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This paper presents a stochastic method for the hourly scheduling of optimal reserves when the hourly forecast errors of wind energy and load are considered. The approach utilizes the stochastic security-constrained unit commitment (SCUC) model and a two-stage stochastic programming for the day-ahead scheduling of wind energy and conventional units with N-1 contingencies. The effect of aggregated hourly demand (DR) response is considered as a means of mitigating transmission violations when uncertainties are considered. The proposed mixed-integer programming (MIP) model applies the Monte Carlo method for representing the hourly wind energy and system load forecast errors. A 6-bus, 118-bus, and the Northwest region of Turkish electric power network are considered to demonstrate the effectiveness of the proposed day-ahead stochastic scheduling method in power systems.