A meso-micro atmospheric perturbation model for wind farm blockage

As wind farms continue to grow in size, mesoscale effects such as blockage and gravity waves become increasingly important. Allaerts & Meyers (J. Fluid Mech., 2019) proposed an atmospheric perturbation model (APM) that can simulate the interaction of wind farms and the atmospheric boundary layer while keeping computational costs low. The model resolves the meso-scale flow, and couples to a wake model to estimate the turbine inflow velocities at the micro-scale. This study presents a new way of coupling the mesoscale APM to a wake model, based on matching the velocity between the models throughout the farm. This method performs well, but requires good estimates of the turbine-level velocity fields by the wake model. Additionally, we investigate the mesoscale effects of a large wind farm, and find that aside from the turbine forces and increased turbulence levels, the dispersive stresses due to subgrid flow heterogeneity also play an important role at the entrance of the farm, and contribute to the global blockage effect. By using the wake model coupling, we can explicitly incorporate these stresses in the model. The resulting APM is validated using 27 LES simulations of a large wind farm under different atmospheric conditions. The APM and LES results are compared on both meso- and turbine-scale, and on turbine power output. The APM captures the overall effects gravity waves have on wind farm power production, and significantly outperforms standard wake models.