Articles | Volume 7, issue 4
https://doi.org/10.5194/wes-7-1455-2022
https://doi.org/10.5194/wes-7-1455-2022
Research article
 | 
15 Jul 2022
Research article |  | 15 Jul 2022

A physically interpretable data-driven surrogate model for wake steering

Balthazar Arnoldus Maria Sengers, Matthias Zech, Pim Jacobs, Gerald Steinfeld, and Martin Kühn

Data sets

A physically interpretable data-driven surrogate model for wake steering B. A. M. Sengers https://doi.org/10.5281/zenodo.6821164

Model code and software

Model code B. A. M. Sengers and M. Zech https://doi.org/10.5281/zenodo.6759129

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Short summary
Wake steering aims to redirect the wake away from a downstream turbine. This study explores the potential of a data-driven surrogate model whose equations can be interpreted physically. It estimates wake characteristics from measurable input variables by utilizing a simple linear model. The model shows encouraging results in estimating available power in the far wake, with significant improvements over currently used analytical models in conditions where wake steering is deemed most effective.
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