  Security Constraint Unit commitment (SCUC) is one of the significant
challenges in operation of power grids which tries to regulate the status of
the generation units (ON or OFF) and providing an efficient power dispatch
within the grid. While many researches tried to address the SCUC challenges, it
is a mixed-integer optimization problem that is difficult to reach global
optimum. In this study, a novel modified genetic algorithm based on
Multicellular Organisms Mechanisms (GAMOM) is developed to find an optimal
solution for SCUC problem. The presentation of the GAMOM on the SCUC contain
two sections, the GA and modified GAMOM sections. Hence, a set of population is
considered for the SCUC problem. Next, an iterative process is used to obtain
the greatest SCUC population. Indeed, the best population is selected so that
the total operating cost is minimized and also all system and units constraints
are satisfied. The effectiveness of the proposed GAMOM algorithm is determined
by the simulation studies which demonstrate the convergence speed. Finally, the
proposed technique is compared with well-known existing approaches.
