Uncertainty quantification of structural blade parameters for the aeroelastic damping of wind turbines: a code-to-code comparison

Abstract. Uncertainty quantification (UQ) is a well-established category of methods to estimate the effect of parameter variations on a quantity of interest based on a solid mathematical foundation. In the wind energy field most UQ studies focus on the sensitivity of turbine loads. This article presents a framework, wrapped around a modern Python UQ library, to analyze the impact of uncertain turbine properties on aeroelastic stability. The UQ methodology applies a polynomial chaos expansion surrogate model. A comparison is made between different wind turbine simulation tools on the engineering model level (alaska/Wind, Bladed, HAWC2/HAWCStab2, and Simpack). Two case studies are used to demonstrate the effectiveness of the method to analyze the sensitivity of the aeroelastic damping of an unstable turbine mode to variations of structural blade cross-section parameters. The code-to-code comparison shows good agreement between the simulation tools for the reference model, but also significant differences in the sensitivities.

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Publication Details

Journal
Wind energy science
Published
2024-08-20
DOI
https://doi.org/10.5194/wes-9-1747-2024
Citations
2
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
Field-Weighted Citation Impact
0.92
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article

Uncertainty quantification of structural blade parameters for the aeroelastic damping of wind turbines: a code-to-code comparison

Hendrik Verdonck, Oliver Hach, Claudio Balzani, Johannes Rieke et al.
2 citations
Wind energy science
Probabilistic and Robust Engineering Design
0.92
article

Uncertainty quantification of structural blade parameters for the aeroelastic damping of wind turbines: a code-to-code comparison

Hendrik Verdonck, Oliver Hach, Claudio Balzani, Johannes Rieke, Jelmer D. Polman, Sarah Müller, Otto Schramm
article en
2 citations

Abstract

Abstract. Uncertainty quantification (UQ) is a well-established category of methods to estimate the effect of parameter variations on a quantity of interest based on a solid mathematical foundation. In the wind energy field most UQ studies focus on the sensitivity of turbine loads. This article presents a framework, wrapped around a modern Python UQ library, to analyze the impact of uncertain turbine properties on aeroelastic stability. The UQ methodology applies a polynomial chaos expansion surrogate model. A comparison is made between different wind turbine simulation tools on the engineering model level (alaska/Wind, Bladed, HAWC2/HAWCStab2, and Simpack). Two case studies are used to demonstrate the effectiveness of the method to analyze the sensitivity of the aeroelastic damping of an unstable turbine mode to variations of structural blade cross-section parameters. The code-to-code comparison shows good agreement between the simulation tools for the reference model, but also significant differences in the sensitivities.

Wind energy scienceVol. 9(8)
Leibniz University Hannover (DE), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), Nordex (Germany) (DE)
Affordable and clean energy
Openalex Percentile: Top 21%
Probabilistic and Robust Engineering Design
0.92
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Uncertainty quantification of structural blade parameters for the aeroelastic damping of wind turbines: a code-to-code comparison — Hendrik Verdonck, Oliver Hach, et al. · Wind energy science (2024) | TGRS Research Map | TGRS