Particle Swarm Optimization Based Approach to Maintenance Scheduling Using Levelized Risk Method

Abstract

Maintenance scheduling plays a very important and vital role in power system planning. Any equipment irrespective of its size and complexity will have to be serviced periodically to ensure that the equipment does not fail to operate during normal operation. However, the maintenance-scheduling problem is a constrained optimization problem. The objective function of this problem is to reduce the loss of load probability (LOLP) for a given power system while at the same time, all the generators in the given power system has been serviced completely. The method used in this paper is the levelized risk method, which is being used widely compared to the other methods. The challenge with this paper lies in creating a maintenance schedule which satisfies the constraints with an optimum LOLP for the given power system. Particle swarm optimization (PSO) technique has been used to solve this constrained optimization problem effectively. An IEEE reliability test system (RTS) is taken and a maintenance schedule is prepared for that system.