Among all the viable renewable energy options, the contribution of wind energy is (10-12) %. However, WTG's high failure rate hampered the full use of wind power. Generally, the gearbox is the critical failure part among all others, which affects the efficiency of the farm. Hence, to decrease the failure rate, the service life of the gearbox needs to be improved, which can be done by reducing the power losses and weight of the WTG. Both the objective functions are set to be minimized with various comprehensive lists of traditional mechanical constraints. However, by introducing the scuffing aspect into the wind turbine gearbox, exploring optimization brings novelty to the current research. Further, WTG optimization has been carried out using a Non-Dominated Sorting Genetic Algorithm (NSGA-II) for three different involute gear tooth profiles: unmodified, smooth meshing, and high load ca pacity. A Planetary-Helical-Helical (PHH) model is chosen for the study, where the planetary gear train is the first stage, followed by two stages of helical gear pairs. Later, the results of WTG are compared with and without scuffing constraint by using ISO VG PAO 320, 680, and 1000 oils, and it is found that PAO 320 outperforms the other oils. Also, the chosen model's power loss is significantly reduced with scuffing constraint.