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A Review on Failure Modes of Wind Turbine Components

Author

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  • Abdul Ghani Olabi

    (Department of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
    Mechanical Engineering and Design, School of Engineering and Applied Science, Aston University, Aston Triangle, Birmingham B4 7ET, UK)

  • Tabbi Wilberforce

    (Mechanical Engineering and Design, School of Engineering and Applied Science, Aston University, Aston Triangle, Birmingham B4 7ET, UK)

  • Khaled Elsaid

    (Chemical Engineering Program, Texas A&M University at Qatar, Doha 23874, Qatar)

  • Enas Taha Sayed

    (Centre for Advanced Materials Research, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
    Chemical Engineering Department, Faculty of Engineering, Minia University, Minya 61519, Egypt)

  • Tareq Salameh

    (Department of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates)

  • Mohammad Ali Abdelkareem

    (Department of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
    Centre for Advanced Materials Research, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
    Chemical Engineering Department, Faculty of Engineering, Minia University, Minya 61519, Egypt)

  • Ahmad Baroutaji

    (Department of Mechanical Engineering, University of Wolverhampton, Wulfruna St, Wolverhampton WV1 1LY, UK)

Abstract

To meet the increasing energy demand, renewable energy is considered the best option. Its patronage is being encouraged by both the research and industrial community. The main driving force for most renewable systems is solar energy. It is abundant and pollutant free compared to fossil products. Wind energy is also considered an abundant medium of energy generation and often goes hand in hand with solar energy. The last few decades have seen a sudden surge in wind energy compared to solar energy due to most wind energy systems being cost effective compared to solar energy. Wind turbines are often categorised as large or small depending on their application and energy generation output. Sustainable materials for construction of different parts of wind turbines are being encouraged to lower the cost of the system. The turbine blades and generators perform crucial roles in the overall operation of the turbines; hence, their material composition is very critical. Today, most turbine blades are made up of natural fiber-reinforced polymer (NFRP) as well as glass fiber-reinforced polymer (GFRP). Others are also made from wood and some metallic materials. Each of the materials introduced has specific characteristics that affect the system’s efficiency. This investigation explores the influence of these materials on turbine efficiency. Observations have shown that composites reinforced with nanomaterials have excellent mechanical characteristics. Carbon nanotubes have unique characteristics that may make them valuable in wind turbine blades in the future. It is possible to strengthen carbon nanotubes with various kinds of resins to get a variety of different characteristics. Similarly, the end-of-life treatment methods for composite materials is also presented.

Suggested Citation

  • Abdul Ghani Olabi & Tabbi Wilberforce & Khaled Elsaid & Enas Taha Sayed & Tareq Salameh & Mohammad Ali Abdelkareem & Ahmad Baroutaji, 2021. "A Review on Failure Modes of Wind Turbine Components," Energies, MDPI, vol. 14(17), pages 1-44, August.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:17:p:5241-:d:620905
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    References listed on IDEAS

