Wind Energy Science
Wind Energy Science
WES
Articles | Volume 5, issue 3
Articles | Volume 5, issue 3
https://doi.org/10.5194/wes-5-1007-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-5-1007-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 5, issue 3
Research article
 | 
17 Aug 2020
Research article |  | 17 Aug 2020

A surrogate model approach for associating wind farm load variations with turbine failures

Laura Schröder, Nikolay Krasimirov Dimitrov, and David Robert Verelst

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Latest update: 20 Nov 2024
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Short summary
We suggest a methodology for correlating loads with component reliability of turbines in wind farms by combining physical modeling with machine learning. The suggested approach is demonstrated on an offshore wind farm for comparing performance, loads and lifetime estimations against recorded main bearing failures from maintenance reports. It is found that turbines positioned at the border of the wind farm with a higher expected AEP are estimated to experience earlier main bearing failures.
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