• DocumentCode
    2122968
  • Title

    Optimal SVC placement for voltage stability reinforcement of power systems with most critical and N-1 security criteria

  • Author

    Huang, Jiansheng ; Jiang, Zhuhan ; Negnevitsky, Michael

  • Author_Institution
    Sch. of Comput., Eng. & Math., Univ. of Western Sydney, Penrith, NSW, Australia
  • fYear
    2012
  • fDate
    9-12 Sept. 2012
  • Firstpage
    415
  • Lastpage
    420
  • Abstract
    This paper presents a messy genetic-algorithm-based optimization scheme for SVC planning, aimed at voltage stability enhancement of power systems under most critical and N-1 operation conditions. The SVC placement was formulated as a multi-objective optimization problem in terms of maximum worst-case reactive power margin, highest load voltages towards the critical operating points, minimum real power losses, and lowest SVC device costs. During the genetic algorithm search for the optimal solution, the most critical disturbance scenario was estimated with each SVC placement and the configuration of the original power system. The preselected candidate was further checked against the N-1 security criterion.
  • Keywords
    genetic algorithms; losses; power system security; power system stability; reactive power; static VAr compensators; N-1 security criteria; SVC planning; messy genetic algorithm-based optimization scheme; minimum real power losses; multiobjective optimization problem; optimal SVC placement; reactive power; static VAR compensators; voltage stability reinforcement; Genetic algorithms; Optimization; Planning; Power system stability; Reactive power; Stability criteria; Static VAr compensators; Fuzzy logic performance index; Lagrange multiplier method; Messy genetic algorithm; Multi-objective optimization; N-1 security criterion; Voltage stability reinforcement; Worst-case reactive power margin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Energy Conference and Exhibition (ENERGYCON), 2012 IEEE International
  • Conference_Location
    Florence
  • Print_ISBN
    978-1-4673-1453-4
  • Type

    conf

  • DOI
    10.1109/EnergyCon.2012.6347793
  • Filename
    6347793