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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