Transmission expansion planning using neuro-computing hybridized with genetic algorithm

Katsuhisa Yoshimoto, Keiichiro Yasuda, Ryuichi Yokoyama

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    32 Citations (Scopus)

    Abstract

    The aim of transmission expansion planning is to determine which right-of-way to construct new lines in order to meet the future load in the most economical way. This problem has been solved by the mathematical programming techniques, which require considerable computational efforts, or by successive planning based on sensitivity analysis, which find a single non-optimal solution. Although another method that has efficiency for combinatorial problems is the neuro-computing, this approach obtains poor solutions while it saves computational efforts. The most desirable approach for this planning problem can find many good solutions in reasonable time, because experts of planning will easily plan the economical and reliable expansion according to these solutions by compare with each other. This paper presents an approach for solving transmission expansion planning based on neuro-computing hybridized with genetic algorithm. This approach generates suitable initial states, which include past information, of neural networks utilizing genetic algorithm. Mingling neuro-computing and genetic algorithm, the proposed approach can find many good solutions in reasonable time making full use of their merits. Computational examples show the effectiveness of the proposed approach by comparison with conventional approaches.

    Original languageEnglish
    Title of host publicationProceedings of the IEEE Conference on Evolutionary Computation
    Place of PublicationPiscataway, NJ, United States
    PublisherIEEE
    Pages126-131
    Number of pages6
    Volume1
    Publication statusPublished - 1995
    EventProceedings of the 1995 IEEE International Conference on Evolutionary Computation. Part 1 (of 2) - Perth, Aust
    Duration: 1995 Nov 291995 Dec 1

    Other

    OtherProceedings of the 1995 IEEE International Conference on Evolutionary Computation. Part 1 (of 2)
    CityPerth, Aust
    Period95/11/2995/12/1

    Fingerprint

    Genetic algorithms
    Planning
    Rights of way
    Mathematical programming
    Sensitivity analysis
    Neural networks

    ASJC Scopus subject areas

    • Engineering(all)

    Cite this

    Yoshimoto, K., Yasuda, K., & Yokoyama, R. (1995). Transmission expansion planning using neuro-computing hybridized with genetic algorithm. In Proceedings of the IEEE Conference on Evolutionary Computation (Vol. 1, pp. 126-131). Piscataway, NJ, United States: IEEE.

    Transmission expansion planning using neuro-computing hybridized with genetic algorithm. / Yoshimoto, Katsuhisa; Yasuda, Keiichiro; Yokoyama, Ryuichi.

    Proceedings of the IEEE Conference on Evolutionary Computation. Vol. 1 Piscataway, NJ, United States : IEEE, 1995. p. 126-131.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Yoshimoto, K, Yasuda, K & Yokoyama, R 1995, Transmission expansion planning using neuro-computing hybridized with genetic algorithm. in Proceedings of the IEEE Conference on Evolutionary Computation. vol. 1, IEEE, Piscataway, NJ, United States, pp. 126-131, Proceedings of the 1995 IEEE International Conference on Evolutionary Computation. Part 1 (of 2), Perth, Aust, 95/11/29.
    Yoshimoto K, Yasuda K, Yokoyama R. Transmission expansion planning using neuro-computing hybridized with genetic algorithm. In Proceedings of the IEEE Conference on Evolutionary Computation. Vol. 1. Piscataway, NJ, United States: IEEE. 1995. p. 126-131
    Yoshimoto, Katsuhisa ; Yasuda, Keiichiro ; Yokoyama, Ryuichi. / Transmission expansion planning using neuro-computing hybridized with genetic algorithm. Proceedings of the IEEE Conference on Evolutionary Computation. Vol. 1 Piscataway, NJ, United States : IEEE, 1995. pp. 126-131
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