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Comparative experimental investigation into wake characteristics of turbines in three wind farms areas with varying terrain complexity from LiDAR measurements

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  • Gao, Xiaoxia
  • Chen, Yao
  • Xu, Shinai
  • Gao, Wei
  • Zhu, Xiaoxun
  • Sun, Haiying
  • Yang, Hongxing
  • Han, Zhonghe
  • Wang, Yu
  • Lu, Hao

Abstract

Large-scale turbines’ wake expansion is influenced both by atmospheric conditions and terrain effects. This paper conducted comparative experimental measurements on the wind turbines’ wake in three wind farms areas of different terrain complexities using Doppler Light Detection and Ranging (LiDARs). Three wind farm areas of different terrain complexities in North China were selected and wake expansions were detected by three LiDARs over a six-month measurement period. Three wake interaction conditions of separate, full, and half wakes were discussed separately in the aforementioned three wind farm areas of different terrain complexities with a total of nine different cases. The velocity deficit (VD) exhibited a complex expression with the terrain complexity increases. In separate wake condition, the VD trend of flat terrain was gentle, and the decline slopes in moderate and complex areas were 0.1243 and 0.0082 respectively. Results also showed that the wake width (WW) became wider as the terrain complexity increases, and the more complex the terrain was, the faster the WW changes. In separate wake, upstream of full and half wake, WWs in moderate and complex areas showed the same growth trend with an increase rate of 87.5%, which was twice as much as that in flat terrain. Results of this study can provide guidance for the micro-siting arrangement and control strategies of wind turbines in wind farms with different terrain complexities.

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  • 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).
  • Handle: RePEc:eee:appene:v:307:y:2022:i:c:s0306261921014537
    DOI: 10.1016/j.apenergy.2021.118182
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    6. 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.
    7. 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).
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