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An experimental study on the aerodynamic performance degradation of a wind turbine blade model induced by ice accretion process

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  • Gao, Linyue
  • Liu, Yang
  • Zhou, Wenwu
  • Hu, Hui

Abstract

An experimental study was conducted to characterize aerodynamic performance degradation of wind turbine blades induced by dynamic ice accretion process. The experimental study was performed in an Icing Research Tunnel with a turbine blade model under a typical glaze icing condition. Ice structures were found to accrete rapidly over both the upper and lower surfaces of the blade model after starting the ice accretion experiment. Irregular-shaped ice structures were found to disturb the airflow around the blade model greatly, resulting in large-scale flow separations and shedding of unsteady vortex structures from the ice accreting surface. The aerodynamic performance of the blade model was found to degrade significantly. The performance degradation induced by the ice accretion was found to be a strong function of the angle of attack of the blade model with more significant degradations at lower angles of attack. For the test case at the angle of attack of 5.0°, while the lift decreases to only ∼12% of its original value after 600 s of the ice accretion experiment, the drag was found to increase 4.5 times correspondingly. The detailed flow field measurements were correlated with the aerodynamic force data to elucidate the underlying physics.

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  • Gao, Linyue & Liu, Yang & Zhou, Wenwu & Hu, Hui, 2019. "An experimental study on the aerodynamic performance degradation of a wind turbine blade model induced by ice accretion process," Renewable Energy, Elsevier, vol. 133(C), pages 663-675.
    • Handle: RePEc:eee:renene:v:133:y:2019:i:c:p:663-675
    DOI: 10.1016/j.renene.2018.10.032
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    References listed on IDEAS

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    1. Tomas Wallenius & Ville Lehtomäki, 2016. "Overview of cold climate wind energy: challenges, solutions, and future needs," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 5(2), pages 128-135, March.
    2. 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.
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    Cited by:

    1. Eleni Douvi & Dimitra Douvi, 2023. "Aerodynamic Characteristics of Wind Turbines Operating under Hazard Environmental Conditions: A Review," Energies, MDPI, vol. 16(22), pages 1-43, November.
    2. Gao, Linyue & Tao, Tao & Liu, Yongqian & Hu, Hui, 2021. "A field study of ice accretion and its effects on the power production of utility-scale wind turbines," Renewable Energy, Elsevier, vol. 167(C), pages 917-928.
    3. Gao, Linyue & Liu, Yang & Ma, Liqun & Hu, Hui, 2019. "A hybrid strategy combining minimized leading-edge electric-heating and superhydro-/ice-phobic surface coating for wind turbine icing mitigation," Renewable Energy, Elsevier, vol. 140(C), pages 943-956.
    4. Tao, Tao & Liu, Yongqian & Qiao, Yanhui & Gao, Linyue & Lu, Jiaoyang & Zhang, Ce & Wang, Yu, 2021. "Wind turbine blade icing diagnosis using hybrid features and Stacked-XGBoost algorithm," Renewable Energy, Elsevier, vol. 180(C), pages 1004-1013.
    5. Wang, Qiang & Yi, Xian & Liu, Yu & Ren, Jinghao & Yang, Jianjun & Chen, Ningli, 2024. "Numerical investigation of dynamic icing of wind turbine blades under wind shear conditions," Renewable Energy, Elsevier, vol. 227(C).
    6. 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.
    7. 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.
    8. Xu, Zhi & Zhang, Ting & Li, Xiaojuan & Li, Yan, 2023. "Effects of ambient temperature and wind speed on icing characteristics and anti-icing energy demand of a blade airfoil for wind turbine," Renewable Energy, Elsevier, vol. 217(C).
    9. Yan Li & Ce Sun & Yu Jiang & Fang Feng, 2019. "Scaling Method of the Rotating Blade of a Wind Turbine for a Rime Ice Wind Tunnel Test," Energies, MDPI, vol. 12(4), pages 1-15, February.
    10. Sun, Haoyang & Lin, Guiping & Jin, Haichuan & Bu, Xueqin & Cai, Chujiang & Jia, Qi & Ma, Kuiyuan & Wen, Dongsheng, 2021. "Experimental investigation of surface wettability induced anti-icing characteristics in an ice wind tunnel," Renewable Energy, Elsevier, vol. 179(C), pages 1179-1190.
    11. Tang, Xinzi & Yuan, Keren & Gu, Nengwei & Li, Pengcheng & Peng, Ruitao, 2022. "An interval quantification-based optimization approach for wind turbine airfoil under uncertainties," Energy, Elsevier, vol. 244(PA).

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