4.7 Article

Tidal turbine performance and near-wake characteristics in a sheared turbulent inflow

期刊

RENEWABLE ENERGY
卷 175, 期 -, 页码 840-852

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2021.05.026

关键词

Sheared turbulent inflows; Tidal stream turbine; Near-wake; Performance characteristics; Active grid

资金

  1. US National Science Foundation (CBETFluid Dynamics) [1706358]
  2. Lehigh University
  3. Directorate For Engineering
  4. Div Of Chem, Bioeng, Env, & Transp Sys [1706358] Funding Source: National Science Foundation

向作者/读者索取更多资源

Tidal stream turbines in high-energy tidal sites are affected by turbulent non-homogeneous flow environments, particularly the shear effects caused by turbulent inflow that reduce the power coefficient. The study results show that sheared turbulent inflows lead to increased torque and thrust fluctuations in the turbine model, asymmetry in the near-wake, and gradual effects on wake turbulence and velocity deficit.
Turbulent non-homogenous flow environments at high-energy tidal sites lead to variation in power performance of tidal stream turbines. In addition, non-uniform loading due to combined effects of shear and elevated inflow turbulence affects device survivability. In the current study, an active-grid turbulence generator is used to mimic sheared-turbulent inflow representative of the flood (low shear) and ebb tides (high shear). The performance and near-wake characteristics of a turbine model measured in the sheared-turbulent inflow conditions are compared to conditions where the flow velocity is uniform with low and elevated turbulence intensities (Ti). The sheared-turbulent inflows were observed to result in a 5-15% drop in maximum power coefficient when compared to the low Ti case. An increase of -30% in torque- and -50% in thrust-fluctuations were observed for sheared inflows. Unlike the near axisymmetric wake profiles observed for homogeneous cases, inflow shear was observed to incite asymmetry in the near-wake with an immediate impact in wake turbulence and a more gradual effect on the velocity deficit and integral length scales. The data sets are deemed valuable in calibrating computational models to better predict turbine response and optimize turbine efficiency and the complementing power takeoff system. (C) 2021 Elsevier Ltd. All rights reserved.

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