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
Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/2453 |
Date | January 1997 |
Creators | Dahal, Keshav P., McDonald, J.R. |
Source Sets | Bradford Scholars |
Language | English |
Detected Language | English |
Type | Conference paper, Accepted Manuscript |
Rights | © 1997 International Conference on Adaptive and Natural Computing Algorithms. |
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