Generational and Steady-State Genetic Algorithms for Generator Maintenance Scheduling Problems
The aim of generator maintenance scheduling (GMS) in an electric power system is to allocate a proper maintenance timetable for generators while maintaining a high system reliability, reducing total production cost, extending generator life time etc. In order to solve this complex problem a genetic algorithm technique is proposed here. The paper discusses the implementation of GAs to GMS problems with two approaches: generational and steady state. The results of applying these GAs to a test GMS problem based on a practical power system scenario are presented and analysed. The effect of different GA parameters is also studied.
KeywordsgenetIc algOrIthm Mutation Probability genetIc algOrIthm Approach Genetic Pool Total Production Cost
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