Development of an automatic thresholding method  for wake meandering studies and its application  to the data set from scanning wind lidar

Krutova, Maria; Bakhoday-Paskyabi, Mostafa; Reuder, Joachim; Nielsen, Finn Gunnar

doi:https://doi.org/10.5194/wes-7-849-2022

Articles | Volume 7, issue 2

https://doi.org/10.5194/wes-7-849-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/wes-7-849-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 7, issue 2

Research article

|

08 Apr 2022

Research article |

| 08 Apr 2022

Development of an automatic thresholding method for wake meandering studies and its application to the data set from scanning wind lidar

Maria Krutova, Mostafa Bakhoday-Paskyabi, Joachim Reuder, and Finn Gunnar Nielsen

Model code and software

Adaptive Thresholding Segmentation (ATS) for wake identification and characterization (0.5) M. Krutova https://doi.org/10.5281/zenodo.5888236

matplotlib/matplotlib: REL: v3.4.0 T. A. Caswell, M. Droettboom, A. Lee, E. Sales~de Andrade, J. Hunter, T. Hoffmann, E. Firing, J. Klymak, D. Stansby, N. Varoquaux, J. Hedegaard~Nielsen, B. Root, R. May, P. Elson, J. K. Seppänen, D. Dale, J.-J. Lee, D. McDougall, A. Straw, P. Hobson, C. Gohlke, T. S. Yu, E. Ma, A. F. Vincent, S. Silvester, C. Moad, N. Kniazev, E. Ernest, and P. Ivanov https://doi.org/10.5281/zenodo.4638398

Video supplement

Automatic thresholding method for the wake detection M. Krutova https://doi.org/10.5446/54055

Automatic thresholding method for the wake detection – comparison of the methods M. Krutova https://doi.org/10.5446/56710

Short summary

We described a new automated method to separate the wind turbine wake from the undisturbed flow. The method relies on the wind speed distribution in the measured wind field to select one specific threshold value and split the measurements into wake and background points. The purpose of the method is to reduce the amount of data required – the proposed algorithm does not need precise information on the wind speed or direction and can run on the image instead of the measured data.