This manuscript presents an effort towards the introduction of a new grid generation tool for computational fluid dynamics (CFD) simulations of wind turbines. The tool was developed and designed to considerably reduce the duration and complexity of the grid generation process and, moreover, to enable users to perform an efficient CFD simulation for a complete wind turbine rotor. Furthermore, the tool is fully automatized, thus enabling the user to refine the grid along the desired direction. For the purpose of validation, the quality of the generated grid was checked via a grid independence test. Finally, the grid generator tool was evaluated by means of a series of simulations of the NREL phase VI rotor using a three-dimensional CFD Reynolds averaged Navier–Stokes method. The capability of CFD simulations based on the generated grid in capturing aerodynamic performances (such as the power) and the detailed flow characteristics (e.g. the surface pressure distributions) were investigated under various conditions. The obtained results demonstrate the quality and reliability of the developed grid generation tool.

In this paper, we study a two-person game between one leader and one follower, called the Stackelberg game. The leader player enounces a decision before the others, and the follower takes into account this decision and solves an optimization problem that may have multiple solutions. Then, the leader optimizes his objective by assuming a given follower's reaction depending on his behavior. We consider in this paper a hierarchical equilibrium solution for a two-level game, particularly the strong Stackelberg solutions that corresponds to an optimistic leader's point of view and we give a numerical procedure based on a genetic algorithm (GA) evolution process to compute them. The use of a multimodal genetic algorithm allows us to approach the possible multiple solutions to the lower level problem. The algorithm convergence is illustrated by means of some test cases.

In this work the improved version of an engineering model which accounts for rotational augmentation effects by means of computational fluid dynamics (CFD) calibration is explored and discussed. Based on an analysis of the NREL Phase VI wind turbine, the novel modeling is presented, which uses as base line the formulation proposed by Chaviaropoulos and Hansen. The model is calibrated based on CFD simulations using OpenFOAM. The corresponding correction of the two dimensional polars is straightforward implemented within MoWiT, an in-house software for load calculation. The novel formulation results in improved lift and drag coefficients prediction in all considered cases, reducing the deviation with respect to the rotating CFD cases down to few percent. The optimal configuration including the correction for tip effects of Shen shows better agreements at the very tip of the blade. Furthermore the range of applicability for large wind turbine rotor blades based on a virtual $$10\,\hbox {MW}$$10MW rotor model is discussed.