Reducing wake losses in wind farms by deflecting the wakes through turbine yawing has been shown to be a feasible wind farm controls approach. Nonetheless, the effectiveness of yawing depends not only on the degree of wake deflection but also on the resulting shape of the wake. In this work, the deflection and morphology of wakes behind a wind turbine operating in yawed conditions are studied using wind tunnel experiments of a wind turbine modeled as a porous disk in a uniform inflow. First, by measuring velocity distributions at various downstream positions and comparing with prior studies, we confirm that the non-rotating wind turbine model in yaw generates realistic wake deflections. Second, we characterize the wake shape and make first observations of what is termed a curled wake, displaying significant spanwise asymmetry. The wake curling observed in the experiments is also reproduced qualitatively in large eddy simulations using both actuator disk and actuator line models. When a wind turbine is yawed for the benefit of downstream turbines, the asymmetric shape of the wake must be taken into account since it affects how much of it intersects the downstream turbines.PREPRINT, submitted to the Journal of Renewable and Sustainable Energy (January 2016) Ref. [14] used two aligned turbines in a wind tunnel and tested varying the rotor yaw angle, tip speed ratio, and the blade pitch of the upstream wind turbine only. This study showed that varying the yaw angle of the wind turbine was of comparable benefit to increasing the streamwise spacing between turbines, with an optimal power output occurring at 30 • . Refs. [17,18] studied the effects of controlling yaw angle, tip speed ratio, and the blade pitch of the upstream turbine for scaled model wind turbines, with results also revealing the benefits of yawing the upstream turbine. Further, yaw misalignment has been shown to reduce the steady-state blade loading variations by up to 70%, which has lead to the use of yawing to increase operational life [19]. Ref.[20] studied a rotating wind turbine model in replicated atmospheric boundary layer conditions to discover a deflection of approximately 0.6D in the far wake.Refs. [9,[21][22][23] were computational studies of wake deflection using various yaw angles. Ref.[21] uses LES with an actuator disk model with turbulent inflow and shows that wake deflection can be reproduced in such simulations. They also propose a momentum-based model for the deflection which is compared to LES with reasonable validity in the far wake. Some experimental results are compared, but the authors cite a need for more experimental verification before a wake controller may be developed.Ref.[9] studied wake deflection under various conditions using the SOWFA Large Eddy Simulation (LES) code and using the NREL 5 MW turbine model [24]. When the yaw angle γ was γ = 30 • , the study found the maximum wake deflection to reach about 0.5D in the far wake, where D is the rotor diameter. Ref.[22] studied the near wake structure of a wind turbine unde...

Unsteady-loading and spatio-temporal characteristics of power output are measured in a windtunnel experiment of a micro-scale wind farm model with 100 porous disk models. The model wind farm is placed in a scaled turbulent boundary layer and six different layouts, varied from aligned to staggered, are considered. The measurements are done by making use of a specially designed small-scale porous disk model, instrumented with strain gages. The frequency response of the measurements goes up to the natural frequency of the model, which corresponds to a reduced frequency of 0.6 when normalized by the diameter and the mean hub height velocity. The equivalent range of time-scales, scaled to field-scale values, is 15 seconds and longer. The accuracy and limitations of the acquisition technique are documented and verified with hot-wire measurements. The spatio-temporal measurement capabilities of the experimental setup are used to study the cross-correlation in the power output of various porous

The fluctuations in power output from wind farms display significantly reduced spectra compared to single wind turbines due to power smoothing and averaging. In order to better understand these spectral features and to relate them to properties of turbulent boundary layers, we perform a wind tunnel experiment in which we measure spatio-temporal characteristics of an experimental surrogate of the power output from a micro wind farm with 100 porous disk models. The experimental results show that the frequency spectrum of the total wind farm power follows a power law with a slope between −5/3 and −2, and up to lower frequencies than seen for any individual turbine model. In agreement with previous studies in the literature, peaks in the spectrum are observed at frequencies corresponding to the mean flow convection time between consecutive turbines. In the current work we interpret the sum of power extraction from an array of turbines as a discrete spatial filtering of a turbulent boundary layer and derive the associated transfer function. We apply it to an existing model for the wavenumber-frequency spectrum of turbulent boundary layers. This approach allows us to verify the individual roles of Doppler shift and broadening of frequencies on the resulting spatially sampled frequency spectrum. Comparison with the wind tunnel data confirms that the approach captures and explains the main features in the spectrum, indicating the crucial role of the interaction between the spatial sampling and the space-time correlations inherently present in the flow. The frequency spectrum of the aggregated power from a wind farm thus depends on both the spectrum of the incoming turbulence and its modulation by the spatial distribution of turbines in the boundary layer flow.