• DocumentCode
    157690
  • Title

    Reliability improvement of power distribution system through feeder reconfiguration

  • Author

    Elsaiah, Salem ; Benidris, Mohammed ; Mitra, Joydeep

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI, USA
  • fYear
    2014
  • fDate
    7-10 July 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper describes a method for reliability improvement of power distribution system via feeder reconfiguration. The work presented here is developed based on a linearized network model in the form of DC power flow and linear programming model in which current carrying capacities of distribution feeders and real power constraints have been considered. The optimal open/close status of the sectionalizing and tie-switches are identified using an intelligent binary particle swarm optimization based search method. The probabilistic reliability assessment is conducted using a method based on higher probability order approximation. Several case studies are carried out on a small 33-bus radial distribution system, which is extensively used as an example in solving the distribution system reconfiguration problem. Further, the effect of embedded generation has been considered in one case scenario. The obtained results are reported, discussed, and thoroughly analyzed.
  • Keywords
    approximation theory; linear programming; particle swarm optimisation; power distribution reliability; probability; search problems; DC power flow; current carrying capacities; embedded generation; feeder reconfiguration; higher probability order approximation; intelligent binary particle swarm optimization; linear programming model; linearized network model; power distribution system reliability; probabilistic reliability assessment; radial distribution system; search method; Approximation methods; Linear programming; Niobium; Particle swarm optimization; Power system reliability; Reliability; Switches; Distribution system reconfiguration; linear programming; particle swarm optimization; reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Probabilistic Methods Applied to Power Systems (PMAPS), 2014 International Conference on
  • Conference_Location
    Durham
  • Type

    conf

  • DOI
    10.1109/PMAPS.2014.6960676
  • Filename
    6960676