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Validation of Improved Sampling Concepts for Offshore Wind Turbine Fatigue Design

Author

Listed:
  • Clemens Hübler

    (Institute of Structural Analysis, Leibniz Universität Hannover, ForWind, Appelstr. 9a, D-30167 Hannover, Germany)

  • Wout Weijtjens

    (OWI-lab, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussel, Belgium)

  • Cristian G. Gebhardt

    (Institute of Structural Analysis, Leibniz Universität Hannover, ForWind, Appelstr. 9a, D-30167 Hannover, Germany)

  • Raimund Rolfes

    (Institute of Structural Analysis, Leibniz Universität Hannover, ForWind, Appelstr. 9a, D-30167 Hannover, Germany)

  • Christof Devriendt

    (OWI-lab, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussel, Belgium)

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.

Suggested Citation

  • Clemens Hübler & Wout Weijtjens & Cristian G. Gebhardt & Raimund Rolfes & Christof Devriendt, 2019. "Validation of Improved Sampling Concepts for Offshore Wind Turbine Fatigue Design," Energies, MDPI, vol. 12(4), pages 1-20, February.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:4:p:603-:d:205769
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    References listed on IDEAS

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    1. Häfele, Jan & Hübler, Clemens & Gebhardt, Cristian Guillermo & Rolfes, Raimund, 2018. "A comprehensive fatigue load set reduction study for offshore wind turbines with jacket substructures," Renewable Energy, Elsevier, vol. 118(C), pages 99-112.
    2. Chi-Yu Chian & Yi-Qing Zhao & Tsung-Yueh Lin & Bryan Nelson & Hsin-Haou Huang, 2018. "Comparative Study of Time-Domain Fatigue Assessments for an Offshore Wind Turbine Jacket Substructure by Using Conventional Grid-Based and Monte Carlo Sampling Methods," Energies, MDPI, vol. 11(11), pages 1-17, November.
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    Cited by:

    1. Pim van der Male & Marco Vergassola & Karel N. van Dalen, 2020. "Decoupled Modelling Approaches for Environmental Interactions with Monopile-Based Offshore Wind Support Structures," Energies, MDPI, vol. 13(19), pages 1-35, October.
    2. Mingcan Li & Hanbin Xiao & Lin Pan & Chengjun Xu, 2019. "Study of Generalized Interaction Wake Models Systems with ELM Variation for Off-Shore Wind Farms," Energies, MDPI, vol. 12(5), pages 1-32, March.

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