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Comparison study of URANS and hybrid RANS-LES models on predicting vertical axis wind turbine performance at low, medium and high tip speed ratio ranges

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  • Syawitri, T.P.
  • Yao, Y.F.
  • Chandra, B.
  • Yao, J.

Abstract

Comparison study of unsteady Reynolds-averaged Navier-Stokes (URANS) and hybrid RANS-LES models is carried out for predicting the performance of three-straight-bladed vertical axis wind turbine operating within tip speed ratios (TSRs) ranges of (1.44–3.3). The evaluation is focused on power coefficient, moment coefficient and vortex structure generation, growth and transportation predictions. It was found that URANS turbulence modelling is sufficient for averaged power coefficient prediction and specific range of TSR evaluation, and it also benefits from short simulation run time. To further evaluate flow field details and to understand the underlying flow physics such as dynamic stall behaviour, hybrid RANS-LES turbulence modelling is necessary. Comparing between hybrid models adopted, stress-blended eddy simulation based on transition shear-stress transport (TSST) model has achieved an overall better performance, such as a reduction of simulation discrepancy by 50% in low TSRs range compared to TSST turbulence model. In both medium and high TSRs ranges, the modelling discrepancies are less than 3% compared to TSST turbulence models at about 25% extra computational time. Furthermore, in high TSRs range, hybrid RANS-LES models are able to predict the appearance of vortex shedding at high azimuthal angles (θ ≥ 180°) for which URANS models failed to capture.

Suggested Citation

  • Syawitri, T.P. & Yao, Y.F. & Chandra, B. & Yao, J., 2021. "Comparison study of URANS and hybrid RANS-LES models on predicting vertical axis wind turbine performance at low, medium and high tip speed ratio ranges," Renewable Energy, Elsevier, vol. 168(C), pages 247-269.
    • Handle: RePEc:eee:renene:v:168:y:2021:i:c:p:247-269
    DOI: 10.1016/j.renene.2020.12.045
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    References listed on IDEAS

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    2. Kamal, Ahmed M. & Nawar, Mohamed A.A. & Attai, Youssef A. & Mohamed, Mohamed H., 2023. "Archimedes Spiral Wind Turbine performance study using different aerofoiled blade profiles: Experimental and numerical analyses," Energy, Elsevier, vol. 262(PB).
    3. Shen, He & Ruiz, Alexis & Li, Ni, 2023. "Fast online reinforcement learning control of small lift-driven vertical axis wind turbines with an active programmable four bar linkage mechanism," Energy, Elsevier, vol. 262(PA).
    4. Kamal, Ahmed M. & Nawar, Mohamed A.A. & Attai, Youssef A. & Mohamed, Mohamed H., 2022. "Blade design effect on Archimedes Spiral Wind Turbine performance: Experimental and numerical evaluations," Energy, Elsevier, vol. 250(C).

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