• DocumentCode
    3313524
  • Title

    Adaptive Ant Colony Algorithm Based Global Optimization Control of Voltage/Reactive Power in the Substation

  • Author

    Jiang, Huilan ; Jia, Mengdan ; Lin, Liu

  • Author_Institution
    Key Lab. of Power Syst. Simulation, Tianjin Univ., Tianjin
  • Volume
    7
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    466
  • Lastpage
    470
  • Abstract
    This paper presents a voltage/reactive power global optimization control method in the substation by adaptive ant colony algorithm. It can dynamically adjust pheromone updating strategy and probability of paths selection according to the distribution uniformity of solutions in the optimal process. This method, comprehensively considering the voltage of low-voltage side, the reactive at high-voltage side and the constraint of action numbers of capacitors and transformer taps in one day, makes the control strategy used assure that the voltage, reactive and adjusting times of transformer taps and capacitors can achieve their integrated optimality. Take the practical triple-wound substation for instance, the result of simulating it proves the effectiveness of the method which is presented in this paper, and achieves the desired effect.
  • Keywords
    optimisation; power capacitors; probability; reactive power control; transformer substations; voltage control; adaptive ant colony algorithm; capacitors; global optimization control; paths selection probability; pheromone updating strategy; reactive power control; substation; transformer; voltage control; Adaptive control; Ant colony optimization; Capacitors; Convergence; Fuzzy control; Optimal control; Programmable control; Reactive power control; Substations; Voltage control; adaptive ant colony algorithm; optimization control; substation; voltage and reactive;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2008. ICNC '08. Fourth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-0-7695-3304-9
  • Type

    conf

  • DOI
    10.1109/ICNC.2008.767
  • Filename
    4668021