Abstract—The goal of an optimal Generator Maintenance Scheduling (GMS) is solved in order to generate optimal preventive maintenance schedule of generating units for economical and reliable operation of a power system while satisfying system load demand and crew constraints. In this paper a Modified Artificial Bee Colony (MABC) algorithm is applied to solve the GMS optimization problem efficiently. The MABC algorithm is proposed in order to handle the system constraints effectively and obtain the better maintenance schedules. The efficacy of the proposed algorithm is illustrated with 13 generating units and 21 generating units with two different load demands. The simulation results are compared with Discrete Particle Swarm Optimization (DPSO), Modified Discrete Particle Swarm Optimization (MDPSO) and Multiple Swarms - Modified discrete Particle Swarm Optimization (MSMDPSO) which is also population based heuristic search algorithms. From the numerical results, it is found that the MABC based approach is able to provide a better solution for GMS.

Index Terms—Generator maintenance scheduling, optimal scheduling, modified artificial bee colony (MABC) algorithm, meta – heuristic algorithm.

The authors are with Department of Electrical Engineering, Annamalai University, Annamalainagar, Tamilnadu, India. (e-mail:anand_r1979@yahoo.com,dr_smani@yahoo.co.in,ganeshshriraj@gmail.com).

Cite: R. Anandhakumar, S. Subramanian, and S. Ganesan, "Modified ABC Algorithm for Generator Maintenance Scheduling," International Journal of Computer and Electrical Engineering vol. 3, no. 6, pp. 812-819, 2011.