IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v227y2024ics0960148124005603.html
   My bibliography  Save this article

Numerical investigation of dynamic icing of wind turbine blades under wind shear conditions

Author

Listed:
  • Wang, Qiang
  • Yi, Xian
  • Liu, Yu
  • Ren, Jinghao
  • Yang, Jianjun
  • Chen, Ningli

Abstract

In the wind shear icing environment, the periodically varying inflow conditions experienced by wind turbine blades can significantly enhance the dynamic icing characteristics, which poses a great challenge to wind turbine icing research. To investigate this phenomenon, the Improved Multi-Shot Icing Computational Model (IMSICM) is utilized. In IMSICM, an efficient dynamic icing computational frame is designed by using the 3D Free Wake Lifting Line method coupled with the 2D Viscous and Inviscid Interaction method to calculate the flow field. Meanwhile, the Lagrangian method is applied to compute the water droplet impingement information and the Messinger Model is used to simulate the ice growth. After validation of IMSICM by the icing wind tunnel experimental results, the wind shear icing processes of the NREL 5 MW wind turbine under different wind shear conditions are analyzed. The results show that different from the linear growth behavior of Rime ice, the nonlinear features of Glaze ice development are significant. The wind shear effect has a greater impact on the Glaze ice shape, mainly manifested as the ice protrusions behind the main ice horn are suppressed. This phenomenon is mainly due to the combined effect of water impingement shadowing and heat transfer reduction.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:renene:v:227:y:2024:i:c:s0960148124005603
    DOI: 10.1016/j.renene.2024.120495
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124005603
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2024.120495?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. 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.
    2. Wang, Qiang & Xiao, Jingping & Zhang, Tingting & Yang, Jianjun & Shi, Yu, 2020. "A new wind turbine icing computational model based on Free Wake Lifting Line Model and Finite Area Method," Renewable Energy, Elsevier, vol. 146(C), pages 342-358.
    3. 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.
    4. Li, Jiale & Wang, Xuefei & Yu, Xiong (Bill), 2018. "Use of spatio-temporal calibrated wind shear model to improve accuracy of wind resource assessment," Applied Energy, Elsevier, vol. 213(C), pages 469-485.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Sun, Haoyang & Lin, Guiping & Jin, Haichuan & Guo, Jinghui & Ge, Kun & Wang, Jiaqi & He, Xi & Wen, Dongsheng, 2023. "2D Numerical investigation of surface wettability induced liquid water flow on the surface of the NACA0012 airfoil," Renewable Energy, Elsevier, vol. 205(C), pages 326-339.
    3. 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).
    4. 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.
    5. Fan Cai & Yuesong Jiang & Wanqing Song & Kai-Hung Lu & Tongbo Zhu, 2024. "Short-Term Wind Turbine Blade Icing Wind Power Prediction Based on PCA-fLsm," Energies, MDPI, vol. 17(6), pages 1-15, March.
    6. Chen, Wanqiu & Qiu, Yingning & Feng, Yanhui & Li, Ye & Kusiak, Andrew, 2021. "Diagnosis of wind turbine faults with transfer learning algorithms," Renewable Energy, Elsevier, vol. 163(C), pages 2053-2067.
    7. Han, Qinkai & Wang, Tianyang & Chu, Fulei, 2022. "Nonparametric copula modeling of wind speed-wind shear for the assessment of height-dependent wind energy in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    8. Crippa, Paola & Alifa, Mariana & Bolster, Diogo & Genton, Marc G. & Castruccio, Stefano, 2021. "A temporal model for vertical extrapolation of wind speed and wind energy assessment," Applied Energy, Elsevier, vol. 301(C).
    9. 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).
    10. Gualtieri, Giovanni, 2019. "A comprehensive review on wind resource extrapolation models applied in wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 215-233.
    11. Yang, Zihao & Dong, Sheng, 2024. "A novel framework for wind energy assessment at multi-time scale based on non-stationary wind speed models: A case study in China," Renewable Energy, Elsevier, vol. 226(C).
    12. Li, Jiale & Song, Zihao & Wang, Xuefei & Wang, Yanru & Jia, Yaya, 2022. "A novel offshore wind farm typhoon wind speed prediction model based on PSO–Bi-LSTM improved by VMD," Energy, Elsevier, vol. 251(C).
    13. 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.
    14. 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.
    15. Zhang, Jincheng & Zhao, Xiaowei, 2021. "Spatiotemporal wind field prediction based on physics-informed deep learning and LIDAR measurements," Applied Energy, Elsevier, vol. 288(C).
    16. Thanh-Cao Le & Tran-Huu-Tin Luu & Huu-Phuong Nguyen & Trung-Hau Nguyen & Duc-Duy Ho & Thanh-Canh Huynh, 2022. "Piezoelectric Impedance-Based Structural Health Monitoring of Wind Turbine Structures: Current Status and Future Perspectives," Energies, MDPI, vol. 15(15), pages 1-31, July.
    17. He, J.Y. & Li, Q.S. & Chan, P.W. & Zhao, X.D., 2023. "Assessment of future wind resources under climate change using a multi-model and multi-method ensemble approach," Applied Energy, Elsevier, vol. 329(C).
    18. 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.
    19. 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.
    20. Guo, Peng & Infield, David, 2021. "Wind turbine blade icing detection with multi-model collaborative monitoring method," Renewable Energy, Elsevier, vol. 179(C), pages 1098-1105.

    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:227:y:2024:i:c:s0960148124005603. 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.