An optimization model is developed for scheduling electricity and heat production in a microgrid under a day-ahead market environment considering the operation constraints and the volatility of wind power generation. The model optimizes the total operation costs from energy and heating consumption， meanwhile considers the minimization of the actual flow deviation at the point of common coupling（PCC） from scheduled values. The stochastic nature of wind output is represented by different scenarios with the help of scenario generation and reduction techniques. The model is finally formulated into a mixed-integer programming（MIP） problem. Numerical simulations present the efficacy of the proposed model for day-ahead scheduling of a microgrid with wind penetration under the deregulated environment.