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An optimal preventive generator maintenance scheduling (GMS) in a smart grid environment comprising wind-hydrothermal energy resources is presented in this paper. GMS problem is solved with the aim of maximizing economic benefits subject to satisfying system constraints. This GMS formulation becomes a challenging problem because of the variability and intermittency of wind speed and the incorporation of uncertainty in wind generation. The objective is to perform preventive GMS in such a manner that the annual generation cost is minimized, the annual cost saving is increased while all operating constraints are satisfied in the presence of uncertainty in wind generation. Discrete modified particle swarm optimization (MPSO-D) algorithm is used to solve this problem. The results presented on a typical Nigerian power system show the potential and benefits obtainable from increasing wind power penetration.