  Next-generation models of wind farm flows are increasingly needed to assist
the design, operation, and performance diagnostic of modern wind power plants.
Accuracy in the descriptions of the wind farm aerodynamics, including the
effects of atmospheric stability, coalescing wakes, and the pressure field
induced by the turbine rotors, and low computational costs are necessary
attributes for such tools. The Pseudo-2D RANS model is formulated to provide an
efficient solution of the Navier-Stokes equations governing wind-farm flows
installed in flat terrain and offshore. The turbulence closure and actuator
disk model are calibrated based on wind LiDAR measurements of wind turbine
wakes collected under different operative and atmospheric conditions. A
shallow-water formulation is implemented to achieve a converged solution for
the velocity and pressure fields across a farm with computational costs
comparable to those of mid-fidelity engineering wake models. The theoretical
foundations and numerical scheme of the Pseudo-2D RANS model are provided,
together with a detailed description of the verification and validation
processes. The model is assessed against a large dataset of power production
for an onshore wind farm located in North Texas showing a normalized mean
absolute error of 5.6% on the 10-minute-averaged active power and 3% on the
clustered wind farm efficiency, which represent 8% and 24%, respectively,
improvements with respect to the best-performing engineering wake model tested
in this work.
