IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v252y2025ics0960148125011942.html

Wake characteristics of wind turbine in anisotropic terrain based on field experiment combined with LES

Author

Listed:
  • Xu, Zongyuan
  • Gao, Xiaoxia
  • Zhu, Yuting
  • Gong, Xiaoyu
  • Han, Zhonghe
  • Zhu, Xiaoxun
  • Wang, Yu
  • Zhao, Wensheng

Abstract

Due to the complexity of the terrain-wake coupling effect, accurate evaluation of wake characteristics is critical for power production and the safety of complex terrain wind farms. This study delves into the wake characteristics (wake velocity field, wake deficit, and wake expansion) in different terrain conditions combined LiDAR-based field experiment with large eddy simulation (LES). LES was conducted to investigate the influence of pressure gradient and turbulence intensity on the wake development and decouple the terrain effect on the turbine wake. Several commonly used models for wake centerline and wake expansion are evaluated by the field measured data. Theoretical analysis for the results of multi-methodology indicates that the unfavorable pressure gradient has a great influence on the wake structure and wake velocity deficit in leeward slope cases. In addition to the impact of atmospheric coherent turbulence, the terrain inducement effect makes the wake meandering characteristics more remarkable. Turbulent kinetic energy analysis reveals that stronger turbulence intensity in the upper wake layer exacerbates the vertical asymmetry of wake velocity. This study provides better guidance for control strategies and power enhancement of wind turbines in complex terrain.

Suggested Citation

  • Xu, Zongyuan & Gao, Xiaoxia & Zhu, Yuting & Gong, Xiaoyu & Han, Zhonghe & Zhu, Xiaoxun & Wang, Yu & Zhao, Wensheng, 2025. "Wake characteristics of wind turbine in anisotropic terrain based on field experiment combined with LES," Renewable Energy, Elsevier, vol. 252(C).
  • Handle: RePEc:eee:renene:v:252:y:2025:i:c:s0960148125011942
    DOI: 10.1016/j.renene.2025.123532
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148125011942
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2025.123532?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Zhenqing & Diao, Zheng & Ishihara, Takeshi, 2019. "Study of the flow fields over simplified topographies with different roughness conditions using large eddy simulations," Renewable Energy, Elsevier, vol. 136(C), pages 968-992.
    2. Chen, Yao & Yan, Bowen & Yu, Meng & Huang, Guoqing & Qian, Guowei & Yang, Qingshan & Zhang, Kai & Mo, Ruiyu, 2025. "Wind tunnel study of wind turbine wake characteristics over two-dimensional hill considering the effects of terrain slope and turbine position," Applied Energy, Elsevier, vol. 380(C).
    3. Wang, Tengyuan & Cai, Chang & Wang, Xinbao & Wang, Zekun & Chen, Yewen & Song, Juanjuan & Xu, Jianzhong & Zhang, Yuning & Li, Qingan, 2023. "A new Gaussian analytical wake model validated by wind tunnel experiment and LiDAR field measurements under different turbulent flow," Energy, Elsevier, vol. 271(C).
    4. Yang, Qingshan & Zhang, Xingxin & Li, Tian & Law, Siu-seong & Zhou, Xuhong & Lu, Dawei, 2025. "Study on wind turbine wake effect and analytical model in hilly terrain," Renewable Energy, Elsevier, vol. 244(C).
