Wind Energy Science
Wind Energy Science
WES
Articles | Volume 6, issue 5
Articles | Volume 6, issue 5
https://doi.org/10.5194/wes-6-1117-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-6-1117-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 6, issue 5
Research article
 | 
09 Sep 2021
Research article |  | 09 Sep 2021

Probabilistic estimation of the Dynamic Wake Meandering model parameters using SpinnerLidar-derived wake characteristics

Davide Conti, Nikolay Dimitrov, Alfredo Peña, and Thomas Herges

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Short summary
We carry out a probabilistic calibration of the Dynamic Wake Meandering (DWM) model using high-spatial- and high-temporal-resolution nacelle-based lidar measurements of the wake flow field. The experimental data were collected from the Scaled Wind Farm Technology (SWiFT) facility in Texas. The analysis includes the velocity deficit, wake-added turbulence, and wake meandering features under various inflow wind and atmospheric-stability conditions.
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