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Modelling turbulence with an Actuator Disk representing a tidal turbine

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  • Nguyen, Van Thinh
  • Guillou, Sylvain S.
  • Thiébot, Jérôme
  • Santa Cruz, Alina

Abstract

RANS turbulence models in association with the Actuator Disk theory is among the most popular concepts to predict the wake of tidal turbines. This methodology has the advantage of giving accurate results at affordable computing costs. In this paper, several turbulence models usually used to simulate the wake behind a turbine represented by a porous disk are compared. The tested models are the Standard and the Realizable k-ε models, the SST k-ω model and the Reynolds Stress Model (RSM). The results of the simulations are validated against experimental data measured behind a porous disk placed in a laboratory water flume. The experimental data consist of a set of turbulence intensity and velocity profiles. Without modifying the turbulence models, both velocities and turbulence intensities are well simulated by all the models in the far wake. However, in the near wake, the results strongly differ from one model to another. In the vicinity of the disk, the Standard k-ε model provides the most accurate results. The other models tend to underestimate the turbulence production as the fluid passes through the disk. To compensate this, another set of simulations are performed adding TKE (Turbulent Kinetic Energy) within the porous disk. The optimal amount of additional TKE differs from one model to another. Except for the Standard k-ε model, the correlation between the model and the experimental results is significantly improved when enhancing the TKE in the area occupied by the disk.

Suggested Citation

  • Nguyen, Van Thinh & Guillou, Sylvain S. & Thiébot, Jérôme & Santa Cruz, Alina, 2016. "Modelling turbulence with an Actuator Disk representing a tidal turbine," Renewable Energy, Elsevier, vol. 97(C), pages 625-635.
  • Handle: RePEc:eee:renene:v:97:y:2016:i:c:p:625-635
    DOI: 10.1016/j.renene.2016.06.014
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    References listed on IDEAS

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    Cited by:

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    4. Tian, Linlin & Song, Yilei & Zhao, Ning & Shen, Wenzhong & Zhu, Chunling & Wang, Tongguang, 2020. "Effects of turbulence modelling in AD/RANS simulations of single wind & tidal turbine wakes and double wake interactions," Energy, Elsevier, vol. 208(C).
    5. Lo Brutto, Ottavio A. & Thiébot, Jérôme & Guillou, Sylvain S. & Gualous, Hamid, 2016. "A semi-analytic method to optimize tidal farm layouts – Application to the Alderney Race (Raz Blanchard), France," Applied Energy, Elsevier, vol. 183(C), pages 1168-1180.
    6. Anas Rahman & Vengatesan Venugopal & Jerome Thiebot, 2018. "On the Accuracy of Three-Dimensional Actuator Disc Approach in Modelling a Large-Scale Tidal Turbine in a Simple Channel," Energies, MDPI, vol. 11(8), pages 1-21, August.
    7. Linlin Tian & Yilei Song & Ning Zhao & Wenzhong Shen & Tongguang Wang, 2019. "AD/RANS Simulations of Wind Turbine Wake Flow Employing the RSM Turbulence Model: Impact of Isotropic and Anisotropic Inflow Conditions," Energies, MDPI, vol. 12(21), pages 1-14, October.
    8. Lo Brutto, Ottavio A. & Nguyen, Van Thinh & Guillou, Sylvain S. & Thiébot, Jérôme & Gualous, Hamid, 2016. "Tidal farm analysis using an analytical model for the flow velocity prediction in the wake of a tidal turbine with small diameter to depth ratio," Renewable Energy, Elsevier, vol. 99(C), pages 347-359.
    9. Garcia-Novo, Patxi & Inubuse, Masako & Matsuno, Takeshi & Kyozuka, Yusaku & Archer, Philip & Matsuo, Hiroshi & Henzan, Katsuhiro & Sakaguchi, Daisaku, 2024. "Characterization of the wake generated downstream of a MW-scale tidal turbine in Naru Strait, Japan, based on vessel-mounted ADCP data," Energy, Elsevier, vol. 299(C).
    10. Thiébaut, Maxime & Quillien, Nolwenn & Maison, Antoine & Gaborieau, Herveline & Ruiz, Nicolas & MacKenzie, Seumas & Connor, Gary & Filipot, Jean-François, 2022. "Investigating the flow dynamics and turbulence at a tidal-stream energy site in a highly energetic estuary," Renewable Energy, Elsevier, vol. 195(C), pages 252-262.
    11. Brown, S.A. & Ransley, E.J. & Greaves, D.M., 2020. "Developing a coupled turbine thrust methodology for floating tidal stream concepts: Verification under prescribed motion," Renewable Energy, Elsevier, vol. 147(P1), pages 529-540.
    12. Chen, Yaling & Wang, Dayu & Wang, Dangwei, 2024. "The flow field within a staggered hydrokinetic turbine array," Renewable Energy, Elsevier, vol. 224(C).
    13. Tian, Linlin & Song, Yilei & Wang, Zhenming & Zhao, Ning & Zhu, Chunling & Lu, Xiyun, 2024. "Predictive capability of an improved AD/RANS method for multiple wind turbines and wind farm wakes," Energy, Elsevier, vol. 297(C).
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    15. Chen, Yaling & Lin, Binliang & Lin, Jie & Wang, Shujie, 2017. "Experimental study of wake structure behind a horizontal axis tidal stream turbine," Applied Energy, Elsevier, vol. 196(C), pages 82-96.
    16. Jérôme Thiébot & Nasteho Djama Dirieh & Sylvain Guillou & Nicolas Guillou, 2021. "The Efficiency of a Fence of Tidal Turbines in the Alderney Race: Comparison between Analytical and Numerical Models," Energies, MDPI, vol. 14(4), pages 1-13, February.
    17. Yang, Zhixue & Ren, Zhouyang & Li, Hui & Pan, Zhen & Xia, Weiyi, 2024. "A review of tidal current power generation farm planning: Methodologies, characteristics and challenges," Renewable Energy, Elsevier, vol. 220(C).
    18. Lo Brutto, Ottavio A. & Guillou, Sylvain S. & Thiébot, Jérôme & Gualous, Hamid, 2017. "Assessing the effectiveness of a global optimum strategy within a tidal farm for power maximization," Applied Energy, Elsevier, vol. 204(C), pages 653-666.

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