A New Multi-Objective Evolutionary Algorithm for Optimizing the Aerodynamic Design of HAWT Rotor

This paper presents a new multi-objective evolutionary algorithm (MOEA) for optimum aerodynamic design of horizontal-axis wind turbines (HAWT). The design problem is set to find the blade shape such that optimizing multi-objective at different airfoil profiles. Combined Blade Element Momentum (BEM) theory and two different algorithms (Genetic (GA) and Enumeration) are used. Flow around subsonic airfoils is analyzed using XFOIL software. WINDMEL III wind turbine is selected to improve its aerodynamic performance with different airfoil profiles technique of National Renewable Energy Laboratory (NREL) family. Employing Genetic Algorithm embodied in Blade Element Momentum theory to calculate power, thrust and starting torque coefficients that are the fitness function. Another method, Enumeration method, is used to enhance evolutionary method results. The optimum solution acquired from combination of Genetic Algorithm and Blade Element Momentum theory of three blades configuration increased power coefficient by (25.8 %) and thrust coefficient by (16.6%). Enumeration method results increased power coefficient by (13.8%), while thrust coefficient decreased by (0.2%) from the original design. In general, the evolutionary method of combined GA and BEM theory with different airfoil profiles technique improved the turbine aerodynamic performance, and the results are in good agreement with other published papers.