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Investigation of wake characteristic of a 30 kW rated power Horizontal Axis Wind Turbine with wake model and field measurement

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  • Li, Qing'an
  • Maeda, Takao
  • Kamada, Yasunari
  • Hiromori, Yuto

Abstract

A field measurement and wake model based on experimental data were introduced to investigate the wake characteristics of a HAWT (Horizontal Axis Wind Turbine) in a wind farm. In the present study, a HAWT generator of capacity 30 kW with the rotor diameter of 10.0 m was used. Firstly, the reference wind was measured with inflow measurement mast. And then, the wake flow was examined in the different tip speed ratios and pitch angles at the wind turbine wake position of x/D = 2.0 by ultrasonic anemometers, three-cup type anemometers and wind vane. Finally, the wake velocity distribution was predicted by the wake model with Gaussian function. As a result, the non-dimensional wind velocity ratio UNR reached the minimum value around y/R = 0.50 and increased as it went laterally away from y/R = 0.50. Furthermore, the non-dimensional wind velocity ratio UNR decreased with the increase of the pitch angle. When the pitch angles were 0°, 2° and 4°, the minimum UNR were about 0.77, 0.78 and 0.84 at the horizontal position of y/R = 0.5. Meanwhile, the full wake widths at half maximum of 1.04, 0.98 and 1.09 were obtained at the pitch angle of 0°. This study provided rich information for the prediction of annual power generation of the downstream wind turbine in wind farm.

Suggested Citation

  • Li, Qing'an & Maeda, Takao & Kamada, Yasunari & Hiromori, Yuto, 2018. "Investigation of wake characteristic of a 30 kW rated power Horizontal Axis Wind Turbine with wake model and field measurement," Applied Energy, Elsevier, vol. 225(C), pages 1190-1204.
    • Handle: RePEc:eee:appene:v:225:y:2018:i:c:p:1190-1204
    DOI: 10.1016/j.apenergy.2018.05.022
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    Cited by:

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    2. Wu, Guangxing & Zhang, Chaoyu & Cai, Chang & Yang, Ke & Shi, Kezhong, 2020. "Uncertainty prediction on the angle of attack of wind turbine blades based on the field measurements," Energy, Elsevier, vol. 200(C).
    3. Li, Qing'an & Cai, Chang & Kamada, Yasunari & Maeda, Takao & Hiromori, Yuto & Zhou, Shuni & Xu, Jianzhong, 2021. "Prediction of power generation of two 30 kW Horizontal Axis Wind Turbines with Gaussian model," Energy, Elsevier, vol. 231(C).
    4. Sun, Haiying & Gao, Xiaoxia & Yang, Hongxing, 2020. "Experimental study on wind speeds in a complex-terrain wind farm and analysis of wake effects," Applied Energy, Elsevier, vol. 272(C).
    5. Li, Qing'an & Xu, Jianzhong & Maeda, Takao & Kamada, Yasunari & Nishimura, Shogo & Wu, Guangxing & Cai, Chang, 2019. "Laser Doppler Velocimetry (LDV) measurements of airfoil surface flow on a Horizontal Axis Wind Turbine in boundary layer," Energy, Elsevier, vol. 183(C), pages 341-357.
    6. 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).
    7. Cheng, Yu & Zhang, Mingming & Zhang, Ziliang & Xu, Jianzhong, 2019. "A new analytical model for wind turbine wakes based on Monin-Obukhov similarity theory," Applied Energy, Elsevier, vol. 239(C), pages 96-106.
    8. Yanzhao Yang & Zhiping Guo & Qing Song & Yanfeng Zhang & Qing’an Li, 2018. "Effect of Blade Pitch Angle on the Aerodynamic Characteristics of a Straight-bladed Vertical Axis Wind Turbine Based on Experiments and Simulations," Energies, MDPI, vol. 11(6), pages 1-15, June.

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