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An effect assessment and prediction method of ultrasonic de-icing for composite wind turbine blades

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  • Wang, Yibing
  • Xu, Yuanming
  • Lei, Yuyong

Abstract

Wind turbines operating in cold and moist climates often suffer from icing events. Ice accretion on wind turbine blades threatens safe operation of wind turbines. Additionally, this phenomenon results in deterioration in power performance, which undoubtedly leads to economic losses. Ultrasonic guided wave anti-/de-icing technology has advantages of low energy consumption, light weight and low cost. However, there are few systematic methods to evaluate the de-icing effect of ultrasonic de-icing system on composite wind turbine blades. In this paper, an integrated and systematic method for the assessment and prediction of ultrasonic de-icing effect for composite wind turbine blades was proposed. Firstly, the interface integrity extent (IIE) and its rate of change were defined to describe the ice de-bonding behavior. Secondly, the adhesive strength of ice on the composite surface was measured, and an ultrasonic de-icing experiment was carried out. Thirdly, the optimal frequency for this de-icing system was calculated, and the stress distribution in the interface was obtained using numerical simulations. Finally, after determining the rate of change of IIE and carrying out the parameter fitting, the method for the assessment and prediction of ultrasonic de-icing effect was established. This method provides guidance for the design of ultrasonic de-icing systems.

Suggested Citation

  • Wang, Yibing & Xu, Yuanming & Lei, Yuyong, 2018. "An effect assessment and prediction method of ultrasonic de-icing for composite wind turbine blades," Renewable Energy, Elsevier, vol. 118(C), pages 1015-1023.
    • Handle: RePEc:eee:renene:v:118:y:2018:i:c:p:1015-1023
    DOI: 10.1016/j.renene.2017.10.074
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    References listed on IDEAS

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    1. Wang, Zhenjun & Xu, Yuanming & Gu, Yuting, 2015. "A light lithium niobate transducer design and ultrasonic de-icing research for aircraft wing," Energy, Elsevier, vol. 87(C), pages 173-181.
    2. Kumar, Yogesh & Ringenberg, Jordan & Depuru, Soma Shekara & Devabhaktuni, Vijay K. & Lee, Jin Woo & Nikolaidis, Efstratios & Andersen, Brett & Afjeh, Abdollah, 2016. "Wind energy: Trends and enabling technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 209-224.
    3. Wang, Yibing & Xu, Yuanming & Huang, Qi, 2017. "Progress on ultrasonic guided waves de-icing techniques in improving aviation energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 638-645.
    4. Dalili, N. & Edrisy, A. & Carriveau, R., 2009. "A review of surface engineering issues critical to wind turbine performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(2), pages 428-438, February.
    5. Habibi, Hossein & Cheng, Liang & Zheng, Haitao & Kappatos, Vassilios & Selcuk, Cem & Gan, Tat-Hean, 2015. "A dual de-icing system for wind turbine blades combining high-power ultrasonic guided waves and low-frequency forced vibrations," Renewable Energy, Elsevier, vol. 83(C), pages 859-870.
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    Cited by:

    1. Dong, Xinghui & Gao, Di & Li, Jia & Jincao, Zhang & Zheng, Kai, 2020. "Blades icing identification model of wind turbines based on SCADA data," Renewable Energy, Elsevier, vol. 162(C), pages 575-586.
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    4. Madi, Ezieddin & Pope, Kevin & Huang, Weimin & Iqbal, Tariq, 2019. "A review of integrating ice detection and mitigation for wind turbine blades," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 269-281.
    5. Yang Zhao & Xi Wang & Qibin Zhou & Zhenxing Wang & Xiaoyan Bian, 2020. "Numerical Study of Lightning Protection of Wind Turbine Blade with De-Icing Electrical Heating System," Energies, MDPI, vol. 13(3), pages 1-11, February.
    6. Ruqaya Khammas & Heli Koivuluoto, 2022. "Durable Icephobic Slippery Liquid-Infused Porous Surfaces (SLIPS) Using Flame- and Cold-Spraying," Sustainability, MDPI, vol. 14(14), pages 1-21, July.
    7. Wang, Yibing & Xu, Yuanming & Su, Fei, 2020. "Damage accumulation model of ice detach behavior in ultrasonic de-icing technology," Renewable Energy, Elsevier, vol. 153(C), pages 1396-1405.
    8. Valery Okulov & Ivan Kabardin & Dmitry Mukhin & Konstantin Stepanov & Nastasia Okulova, 2021. "Physical De-Icing Techniques for Wind Turbine Blades," Energies, MDPI, vol. 14(20), pages 1-16, October.

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