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Validation of Improved Sampling Concepts for Offshore Wind Turbine Fatigue Design. / Hübler, Clemens; Weijtjens, Wout; Gebhardt, Cristian G.; Rolfes, Raimund; Devriendt, Christof.

In: Energies, Vol. 12, No. 4, 603, 14.02.2019.

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Hübler, Clemens ; Weijtjens, Wout ; Gebhardt, Cristian G. ; Rolfes, Raimund ; Devriendt, Christof. / Validation of Improved Sampling Concepts for Offshore Wind Turbine Fatigue Design. In: Energies. 2019 ; Vol. 12, No. 4.

BibTeX

@article{643808c25eb944f3982a19366fe18093,
title = "Validation of Improved Sampling Concepts for Offshore Wind Turbine Fatigue Design",
abstract = "Fatigue damage is a design-driving phenomenon for substructures of offshore wind turbines. However, fatigue design based on numerical simulations is quite uncertain. One main reason for this uncertainty is scattering offshore conditions combined with a limited number of simulations (samples). According to current standards, environmental conditions are sampled using a deterministic grid of the most important environmental conditions (e.g., wind speed and direction, significant wave height, and wave period). Recently, there has been some effort to reduce the inherent uncertainty of damage calculations due to limited data by applying other sampling concepts. Still, the investigation of this uncertainty and of methods to reduce it is a subject of ongoing research. In this work, two improved sampling concepts—previously proposed by the authors and reducing the uncertainty due to limited sampling—are validated. The use of strain measurement data enables a realistic estimate of the inherent uncertainty due to limited samples, as numerical effects, etc., are excluded. Furthermore, an extensive data set of three years of data of two turbines of the Belgian wind farm Northwind is available. It is demonstrated that two previously developed sampling methods are generally valid. For a broad range of model types (i.e., input dimensions as well as degrees of non-linearity), they outperform standard sampling concepts such as deterministic grid sampling or Monte Carlo sampling. Hence, they can reduce the uncertainty while keeping the sampling effort constant, or vice versa.",
keywords = "offshore wind energy, fatigue, uncertainty, monitoring, strain measurements, sampling concepts",
author = "Clemens H{\"u}bler and Wout Weijtjens and Gebhardt, {Cristian G.} and Raimund Rolfes and Christof Devriendt",
year = "2019",
month = "2",
day = "14",
doi = "10.3390/en12040603",
language = "English",
volume = "12",
journal = "Energies",
issn = "1996-1073",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "4",

}

RIS

TY - JOUR

T1 - Validation of Improved Sampling Concepts for Offshore Wind Turbine Fatigue Design

AU - Hübler, Clemens

AU - Weijtjens, Wout

AU - Gebhardt, Cristian G.

AU - Rolfes, Raimund

AU - Devriendt, Christof

PY - 2019/2/14

Y1 - 2019/2/14

N2 - Fatigue damage is a design-driving phenomenon for substructures of offshore wind turbines. However, fatigue design based on numerical simulations is quite uncertain. One main reason for this uncertainty is scattering offshore conditions combined with a limited number of simulations (samples). According to current standards, environmental conditions are sampled using a deterministic grid of the most important environmental conditions (e.g., wind speed and direction, significant wave height, and wave period). Recently, there has been some effort to reduce the inherent uncertainty of damage calculations due to limited data by applying other sampling concepts. Still, the investigation of this uncertainty and of methods to reduce it is a subject of ongoing research. In this work, two improved sampling concepts—previously proposed by the authors and reducing the uncertainty due to limited sampling—are validated. The use of strain measurement data enables a realistic estimate of the inherent uncertainty due to limited samples, as numerical effects, etc., are excluded. Furthermore, an extensive data set of three years of data of two turbines of the Belgian wind farm Northwind is available. It is demonstrated that two previously developed sampling methods are generally valid. For a broad range of model types (i.e., input dimensions as well as degrees of non-linearity), they outperform standard sampling concepts such as deterministic grid sampling or Monte Carlo sampling. Hence, they can reduce the uncertainty while keeping the sampling effort constant, or vice versa.

AB - Fatigue damage is a design-driving phenomenon for substructures of offshore wind turbines. However, fatigue design based on numerical simulations is quite uncertain. One main reason for this uncertainty is scattering offshore conditions combined with a limited number of simulations (samples). According to current standards, environmental conditions are sampled using a deterministic grid of the most important environmental conditions (e.g., wind speed and direction, significant wave height, and wave period). Recently, there has been some effort to reduce the inherent uncertainty of damage calculations due to limited data by applying other sampling concepts. Still, the investigation of this uncertainty and of methods to reduce it is a subject of ongoing research. In this work, two improved sampling concepts—previously proposed by the authors and reducing the uncertainty due to limited sampling—are validated. The use of strain measurement data enables a realistic estimate of the inherent uncertainty due to limited samples, as numerical effects, etc., are excluded. Furthermore, an extensive data set of three years of data of two turbines of the Belgian wind farm Northwind is available. It is demonstrated that two previously developed sampling methods are generally valid. For a broad range of model types (i.e., input dimensions as well as degrees of non-linearity), they outperform standard sampling concepts such as deterministic grid sampling or Monte Carlo sampling. Hence, they can reduce the uncertainty while keeping the sampling effort constant, or vice versa.

KW - offshore wind energy

KW - fatigue

KW - uncertainty

KW - monitoring

KW - strain measurements

KW - sampling concepts

U2 - 10.3390/en12040603

DO - 10.3390/en12040603

M3 - Article

VL - 12

JO - Energies

JF - Energies

SN - 1996-1073

IS - 4

M1 - 603

ER -

ID: 44148332