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The performance of a wind turbine rotor depends on the wind characteristics of the site and the aerodynamic shape of the blades. The blade geometry determines the torque and the power generated by the rotor. This study investigates the enhancement of small Horizontal Axis Wind Turbine (HAWT) rotor performance by using Response Surface Methodology (RSM) through Computational Fluid Dynamics (CFD) tools. The optimization process employs a curve-fitting technique to optimally distribute the chord length and twist angle along the blade. The obtained design is analysed using the CFD-Tools Ansys-fluent. To account for full turbulence effects, the SST (Shear Stress Transport) turbulence model is utilized for initial simulations. To enhance the reliability and precision of the optimization results, a refinement method is implemented, incorporating the top three candidate solutions identified through the Multi-Objective Genetic Algorithm (MOGA) into the Design of Experiments (DOE) table. Three optimization loops are performed, focusing on outperforming the initial design points from MOGA against the best candidates in the DOE table. Additionally, the study expands the input variable constraints from 10% to 40%, based on a comparative analysis, to assess and demonstrate the effectiveness of the optimization strategy. This multi-step approach ensures a robust and efficient optimization process for improving HAWT rotor performance.