    as
    1. Lin, Yonggang & Tu, Le & Liu, Hongwei & Li, Wei, 2016. "Fault analysis of wind turbines in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 482-490.
    2. Hayashi, Daisuke & Huenteler, Joern & Lewis, Joanna I., 2018. "Gone with the wind: A learning curve analysis of China's wind power industry," Energy Policy, Elsevier, vol. 120(C), pages 38-51.
    3. Peng Guo & Nan Bai, 2011. "Wind Turbine Gearbox Condition Monitoring with AAKR and Moving Window Statistic Methods," Energies, MDPI, vol. 4(11), pages 1-17, November.
    4. Elia, A. & Taylor, M. & Ó Gallachóir, B. & Rogan, F., 2020. "Wind turbine cost reduction: A detailed bottom-up analysis of innovation drivers," Energy Policy, Elsevier, vol. 147(C).
    5. Neij, Lena, 2008. "Cost development of future technologies for power generation--A study based on experience curves and complementary bottom-up assessments," Energy Policy, Elsevier, vol. 36(6), pages 2200-2211, June.
    6. Abdallah, I. & Natarajan, A. & Sørensen, J.D., 2015. "Impact of uncertainty in airfoil characteristics on wind turbine extreme loads," Renewable Energy, Elsevier, vol. 75(C), pages 283-300.
    7. Tanveer, Waqas Hassan & Abdelkareem, Mohammad Ali & Kolosz, Ben W. & Rezk, Hegazy & Andresen, John & Cha, Suk Won & Sayed, Enas Taha, 2021. "The role of vacuum based technologies in solid oxide fuel cell development to utilize industrial waste carbon for power production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
    8. Kavlak, Goksin & McNerney, James & Trancik, Jessika E., 2018. "Evaluating the causes of cost reduction in photovoltaic modules," Energy Policy, Elsevier, vol. 123(C), pages 700-710.
    9. Xiyun Yang & Jinxia Li & Wei Liu & Peng Guo, 2011. "Petri Net Model and Reliability Evaluation for Wind Turbine Hydraulic Variable Pitch Systems," Energies, MDPI, vol. 4(6), pages 1-20, June.
    10. Yu, Yang & Li, Hong & Che, Yuyuan & Zheng, Qiongjie, 2017. "The price evolution of wind turbines in China: A study based on the modified multi-factor learning curve," Renewable Energy, Elsevier, vol. 103(C), pages 522-536.
    11. Chehouri, Adam & Younes, Rafic & Ilinca, Adrian & Perron, Jean, 2015. "Review of performance optimization techniques applied to wind turbines," Applied Energy, Elsevier, vol. 142(C), pages 361-388.
    12. Shen, Xin & Zhu, Xiaocheng & Du, Zhaohui, 2011. "Wind turbine aerodynamics and loads control in wind shear flow," Energy, Elsevier, vol. 36(3), pages 1424-1434.
    13. Kusiak, Andrew & Li, Wenyan, 2011. "The prediction and diagnosis of wind turbine faults," Renewable Energy, Elsevier, vol. 36(1), pages 16-23.
    14. Kusiak, Andrew & Zhang, Zijun & Verma, Anoop, 2013. "Prediction, operations, and condition monitoring in wind energy," Energy, Elsevier, vol. 60(C), pages 1-12.
    15. Qiu, Yueming & Anadon, Laura D., 2012. "The price of wind power in China during its expansion: Technology adoption, learning-by-doing, economies of scale, and manufacturing localization," Energy Economics, Elsevier, vol. 34(3), pages 772-785.
    16. Luz, Thiago & Moura, Pedro, 2019. "100% Renewable energy planning with complementarity and flexibility based on a multi-objective assessment," Applied Energy, Elsevier, vol. 255(C).
    17. Levitt, Andrew C. & Kempton, Willett & Smith, Aaron P. & Musial, Walt & Firestone, Jeremy, 2011. "Pricing offshore wind power," Energy Policy, Elsevier, vol. 39(10), pages 6408-6421, October.
    18. Yang, Ruizhen & He, Yunze & Zhang, Hong, 2016. "Progress and trends in nondestructive testing and evaluation for wind turbine composite blade," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1225-1250.
    19. McNerney, James & Doyne Farmer, J. & Trancik, Jessika E., 2011. "Historical costs of coal-fired electricity and implications for the future," Energy Policy, Elsevier, vol. 39(6), pages 3042-3054, June.
    20. 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.
    21. Li, He & Diaz, H. & Guedes Soares, C., 2021. "A developed failure mode and effect analysis for floating offshore wind turbine support structures," Renewable Energy, Elsevier, vol. 164(C), pages 133-145.
    22. Clarke, Leon & Weyant, John & Edmonds, Jae, 2008. "On the sources of technological change: What do the models assume," Energy Economics, Elsevier, vol. 30(2), pages 409-424, March.
    23. Lin, Boqiang & He, Jiaxin, 2016. "Learning curves for harnessing biomass power: What could explain the reduction of its cost during the expansion of China?," Renewable Energy, Elsevier, vol. 99(C), pages 280-288.
    24. Candelise, Chiara & Winskel, Mark & Gross, Robert J.K., 2013. "The dynamics of solar PV costs and prices as a challenge for technology forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 96-107.
    25. Karthikeyan, N. & Kalidasa Murugavel, K. & Arun Kumar, S. & Rajakumar, S., 2015. "Review of aerodynamic developments on small horizontal axis wind turbine blade," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 801-822.
    26. Samadi, Sascha, 2018. "The experience curve theory and its application in the field of electricity generation technologies – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2346-2364.
    27. Kress, C. & Chokani, N. & Abhari, R.S., 2015. "Downwind wind turbine yaw stability and performance," Renewable Energy, Elsevier, vol. 83(C), pages 1157-1165.
    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. Staffell, Iain & Green, Richard, 2014. "How does wind farm performance decline with age?," Renewable Energy, Elsevier, vol. 66(C), pages 775-786.
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