Uncertainty Analysis for Fatigue Load Estimators in Wind Turbines

ABSTRACT Like explicit measurements of fatigue loads, their estimation using suitable algorithms is subject to uncertainty. This paper proposes a method to quantify this uncertainty. It is well‐suited for two‐stage, time‐series‐based algorithms that estimate remaining useful lifetime. Key element is a model, which is used to propagate measurement and physical uncertainties. A special feature of the method is that it can take into account known deterministic errors of the estimation algorithm. The application of the procedure is illustrated using an example setup with a common algorithm for the estimation of tower bottom loads. This demonstrates that the method provides a meaningful quantification of uncertainty in form of a coefficient of variation and clearly identifies the main sources of uncertainty. Thus, the proposed method is an important contribution towards the practical application of fatigue load estimators for wind turbines.

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Publication Details

Journal
Wind Energy
Published
2025-02-07
DOI
https://doi.org/10.1002/we.2977
Primary Topic
Structural Health Monitoring Techniques
Type
article
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article

Uncertainty Analysis for Fatigue Load Estimators in Wind Turbines

Boris Fischer, Jörg Schwarte, Phillip Kretschmer, Jacob Laborenz
Wind Energy
Structural Health Monitoring Techniques
article

Uncertainty Analysis for Fatigue Load Estimators in Wind Turbines

Boris Fischer, Jörg Schwarte, Phillip Kretschmer, Jacob Laborenz
article en

Abstract

ABSTRACT Like explicit measurements of fatigue loads, their estimation using suitable algorithms is subject to uncertainty. This paper proposes a method to quantify this uncertainty. It is well‐suited for two‐stage, time‐series‐based algorithms that estimate remaining useful lifetime. Key element is a model, which is used to propagate measurement and physical uncertainties. A special feature of the method is that it can take into account known deterministic errors of the estimation algorithm. The application of the procedure is illustrated using an example setup with a common algorithm for the estimation of tower bottom loads. This demonstrates that the method provides a meaningful quantification of uncertainty in form of a coefficient of variation and clearly identifies the main sources of uncertainty. Thus, the proposed method is an important contribution towards the practical application of fatigue load estimators for wind turbines.

Wind EnergyVol. 28(3)
Nordex (Germany) (DE), Fraunhofer Institute for Energy Economics and Energy System Technology (DE)
Affordable and clean energy
Openalex Percentile: Top 97%
Structural Health Monitoring Techniques
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