Field Experiments

The field experiments of the WiRE lab focus on measurements of the atmospheric flow around turbines using modern remote sensing instruments, an in-house UAV measurement platform, and in-situ instruments. Research topics currently investigated are the wake of yawed wind turbines, the influence of wind veer on the wake, and wake meandering. The WiRE lab also develops the methods required to carry out the aforementioned research.

Wake recovery

The wind turbine wake is a spatial volume of reduced velocity and increased turbulence downstream of a wind turbine. It can affect other turbines downstream negatively by decreasing their performance and durability. Field experiments of the WiRE lab showed the dependency of the wake recovery on the turbulence levels of the environment and quantified it (Fig. 1).

Field Experiement
Figure 1: Longitudinal velocity field (top) and turbulence intensity (bottom) downstream of wind turbine. The left shows a low turbulence inflow typical for nighttime and the right colum shows a high turbulence inflow typical during daytime. Figure adapted form [1].

Active wake steering

 Active wake steering or also known as active yaw control is a wind turbine control strategy with the aim to deflect the wake away from downstream turbines. A field test of active wake steering was conducted at a full-scale wind farm (Fig. 1 and Fig. 2). Results from this campaign showed that yawing a wind turbine deflects the wake as expected from modelling and highlighted the importance of precise and accurate wind direction measurements for the input of the yaw controller.

Field Measurements
Figure 2: Deployment of a Doppler LiDAR on the nacelle of a wind turbine for an active wake steering field test at a wind farm in north-western Colorado, US.
Field measurement
Figure 3: Wake deflection from a yawed wind turbine compare with model prediction (solid black line). Note the difference to the non-yawed wind turbines further downstream.

Wind veer affects span-wise cross section of the wake

The shape of the temporal-averaged wake is strongly influenced by a change of the wind direction with height, called wind veer, that is typical for the atmospheric boundary layer. Field experiments showed that prediction of an analytical model developed by WiRE [5] replicated the findings of the real world (Fig. 4).

Field measurement
Figure 4:  Example cases of volumetric wake measurements for weak wind veer (a–c) and strong wind veer (d–f). The left column (a,d) shows the wind direction profile of the inflow, the middle colum (b,e) a horizontal cross section of the longitudinal velocity deficit at hub height, and the right column (c,f) a vertical cross section of the longitudinal velocity at a distance of 6 rotor diameters. Figure was published in [4].


  • [1] Carbajo Fuertes, F.; Markfort, C.D.; Porté-Agel, F. Wind Turbine Wake Characterization with Nacelle-Mounted Wind Lidars for Analytical Wake Model Validation. Remote Sens. 2018, 10, 668.
  • [2] Brugger, P., Debnath, M., Scholbrock, A., Fleming, P., Moriarty, P., Simley, E., Jager, D., Roadman, J., Murphy, M., Zong, H., and Porté-Agel, F.: Lidar measurements of yawed-wind-turbine wakes: characterization and validation of analytical models, Wind Energ. Sci., 5, 1253–1272,, 2020.
  • [3] Bastankhah, M., & Porté-Agel, F. (2016). Experimental and theoretical study of wind turbine wakes in yawed conditions. Journal of Fluid Mechanics, 806, 506-541. doi:10.1017/jfm.2016.595
  • [4] Brugger, P.; Fuertes, F.C.; Vahidzadeh, M.; Markfort, C.D.; Porté-Agel, F. Characterization of Wind Turbine Wakes with Nacelle-Mounted Doppler LiDARs and Model Validation in the Presence of Wind Veer. Remote Sens. 2019, 11, 2247
  • [5] Abkar, M.; Sørensen, J.N.; Porté-Agel, F. An Analytical Model for the Effect of Vertical Wind Veer on Wind Turbine Wakes. Energies 2018, 11, 1838.