Wind Energy Science
Wind Energy Science
WES
Articles | Volume 11, issue 6
Articles | Volume 11, issue 6
https://doi.org/10.5194/wes-11-1963-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-11-1963-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 6
Research article
 | 
04 Jun 2026
Research article |  | 04 Jun 2026

Remote diagnostics for power converter faults in wind turbines based on converter control system data

Timo Lichtenstein, Martin Hippenstiel, and Katharina Fischer

Viewed

Total article views: 1,186 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
763 368 55 1,186 64 69
  • HTML: 763
  • PDF: 368
  • XML: 55
  • Total: 1,186
  • BibTeX: 64
  • EndNote: 69
Views and downloads (calculated since 06 Oct 2025)
Cumulative views and downloads (calculated since 06 Oct 2025)

Viewed (geographical distribution)

Total article views: 1,186 (including HTML, PDF, and XML) Thereof 1,073 with geography defined and 113 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Saved (final revised paper)

Latest update: 26 Aug 2026
Download
Short summary
Power converter faults in wind turbines often lead to costly downtime and repeated maintenance. We present a practical, explainable, and fully data-driven approach that utilizes high-resolution converter control system records, 1 min operating data, and event logs to predict whether a fault leads to a long or short standstill. By combining engineered features with interpretable feature reduction, we achieve 89 % accuracy and an F1 score of 0.86, providing support for remote decision-making.
Read more
Share
Altmetrics
Final-revised paper
Preprint