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基于激光测风雷达扫描图像的风电机组尾流分析

Wake Analysis of Wind Turbine Based on Scanning Images from Doppler Lidar

  • 摘要:
    目的 为了充分挖掘激光测风雷达在风电机组尾流观测中的数据价值,深入研究尾流三维结构与风速衰减规律,进而对改进尾流模型以及提升中尺度气象模式预测精度提出建议。
    方法 文章通过建立1种在雷达径向速度图像上直接定位和分析风电机组尾流的新方法,提取了不同尾流叠加状态下的尾流区长度、宽度和风速衰减程度等特征参数,并由此验证了3种尾流模型。
    结果 结果显示,单个风电机组的尾流区在基于水平方位扫描的径向速度图上,表现为叶轮扫风面后长度为11.0~13.0倍叶轮直径的条带状区域;在基于垂直剖面扫描的径向速度图上,表现为大致宽度为1.8~2.0倍叶轮直径,并覆盖整个叶轮高度范围的椭圆形区域。当上风向机组的尾流区影响下风向机组时,下风向机组尾流区内的风速分布出现调整,近尾流区内最低风速的对应位置发生前移,远尾流区内的风速恢复变慢,尾流长度有所延长。上风向机组尾流部分叠加时,下风向机组的风速、输出功率出现近5%和15%的降幅;完全叠加时,下风向机组的风速、输出功率降幅扩大近27%和43%。
    结论 研究表明,三维尾流模型对不同尾流叠加状态下顺风向的尾流区结构具有较好的模拟能力,但单高斯分布型的尾流模型无法再现近尾流区内横风向的风速分布特征,实际应用时需审慎评估间距小于3.0倍叶轮直径时的模拟误差。

     

    Abstract:
    Objective To fully explore the data value of lidar in wind turbine wake observation, conduct an in-depth study on the three-dimensional (3D) wake structure and wind speed attenuation characteristics in wake zone, and further provide references for improving engineering models of wake and enhancing the prediction accuracy of mesoscale meteorological models.
    Method This paper established a new method for directly locating and analyzing wind turbine wake on radial velocity images of lidar. It extracted characteristic parameters such as wake length, width and wind speed attenuation under different wake superposition states, and verified three engineering models of wake based on these parameters.
    Result The results show that the wake zone of a single wind turbine appears as a strip-shaped area with a length of 11.0~13.0 times the rotor diameter behind the rotor swept area on the horizontal azimuth scanning radial velocity image. On the vertical cross-section scanning radial velocity image, it presents an elliptical area with a width of approximately 1.8~2.0 times the rotor diameter, covering the entire rotor height range. When the wake zone of the upstream turbine affects the downstream turbine, the wind speed distribution in the wake zone of the downstream turbine adjusts: the corresponding position of the minimum wind speed in the near-wake region moves forward, the wind speed recovery rate in the far-wake region slows down, and the wake length extends slightly. Under partial superposition of the upstream turbine wake, the wind speed and output power of the downstream turbine decrease by nearly 5% and 15% respectively. Under full superposition, the decreases expand to nearly 27% and 43%.
    Conclusion The study indicates that the 3D wake model has good simulation capability for the downstream wake structure under different wake superposition states. However, the single Gaussian distribution wake model cannot reproduce the cross-wind direction wind speed distribution characteristics in the near-wake region. In practical applications, the simulation error should be carefully evaluated when the turbine spacing is less than 3.0 times the rotor diameter.

     

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