Preprints
https://doi.org/10.5194/wes-2023-134
https://doi.org/10.5194/wes-2023-134
07 Nov 2023
 | 07 Nov 2023
Status: a revised version of this preprint is currently under review for the journal WES.

The rotor as a sensor – Observing shear and veer from the operational data of a large wind turbine

Marta Bertelè, Paul J. Meyer, Carlo R. Sucameli, Johannes Fricke, Anna Wegner, Julia Gottschall, and Carlo L. Bottasso

Abstract. This paper demonstrates the observation of wind shear and veer directly from the operational response of a wind turbine equipped with blade load sensors. Two independent neural-based observers, one for shear and one for veer, are first trained using a machine learning approach, and then used to produce estimates of these two wind characteristics from measured blade load harmonics. The study is based on a data set collected at an experimental test site, featuring a highly-instrumented 8 MW wind turbine, an IEC-compliant met mast, and a vertical profiling lidar reaching above the rotor top.

The present study reports the first demonstration of the measurement of wind veer with this technology, and the first validation of shear and veer with respect to lidar measurements spanning the whole rotor height. Results are presented in terms of correlations, exemplary time histories and aggregated statistical metrics. Measurements of shear and veer produced by the observers are very similar to the ones obtained with the widely adopted profiling lidar, while avoiding its complexity and associated costs.

Marta Bertelè, Paul J. Meyer, Carlo R. Sucameli, Johannes Fricke, Anna Wegner, Julia Gottschall, and Carlo L. Bottasso

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2023-134', Torben Knudsen, 04 Dec 2023
  • RC2: 'Comment on wes-2023-134', Anonymous Referee #2, 17 Dec 2023
  • AC1: 'Comment on wes-2023-134', Carlo L. Bottasso, 22 Mar 2024
Marta Bertelè, Paul J. Meyer, Carlo R. Sucameli, Johannes Fricke, Anna Wegner, Julia Gottschall, and Carlo L. Bottasso

Data sets

The rotor as a sensor - Observing shear and veer from the operational data of a large wind turbine M. Bertelè, P. J. Meyer, C. R. Sucameli, J. Fricke, A. Wegner, J. Gottschall, and C. L. Bottasso https://doi.org/10.5281/zenodo.8335021

Marta Bertelè, Paul J. Meyer, Carlo R. Sucameli, Johannes Fricke, Anna Wegner, Julia Gottschall, and Carlo L. Bottasso

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Short summary
A neural observer is used to estimate shear and veer from the operational data of a large wind turbine equipped with blade load sensors. Comparison with independent measurements from a nerby met-mast and profiling lidar demonstrate the ability of the "rotor as a sensor" concept to provide high-quality estimates of these inflow quantities based simply on already available standard operational data. 
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