Analysis of Turbine Wake Characteristics using Proper Orthogonal Decomposition and Triple Decomposition Methods

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Virginia Tech


In the present study, we report the progress made in our efforts to examine the wake flow characteristics behind a commonly-used three-bladed horizontal-axis wind turbine. A series of experiments were performed in a large-scale wind tunnel with a scaled wind turbine model placed in a typical Atmospheric Boundary Layer (ABL) wind under neutral stability conditions. In addition to measuring dynamic wind loads acting on the model turbine by using a force- moment sensor, a high-resolution digital particle image velocimetry (PIV) system was used to achieve detailed flow field measurements to quantify the characteristics of the turbulent vortex flow behind the turbine model. Besides conducting “free-run” PIV measurements to determine the ensemble-averaged statistics of the flow quantities such as mean velocity, Reynolds stress, and turbulence kinetic energy (TKE) distributions in the wake flow, “phase-locked” PIV measurements were also performed to elucidate further details about evolution of the unsteady wake vortex structures in relation to the position of the rotating turbine blades. The detailed flow field measurements were used to validate the analytical models for the velocity deficit prediction in turbine wakes. Proper Orthogonal Decomposition (POD) method was employed in the present study for the data reduction of the PIV measurement results to identify the high energy modes that dominate the turbulent kinetic energy distributions in the turbine wakes. Triple Decomposition (TD) approach was also used to analyze the phase-locked PIV measurement results to elucidate the underling physics related to the intensive turbulent mixing process in the wake flow, which would promote the vertical transport of kinetic energy to entrain more high-speed airflow from above to re-charge the wake flow behind the wind turbine model.




Premaratne, P., Tian, W., & Hu, H. (2015, June). Analysis of turbine wake characteristics using proper orthogonal decomposition and triple decomposition methods. Paper presented at the North American Wind Energy Academy 2015 Symposium, Blacksburg, VA.