Articles | Volume 6, issue 5
Wind Energ. Sci., 6, 1117–1142, 2021
https://doi.org/10.5194/wes-6-1117-2021
Wind Energ. Sci., 6, 1117–1142, 2021
https://doi.org/10.5194/wes-6-1117-2021
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 et al.

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Latest update: 27 Nov 2022
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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.