In this study, the power scheduling problem in μ-grids is investigated taking the uncertainties in power demand and wind power into account. The problem is formulated as a stochastic mixed-integer linear optimization problem with the objective being minimizing the total μ-grid cost. The objective is subject to a set of operational constraints imposed on the generating units and the system itself. A two-stage stochastic programming method has been applied to find the optimal power generation schedule for a μ-grid. The developed approach was implemented in a General Algebraic Modeling System platform (GAMS). The developed method was tested on a μ-grid consisting of eight dispatchable units and a wind turbine. To demonstrate the necessity of uncertainty modeling, the value of the stochastic solution (VSS) and the expected value of perfect information (EVPI) were used to compare the stochastic power schedule obtained with the deterministic one.