• DocumentCode
    2800853
  • Title

    Distribution state estimation considering nonlinear characteristics of practical equipment using hybrid particle swarm optimization

  • Author

    Naka, Shigenori ; Genji, Takamu ; Yura, Toshiki ; Fukuyama, Yoshikazu ; Hayashi, Naoki

  • Author_Institution
    Tech. Res. Centre, Kansai Electr. Power Co. Inc., Hyogo, Japan
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1083
  • Abstract
    This paper proposes a distribution state estimation method using a hybrid particle swarm optimization (HPSO). The proposed method considers practical measurements in distribution systems and assumes that absolute values of voltage and current can be measured at the secondary side buses of substations (S/Ss) and RTUs (remote terminal units) in distribution systems. The method can estimate load and distributed generation output values at each node considering nonlinear characteristics of the practical equipment in distribution systems. The feasibility of the proposed method is demonstrated and compared with the original PSO on practical distribution system models. The results indicate the applicability of the proposed state estimation method to the practical distribution systems
  • Keywords
    distribution networks; optimisation; power system state estimation; absolute current values; absolute voltage values; distributed generation; distribution state estimation method; heuristic method; hybrid particle swarm optimization; nonlinear characteristics; regulator; remote terminal units; secondary side buses; substations; Current measurement; Distributed control; Heuristic algorithms; Hybrid power systems; Particle swarm optimization; Power system modeling; State estimation; Static VAr compensators; Substations; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power System Technology, 2000. Proceedings. PowerCon 2000. International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-6338-8
  • Type

    conf

  • DOI
    10.1109/ICPST.2000.897171
  • Filename
    897171