Abstract

This paper presents a hybrid particle swarm optimization based genetic algorithm and hybrid particle swarm optimization based evolutionary programming for solving long-term generation maintenance scheduling problem. In power system, maintenance scheduling is being done upon the technical requirements of power plants and preserving the grid reliability. The objective function is to sell electricity as much as possible according to the market clearing price forecast. While in power system, technical viewpoints and system reliability are taken into consideration in maintenance scheduling with respect to the economical viewpoint. It will consider security constrained model for preventive maintenance scheduling such as generation capacity, duration of maintenance, maintenance continuity, spinning reserve and reliability index are being taken into account. The proposed hybrid methods are applied to an IEEE test system that consist 24 buses with 32 generating unit system.

Key words: Generation maintenance schedule, optimization, evolutionary programming, particle swarm optimization, genetic algorithm.