Generator maintenance scheduling in power systems using metaheuristic-based hybrid approaches

The effective maintenance scheduling of power system generators is very important for the economical and reliable operation of a power system. his represents a tough scheduling problem which continues to present a challenge for efficient optimization solution techniques. This paper resents the application of metaheuristic approaches, such as a genetic algorithm (GA), simulated annealing (SA) and their hybrid for generator aintenance scheduling (GMS) in power systems using an integer representation. This paper mainly focuses on the application of GA/SA and A/SA/heuristic hybrid approaches. GA/SA hybrid uses the probabilistic acceptance criterion of SA within the GA framework. GA/SA/heuristic ybrid combines heuristic approaches within the GA/SA hybrid to seed the initial population. A case study is formulated in this paper as an nteger programming problem using a reliability-based objective function and typical problem constraints. The implementation and performance f the metaheuristic approaches and their hybrid for the test case study are discussed. The results obtained are promising and show that the hybrid pproaches are less sensitive to the variations of technique parameters and offer an effective alternative for solving the generator maintenance cheduling problem. 2006 Elsevier B.V. All rights reserved.