On the modeling errors of digital twins for load monitoring and fatigue assessment in wind turbine drivetrains

<p>This article presents a systematic assessment of the modeling and estimation errors of digital twins for load and fatigue monitoring in wind turbine drivetrains. The errors in the measurement input, the reduced-order drivetrain models, and the model updating methods are investigated. A stat...

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Main Authors: F. C. Mehlan, A. R. Nejad
Format: Article
Language:English
Published: Copernicus Publications 2025-02-01
Series:Wind Energy Science
Online Access:https://wes.copernicus.org/articles/10/417/2025/wes-10-417-2025.pdf
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author F. C. Mehlan
A. R. Nejad
author_facet F. C. Mehlan
A. R. Nejad
author_sort F. C. Mehlan
collection DOAJ
description <p>This article presents a systematic assessment of the modeling and estimation errors of digital twins for load and fatigue monitoring in wind turbine drivetrains. The errors in the measurement input, the reduced-order drivetrain models, and the model updating methods are investigated. A statistical analysis is conducted on gear and bearing load measurements from numerical studies with 5 and 10 MW drivetrain models and from field measurements of a 1.5 MW research turbine. The error distributions are quantified using normal distributions, and limitations of the digital twin are discussed such as the information loss of 10 min averaged supervisory control and data acquisition system (SCADA) data, the estimation errors of the unknown rotor torque, and the modeling errors in torsional reduced-order drivetrain models. This study contributes to a deeper understanding of the origin and the effects of uncertainty in digital twins and delivers a foundation for further reliability and risk assessment studies.</p>
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institution Kabale University
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language English
publishDate 2025-02-01
publisher Copernicus Publications
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series Wind Energy Science
spelling doaj-art-52c861a955104ca387c68b02ab0579b02025-02-10T12:39:18ZengCopernicus PublicationsWind Energy Science2366-74432366-74512025-02-011041743310.5194/wes-10-417-2025On the modeling errors of digital twins for load monitoring and fatigue assessment in wind turbine drivetrainsF. C. Mehlan0A. R. Nejad1Norwegian University of Science and Technology, Jonsvannsveien 82, 7050 Trondheim, NorwayNorwegian University of Science and Technology, Jonsvannsveien 82, 7050 Trondheim, Norway<p>This article presents a systematic assessment of the modeling and estimation errors of digital twins for load and fatigue monitoring in wind turbine drivetrains. The errors in the measurement input, the reduced-order drivetrain models, and the model updating methods are investigated. A statistical analysis is conducted on gear and bearing load measurements from numerical studies with 5 and 10 MW drivetrain models and from field measurements of a 1.5 MW research turbine. The error distributions are quantified using normal distributions, and limitations of the digital twin are discussed such as the information loss of 10 min averaged supervisory control and data acquisition system (SCADA) data, the estimation errors of the unknown rotor torque, and the modeling errors in torsional reduced-order drivetrain models. This study contributes to a deeper understanding of the origin and the effects of uncertainty in digital twins and delivers a foundation for further reliability and risk assessment studies.</p>https://wes.copernicus.org/articles/10/417/2025/wes-10-417-2025.pdf
spellingShingle F. C. Mehlan
A. R. Nejad
On the modeling errors of digital twins for load monitoring and fatigue assessment in wind turbine drivetrains
Wind Energy Science
title On the modeling errors of digital twins for load monitoring and fatigue assessment in wind turbine drivetrains
title_full On the modeling errors of digital twins for load monitoring and fatigue assessment in wind turbine drivetrains
title_fullStr On the modeling errors of digital twins for load monitoring and fatigue assessment in wind turbine drivetrains
title_full_unstemmed On the modeling errors of digital twins for load monitoring and fatigue assessment in wind turbine drivetrains
title_short On the modeling errors of digital twins for load monitoring and fatigue assessment in wind turbine drivetrains
title_sort on the modeling errors of digital twins for load monitoring and fatigue assessment in wind turbine drivetrains
url https://wes.copernicus.org/articles/10/417/2025/wes-10-417-2025.pdf
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AT arnejad onthemodelingerrorsofdigitaltwinsforloadmonitoringandfatigueassessmentinwindturbinedrivetrains