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Large Eddy Simulation of flow around a single and two in-line horizontal-axis wind turbines

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  • Amin Allah, Veisi
  • Shafiei Mayam, Mohammad Hossein

Abstract

A Large Eddy Simulation (LES) has been employed in order to study the flow field in a single-wind turbine and in two in-line wind turbines. The present study focuses on the flow around a horizontal axis wind turbine in a virtual wind tunnel. The anisotropic residual stress tensor is driven by the Smagorinsky model. The results are consistent with experimental data presented in literature. Streamwise velocity is increased and cross stream velocity is decreased as wake moves in downstream direction. A faster rate of wake recovery is seen for the two in-line setup. The results reveal that turbulence intensity is increased by increasing the downstream distance and two in-line turbines show greater intensity. Wind turbine performance can be affected by the turbulent structures. If this phenomenon occurs, information about turbulent structures would be useful in order to investigate the effect of turbulent structures on wind turbine performance. As a result, we aim to reveal the effect of turbulent structures, by using the λci technique in this study, and to investigate the performance of wind turbines in different conditions. Furthermore, the effects of blade rotation direction are studied in this paper. It is concluded that wind turbine efficiency is increased by 4%.

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  • Amin Allah, Veisi & Shafiei Mayam, Mohammad Hossein, 2017. "Large Eddy Simulation of flow around a single and two in-line horizontal-axis wind turbines," Energy, Elsevier, vol. 121(C), pages 533-544.
  • Handle: RePEc:eee:energy:v:121:y:2017:i:c:p:533-544
    DOI: 10.1016/j.energy.2017.01.052
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    References listed on IDEAS

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    Cited by:

    1. Veisi, Amin Allah & Shafiei Mayam, Mohammad Hossein, 2017. "Effects of blade rotation direction in the wake region of two in-line turbines using Large Eddy Simulation," Applied Energy, Elsevier, vol. 197(C), pages 375-392.
    2. Torres Garcia, E. & Aubrun, S. & Coupiac, O. & Girard, N. & Boquet, M., 2019. "Statistical characteristics of interacting wind turbine wakes from a 7-month LiDAR measurement campaign," Renewable Energy, Elsevier, vol. 130(C), pages 1-11.
    3. Win Naung, Shine & Nakhchi, Mahdi Erfanian & Rahmati, Mohammad, 2021. "High-fidelity CFD simulations of two wind turbines in arrays using nonlinear frequency domain solution method," Renewable Energy, Elsevier, vol. 174(C), pages 984-1005.
    4. Shen, Xin & Chen, Jinge & Hu, Ping & Zhu, Xiaocheng & Du, Zhaohui, 2018. "Study of the unsteady aerodynamics of floating wind turbines," Energy, Elsevier, vol. 145(C), pages 793-809.
    5. Fei, Zhao & Tengyuan, Wang & Xiaoxia, Gao & Haiying, Sun & Hongxing, Yang & Zhonghe, Han & Yu, Wang & Xiaoxun, Zhu, 2020. "Experimental study on wake interactions and performance of the turbines with different rotor-diameters in adjacent area of large-scale wind farm," Energy, Elsevier, vol. 199(C).
    6. Zhang, Sanxia & Luo, Kun & Yuan, Renyu & Wang, Qiang & Wang, Jianwen & Zhang, Liru & Fan, Jianren, 2018. "Influences of operating parameters on the aerodynamics and aeroacoustics of a horizontal-axis wind turbine," Energy, Elsevier, vol. 160(C), pages 597-611.
    7. Yang, Haoze & Ge, Mingwei & Gu, Bo & Du, Bowen & Liu, Yongqian, 2022. "The effect of swell on marine atmospheric boundary layer and the operation of an offshore wind turbine," Energy, Elsevier, vol. 244(PB).

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