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

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    1997-IEE-Galesia97-GMS.pdf (175.3Kb)
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    Publication date
    1997
    Author
    Dahal, Keshav P.
    McDonald, J.R.
    Keyword
    Maintenance scheduling
    Power system generators
    Reliability
    Operation
    Performance
    Genetic algorithms
    Power utility
    Integer programming
    Rights
    Copyright © [1997] IEEE. Reprinted from Second International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, Glasgow 2-4 Sept 1997 (GALESIA 97). New York: IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bradford's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it
    Peer-Reviewed
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    Abstract
    The effective maintenance scheduling of power system generators is very important to a power utility for the economical and reliable operation of a power system. Many mathematical methods have been implemented for generator maintenance scheduling (GMS). However, these methods have many limitations and require many approximations. Here a Genetic Algorithm is proposed for GMS problems in order to overcome some of the limitations of the conventional methods. This paper formulates a general GMS problem using a reliability criterion as an integer programming problem, and demonstrates the use of GAs with three different problem encodings: binary, binary for integer and integer. The GA performances for each of these representations are analysed and compared for a test problem based on a practical power system scenario. The effects of different GA parameters are also studied. The results show that the integer GA is a very effective method for GMS problems.
    URI
    http://hdl.handle.net/10454/2451
    Version
    published version paper
    Citation
    Dahal, K. P. and McDonald, J. R. (1997) Generator maintenance scheduling of electric power systems using genetic algorithms with integer representations. In: Second International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, Glasgow 2-4 Sept 1997 (GALESIA 97). New York: IEEE. Conf. Publ. No. 446. pp.456-461
    Link to publisher’s version
    http://ieeexplore.ieee.org/servlet/opac?punumber=5586
    Type
    Conference paper
    Collections
    Engineering and Digital Technology Publications

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