Assessment of low-frequency aeroacoustic emissions of a wind turbine under rapidly changing wind conditions based on an aero-servo-elastic CFD simulation

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

  • Florian Wenz
  • Oliver Maas
  • Matthias Arnold
  • Thorsten Lutz
  • Ewald Krämer

Externe Organisationen

  • Universität Stuttgart
  • WRD Wobben Research & Development GmbH
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Seiten (von - bis)745-762
Seitenumfang18
FachzeitschriftWIND ENERGY
Jahrgang26
Ausgabenummer8
Frühes Online-Datum1 Mai 2023
PublikationsstatusVeröffentlicht - Aug. 2023

Abstract

A meteorologically challenging situation that represents a demanding control task (rotational speed, pitch and yaw) for a wind turbine is presented and its implementation in a simulation is described. A high-fidelity numerical process chain, consisting of the computational fluid dynamics (CFD) solver FLOWer, the multi-body system (MBS) software SIMPACK and the Ffowcs Williams-Hawkings code ACCO, is used. With it, the aerodynamic, servoelastic and aeroacoustic (<20 Hz) behaviour of a generic wind turbine during a meteorological event with strong and rapid changes in wind speed and direction is investigated. A precursor simulation with the meteorological model system PALM is deployed to generate realistic inflow data. The simulated strong controller response of the wind turbine and the resulting aeroelastic behaviour are analysed. Finally, the low-frequency sound emissions are evaluated and the influence of the different operating and flow parameters during the variable inflow is assessed. It is observed that the wind speed and, linked to it, the rotational speed as well as the turbulence intensity are the main influencing factors for the emitted low-frequency sound power of the wind turbine. Yawed inflow, on the other hand, has little effect unless it changes the operational mode to load reduction, resulting in a swap of the main emitter from the blades to the tower.

ASJC Scopus Sachgebiete

Ziele für nachhaltige Entwicklung

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Assessment of low-frequency aeroacoustic emissions of a wind turbine under rapidly changing wind conditions based on an aero-servo-elastic CFD simulation. / Wenz, Florian; Maas, Oliver; Arnold, Matthias et al.
in: WIND ENERGY, Jahrgang 26, Nr. 8, 08.2023, S. 745-762.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Wenz F, Maas O, Arnold M, Lutz T, Krämer E. Assessment of low-frequency aeroacoustic emissions of a wind turbine under rapidly changing wind conditions based on an aero-servo-elastic CFD simulation. WIND ENERGY. 2023 Aug;26(8):745-762. Epub 2023 Mai 1. doi: 10.1002/we.2826
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abstract = "A meteorologically challenging situation that represents a demanding control task (rotational speed, pitch and yaw) for a wind turbine is presented and its implementation in a simulation is described. A high-fidelity numerical process chain, consisting of the computational fluid dynamics (CFD) solver FLOWer, the multi-body system (MBS) software SIMPACK and the Ffowcs Williams-Hawkings code ACCO, is used. With it, the aerodynamic, servoelastic and aeroacoustic (<20 Hz) behaviour of a generic wind turbine during a meteorological event with strong and rapid changes in wind speed and direction is investigated. A precursor simulation with the meteorological model system PALM is deployed to generate realistic inflow data. The simulated strong controller response of the wind turbine and the resulting aeroelastic behaviour are analysed. Finally, the low-frequency sound emissions are evaluated and the influence of the different operating and flow parameters during the variable inflow is assessed. It is observed that the wind speed and, linked to it, the rotational speed as well as the turbulence intensity are the main influencing factors for the emitted low-frequency sound power of the wind turbine. Yawed inflow, on the other hand, has little effect unless it changes the operational mode to load reduction, resulting in a swap of the main emitter from the blades to the tower.",
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AU - Wenz, Florian

AU - Maas, Oliver

AU - Arnold, Matthias

AU - Lutz, Thorsten

AU - Krämer, Ewald

N1 - Funding Information: The authors gratefully acknowledge the High Performance Computing Center Stuttgart (HLRS) for providing computational resources within the project WEALoads. Open Access funding enabled and organized by Projekt DEAL.

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