• DocumentCode
    1612400
  • Title

    A solution to the Optimal Power Flow using Artificial Bee Colony algorithm

  • Author

    Sumpavakup, C. ; Srikun, I. ; Chusanapiputt, S.

  • Author_Institution
    Dept. of Electr. Power Eng., Mahanakorn Univ. of Technol., Bangkok, Thailand
  • fYear
    2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Optimal Power Flow (OPF) is one of the most vital tools for power system operation analysis, which requires a complex mathematical formulation to find the best solution. Conventional methods such as Linear Programming, Newton-Raphson and Non-linear Programming were previously offered to tackle the complexity of the OPF. However, with the emergence of artificial intelligence, many novel techniques such as Artificial Neural Networks, Genetic Algorithms, Particle Swarm Optimization and other Swarm Intelligence techniques have also received great attention. This paper described the use of Artificial Bee Colony (ABC), which is one of the latest computational intelligence to solve the OPF problems. The results show that solving the OPF problem by the Artificial Bee Colony can be as effective as other swarm intelligence methods in the literature.
  • Keywords
    Newton-Raphson method; artificial intelligence; genetic algorithms; linear programming; load flow; neural nets; nonlinear programming; particle swarm optimisation; Newton-Raphson programming; OPF problems; artificial bee colony algorithm; artificial intelligence; artificial neural networks; complex mathematical formulation; computational intelligence; genetic algorithms; linear programming; nonlinear programming; optimal power flow; particle swarm optimization; power system operation analysis; swarm intelligence techniques; Artificial neural networks; Equations; Gallium; Generators; Mathematical model; Optimization; Runtime; Bees Algorithm; Optimal Power Flow; Swarm Intelligence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power System Technology (POWERCON), 2010 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4244-5938-4
  • Type

    conf

  • DOI
    10.1109/POWERCON.2010.5666516
  • Filename
    5666516