The purpose of this study is the development of an automated two-dimensional airfoil shape optimization procedure for small horizontal axis wind turbines (HAWT), with an emphasis on high thrust and aerodynamically stable performance. The procedure combines the Computational Fluid Dynamics (CFD) analysis with the Response Surface Methodology (RSM), the Biobjective Mesh Adaptive Direct Search (BiMADS) optimization algorithm and an automatic geometry and mesh generation tool. In CFD analysis, a Reynolds Averaged Numerical Simulation (RANS) is applied in combination with a two-equation turbulence model. For describing the system behaviour under alternating wind conditions, a number of CFD 2D-RANS-Simulations with varying Reynolds numbers and wind angles are performed. The number of cases is reduced by the use of RSM. In the analysis, an emphasis is placed upon the role of the blade-to-blade interaction. The average and the standard deviation of the thrust are optimized by a derivative-free optimization algorithm to define a Pareto optimal set, using the BiMADS algorithm. The results show that improvements in the performance can be achieved by modifications of the blade shape and the present procedure can be used as an effective tool for blade shape optimization.

Wind turbines may suffer power loss after a long operation period due to degradation of the surface structure around the leading edge, by accumulation of contaminants and/or by erosion. For understanding the underlying physics, and validating the available prediction methods, the aerodynamics of smooth and artificially roughened airfoil profiles are investigated by different modelling procedures. A spectrum of turbulence models are applied encompassing RANS, URANS and DES. Two approaches are used to model the roughness. In one approach, the roughness is not geometrically resolved but its effect is modelled via the wall-functions of the turbulence models. In the alternative approach, the roughness structures are geometrically resolved, which necessitates a three-dimensional formulation, whereas the wallfunctions based approach may also be applied in two-dimensions. Computational results are compared with the experimental results of other authors, and the predictive capability of different modelling procedures are assessed.