    5. Pata, Ugur Korkut, 2025. "How to progress towards sustainable development by leveraging renewable energy sources, technological advances, and human capital," Renewable Energy, Elsevier, vol. 241(C).
    6. Torres Garcia, E. & Aubrun, S. & Coupiac, O. & Girard, N. & Boquet, M., 2019. "Statistical characteristics of interacting wind turbine wakes from a 7-month LiDAR measurement campaign," Renewable Energy, Elsevier, vol. 130(C), pages 1-11.
    7. Dangi, Nirav & Sodja, Jurij & Ferreira, Carlos Simão & Yu, Wei, 2025. "The effect of turbulent coherent structures in atmospheric flow on wind turbine loads," Renewable Energy, Elsevier, vol. 241(C).
    8. He, Ruiyang & Yang, Hongxing & Sun, Haiying & Gao, Xiaoxia, 2021. "A novel three-dimensional wake model based on anisotropic Gaussian distribution for wind turbine wakes," Applied Energy, Elsevier, vol. 296(C).
    9. Xu, Zongyuan & Gao, Xiaoxia & Zhang, Huanqiang & Lv, Tao & Han, Zhonghe & Zhu, Xiaoxun & Wang, Yu, 2023. "Analysis of the anisotropy aerodynamic characteristics of downstream wind turbine considering the 3D wake expansion based on coupling method," Energy, Elsevier, vol. 263(PD).
    10. Fan, Shuanglong & Liu, Zhenqing, 2025. "Investigation of fully coupled wind field simulations in complex terrain wind farms considering automatic upwind control of turbines," Renewable Energy, Elsevier, vol. 239(C).
    11. Brogna, Roberto & Feng, Ju & Sørensen, Jens Nørkær & Shen, Wen Zhong & Porté-Agel, Fernando, 2020. "A new wake model and comparison of eight algorithms for layout optimization of wind farms in complex terrain," Applied Energy, Elsevier, vol. 259(C).
    12. Sun, Haiying & Yang, Hongxing & Gao, Xiaoxia, 2023. "Investigation into wind turbine wake effect on complex terrain," Energy, Elsevier, vol. 269(C).
    13. Hongtao Niu & Congxin Yang & Yin Wang, 2023. "Experimental Study on the Influence of Incoming Flow on Wind Turbine Power and Wake Based on Wavelet Analysis," Energies, MDPI, vol. 16(16), pages 1-15, August.
    14. Gao, Xiaoxia & Chen, Yao & Xu, Shinai & Gao, Wei & Zhu, Xiaoxun & Sun, Haiying & Yang, Hongxing & Han, Zhonghe & Wang, Yu & Lu, Hao, 2022. "Comparative experimental investigation into wake characteristics of turbines in three wind farms areas with varying terrain complexity from LiDAR measurements," Applied Energy, Elsevier, vol. 307(C).
    15. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
    16. Zhang, Shaohai & Gao, Xiaoxia & Ma, Wanli & Lu, Hongkun & Lv, Tao & Xu, Shinai & Zhu, Xiaoxun & Sun, Haiying & Wang, Yu, 2023. "Derivation and verification of three-dimensional wake model of multiple wind turbines based on super-Gaussian function," Renewable Energy, Elsevier, vol. 215(C).
    17. Arslan Salim Dar & Fernando Porté-Agel, 2022. "An Analytical Model for Wind Turbine Wakes under Pressure Gradient," Energies, MDPI, vol. 15(15), pages 1-13, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lu, Hongkun & Gao, Xiaoxia & Xu, Zongyuan & Xiao, Huan & Gao, Yihan & Zhang, Huanqiang & Ma, Hongyu & Zhu, Yuting & Zhu, Xiaoxun & Wang, Yu, 2025. "Wind direction prediction combined with wind speed in a wind farm," Energy, Elsevier, vol. 333(C).

