Wind Energy Science
Wind Energy Science
WES
Articles | Volume 10, issue 9
Articles | Volume 10, issue 9
https://doi.org/10.5194/wes-10-1943-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-10-1943-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 10, issue 9
Research article
 | 
11 Sep 2025
Research article |  | 11 Sep 2025

Wind turbine wake detection and characterisation utilising blade loads and SCADA data: a generalised approach

Piotr Fojcik, Edward Hart, and Emil Hedevang

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Cited articles

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Azadkia, M. and Chatterjee, S.: A simple measure of conditional dependence, Ann. Stat., 49, 3070–3102, https://doi.org/10.1214/21-AOS2073, 2021. a, b
Barthelmie, R. J., Pryor, S. C., Frandsen, S. T., Hansen, K. S., Schepers, J. G., Rados, K., Schlez, W., Neubert, A., Jensen, L. E., and Neckelmann, S.: Quantifying the Impact of Wind Turbine Wakes on Power Output at Offshore Wind Farms, J. Atmos. Ocean. Tech., 27, 1302–1317, https://doi.org/10.1175/2010JTECHA1398.1, 2010. a
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Increasing the efficiency of wind farms can be achieved via reducing the impact of wakes – flow regions with lower wind speed occurring downwind from turbines. This work describes training and validation of a novel method for the estimation of the wake effects impacting a turbine. The results show that for most tested wind conditions, the developed model is capable of robust detection of wake presence and accurate characterisation of its properties. Further validation and improvements are planned.
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