• DocumentCode
    2675206
  • Title

    Reconfiguration of network skeleton based on discrete particle-swarm optimization for black-start restoration

  • Author

    Liu, Yan ; Gu, Xueping

  • Author_Institution
    Key Lab. of Power Syst. Portection, North China Electr. Power Univ., Baoding
  • fYear
    0
  • fDate
    0-0 0
  • Abstract
    The black start restoration of a power system after a complete blackout is a very important issue to safety of the power system. The reasonable network reconfiguration strategy is necessary for establishing the main network and restoring loads as soon as possible. A skeleton-network reconfiguration strategy is proposed in this paper. Through determining the skeleton network, the burden of network reconfiguration can be reduced effectively. The reconstructing processes are evaluated by a comprehensive index of network reconfiguration efficiency. Furthermore, discrete particle-swarm optimization is employed in reconstructing network skeleton and several relatively-optimal schemes can be obtained as the guidance of the system restoration. Application to the IEEE 30-bus power system shows that reconfiguration schemes derived from the strategy are effective under uncertain system situations and ensure that the following restoration be successful
  • Keywords
    electrical safety; particle swarm optimisation; power system restoration; IEEE 30-bus power system; discrete particle-swarm optimization; network reconfiguration strategy; network skeleton reconfiguration; power system black-start restoration; power system safety; Particle swarm optimization; Power measurement; Power supplies; Power system faults; Power system management; Power system measurements; Power system reliability; Power system restoration; Safety; Skeleton; black start; discrete particle swarm optimization; network reconfiguration; power systems; system restoration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society General Meeting, 2006. IEEE
  • Conference_Location
    Montreal, Que.
  • Print_ISBN
    1-4244-0493-2
  • Type

    conf

  • DOI
    10.1109/PES.2006.1709072
  • Filename
    1709072