  Reynolds-averaged Navier-Stokes (RANS) is one of the most cost-efficient
approaches to simulate wind-farm-atmosphere interactions. However, the
applicability of RANS-based methods is always limited by the accuracy of
turbulence closure models, which introduce various uncertainties into the
models. In this study, we estimate model-form uncertainties in RANS simulations
of wind farms. For this purpose, we compare different RANS models to a
large-eddy simulation (LES). We find that the realizable k-epsilon model is a
representative RANS model for predicting the mean velocity, the turbulence
intensity, and the power losses within the wind farm. We then investigate the
model-form uncertainty associated with this turbulence model by perturbing the
Reynolds stress tensor. The focus is placed on perturbing the shape of the
tensor represented by its eigenvalues. The results show that the perturbed RANS
model successfully estimates the region bounding the LES results for quantities
of interest (QoIs). We also discuss the effect of perturbation magnitude on
various QoIs.
