IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v127y2018icp24-31.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096014811830449X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2018.04.041?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Paduano, Bruno & Parrinello, Luca & Niosi, Francesco & Dell’Edera, Oronzo & Sirigu, Sergej Antonello & Faedo, Nicolás & Mattiazzo, Giuliana, 2024. "Towards standardised design of wave energy converters: A high-fidelity modelling approach," Renewable Energy, Elsevier, vol. 224(C).
    5. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Liang Lu & Minyan Zhu & Haijun Wu & Jianzhong Wu, 2022. "A Review and Case Analysis on Biaxial Synchronous Loading Technology and Fast Moment-Matching Methods for Fatigue Tests of Wind Turbine Blades," Energies, MDPI, vol. 15(13), pages 1-34, July.
    3. Fan Zhang & Juchuan Dai & Deshun Liu & Linxing Li & Xin Long, 2019. "Investigation of the Pitch Load of Large-Scale Wind Turbines Using Field SCADA Data," Energies, MDPI, vol. 12(3), pages 1-20, February.
    4. Hocaoglu, Fatih Onur & Serttas, Fatih, 2017. "A novel hybrid (Mycielski-Markov) model for hourly solar radiation forecasting," Renewable Energy, Elsevier, vol. 108(C), pages 635-643.
    5. Murthy, K.S.R. & Rahi, O.P., 2017. "A comprehensive review of wind resource assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1320-1342.
    6. Lu, Liang & Wu, Haijun & Wu, Jianzhong, 2021. "A case study for the optimization of moment-matching in wind turbine blade fatigue tests with a resonant type exciting approach," Renewable Energy, Elsevier, vol. 174(C), pages 769-785.
    7. Liu, Lei & Shi, Yu & Zhang, Zhe & Zhang, Kang & Hu, Fei, 2023. "Analysis of turbulence intensity in the megacity of Beijing by High-frequency observations on a 325-m Tower," Renewable Energy, Elsevier, vol. 217(C).
    8. Daniel Micallef & Gerard Van Bussel, 2018. "A Review of Urban Wind Energy Research: Aerodynamics and Other Challenges," Energies, MDPI, vol. 11(9), pages 1-27, August.
    9. Stanislawski, Brooke J. & Thedin, Regis & Sharma, Ashesh & Branlard, Emmanuel & Vijayakumar, Ganesh & Sprague, Michael A., 2023. "Effect of the integral length scales of turbulent inflows on wind turbine loads," Renewable Energy, Elsevier, vol. 217(C).
    10. Meng, Hang & Lien, Fue-Sang & Li, Li, 2018. "Elastic actuator line modelling for wake-induced fatigue analysis of horizontal axis wind turbine blade," Renewable Energy, Elsevier, vol. 116(PA), pages 423-437.
    11. Shitang Ke & Lu Xu & Tongguang Wang, 2019. "Aerodynamic Performance and Wind-Induced Responses of Large Wind Turbine Systems with Meso-Scale Typhoon Effects," Energies, MDPI, vol. 12(19), pages 1-24, September.
    12. KC, Anup & Whale, Jonathan & Urmee, Tania, 2019. "Urban wind conditions and small wind turbines in the built environment: A review," Renewable Energy, Elsevier, vol. 131(C), pages 268-283.
    13. Ren, Guorui & Liu, Jinfu & Wan, Jie & Li, Fei & Guo, Yufeng & Yu, Daren, 2018. "The analysis of turbulence intensity based on wind speed data in onshore wind farms," Renewable Energy, Elsevier, vol. 123(C), pages 756-766.
    14. Liu, Zhenqing & Diao, Zheng & Ishihara, Takeshi, 2019. "Study of the flow fields over simplified topographies with different roughness conditions using large eddy simulations," Renewable Energy, Elsevier, vol. 136(C), pages 968-992.
    15. Dai, S.F. & Liu, H.J. & Chu, Y.J. & Lam, H.F. & Peng, H.Y., 2022. "Impact of corner modification on wind characteristics and wind energy potential over flat roofs of tall buildings," Energy, Elsevier, vol. 241(C).
    16. Khazaee, Meghdad & Derian, Pierre & Mouraud, Anthony, 2022. "A comprehensive study on Structural Health Monitoring (SHM) of wind turbine blades by instrumenting tower using machine learning methods," Renewable Energy, Elsevier, vol. 199(C), pages 1568-1579.
    17. Guo, Feng & Mann, Jakob & Peña, Alfredo & Schlipf, David & Cheng, Po Wen, 2022. "The space-time structure of turbulence for lidar-assisted wind turbine control," Renewable Energy, Elsevier, vol. 195(C), pages 293-310.
    18. 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.
    19. Battisti, L. & Benini, E. & Brighenti, A. & Dell’Anna, S. & Raciti Castelli, M., 2018. "Small wind turbine effectiveness in the urban environment," Renewable Energy, Elsevier, vol. 129(PA), pages 102-113.
    20. Jianxiong Gao & Zongwen An & Haixia Kou, 2018. "Fatigue life prediction of wind turbine rotor blade composites considering the combined effects of stress amplitude and mean stress," Journal of Risk and Reliability, , vol. 232(6), pages 598-606, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:127:y:2018:i:c:p:24-31. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.