Articles | Volume 5, issue 3
https://doi.org/10.5194/wes-5-1155-2020
https://doi.org/10.5194/wes-5-1155-2020
Research article
 | 
04 Sep 2020
Research article |  | 04 Sep 2020

Augmented Kalman filter with a reduced mechanical model to estimate tower loads on a land-based wind turbine: a step towards digital-twin simulations

Emmanuel Branlard, Dylan Giardina, and Cameron S. D. Brown

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Emmanuel Branlard on behalf of the Authors (26 Jun 2020)  Manuscript 
ED: Publish subject to technical corrections (20 Jul 2020) by Katherine Dykes
ED: Publish subject to technical corrections (21 Jul 2020) by Gerard J.W. van Bussel (Chief editor)
AR by Emmanuel Branlard on behalf of the Authors (28 Jul 2020)  Author's response   Manuscript 

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Emmanuel Branlard on behalf of the Authors (01 Sep 2020)   Author's adjustment   Manuscript
EA: Adjustments approved (02 Sep 2020) by Katherine Dykes
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Short summary
The paper presents an application of the Kalman filtering technique to estimate loads on a wind turbine. The approach combines a mechanical model and a set of measurements to estimate signals that are not available in the measurements, such as wind speed, thrust, tower position, and tower loads. The model is severalfold faster than real time and is intended to be run online, for instance, to evaluate real-time fatigue life consumption of a field turbine using a digital twin.
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