As a result of the continous growth of Wind Turbines (WTs) implementation worldwide, the problem of WT noise has become more relevant than ever. The increase of noise legal constraints and their non uniformity across different countries and/or regions make it important to address this problem early in the design phase of a WT. However, one might want to reduce the noise produced by WTs that are already in use to comply with new stricter noise limits. In the present work, this problem is addressed by using a WT blade optimization framework to obtain the shape of blade add-ons that could be attached to the blade of a WT (for example, by using some kind of adhesive) to reduce its noise without compromising the performance. Blade Element Momentum (BEM) theory was used to compute the aerodynamic performance of the WT and semi-empirical models were used for the airfoil self-noise and turbulence interaction noise prediction. The aerodynamic analysis of the cross sectional airfoil shapes, required for both the BEM calculations and noise predictions, is performed using the viscous-inviscid interactive code XFOIL. Non-dominated Sorting Genetic Algorithm-II was used as the optimization algorithm. Two NURBS curves were used to define the baseline cross sectional airfoil shape of the blade at certain control sections and another two to define a variation from the baseline, totalling up to 54 design variables. The framework was used to optimize the AOC 15/50 WT, a commercial downwind, three bladed WT. Optimal solutions were selected from the Pareto front and discussed in detail. These solutions ranged from an increase in energy…