<p>This study presents an analysis of the optimization process applied to wind turbine blade design, followed by the incorporation of a winglet at the tip of the optimized blade. The base blade is NREL Phase VI wind turbine blade and is validated against experimental data using blade element momentum (BEM) theory, involving the comparison of power coefficient values with a maximum deviation of 12.8% and minimum deviation of 2.31% at 3.79 and 2.52 tip speed ratio. The optimization technique- a multi-objective genetic algorithm (MOGA) is employed to identify an optimal configuration for the blade. Furthermore, the optimized blade is analyzed employing the winglet configuration at the tip using computational fluid dynamics. Results from the optimization process demonstrate improvements in overall wind turbine performance in terms of annual energy production and reduction in blade mass. The optimization process considers objectives such as annual energy production (AEP) and blade mass, resulting in a 21.8% increase in AEP and a 12.2% decrease in blade mass for the optimized design. The optimal tip speed ratio is determined as 5.41, with a power coefficient of 0.409, showcasing a 9.12% performance improvement over the base blade. Chord and twist parameters for the optimized design are suggested. Additionally, the study explores further enhancements through tip modification and the addition of a winglet, yielding a power coefficient increase of 11.2% to 20.4% across varying wind speeds. Thus, the winglet exhibits a higher power coefficient compared to the optimized blade design. Overall, the optimized blade and winglet design signifies a substantial advancement in aerodynamic technology, offering heightened efficiency, superior performance, and reduced blade mass.</p>