Reduced-order modelling of winglet wind turbine wake characteristics.

Power production of a horizontal-axis wind turbine (HAWT) is affected by unsteady turbulent structures which span large range of length scales. To curb this challenge winglets are attached to the tip of horizontal axis wind turbines to optimize performance by reducing the wing tip vortices which causes extra drag and lift. In this work, we used Proper Orthogonal Decomposition (POD) method as a reduced order model in analyzing the wake characteristics of a horizontal-axis wind turbine (HAWT) with winglets. The method is used to identify energic turbulent modes for near, mid, and far stream wake structures of the optimized three bladed winglet configuration. Measured data in this work was taken from a wind tunnel experimental facility using a prototype scaled model with neutral inlet boundary layer. A high-resolution Particle Image Velocimetry (PIV) was used to capture and characterize the wake vortex structures. The accuracy of the POD reconstruction technique will be validated qualitatively with the statistical-averaged PIV measurement results. The reduced order model provides knowledge of the underlying physics and how the changes in the wake flow affects power and thrust coefficient measurements.