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A Review of Wind Turbine Icing and Anti/De-Icing Technologies

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  • Zhijin Zhang

    (Xuefeng Mountain Energy Equipment Safety National Observation and Research Station, Chongqing University, Chongqing 400044, China)

  • Hang Zhang

    (Xuefeng Mountain Energy Equipment Safety National Observation and Research Station, Chongqing University, Chongqing 400044, China)

  • Xu Zhang

    (Xuefeng Mountain Energy Equipment Safety National Observation and Research Station, Chongqing University, Chongqing 400044, China)

  • Qin Hu

    (Xuefeng Mountain Energy Equipment Safety National Observation and Research Station, Chongqing University, Chongqing 400044, China)

  • Xingliang Jiang

    (Xuefeng Mountain Energy Equipment Safety National Observation and Research Station, Chongqing University, Chongqing 400044, China)

Abstract

The development and utilization of clean energy is becoming more extensive, and wind power generation is one of the key points of this. Occasionally, wind turbines are faced with various extreme environmental impacts such as icing, lightning strikes and so on. In particular, the icing of wind turbines increases icing–wind loads, and results in a reduced power output. And blades broken down lead to large-area shutdown accidents caused by high-speed rotating, which seriously affects the reliability and equipment safety of wind power generation. Relevant institutions and researchers at home and abroad have carried out a lot of research on this. This paper summarizes the formation and influencing factors of wind turbine icing, the influence of icing on wind power generation, and defense technologies. First, it introduces the formation conditions and mechanisms of icing in wind farm regions and the relationship between meteorological and climatic characteristics and icing, and analyzes the key influence factors on icing. Then, the impact of icing on wind turbines is explained from the aspects of mechanical operation, the power curve, jeopardies and economic benefits. And then the monitoring and safety status of wind turbines icing is analyzed, which involves collecting the relevant research on anti-de-icing in wind power generation, introducing various anti/de-icing technologies, and analyzing the principle of icing defense. Finally, this paper summarizes wind turbine icing and its defense technologies, and puts forward the future research direction based on the existing problems of wind power generation icing.

Suggested Citation

  • Zhijin Zhang & Hang Zhang & Xu Zhang & Qin Hu & Xingliang Jiang, 2024. "A Review of Wind Turbine Icing and Anti/De-Icing Technologies," Energies, MDPI, vol. 17(12), pages 1-34, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:12:p:2805-:d:1410757
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    References listed on IDEAS

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    1. Sima Rastayesh & Lijia Long & John Dalsgaard Sørensen & Sebastian Thöns, 2019. "Risk Assessment and Value of Action Analysis for Icing Conditions of Wind Turbines Close to Highways," Energies, MDPI, vol. 12(14), pages 1-15, July.
    2. Mu, Zhongqiu & Guo, Wenfeng & Li, Yan & Tagawa, Kotaro, 2023. "Wind tunnel test of ice accretion on blade airfoil for wind turbine under offshore atmospheric condition," Renewable Energy, Elsevier, vol. 209(C), pages 42-52.
    3. Hacıefendioğlu, Kemal & Başağa, Hasan Basri & Yavuz, Zafer & Karimi, Mohammad Tordi, 2022. "Intelligent ice detection on wind turbine blades using semantic segmentation and class activation map approaches based on deep learning method," Renewable Energy, Elsevier, vol. 182(C), pages 1-16.
    4. Daniliuk, Vladislav & Xu, Yuanming & Liu, Ruobing & He, Tianpeng & Wang, Xi, 2020. "Ultrasonic de-icing of wind turbine blades: Performance comparison of perspective transducers," Renewable Energy, Elsevier, vol. 145(C), pages 2005-2018.
    5. Owusu, Kwadwo Poku & Kuhn, David C.S. & Bibeau, Eric L., 2013. "Capacitive probe for ice detection and accretion rate measurement: Proof of concept," Renewable Energy, Elsevier, vol. 50(C), pages 196-205.
    6. Lijun Zhang & Kai Liu & Yufeng Wang & Zachary Bosire Omariba, 2018. "Ice Detection Model of Wind Turbine Blades Based on Random Forest Classifier," Energies, MDPI, vol. 11(10), pages 1-15, September.
    7. Wang, Qiang & Yi, Xian & Liu, Yu & Ren, Jinghao & Li, Weihao & Wang, Qiao & Lai, Qingren, 2020. "Simulation and analysis of wind turbine ice accretion under yaw condition via an Improved Multi-Shot Icing Computational Model," Renewable Energy, Elsevier, vol. 162(C), pages 1854-1873.
    8. Chang Cai & Jicai Guo & Xiaowen Song & Yanfeng Zhang & Jianxin Wu & Shufeng Tang & Yan Jia & Zhitai Xing & Qing’an Li, 2023. "Review of Data-Driven Approaches for Wind Turbine Blade Icing Detection," Sustainability, MDPI, vol. 15(2), pages 1-20, January.
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