• DocumentCode
    1783553
  • Title

    Optimal power flow using hybrid PSOGSA algorithm

  • Author

    Radosavljevic, Jordan ; Arsic, Nebojsa ; Jevtic, Miroljub

  • Author_Institution
    Fac. of Tech. Sci., Univ. of Pristina in Kosovska Mitrovica, Kosovska Mitrovica, Serbia
  • fYear
    2014
  • fDate
    14-14 Oct. 2014
  • Firstpage
    136
  • Lastpage
    140
  • Abstract
    This paper presents a new hybrid algorithm based on the particle swarm optimization (PSO) and the gravitational search algorithm (GSA) for solving the optimal power flow (OPF) in power systems. Performance of this approach for the OPF problem is studied and evaluated on the standard IEEE 30-bus test system with different objective functions. Simulation results on the OPF problem show that the hybrid PSOGSA algorithm provides effective and robust high-quality solution.
  • Keywords
    load flow; particle swarm optimisation; power systems; IEEE 30-bus test system; OPF; gravitational search algorithm; hybrid PSOGSA algorithm; optimal power flow; particle swarm optimization; power systems; Educational institutions; Electrical engineering; Fuels; Generators; Hybrid power systems; Linear programming; Load flow; Optimal power flow; gravitational search algorithm; hybrid optimization algorithm; particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Electrical Engineering of Riga Technical University (RTUCON), 2014 55th International Scientific Conference on
  • Conference_Location
    Riga
  • Print_ISBN
    978-1-4799-7460-3
  • Type

    conf

  • DOI
    10.1109/RTUCON.2014.6998173
  • Filename
    6998173