  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.
