Abstract-This paper proposes a novel hybrid technique that combines the priority list (PL) with the binary crow search algorithm (BCSA) for solving the unit commitment problem (UCP). Firstly, the PL method aims to sort the generating units in ascending order according to their average full load costs which are the total costs that are computed at the maximum generation outputs. Secondly, the BCSA is developed and employed to search for the optimal schedule of the generating units to face the next hourly demand with minimum total operating costs that are related to the optimal power generation schedule at certain loading level. BCSA is a new meta-heuristic optimizer, which is featured of the crow's intelligence. It has only two adjustable parameters that make its implementation very simple and easy compared to other optimization techniques. Its effectiveness and feasibility were confirmed by 4, 10, and 26-unit systems and the results are compared with those obtained by GA, PSO, APSO, and BDE. The simulation results demonstrate the capability of the proposed PLBCSA in solving the UC problem with good convergence rate compared with the previous methods in the literature. Around of 2-4% reduction in the total costs is achieved using the proposed PLBCSA for the 26-unit test system compared with GA, PSO and the implemented PL-BPSO solutions.