Previous research has revealed the need for a validation study that considers several wake quantities and code types so that decisions on the trade-off between accuracy and computational cost can be well informed and appropriate to the intended application. In addition to guiding code choice and setup, rigorous model validation exercises are needed to identify weaknesses and strengths of specific models and guide future improvements. Here, we consider 13 approaches to simulating wakes observed with a nacelle-mounted lidar at the Scaled Wind Technology Facility (SWiFT) under varying atmospheric conditions. We find that some of the main challenges in wind turbine wake modeling are related to simulating the inflow. In the neutral benchmark, model performance tracked as expected with model fidelity, with large-eddy simulations performing the best. In the more challenging stable case, steady-state Reynolds-averaged Navier-Stokes simulations were found to outperform other model alternatives because they provide the ability to more easily prescribe noncanonical inflows and their low cost allows for simulations to be repeated as needed. Dynamic measurements were only available for the unstable benchmark at a single downstream distance. These dynamic analyses revealed that differences in the performance of time-stepping models come largely from differences in wake meandering. This highlights the need for more validation exercises that take into account wake dynamics and are able to identify where these differences come from: mesh setup, inflow, turbulence models, or wake-meandering parameterizations. In addition to model validation findings, we summarize lessons learned and provide recommendations for future benchmark exercises.

For large wind farms, kinetic energy must be entrained from the flow above the wind turbines to replenish wakes and enable power extraction in the array. Various statistical features of turbulence causing vertical entrainment of mean-flow kinetic energy are studied using hot-wire velocimetry data taken in a model wind farm in a scaled wind tunnel experiment. Conditional statistics and spectral decompositions are employed to characterize the most relevant turbulent flow structures and determine their length-scales. Sweep and ejection events are shown to be the largest contributors to the vertical kinetic energy flux, although their relative contribution depends upon the location in the wake. Sweeps are shown to be dominant in the region above the wind turbine array. A spectral analysis of the data shows that large scales of the flow, about the size of the rotor diameter in length or larger, dominate the vertical entrainment. The flow is less incoherent below the array, causing decreased vertical fluxes there. The results show that improving the rate of vertical kinetic energy entrainment into wind turbine arrays is a standing challenge and would require modifying the large-scale structures of the flow. Such an optimization would in the future aid recovery of the wind turbine wake towards conditions corresponding to the undisturbed atmospheric boundary layer. V C 2012 American Institute of Physics. [http://dx.

Cartesian and row-offset wind turbine array configurations were tested investigating the wake interaction and recovery dynamics. The snapshot proper orthogonal decomposition is applied to velocity measurements. Resulting modes are used in constructing low-dimensional descriptions of turbulence statistics including the turbulence kinetic energy production and the flux of turbulence kinetic energy. Descriptions of the turbulent behavior are made on the basis of the span of the streamwise average profile of the Reynolds shear stress, uv, with the addition of orthogonal modes. The Reynolds stress criterion was selected for the convergence of the model as it is a good representation of the range of turbulent dynamics in the wake of a wind turbine. The description demonstrates that the turbulence kinetic energy production and the flux of turbulence kinetic energy are accurately rebuilt with approximately 1% of the total resultant orthogonal modes. Structures associated with the top-tip of the rotor blade reconstruct with fewer modes than those associated with the bottom-tip of the rotor or the nacelle. This confirms that the greatest part of the turbulence kinetic energy is located high in the turbine canopy as described by the turbulent stresses. Overall, behavior of individual turbines in recovered positions within the arrays requires fewer modes to converge than those in locations with less recovered inflows.

Model wind turbine arrays were developed for the purpose of investigating the wake interaction and turbine canopy layer in a standard cartesian and row-offset turbine array configurations. Stereographic particle image velocimetry was used to collect flow data upstream and downstream of entrance and exit row turbines in each configuration. Wakes for all cases were analyzed for energy content and recovery behavior including entrainment of high-momentum flow from above the turbine canopy layer. The row-offset arrangement of turbines within an array grants an increase in streamwise spacing of devices and allows for greater wake remediation between successive rows. These effects are seen in exit row turbine wakes as changes to statistical quantities including the in-plane Reynolds stress, uv, and the production of turbulence. The recovery of wakes also strongly mitigates the perceived underperformance of wind turbines within an array. The flux of kinetic energy is demonstrated to be more localized in the entrance rows and in the offset arrangement. Extreme values for the flux of kinetic energy are about 7:5% less in the exit row of the cartesian arrangement than in the offset arrangement. Measurements of mechanical torque at entrance and exit row turbines lead to curves of power coefficient and demonstrate an increase in efficiency in row-offset configurations.

No abstract