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RANS and DDES simulations of a horizontal-axis wind turbine under stalled flow condition using OpenFOAM

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  • Zhang, Ye
  • Deng, Shuanghou
  • Wang, Xiaofang

Abstract

This paper presents a numerical study of a horizontal axis wind turbine under stalled flow condition with the tip speed ratio λ=4.17. Both RANS and DDES simulations are performed using OpenFOAM in order to predict the aerodynamic characteristics of the wind turbine rotor. In addition, numerical results are compared with experimental data where a good agreement is achieved. The complex and unsteady root flow characteristics are comprehensively investigated. Numerical result shows that in terms of aerodynamic blade loading, DDES performs much better than RANS in aerodynamic prediction, where the error has been reduced from 20% to 5%. The Strouhal numbers are in the range 0.16≤St≤0.20 for blade sections r/R=0.25, 0.60 and 0.82, indicating two-dimensional bluff body vortex shedding occurs in stall or deep stall conditions. A very low Strouhal number is observed at r/R=0.92 with a value of 0.018. The low value of St corresponds the flow at r/R=0.92 section is in the near post-stall regime, with three-dimensional surface flow typologies, with periodic switching between stalled and unstalled conditions.

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  • Zhang, Ye & Deng, Shuanghou & Wang, Xiaofang, 2019. "RANS and DDES simulations of a horizontal-axis wind turbine under stalled flow condition using OpenFOAM," Energy, Elsevier, vol. 167(C), pages 1155-1163.
  • Handle: RePEc:eee:energy:v:167:y:2019:i:c:p:1155-1163
    DOI: 10.1016/j.energy.2018.11.014
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    References listed on IDEAS

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    1. Chehouri, Adam & Younes, Rafic & Ilinca, Adrian & Perron, Jean, 2015. "Review of performance optimization techniques applied to wind turbines," Applied Energy, Elsevier, vol. 142(C), pages 361-388.
    2. Wang, Long & Wang, Tongguang & Wu, Jianghai & Chen, Guoping, 2017. "Multi-objective differential evolution optimization based on uniform decomposition for wind turbine blade design," Energy, Elsevier, vol. 120(C), pages 346-361.
    3. Shen, Xin & Chen, Jin-Ge & Zhu, Xiao-Cheng & Liu, Peng-Yin & Du, Zhao-Hui, 2015. "Multi-objective optimization of wind turbine blades using lifting surface method," Energy, Elsevier, vol. 90(P1), pages 1111-1121.
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    Cited by:

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    6. Nakhchi, M.E. & Naung, S. Win & Dala, L. & Rahmati, M., 2022. "Direct numerical simulations of aerodynamic performance of wind turbine aerofoil by considering the blades active vibrations," Renewable Energy, Elsevier, vol. 191(C), pages 669-684.
    7. Huiwen Zhang & Changlong Li & Jianhui Zhang & Zhen Wu & Zhiping Zhang & Jing Hu & Lei Cao & Longlong Song & Jianping Ma & Bin Xiao, 2022. "Numerical Simulation Analysis of the Formation and Morphological Evolution of Asymmetric Crescentic Dunes," Sustainability, MDPI, vol. 14(14), pages 1-23, July.
    8. Shantanu Purohit & Ijaz Fazil Syed Ahmed Kabir & E. Y. K. Ng, 2021. "On the Accuracy of uRANS and LES-Based CFD Modeling Approaches for Rotor and Wake Aerodynamics of the (New) MEXICO Wind Turbine Rotor Phase-III," Energies, MDPI, vol. 14(16), pages 1-26, August.
    9. Zhong, Junwei & Li, Jingyin, 2020. "Aerodynamic performance prediction of NREL phase VI blade adopting biplane airfoil," Energy, Elsevier, vol. 206(C).

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