Optimization of Wind Turbine Blade Airfoils Using a Multi-Objective Genetic Algorithm


Abstract

The FX, DU, and NACA 64 series airfoils are thick airfoils widely used for wind turbine blade applications. They have several advantages in meeting the intrinsic requirements for wind turbines in terms of design point, off-design capabilities, and structural properties. This study employs a multi-objective genetic algorithm for shape optimization of FX, DU, and NACA 64 series airfoils to achieve two objectives, namely, the generation of both maximum lift and maximum lift-to-drag ratio. A commercially available computational fluid dynamics software package is employed for calculation of the flowfield using the Reynolds-averaged Navier Stokes equations in conjunction with a turbulence model. It is shown that the multi-objective genetic algorithm can generate superior airfoils compared to the original airfoils.