This work compares the performances of a Horizontal Axis Wind Turbine (HAWT) and a Vertical Axis Wind Turbine (VAWT) using Wall modeled Large Eddy Simulation (WMLES) coupled with an actuator line method. The wind turbines are located in the vicinity of a real size industrial building. Both wind turbines are sized to produce the same power at their respective optimum Tip Speed Ratio for a same incident wind speed. Two relevant incident wind directions (SW and SSW) are investigated, the influence of the building on the performance of the two wind turbines is also analysed. The results obtained show that the HAWT has a better overall performance compared to the VAWT. Overspeeds are observed for both directions analysed, due to the presence of the building which locally increases the flow velocity. However, these overspeeds remain low due to the low height of the building. The change of wind direction only slightly impacts the HAWT production, while the VAWT production remains insensitive. However, the presence of the building improves the global production of both wind turbines. Qualitatively, this change of wind direction induces a deviation in the wake of both turbines, which is greater for a SW direction.

The development of turbulent vortical wakes released downstream of wind turbines is crucial as it presents many technological implications for wind farm design and exploitation. The numerical prediction of these wakes constitutes a challenging problem as they involve the shedding of fine vortical structures, their instabilities, and interactions with a turbulent ambient flow. A Large Eddy Simulation (LES) approach allows capturing such flow phenomena, which implies a suitable mesh. Adaptive Mesh Refinement (AMR) is used to refine the mesh in the wind turbine wake to limit the computational cost. A methodology is developed to define and capture the wake envelope adequately. Three main parts of this methodology can be identified: The wind turbine wake detection, the target cell size required and adaptation frequency. The target cell size needed to properly capture the wind turbine wake is investigated in previous work [1], while this paper focuses on wind turbine wake detection. A strategy based on a progress variable with a source term in the rotor region is used to capture the wake. This variable is transported by the flow and thus defines the wake envelope. AMR is used to refine the mesh within this region. To validate the method, a comparison between an adaptive mesh case and a reference mesh case has been performed on a single rotor and a two aligned rotor configuration. For both, the wind turbine wake tracking method is effective. The progress variable is transported correctly and leads to a well-defined wake area. The mesh is refined adequately within it. The physical comparison between cases showed similar results, while the performance comparison showed a computational cost reduction of 30% in the single turbine configuration and 50% in the two turbines configuration. Therefore, our methodology coupled with adaptive mesh refinement can adequately capture wind turbine wake, define an accurate wake envelope and decrease the computational cost for the same physical precision.