited, Beijing 100024, China)

  • Xiaofeng Dong

    () (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China
    School of Civil Engineering, Tianjin University, Tianjin 300350, China)

  • Qi Jiang

    () (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China
    School of Civil Engineering, Tianjin University, Tianjin 300350, China)

  • Yue Zhao

    () (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China
    School of Civil Engineering, Tianjin University, Tianjin 300350, China)

Abstract

With the depletion of fossil energy, offshore wind power has become an irreplaceable energy source for most countries in the world. In recent years, offshore wind power generation has presented the gradual development trend of larger capacity, taller towers, and longer blades. The more flexible towers and blades have led to the structural operational safety of the offshore wind turbine (OWT) receiving increasing worldwide attention. From this perspective, health monitoring systems and operational safety evaluation techniques of the offshore wind turbine structure, including the monitoring system category, data acquisition and transmission, feature information extraction and identification, safety evaluation and reliability analysis, and the intelligent operation and maintenance, were systematically investigated and summarized in this paper. Furthermore, a review of the current status, advantages, disadvantages, and the future development trend of existing systems and techniques was also carried out. Particularly, the offshore wind power industry will continue to develop into deep ocean areas in the next 30 years in China. Practical and reliable health monitoring systems and safety evaluation techniques are increasingly critical for offshore wind farms. Simultaneously, they have great significance for strengthening operation management, making efficient decisions, and reducing failure risks, and are also the key link in ensuring safe energy compositions and achieving energy development targets in China. The aims of this article are to inform more scholars and experts about the status of the health monitoring and safety evaluation of the offshore wind turbine structure, and to contribute toward improving the efficiency of the corresponding systems and techniques.

Suggested Citation

  • Jijian Lian & Ou Cai & Xiaofeng Dong & Qi Jiang & Yue Zhao, 2019. "Health Monitoring and Safety Evaluation of the Offshore Wind Turbine Structure: A Review and Discussion of Future Development," Sustainability, MDPI, Open Access Journal, vol. 11(2), pages 1-29, January.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:2:p:494-:d:198826
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    References listed on IDEAS

