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A dual de-icing system for wind turbine blades combining high-power ultrasonic guided waves and low-frequency forced vibrations

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  • Habibi, Hossein
  • Cheng, Liang
  • Zheng, Haitao
  • Kappatos, Vassilios
  • Selcuk, Cem
  • Gan, Tat-Hean

Abstract

Wind turbines mounted on cold climate sites are subject to icing which could significantly influence the performance of the turbine blades for harvesting wind energy. In this study, an innovative dual de-icing system under development is described. This either prevents ice accumulation (anti-icing) or removes any ice layer present on the surface of the blade material (de-icing). A modelling study on ultrasonic guided waves propagating in composite blades was used to determine the optimal frequency and location of the transducers for ensuring wave propagation, causing the required level of energy concentration and resulting shear stress across the leading edge of the turbine's blade. In parallel, the effects of low frequency vibrations have been investigated through modal and harmonic analyses. This allowed specification and optimisation of the positioning of shaker(s), together with the magnitude and direction of harmonic forces required to induce sufficient acceleration to the blade surface for ice removal. An appropriate survey was also carried out to evaluate the potential for fatigue failure of the blade due to harmonic forces induced by shakers. The proposed technique configures and presents an active solution for the icing problem, allowing safe and reliable operation of wind turbines in adverse weather conditions.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:83:y:2015:i:c:p:859-870
    DOI: 10.1016/j.renene.2015.05.025
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    References listed on IDEAS

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    1. Kong, C. & Bang, J. & Sugiyama, Y., 2005. "Structural investigation of composite wind turbine blade considering various load cases and fatigue life," Energy, Elsevier, vol. 30(11), pages 2101-2114.
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    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.
    2. Sudhakar Gantasala & Jean-Claude Luneno & Jan-Olov Aidanpää, 2017. "Investigating How an Artificial Neural Network Model Can Be Used to Detect Added Mass on a Non-Rotating Beam Using Its Natural Frequencies: A Possible Application for Wind Turbine Blade Ice Detection," Energies, MDPI, vol. 10(2), pages 1-21, February.
    3. 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.
    4. Liu, Wenyi, 2016. "Design and kinetic analysis of wind turbine blade-hub-tower coupled system," Renewable Energy, Elsevier, vol. 94(C), pages 547-557.
    5. 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.
    6. Sun, Shilin & Wang, Tianyang & Chu, Fulei, 2022. "In-situ condition monitoring of wind turbine blades: A critical and systematic review of techniques, challenges, and futures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    7. Jiawei Jiang & Yizhou Shen & Yangjiangshan Xu & Zhen Wang & Jie Tao & Senyun Liu & Weilan Liu & Haifeng Chen, 2024. "An energy-free strategy to elevate anti-icing performance of superhydrophobic materials through interfacial airflow manipulation," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    8. Yan Li & He Shen & Wenfeng Guo, 2021. "Simulation and Experimental Study on the Ultrasonic Micro-Vibration De-Icing Method for Wind Turbine Blades," Energies, MDPI, vol. 14(24), pages 1-15, December.
    9. 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.
    10. Jiménez, Alfredo Arcos & García Márquez, Fausto Pedro & Moraleda, Victoria Borja & Gómez Muñoz, Carlos Quiterio, 2019. "Linear and nonlinear features and machine learning for wind turbine blade ice detection and diagnosis," Renewable Energy, Elsevier, vol. 132(C), pages 1034-1048.
    11. 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.
    12. Zeng, Jing & Song, Bingliang, 2017. "Research on experiment and numerical simulation of ultrasonic de-icing for wind turbine blades," Renewable Energy, Elsevier, vol. 113(C), pages 706-712.
    13. Dimitris Al. Katsaprakakis & Nikos Papadakis & Ioannis Ntintakis, 2021. "A Comprehensive Analysis of Wind Turbine Blade Damage," Energies, MDPI, vol. 14(18), pages 1-31, September.
    14. Kaewniam, Panida & Cao, Maosen & Alkayem, Nizar Faisal & Li, Dayang & Manoach, Emil, 2022. "Recent advances in damage detection of wind turbine blades: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    15. Chen, Bin & Yu, Songhao & Yu, Yang & Zhou, Yilin, 2020. "Acoustical damage detection of wind turbine blade using the improved incremental support vector data description," Renewable Energy, Elsevier, vol. 156(C), pages 548-557.
    16. Ma, Liqun & Zhang, Zichen & Gao, Linyue & Liu, Yang & Hu, Hui, 2020. "An exploratory study on using Slippery-Liquid-Infused-Porous-Surface (SLIPS) for wind turbine icing mitigation," Renewable Energy, Elsevier, vol. 162(C), pages 2344-2360.

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