TOWARDS COMPUTATIONAL PREDICTION OF WIND TURBINE FLOW AND NOISE

Wind energy is a clean, renewable, and fast-growing energy source for power generation. However, the noise issue, especially the aerodynamic noise, has become a critical obstacle in wind energy development. To determine the impact of the wind turbine noise and to guide the design and siting of wind turbines to minimize the disturbances on the local community, better understanding of the noise generation mechanisms as well as more accurate noise prediction techniques are necessary. Computational fluid dynamics (CFD) modeling of the National Renewable Energy Laboratory (NREL) Phase VI wind turbine at different wind speeds and tip pitch angles have been performed using ANSYS Fluent. The computational domain extends about 3 times of the wind turbine blade radius in the upstream direction, and 6 times the blade radius in the downstream and transverse directions. The shear-stress transport (SST) k-omega turbulence model is used. Second-order upwind schemes are used for the momentum and turbulence equations. The predicted pressure coefficients and power are in good agreement with the experimental data. The effects of wind speed and tip pitch angle on noise generation have also been investigated using the broadband noise source model. The Ffowcs-Williams Hawkings equation is also currently being used to obtain the far-field noise.