    as
    1. Tian, Zhigang & Jin, Tongdan & Wu, Bairong & Ding, Fangfang, 2011. "Condition based maintenance optimization for wind power generation systems under continuous monitoring," Renewable Energy, Elsevier, vol. 36(5), pages 1502-1509.
    2. Kim, Dong Hyawn & Lee, Sang Geun, 2015. "Reliability analysis of offshore wind turbine support structures under extreme ocean environmental loads," Renewable Energy, Elsevier, vol. 79(C), pages 161-166.
    3. Schubel, P.J. & Crossley, R.J. & Boateng, E.K.G. & Hutchinson, J.R., 2013. "Review of structural health and cure monitoring techniques for large wind turbine blades," Renewable Energy, Elsevier, vol. 51(C), pages 113-123.
    4. repec:eee:renene:v:115:y:2018:i:c:p:521-532 is not listed on IDEAS
    5. Ossai, Chinedu I. & Boswell, Brian & Davies, Ian J., 2016. "A Markovian approach for modelling the effects of maintenance on downtime and failure risk of wind turbine components," Renewable Energy, Elsevier, vol. 96(PA), pages 775-783.
    6. Marino, Enzo & Giusti, Alessandro & Manuel, Lance, 2017. "Offshore wind turbine fatigue loads: The influence of alternative wave modeling for different turbulent and mean winds," Renewable Energy, Elsevier, vol. 102(PA), pages 157-169.
    7. Liu, Xiaofeng & Bo, Lin & Luo, Hongling, 2016. "Dynamical measurement system for wind turbine fatigue load," Renewable Energy, Elsevier, vol. 86(C), pages 909-921.
    8. Liu, Wenyi & Tang, Baoping & Jiang, Yonghua, 2010. "Status and problems of wind turbine structural health monitoring techniques in China," Renewable Energy, Elsevier, vol. 35(7), pages 1414-1418.
    9. Kim, Soo-Hyun & Shin, Hyung-Ki & Joo, Young-Chul & Kim, Keon-Hoon, 2015. "A study of the wake effects on the wind characteristics and fatigue loads for the turbines in a wind farm," Renewable Energy, Elsevier, vol. 74(C), pages 536-543.
    10. Kusiak, Andrew & Zhang, Zijun & Verma, Anoop, 2013. "Prediction, operations, and condition monitoring in wind energy," Energy, Elsevier, vol. 60(C), pages 1-12.
    11. Zheng, Tengfei & Qiang, Maoshan & Chen, Wenchao & Xia, Bingqing & Wang, Jianing, 2016. "An externality evaluation model for hydropower projects: A case study of the Three Gorges Project," Energy, Elsevier, vol. 108(C), pages 74-85.
    12. Maria Martinez Luengo & Athanasios Kolios, 2015. "Failure Mode Identification and End of Life Scenarios of Offshore Wind Turbines: A Review," Energies, MDPI, Open Access Journal, vol. 8(8), pages 1-16, August.
    13. Pierre Tchakoua & René Wamkeue & Mohand Ouhrouche & Fouad Slaoui-Hasnaoui & Tommy Andy Tameghe & Gabriel Ekemb, 2014. "Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges," Energies, MDPI, Open Access Journal, vol. 7(4), pages 1-36, April.
    14. Jin, Xin & Ju, Wenbin & Zhang, Zhaolong & Guo, Lianxin & Yang, Xiangang, 2016. "System safety analysis of large wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1293-1307.
    15. repec:gam:jeners:v:10:y:2017:i:4:p:574-:d:96525 is not listed on IDEAS
    16. Kilic, Gokhan & Unluturk, Mehmet S., 2015. "Testing of wind turbine towers using wireless sensor network and accelerometer," Renewable Energy, Elsevier, vol. 75(C), pages 318-325.
    17. repec:eee:reensy:v:94:y:2009:i:6:p:1057-1063 is not listed on IDEAS
    18. Yang, Wenxian & Court, Richard & Jiang, Jiesheng, 2013. "Wind turbine condition monitoring by the approach of SCADA data analysis," Renewable Energy, Elsevier, vol. 53(C), pages 365-376.
    19. repec:eee:renene:v:125:y:2018:i:c:p:133-154 is not listed on IDEAS
    20. Rezaei, Mohammad M. & Behzad, Mehdi & Moradi, Hamed & Haddadpour, Hassan, 2016. "Modal-based damage identification for the nonlinear model of modern wind turbine blade," Renewable Energy, Elsevier, vol. 94(C), pages 391-409.
    21. Sun, Peng & Li, Jian & Wang, Caisheng & Lei, Xiao, 2016. "A generalized model for wind turbine anomaly identification based on SCADA data," Applied Energy, Elsevier, vol. 168(C), pages 550-567.
    22. Ozbek, Muammer & Rixen, Daniel J. & Erne, Oliver & Sanow, Gunter, 2010. "Feasibility of monitoring large wind turbines using photogrammetry," Energy, Elsevier, vol. 35(12), pages 4802-4811.
    23. repec:eee:renene:v:125:y:2018:i:c:p:172-181 is not listed on IDEAS
    24. Sun, Xiaojing & Huang, Diangui & Wu, Guoqing, 2012. "The current state of offshore wind energy technology development," Energy, Elsevier, vol. 41(1), pages 298-312.
    25. Koukoura, Christina & Natarajan, Anand & Vesth, Allan, 2015. "Identification of support structure damping of a full scale offshore wind turbine in normal operation," Renewable Energy, Elsevier, vol. 81(C), pages 882-895.
    26. Peng Guo & David Infield, 2012. "Wind Turbine Tower Vibration Modeling and Monitoring by the Nonlinear State Estimation Technique (NSET)," Energies, MDPI, Open Access Journal, vol. 5(12), pages 1-15, December.
    27. Zhang, Mingming & Tan, Bin & Xu, Jianzhong, 2016. "Smart fatigue load control on the large-scale wind turbine blades using different sensing signals," Renewable Energy, Elsevier, vol. 87(P1), pages 111-119.
    28. García Márquez, Fausto Pedro & Tobias, Andrew Mark & Pinar Pérez, Jesús María & Papaelias, Mayorkinos, 2012. "Condition monitoring of wind turbines: Techniques and methods," Renewable Energy, Elsevier, vol. 46(C), pages 169-178.
    29. Hameed, Z. & Ahn, S.H. & Cho, Y.M., 2010. "Practical aspects of a condition monitoring system for a wind turbine with emphasis on its design, system architecture, testing and installation," Renewable Energy, Elsevier, vol. 35(5), pages 879-894.
    30. repec:eee:renene:v:123:y:2018:i:c:p:817-827 is not listed on IDEAS
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    More about this item

    Keywords

    offshore wind turbine; health monitoring system; feature information extraction; reliability analysis; safety evaluation;

    JEL classification:

    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
    • Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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