Combined genetic algorithm and simulated annealing for preventive unit maintenance scheduling in power system

The provision of un-interrupted power supply for all customers has always been one of the fundamental concern of maintenance scheduling. The maintenance scheduling (MS) is characterized as a constrained optimization problem. Combined genetic algorithm and simulated annealing (CGASA) are proposed in this paper for reliable preventive unit maintenance scheduling (PUMS). This approach is used to find the timetable of scheduled maintenance outages in power system. It is observed that the proposed method is more reliable and gives better quality of solution with improved search performance. It is tested on 62 unit state electricity system of Victoria.