The simulation of the complex flow in a wind turbine wake is a challenging problem. To date, much of the research has been inhibited by both the time and computational costs associated with turbulence modelling. Additionally, the majority of numerical investigations focus on turbine performance and therefore neglect the near wake of a Horizontal Axis Wind Turbine (HAWT) entirely. This investigation focuses on experimentally and numerically quantifying the near wake structure of a model HAWT. The Shear Stress Transport (SST) k−ωk−ω, Elliptical-Blending Reynolds Stress Model (EB-RSM) and the Reynolds Stress Transport (RST) turbulence models were used to model a turbine wake in the current study, with the results verified against experimental hot-wire data. Near wake velocity and turbulence characteristics were investigated to determine if low-order models can accurately predict the magnitude and distribution of velocity and turbulence values in the near wake of a model HAWT. The HAWT model was operated at two TSR values of 2.54 and 3.87. All models predicted velocity deficit values to within 2–4% and 4–7% of experimental results for TSR values of 2.54 and 3.87 respectively. Results showed that all models were able to accurately predict the mean velocity deficit generated in the near wake. All models were able to predict the fluctuating u and v velocity components in the near wake to the correct order of magnitude with the fluctuating velocity components having an inverse Laplace distribution in the wake. However, all models under-estimated the magnitude of these velocity values with predictions as low as −43% of experimental results.
|Number of pages||22|
|Journal||Journal of Wind Engineering and Industrial Aerodynamics|
|Early online date||15 Mar 2018|
|Publication status||Published - May 2018|