  This work introduces the Area Localized Coupled (ALC) model, which extends
earlier approaches to coupling classical wake superposition and atmospheric
boundary layer models in order to enable applicability to arbitrary wind-farm
layouts. Coupling wake and top-down boundary layer models is particularly
challenging since the latter requires averaging over planform areas associated
with certain turbine-specific regions of the flow. The ALC model uses Voronoi
tesselation to define a local area around each turbine. A top-down description
of a developing internal boundary layers is then applied over Voronoi cells
upstream of each turbine to estimate the local mean velocity profile. Coupling
between the velocity at hub-height based on this localized top-down model and a
wake model is achieved by enforcing a minimum least-square-error in mean
velocity in each cell. The ALC model is implemented using a wake model with a
profile that transitions from a top-hat to Gaussian function and accounts for
wake interactions through linear superposition. Detailed comparisons to
large-eddy simulation (LES) data demonstrate the efficacy of the model in
accurate predictions of both power and hub height velocity for complex wind
farm geometries. Further validation with LES for a hybrid array-random farm
that has half of the turbines arranged in an array and the other half randomly
distributed indicates the model's versatility with respect to capturing results
from different wind farm configurations. In both cases, the ALC model is shown
to produce improved power predictions for both the farm and individual turbines
over prevailing approaches for a range of wind inflow directions.
