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Assessing the IEC simplified fatigue load equations for small wind turbine blades: How simple is too simple?

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  • Evans, S.P.
  • Bradney, D.R.
  • Clausen, P.D.

Abstract

It is well known that wind turbine blades are fatigue critical, with much literature and methodologies available for assessing fatigue loading of large wind turbine blades. Little research effort has been directed at assessing the fatigue life of small wind turbines which operate at higher rotational speeds and are subject to highly unsteady aerodynamic loading. In this paper the simplified load model proposed in IEC 61400.2 is used to determine the fatigue life of a small 5 kW wind turbine blade. This estimated life is compared to that determined from both measured operational data and aeroelastic simulations. Fatigue life was estimated by the standard at 0.09 years, compared to 9.18 years from field measurements and 3.26 years found via aeroelastic simulations. All methods fell below the 20 year design life, with the standard over-conservative by a factor of 102 and 36 for measurements and simulations respectively. To the best of the authors' knowledge these three fatigue methods specified in the standard have not been quantitatively compared and assessed for small wind turbines. Results are of importance to small wind turbine developers as they seek best practice for determining blade fatigue life. Shortcomings of the IEC methodology are detailed and discussed.

Suggested Citation

  • Evans, S.P. & Bradney, D.R. & Clausen, P.D., 2018. "Assessing the IEC simplified fatigue load equations for small wind turbine blades: How simple is too simple?," Renewable Energy, Elsevier, vol. 127(C), pages 24-31.
    • Handle: RePEc:eee:renene:v:127:y:2018:i:c:p:24-31
    DOI: 10.1016/j.renene.2018.04.041
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    References listed on IDEAS

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    1. Evans, S.P. & Clausen, P.D., 2015. "Modelling of turbulent wind flow using the embedded Markov chain method," Renewable Energy, Elsevier, vol. 81(C), pages 671-678.
    2. Bashirzadeh Tabrizi, Amir & Whale, Jonathan & Lyons, Thomas & Urmee, Tania & Peinke, Joachim, 2017. "Modelling the structural loading of a small wind turbine at a highly turbulent site via modifications to the Kaimal turbulence spectra," Renewable Energy, Elsevier, vol. 105(C), pages 288-300.
    3. Jang, Yun Jung & Choi, Chan Woong & Lee, Jang Ho & Kang, Ki Weon, 2015. "Development of fatigue life prediction method and effect of 10-minute mean wind speed distribution on fatigue life of small wind turbine composite blade," Renewable Energy, Elsevier, vol. 79(C), pages 187-198.
    4. Dimitrov, Nikolay & Natarajan, Anand & Mann, Jakob, 2017. "Effects of normal and extreme turbulence spectral parameters on wind turbine loads," Renewable Energy, Elsevier, vol. 101(C), pages 1180-1193.
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    Cited by:

    1. Liu, Zhenqing & Wang, Yize & Nyangi, Patrice & Zhu, Zhiwen & Hua, Xugang, 2021. "Proposal of a novel GPU-accelerated lifetime optimization method for onshore wind turbine dampers under real wind distribution," Renewable Energy, Elsevier, vol. 168(C), pages 516-543.
    2. KC, Anup & Whale, Jonathan & Evans, Samuel P. & Clausen, Philip D., 2020. "An investigation of the impact of wind speed and turbulence on small wind turbine operation and fatigue loads," Renewable Energy, Elsevier, vol. 146(C), pages 87-98.
    3. Rakib, M.I. & Evans, S.P. & Clausen, P.D., 2020. "Measured gust events in the urban environment, a comparison with the IEC standard," Renewable Energy, Elsevier, vol. 146(C), pages 1134-1142.
    4. Monjardín-Gámez, José de Jesús & Campos-Amezcua, Rafael & Gómez-Martínez, Roberto & Sánchez-García, Raúl & Campos-Amezcua, Alfonso & Trujillo-Franco, Luis G. & Abundis-Fong, Hugo F., 2023. "Large eddy simulation and experimental study of the turbulence on wind turbines," Energy, Elsevier, vol. 273(C).

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