Wind Turbine Blade Section Optimization Shape Using Improved Genetic Algorithm by Coupling Parameterization /

Abstract

Airfoil shape optimization is one of the challenging tasks in the designing process of wind turbine blades. The tip airfoil plays a key role in the blade it affects the overall efficiency of the wind turbine, including aerodynamic properties such as coefficient of lift, coefficient of drag, and moment force. In this research endeavor, an improved evolutionary algorithm (genetic algorithm) was explored to optimize the aerodynamic performance of the tip airfoil. A genetic algorithm was coupled with the PARSEC parameterization method to generate the 12 design variables using the sixth degree of polynomial equations. Notable cambered airfoil NREL S810 wasincorporated for the aerodynamic analysis and optimization in this study. For the analysis of airfoils, an interactive program of XFOIL was integrated with MATLAB to evaluate the fitness values under the defined geometry constraint of each iterative shape of an airfoil. The results showed that the optimized NREL S810 airfoil exhibited a higher lift coefficient and lift-to-drag ratio compared to the baseline airfoil. Furthermore, the re verification of genetic algorithm optimized airfoil results was accomplished using the combining Reynolds-averaged Navier Stokes (RANS) with two models 𝑘 − 𝜔 and 𝑘 − 𝜀 SST turbulence model. The concluded computational fluid dynamics (CFD) result showed a significant improvement in the coefficient of lift and lift-to-drag ratio of 34.8 % and 19.4 % respectively, at an angle of attack 6.1°, wind speed 14.6 𝑚/𝑠 and 𝑅𝑒 = 1 million compared with experimental data published by the Ohio University State (OUS). Overall, the applicability of design solutions tends to optimize airfoils in less computational time compared to those of traditional ones.