Optimal capacitor placement considering voltage stability margin based on improved PSO algorithm

  • Taegyun Kim*
  • , Yunhwan Lee
  • , Byongjun Lee
  • , Hwachang Song
  • , Taekyun Kim*
  • *Corresponding author for this work

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

    4 Citations (Scopus)

    Abstract

    This paper presents the optimal capacitor placement (OCP) algorithm for the voltage stability enhancement. The problem of OCP is composed by the integer variables and highly nonlinear equations. Generally, this problem can be solved by the OPF algorithms, but the OPF has the defect to solve the problems contained the integer variables and to find the global solution. The particle swarm optimization (PSO) algorithm is the modern heuristic optimization algorithm, so it is easy to treat integer variables and to find the global solution. This paper presents the method for OCP based on the PSO and the method to improve the convergence and search speed of the PSO using the dual variables obtained through the nonlinear interior point method. This algorithm is tested by the NewEngland 39-buses test system.

    Original languageEnglish
    Title of host publication2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09
    DOIs
    Publication statusPublished - 2009 Dec 9
    Event2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09 - Curitiba, Brazil
    Duration: 2009 Nov 82009 Nov 12

    Publication series

    Name2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09

    Other

    Other2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09
    Country/TerritoryBrazil
    CityCuritiba
    Period09/11/809/11/12

    Keywords

    • Optimal capacitor placement
    • Optimal power flow
    • Optimal var planning
    • PSO
    • Steady state voltage stability

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Science Applications
    • Energy Engineering and Power Technology

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