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Hierarchical four-step global sensitivity analysis of offshore wind turbines based on aeroelastic time domain simulations

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  • Hübler, Clemens
  • Gebhardt, Cristian Guillermo
  • Rolfes, Raimund

Abstract

Although uncertainties are present in all real parameters, numerical calculations of the structural behaviour of offshore wind turbines are usually conducted with deterministic values. However, with this approach, optimisation processes can be misleading and reliability levels cannot be calculated. The reasons for deterministic calculations are high computing times of probabilistic approaches and the lack of knowledge about the scatter of data. For deterministic approaches, more complex models with higher computing times are possible, although they, are less generally valid. Therefore, it is useful to identify the most influential parameters that have to be treated in a probabilistic manner using sensitivity analyses is valuable. Contrary to rudimentary sensitivity approaches being used in offshore wind energy so far, this paper presents a new four-step sensitivity analysis reducing the probabilistic parameter subset step by step and aiming to achieve a compromise between computing time and complexity. It can be shown that for different substructures and different load cases, only a small parameter subset is influential and many other inputs can be regarded as deterministic without losing accuracy. However, attention must be paid to the slight differences among substructures. Therefore, it must be highlighted that not all results are general.

Suggested Citation

  • Hübler, Clemens & Gebhardt, Cristian Guillermo & Rolfes, Raimund, 2017. "Hierarchical four-step global sensitivity analysis of offshore wind turbines based on aeroelastic time domain simulations," Renewable Energy, Elsevier, vol. 111(C), pages 878-891.
  • Handle: RePEc:eee:renene:v:111:y:2017:i:c:p:878-891
    DOI: 10.1016/j.renene.2017.05.013
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    Cited by:

    1. Velarde, Joey & Kramhøft, Claus & Sørensen, John Dalsgaard, 2019. "Global sensitivity analysis of offshore wind turbine foundation fatigue loads," Renewable Energy, Elsevier, vol. 140(C), pages 177-189.
    2. 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.
    3. Carta, José A. & Díaz, Santiago & Castañeda, Alberto, 2020. "A global sensitivity analysis method applied to wind farm power output estimation models," Applied Energy, Elsevier, vol. 280(C).
    4. Hübler, Clemens, 2020. "Global sensitivity analysis for medium-dimensional structural engineering problems using stochastic collocation," Reliability Engineering and System Safety, Elsevier, vol. 195(C).

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