A messy genetic algorithm based optimization scheme for SVC placement of power systems under critical operation contingence

Jiansheng Huang, Michael Negnevitsky, Stephanie Kawada

    Research output: Chapter in Book / Conference PaperConference Paper

    Abstract

    In the paper the authors present a messy genetic algorithm-based optimization scheme for voltage stability enhancement of power systems under critical operation conditions. The placement of SVCs in a power system has been posed as a multi-objective optimization in terms of maximum worst-case reactive margin, highest load voltages at the critical operating points, minimum real power losses and lowest device costs. During the genetic algorithm search for the optimal solution, the most critical disturbance scenario is estimated with the configuration of the original power system and each candidate SVC placement. By using this estimation, the SVC placement can be greatly simplified. With a fuzzy performance index, the multi-objective optimization can be further transformed into a constrained problem with a single nondifferentiable objective function containing both continuous and discrete variables.
    Original languageEnglish
    Title of host publicationProceedings of the International Conference on Computer Science and Software Engineering (CSSE), held 12-14 December 2008, Wuhan, Hubei, China
    PublisherIEEE
    Number of pages6
    ISBN (Print)9780769533360
    Publication statusPublished - 2008
    EventInternational Conference on Computer Science and Software Engineering -
    Duration: 1 Jan 2008 → …

    Conference

    ConferenceInternational Conference on Computer Science and Software Engineering
    Period1/01/08 → …

    Keywords

    • genetic algorithms
    • voltage regulators
    • power systems

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