Bi-objective optimization of maintenance scheduling for power systems

Enhance the quality of energy production in power generating stations and reducing its cost have become of paramount importance. One of the methods to reach that goal is by minimizing the maintenance scheduling time. For this purpose, a new competitive mechanism, based on a modified genetic algorithm (MGA), has been proposed to perform the preventive maintenance (PM) scheduling. Firstly, a mono-objective optimization (makespan) has implemented, and the results were quite good. Secondly, and in order to benefit from the waste time, a bi-objective optimization was developed to find a trade-off between makespan and training time of operators. Finally, the MGA-based maintenance scheduling was tested on a hybrid renewable power system (HRPS), that uses photovoltaic modules and a fuel cell (PV/FC) as sources and the telecommunication platform as load, the obtained results have proved the high efficiency of the proposed MGA-based maintenance scheduling.