shape optimization of nrel s809 airfoil for wind turbine blades using a multiobjective genetic algorithm

The goal of this paper is to employ a multiobjective genetic algorithm (MOGA) to optimize the shape of a well-known wind turbine airfoil S809 to improve its lift and drag characteristics, in particular to achieve two objectives, that is, to increase its lift and its lift to drag ratio. The commercially available software FLUENT is employed to calculate the flow field on an adaptive structured mesh using the Reynolds-Averaged Navier-Stokes (RANS) equations in conjunction with a two-equation k-ω SST turbulence model. The results show significant improvement in both lift coefficient and lift to drag ratio of the optimized airfoil compared to the original S809 airfoil. In addition, MOGA results are in close agreement with those obtained by the adjoint-based optimization technique.