• DocumentCode
    2015545
  • Title

    Load margin analysis for steady state voltage stability using PSO technique

  • Author

    Indira, A. ; Mandal, Srimanta ; Acharjee, Partha ; Thakur, S.S.

  • Author_Institution
    Electr. Eng. Dept., N. I. T., Durgapur, India
  • fYear
    2009
  • fDate
    27-29 Dec. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    For steady state voltage stability, load margin analysis is one of the efficient procedures. The mathematical modeling of load margin is formulated as an optimization problem considering in-equality constraints-voltage limits and reactive power generation limits of PV buses. Two particle swarm optimization (PSO) techniques namely adaptive PSO (APSO) and Hybrid PSO (HPSO) are developed. In APSO technique, new formulas are designed to get adaptive tuning parameters. In HPSO technique, breeding and subpopulation of genetic algorithm (GA) are incorporated in PSO to add diversity & to overcome local optima. The effectiveness and efficiency of the proposed techniques is established giving different test results of IEEE standard systems.
  • Keywords
    genetic algorithms; particle swarm optimisation; power system stability; reactive power; PSO technique; adaptive PSO; adaptive tuning parameters; genetic algorithm; hybrid PSO; load margin analysis; mathematical modeling; optimization problem; particle swarm optimization; reactive power generation; steady state voltage stability; Constraint optimization; Genetic algorithms; Mathematical model; Particle swarm optimization; Power generation; Reactive power; Stability analysis; Steady-state; System testing; Voltage; adaptive particle swarm optimizaion; hybrid particle swarm optimization; load margin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Systems, 2009. ICPS '09. International Conference on
  • Conference_Location
    Kharagpur
  • Print_ISBN
    978-1-4244-4330-7
  • Electronic_ISBN
    978-1-4244-4331-4
  • Type

    conf

  • DOI
    10.1109/ICPWS.2009.5442658
  • Filename
    5442658