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Turbulence Modeling of Iced Wind Turbine Airfoils

Author

Listed:
  • Fahed Martini

    (Wind Energy Research Laboratory, The University of Quebec at Rimouski, Rimouski, QC G5L 3A1, Canada)

  • Hussein Ibrahim

    (Technological Institute for Industrial Maintenance, Cégep de Sept-Îles, Sept-Îles, QC G4R 5B7, Canada)

  • Leidy Tatiana Contreras Montoya

    (Wind Energy Research Laboratory, The University of Quebec at Rimouski, Rimouski, QC G5L 3A1, Canada)

  • Patrick Rizk

    (Wind Energy Research Laboratory, The University of Quebec at Rimouski, Rimouski, QC G5L 3A1, Canada)

  • Adrian Ilinca

    (Wind Energy Research Laboratory, The University of Quebec at Rimouski, Rimouski, QC G5L 3A1, Canada)

Abstract

Icing is a severe problem faced by wind turbines operating in cold climates. It is affected by various fluctuating parameters. Due to ice accretion, a significant drop in the aerodynamic performance of the blades’ airfoils leads to productivity loss in wind turbines. When ice accretes on airfoils, it leads to a geometry deformation that seriously increases turbulence, particularly on the airfoil suction side at high angles of attack. Modeling and simulation are indispensable tools to estimate the effect of icing on the operation of wind turbines and gain a better understanding of the phenomenon. This paper presents a numerical study to assess the effect of surface roughness distribution, along with the effect of two turbulence models on estimating wind turbine airfoils’ aerodynamic performance losses in the presence of ice. Aerodynamic parameter estimation was performed using ANSYS FLUENT, while ice accretion was simulated using ANSYS FENSAP-ICE. The results using the adopted modeling approaches and the simulation tools were compared with another numerical study and validated against experimental data. The validation process demonstrated the model’s accuracy when considering roughness distribution via the beading model available in ANSYS FENSAP-ICE. The two turbulence models examined (Spalart–Allmaras and k-ω SST) gave comparable results except for the drag at high angles of attack. The k-ω SST model was more efficient in replicating turbulence at high angles of attack, leading to higher accuracy in aerodynamic loss estimation.

Suggested Citation

  • Fahed Martini & Hussein Ibrahim & Leidy Tatiana Contreras Montoya & Patrick Rizk & Adrian Ilinca, 2022. "Turbulence Modeling of Iced Wind Turbine Airfoils," Energies, MDPI, vol. 15(22), pages 1-20, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8325-:d:966088
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    References listed on IDEAS

    as
    1. Fahed Martini & Leidy Tatiana Contreras Montoya & Adrian Ilinca, 2021. "Review of Wind Turbine Icing Modelling Approaches," Energies, MDPI, vol. 14(16), pages 1-26, August.
    2. Hu, Liangquan & Zhu, Xiaocheng & Hu, Chenxing & Chen, Jinge & Du, Zhaohui, 2017. "Wind turbines ice distribution and load response under icing conditions," Renewable Energy, Elsevier, vol. 113(C), pages 608-619.
    3. Villalpando, Fernando & Reggio, Marcelo & Ilinca, Adrian, 2016. "Prediction of ice accretion and anti-icing heating power on wind turbine blades using standard commercial software," Energy, Elsevier, vol. 114(C), pages 1041-1052.
    4. Zanon, Alessandro & De Gennaro, Michele & Kühnelt, Helmut, 2018. "Wind energy harnessing of the NREL 5 MW reference wind turbine in icing conditions under different operational strategies," Renewable Energy, Elsevier, vol. 115(C), pages 760-772.
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    1. Fahed Martini & Adrian Ilinca & Patrick Rizk & Hussein Ibrahim & Mohamad Issa, 2022. "A Survey of the Quasi-3D Modeling of Wind Turbine Icing," Energies, MDPI, vol. 15(23), pages 1-32, November.
    2. Alina Fazylova & Baurzhan Tultayev & Teodor Iliev & Ivaylo Stoyanov & Ivan Beloev, 2023. "Development of a Control Unit for the Angle of Attack of a Vertically Axial Wind Turbine," Energies, MDPI, vol. 16(13), pages 1-20, July.

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