The aim of this paper is to foster wind turbine blade design optimization using Genetic Algorithm considering NACA64A410 as a case. The design optimization of turbine blades using GA with regards to different objective functions are described and found supportive one another. NACA64A410 aerofoil shape is modeled as baseline aerofoil using fifth order Bezier curve functions with acceptable error to find control points that to shape of the aerofoil. Design of Experiment is planned for eight design variables with three levels each. 27 analyses are conducted with a varying control point values using ANSYS Fluent 14.0 workbench. Lift and drag coefficients are recorded as an output for each analyses. The objective function is formulated as a minimization problem of drag-to-lift coefficient ratio subjected to bounded constraints using 8 control points’ y-coordinate values. Using MINITAB-, control point values, as an input and drag- to-lift coefficient ratio, as response, are modeled with full quadratic surface response model function which is later optimized in MATLAB GA Toolbox. The optimization showed that drag-to-lift coefficient ratio is minimized taking control points as parameters of the minimization objective function. About 16.5% drag-to-lift reduction is achieved by implementing the aerodynamic shape optimization methodology that has been used in this research.  Finally, it’s recommended that one can model aerofoil using Bezier curve modeling technique and integrate it with GA for finding optimal value of objective function of any sort.

Keywords: Aerofoil, Bezier Curve, Response Surface Model, Optimization, Genetic Algorithm