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Proposal of fully-coupled actuated disk model for wind turbine operation modeling in turbulent flow field due to complex topography

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  • Fan, Shuanglong
  • Liu, Zhenqing

Abstract

The wind speed and direction of flow fields in the time and space domains are complicated owing to topographic relief, and it is not yet known how time-varying incoming wind speed and automatic windward effect interact with the wake characteristics of wind turbines. To address this, semi-coupled ADM-SR model (SR model) and a fully coupled ADM-DR model (DR model) are proposed in this study. The wakes of wind turbines located at various locations on the slant ridge were then compared. The wake velocity deficit of the wind turbines using the SR and DR models were found to be up to 40% and 20% upstream of the ridge, respectively, with large variations. Downstream, the wind turbine wakes of both models were similar. The DR model with the automatic windward orientation caused the wind turbine actuator disk to rotate by 9.24° and 7.40° perpendicular to the tangential direction of the streamline, and the accuracy of the control procedure was verified. Furthermore, the lower the turbulence intensity, the greater the difference between the predictions of the two models, and the power prediction value of the DR model was approximately 80% higher than that of the SR model.

Suggested Citation

  • Fan, Shuanglong & Liu, Zhenqing, 2023. "Proposal of fully-coupled actuated disk model for wind turbine operation modeling in turbulent flow field due to complex topography," Energy, Elsevier, vol. 284(C).
    • Handle: RePEc:eee:energy:v:284:y:2023:i:c:s0360544223019035
    DOI: 10.1016/j.energy.2023.128509
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    References listed on IDEAS

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    Cited by:

    1. Hu, Weicheng & Liu, Zhenqing & Li, Tian & Deng, Yangchen & Guo, Wenjie, 2025. "A double Gaussian wake model for single and multiple yawed wind turbines," Energy, Elsevier, vol. 324(C).
    2. 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).
    3. Meng, Hang & Chen, Tao & Chen, Xiaodong & Ge, Mingwei & Han, Yunzhou & Liu, Yongqian, 2024. "Simplified Polynomial-asymptotic-distribution Actuator Disc (SPAD) method for wind turbine wake simulation based on k-ϵ-fP turbulence model," Renewable Energy, Elsevier, vol. 236(C).
    4. Zhang, Guodao & Zhou, Haijun & Ge, Yisu & Magabled, Sharafzher M. & Abbas, Mohamed & Pan, Xiaotian & Ponnore, Joffin Jose & Asilza, Hamd & Liu, Jian & Yang, Yanhong, 2024. "Enhancing on-grid renewable energy systems: Optimal configuration and diverse design strategies," Renewable Energy, Elsevier, vol. 235(C).
    5. 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).
    6. Zhang, Dayu & Chai, Kaixin & Guo, Penghua & Hu, Qiao & Li, Jingyin & Shams, Ayesha, 2024. "A novel full-process test bench for deep-sea in-situ power generation systems," Energy, Elsevier, vol. 297(C).

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