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Influences of yaw angle and turbulence intensity on the performance of a 20 kW in-stream hydrokinetic turbine

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  • Tian, Wenlong
  • VanZwieten, James H.
  • Pyakurel, Parakram
  • Li, Yanjun

Abstract

Three-dimensional transient CFD (Computational Fluid Dynamics) simulations are performed to study the hydrodynamic performance of an ocean current turbine with a 3.0 m diameter 3-bladed rotor. Simulations are based on the RANS (Reynolds Averaged Navier–Stokes) equations and the shear stress transport k-ω turbulent model is utilized. The influence of yaw angle and upstream TI (turbulence intensity) on the turbine performance is studied. The CFD method is first validated using existing experimental data and good agreement is obtained. The performance of the turbine, including power, thrust and wake characteristics are then studied at different TSR (tip speed ratios). The turbine obtains a maximum coefficient of power (Cp) of 0.4642 at TSR = 6 and the coefficient of thrust (Ct) increases over the entire evaluated TSR range to a value of 0.8788 at a TSR = 10. Simulations are also performed at four different yaw angles, 0°, 5°, 10° and 15° which show that both Cp and Ct decrease as yaw angle increases. Finally simulations of three different TIs, 3%, 6% and 9%, are performed and analyzed. Results show that TI minimally affects Cp and Ct for the considered TI range, but greatly influences the downstream wake structure.

Suggested Citation

  • Tian, Wenlong & VanZwieten, James H. & Pyakurel, Parakram & Li, Yanjun, 2016. "Influences of yaw angle and turbulence intensity on the performance of a 20 kW in-stream hydrokinetic turbine," Energy, Elsevier, vol. 111(C), pages 104-116.
    • Handle: RePEc:eee:energy:v:111:y:2016:i:c:p:104-116
    DOI: 10.1016/j.energy.2016.05.012
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    10. Kumar, Anuj & Saini, R.P., 2017. "Performance analysis of a Savonius hydrokinetic turbine having twisted blades," Renewable Energy, Elsevier, vol. 108(C), pages 502-522.
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    14. Modali, Pranav K. & Vinod, Ashwin & Banerjee, Arindam, 2021. "Towards a better understanding of yawed turbine wake for efficient wake steering in tidal arrays," Renewable Energy, Elsevier, vol. 177(C), pages 482-494.
    15. Yan Pei & Zheng Qian & Bo Jing & Dahai Kang & Lizhong Zhang, 2018. "Data-Driven Method for Wind Turbine Yaw Angle Sensor Zero-Point Shifting Fault Detection," Energies, MDPI, vol. 11(3), pages 1-14, March.
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