The paper demonstrates the potential of an unsteady RANS 3D approach to predict the effects of skewed winds on the performance of an H-type vertical-axis wind turbine (VAWT). The approach is validated through a comparison between numerical and experimental results for a full-scale Darrieus turbine, demonstrating an improved prediction ability of 3D CFD with respect to both 2D CFD and semi-empirical models based on the double multiple stream tubes method. A 3D URANS approach is then adopted to investigate the power increase observed for a straight-bladed small-scale turbine in a wind tunnel when the rotational axis is inclined from 0° to 15° from the vertical. The main advantage of this approach is a more realistic description of complex three-dimensional flow characteristics, such as dynamic stall, and the opportunity to derive local blade flow conditions on any blade portion during upwind and downwind paths. Consequently, in addition to deriving the turbine overall performance in terms of power coefficient, a better insight into the temporal and spatial evolution of the physical mechanisms is obtained. Our principal finding is that the power gain in skewed flows is obtained during the downwind phase of the revolution as the end part of the blade is less disturbed by the wake generated during the upwind phase.