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

Loew, Stefan; Bottasso, Carlo L.

doi:https://doi.org/10.5194/wes-7-1605-2022

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

Download

Final revised paper (published on 03 Aug 2022)
Preprint (discussion started on 25 Oct 2021)

Interactive discussion

Status: closed

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.

Citation: https://doi.org/10.5194/wes-2021-119-RC1
- 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
  
  Citation: https://doi.org/10.5194/wes-2021-119-RC2
  - AC1: 'Reply on RC2 & RC3', Stefan Loew, 01 Jun 2022
    
    The comment was uploaded in the form of a supplement: https://wes.copernicus.org/preprints/wes-2021-119/wes-2021-119-AC1-supplement.pdf
    
    Citation: https://doi.org/10.5194/wes-2021-119-AC1
RC3:
'Comment on wes-2021-119', Nikhar Abbas, 05 May 2022

Please see attached

Citation: https://doi.org/10.5194/wes-2021-119-RC3
- AC1: 'Reply on RC2 & RC3', Stefan Loew, 01 Jun 2022
  
  The comment was uploaded in the form of a supplement: https://wes.copernicus.org/preprints/wes-2021-119/wes-2021-119-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/wes-2021-119-AC1

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Stefan Loew on behalf of the Authors (02 Jun 2022) Author's response Author's tracked changes Manuscript

ED: Publish as is (20 Jun 2022) by Amir R. Nejad

ED: Publish as is (23 Jun 2022) by Paul Fleming (Chief editor)

AR by Stefan Loew on behalf of the Authors (07 Jul 2022) Manuscript

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.