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Generator maintenance scheduling of electric power systems using genetic algorithms with integer representations

By Keshav P. Dahal and J.R. McDonald

Abstract

The effective maintenance scheduling of power system\ud generators is very important to a power utility for the\ud economical and reliable operation of a power system.\ud Many mathematical methods have been implemented for\ud generator maintenance scheduling (GMS). However,\ud these methods have many limitations and require many\ud approximations. Here a Genetic Algorithm is proposed\ud for GMS problems in order to overcome some of the\ud limitations of the conventional methods.\ud This paper formulates a general GMS problem using a\ud reliability criterion as an integer programming problem,\ud and demonstrates the use of GAs with three different\ud problem encodings: binary, binary for integer and\ud integer. The GA performances for each of these\ud representations are analysed and compared for a test\ud problem based on a practical power system scenario. The\ud effects of different GA parameters are also studied. The\ud results show that the integer GA is a very effective\ud method for GMS problems

Topics: Maintenance scheduling, Power system generators, Reliability, Operation, Performance, Genetic algorithms, Power utility, Integer programming
Year: 1997
OAI identifier: oai:bradscholars.brad.ac.uk:10454/2451
Provided by: Bradford Scholars

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