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

J. S. Huang, Michael Negnevitsky

Research output: Chapter in Book / Conference PaperConference Paperpeer-review

8 Citations (Scopus)

Abstract

In the paper the authors present a messy geneticalgorithm-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 - International Conference on Computer Science and Software Engineering, CSSE 2008
Pages467-472
Number of pages6
DOIs
Publication statusPublished - 2008
EventInternational Conference on Computer Science and Software Engineering, CSSE 2008 - Wuhan, Hubei, China
Duration: 12 Dec 200814 Dec 2008

Publication series

NameProceedings - International Conference on Computer Science and Software Engineering, CSSE 2008
Volume1

Conference

ConferenceInternational Conference on Computer Science and Software Engineering, CSSE 2008
Country/TerritoryChina
CityWuhan, Hubei
Period12/12/0814/12/08

Keywords

  • Messy genetic algorithm
  • Multi-objective optimization
  • Non-linear programming
  • Voltage stability

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