    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. Zhang, Ziyu & Huang, Peng & Bitsuamlak, Girma & Cao, Shuyang, 2024. "Large-eddy simulation of upwind-hill effects on wind-turbine wakes and power performance," Energy, Elsevier, vol. 294(C).
    2. Xu, Zongyuan & Gao, Xiaoxia & Zhang, Huanqiang & Lu, Hongkun & Han, Zhonghe & Zhu, Xiaoxun & Wang, Yu & Zhao, Wensheng, 2025. "Coupled effects of 3D wake expansion and terrain anisotropy on downstream wind turbine power performance and fatigue load," Energy, Elsevier, vol. 334(C).
    3. Wang, Tengyuan & Cai, Chang & Liu, Junbo & Peng, Chaoyi & Wang, Yibo & Sun, Xiangyu & Zhong, Xiaohui & Zhang, Jingjing & Li, Qingan, 2024. "Wake characteristics and vortex structure evolution of floating offshore wind turbine under surge motion," Energy, Elsevier, vol. 302(C).
    4. Chen, Yao & Yan, Bowen & Yu, Meng & Huang, Guoqing & Qian, Guowei & Yang, Qingshan & Zhang, Kai & Mo, Ruiyu, 2025. "Wind tunnel study of wind turbine wake characteristics over two-dimensional hill considering the effects of terrain slope and turbine position," Applied Energy, Elsevier, vol. 380(C).
    5. Amiri, Mojtaba Maali & Shadman, Milad & Estefen, Segen F., 2024. "A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    6. Zhang, Shaohai & Duan, Huanfeng & Lu, Lin & He, Ruiyang & Gao, Xiaoxia & Zhu, Songye, 2024. "Quantification of three-dimensional added turbulence intensity for the horizontal-axis wind turbine considering the wake anisotropy," Energy, Elsevier, vol. 294(C).
    7. Bowen Yan & Shuangchen Tang & Meng Yu & Guowei Qian & Yao Chen, 2025. "Atmospheric Turbulence Effects on Wind Turbine Wakes over Two-Dimensional Hill: A Wind Tunnel Study," Energies, MDPI, vol. 18(11), pages 1-16, May.
    8. Wang, Tengyuan & Cai, Chang & Wang, Xinbao & Wang, Zekun & Chen, Yewen & Song, Juanjuan & Xu, Jianzhong & Zhang, Yuning & Li, Qingan, 2023. "A new Gaussian analytical wake model validated by wind tunnel experiment and LiDAR field measurements under different turbulent flow," Energy, Elsevier, vol. 271(C).
    9. Yang, Qingshan & Zhang, Xingxin & Li, Tian & Law, Siu-seong & Zhou, Xuhong & Lu, Dawei, 2025. "Study on wind turbine wake effect and analytical model in hilly terrain," Renewable Energy, Elsevier, vol. 244(C).
    10. Xiaoxia, Gao & Luqing, Li & Shaohai, Zhang & Xiaoxun, Zhu & Haiying, Sun & Hongxing, Yang & Yu, Wang & Hao, Lu, 2022. "LiDAR-based observation and derivation of large-scale wind turbine's wake expansion model downstream of a hill," Energy, Elsevier, vol. 259(C).
    11. Lu, Hongkun & Gao, Xiaoxia & Xu, Zongyuan & Xiao, Huan & Gao, Yihan & Zhang, Huanqiang & Ma, Hongyu & Zhu, Yuting & Zhu, Xiaoxun & Wang, Yu, 2025. "Wind direction prediction combined with wind speed in a wind farm," Energy, Elsevier, vol. 333(C).
    12. He, Guifeng & Sun, Haiying & He, Ruiyang, 2026. "A novel analytical wake model for floating offshore wind turbines with pitch motion effects," Renewable Energy, Elsevier, vol. 256(PD).
    13. Zhang, Shaohai & Gao, Xiaoxia & Ma, Wanli & Lu, Hongkun & Lv, Tao & Xu, Shinai & Zhu, Xiaoxun & Sun, Haiying & Wang, Yu, 2023. "Derivation and verification of three-dimensional wake model of multiple wind turbines based on super-Gaussian function," Renewable Energy, Elsevier, vol. 215(C).
    14. Wang, Bingchen & Ding, Lifu & Xiao, Tannan & Chen, Ying & Lu, Qiuyu, 2025. "A novel analytical wake model for mountain wind farms considering variable surface roughness and wake effects of near-middle region," Renewable Energy, Elsevier, vol. 243(C).
    15. Fan, Shuanglong & Liu, Zhenqing, 2025. "Investigation of fully coupled wind field simulations in complex terrain wind farms considering automatic upwind control of turbines," Renewable Energy, Elsevier, vol. 239(C).
    16. Shen, Wen Zhong & Lin, Jian Wei & Jiang, Yu Hang & Feng, Ju & Cheng, Li & Zhu, Wei Jun, 2023. "A novel yaw wake model for wind farm control applications," Renewable Energy, Elsevier, vol. 218(C).
    17. Zilong, Ti & Xiao Wei, Deng, 2022. "Layout optimization of offshore wind farm considering spatially inhomogeneous wave loads," Applied Energy, Elsevier, vol. 306(PA).
    18. Wang, Mingwei & Zhang, Mingming & Qin, Caiyan & Sun, Haiying & Deng, Xiaowei, 2026. "A data-driven double-Gaussian wake model reflecting the wake evolution process," Renewable Energy, Elsevier, vol. 257(C).
    19. Duan, Guiyue & Gattari, Daniele & Porté-Agel, Fernando, 2025. "Theoretical and experimental study on power performance and wake characteristics of a floating wind turbine under pitch motion," Applied Energy, Elsevier, vol. 378(PA).
    20. Li, Rui & Zhang, Jincheng & Zhao, Xiaowei, 2022. "Dynamic wind farm wake modeling based on a Bilateral Convolutional Neural Network and high-fidelity LES data," Energy, Elsevier, vol. 258(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:252:y:2025:i:c:s0960148125011942. 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.