Optimal Generator Maintenance Scheduling Using a Hybrid Metaheuristic Approach

This paper presents an optimal approach for solving the generator maintenance scheduling (GMS) problem using a hybrid metaheuristic-based method. The GMS problem is formulated mathematically as a minimization problem of an aggregated objective function that handles both the reliability performance and the constraints violations. A new optimization approach, based on simulated annealing (SA) and ant colony optimization (ACO) is proposed to solve this problem. The optimization results for a 21-unit test system show that the proposed hybrid approach is more efficient than the standard SA and ACO methods and also genetic algorithms (GAs). It is also shown that the proposed approach is less sensitive to the variations of some control parameters and is more reliable than the other approaches.

[1]  J. R. McDonald,et al.  A review of generator maintenance scheduling using artificial intelligence techniques , 1997 .

[2]  R. Anandhakumar,et al.  Artificial Bee Colony Based Solution Technique for Generator Maintenance Scheduling , 2012 .

[3]  Keshav Dahal,et al.  Generator maintenance scheduling in power systems using metaheuristic-based hybrid approaches , 2007 .

[4]  Angus R. Simpson,et al.  Ant colony optimization for power plant maintenance scheduling optimization , 2005, GECCO '05.

[5]  Conversion and delivery of electrical energy in the 21st century , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[6]  Yasuhiro Hayashi,et al.  An algorithm for thermal unit maintenance scheduling through combined use of GA, SA and TS , 1997 .

[7]  Ganesh K. Venayagamoorthy,et al.  Optimal maintenance scheduling of generators using multiple swarms-MDPSO framework , 2010, Eng. Appl. Artif. Intell..

[8]  James R. McDonald,et al.  Generator maintenance scheduling using a genetic algorithm with a fuzzy evaluation function , 1999, Fuzzy Sets Syst..

[9]  Edmund K. Burke,et al.  Hybrid evolutionary techniques for the maintenance scheduling problem , 2000 .

[10]  Vlachos Aristidis,et al.  Meta-heuristic optimization techniques in power systems , 2007 .

[11]  J. R. McDonald,et al.  Modern heuristic techniques for scheduling generator maintenance in power systems , 2000 .

[12]  Jin-Ho Kim,et al.  Generating Unit Maintenance Scheduling using Hybrid PSO Algorithm , 2007, 2007 International Conference on Intelligent Systems Applications to Power Systems.

[13]  Angus R. Simpson,et al.  Ant colony optimization for power plant maintenance scheduling optimization , 2005, GECCO '05.

[14]  Johann Dréo,et al.  Metaheuristics for Hard Optimization: Methods and Case Studies , 2005 .

[15]  Koichi Nara,et al.  Maintenance scheduling by using simulated annealing method (for power plants) , 1991 .

[16]  Pavlos S. Georgilakis,et al.  An ant colony optimization solution to the integrated generation and transmission maintenance scheduling problem , 2008 .