Lidar-assisted model predictive control of wind turbine fatigue via online rainflow-counting considering stress history
- Wind Energy Institute, Technical University of Munich, 85748 Garching b. München, Germany
- Wind Energy Institute, Technical University of Munich, 85748 Garching b. München, Germany
Abstract. The formulation of Parametric Online Rainflow Counting implements the standard fatigue estimation process and a stress history in the cost function of a Model Predictive Controller. The formulation is tested in realistic simulation scenarios where the states are estimated by a Moving Horizon Estimator and the wind is predicted by a lidar simulator. The tuning procedure for the controller toolchain is carefully explained. In comparison to a conventional MPC in a turbulent wind setting, the novel formulation is especially superior with low lidar quality, benefits more from the availability of a wind prediction, and exhibits a more robust performance with shorter prediction horizons. A simulation excerpt with the novel formulation provides deeper insight into the update of the stress history and the fatigue cost parameters. Finally, in a deterministic gust setting, both the conventional and the novel MPC - despite their completely different fatigue cost - exhibit similar pitch behavior and tower oscillation.
Stefan Loew and Carlo L. Bottasso
Status: final response (author comments only)
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RC1: 'Comment on wes-2021-119', Valentin Chabaud, 21 Jan 2022
See attached file for comments.
The presentation quality is deemed "good" and not "excellent" due to subjective writing style, see main comment.
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RC2: 'EDIT: resent comment with correct attachment, the previous one was the orginal manuscript', Valentin Chabaud, 21 Jan 2022
The comment was uploaded in the form of a supplement: https://wes.copernicus.org/preprints/wes-2021-119/wes-2021-119-RC2-supplement.pdf
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RC2: 'EDIT: resent comment with correct attachment, the previous one was the orginal manuscript', Valentin Chabaud, 21 Jan 2022
- RC3: 'Comment on wes-2021-119', Nikhar Abbas, 05 May 2022
Stefan Loew and Carlo L. Bottasso
Stefan Loew and Carlo L. Bottasso
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