The variability and uncertainty of renewable resources impose new challenges in the operational planning related to the unit commitment of generation units. The development of day-ahead multi-period optimal power flow, under integration of wind power, requires modelling of multiple scenarios in order to ensure an optimal power flow minimising the generation cost. A progressive hedging approach has been proposed and developed to solve efficiently the unit commitment problem as a two-stage stochastic programming problem to update each stage in parallel. The performance of progressive hedging is compared with a standard mixed-integer linear programming problem. The results indicate that the computation time is 50 times faster than standard mixed-integer linear programming. The test case system is based on a reduced version of the interconnected Colombian system. The comparative results indicate an important reduction in computational time.