Articles | Volume 7, issue 4
https://doi.org/10.5194/wes-7-1605-2022
https://doi.org/10.5194/wes-7-1605-2022
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

Data sets

Matlab figure files for key result plots Stefan Loew https://doi.org/10.5281/zenodo.6600688

Model code and software

MATLAB function and a test script for the PORFC parameter generation Stefan Loew https://doi.org/10.5281/zenodo.6600832

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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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