Abstract- In this study, an optimal solution for day-ahead programming in a Security Constrained Unit Commitment (SCUC) problem in power system has been presented. In fact this programming concentrates on providing coordination between generation units when a variation in load constraints is occurred. The goal of this coordination is to reduce the power system total cost. A practical and accurate method called Particle Swarm Optimization (PSO) has been used to solve this problem. The system considered in this study contains thermal and photovoltaic units. Monte Carlo method has been employed to model the uncertainty of photovoltaic units and system load. The objective function in this optimization is a second order polynomial including fuel and operation costs. Results of simulation shows that unit commitment programming with this method decrease system operation costs remarkably and simultaneously satisfies all system constraints. This method has higher accuracy and convergence speed with respect to the conventional methods.