Wind Energy Science
Wind Energy Science
WES
Articles | Volume 7, issue 4
Articles | Volume 7, issue 4
https://doi.org/10.5194/wes-7-1605-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-7-1605-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 7, issue 4
Research article
 | 
03 Aug 2022
Research article |  | 03 Aug 2022

Lidar-assisted model predictive control of wind turbine fatigue via online rainflow counting considering stress history

Stefan Loew and Carlo L. Bottasso

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Latest update: 13 Dec 2024
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Short summary
This publication presents methods to improve the awareness and control of material fatigue for wind turbines. This is achieved by enhancing a sophisticated control algorithm which utilizes wind prediction information from a laser measurement device. The simulation results indicate that the novel algorithm significantly improves the economic performance of a wind turbine. This benefit is particularly high for situations when the prediction quality is low or the prediction time frame is short.
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