• DocumentCode
    3579080
  • Title

    Optimal reconfiguration of electrical distribution network using selective particle swarm optimization algorithm

  • Author

    Tandon, Ankush ; Saxena, D.

  • Author_Institution
    Dept. of Electr. Eng., Malaviya Nat. Inst. of Technol. Jaipur, Jaipur, India
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents an effective methodology to optimally reconfigure an electrical distribution network. Selective Particle Swarm Optimization (SPSO) algorithm is proposed to find the optimal combination of switches that results in a radial configuration with minimum system power loss. SPSO is a modified Binary Particle Swarm Optimization (BPSO) with selective search space. Comparative analysis of SPSO with BPSO for network reconfiguration, under four different loading conditions, namely base, light, medium and heavy, on IEEE 69 bus system is presented to demonstrate the suitability of the proposed method. It is observed that SPSO outperforms BPSO in terms of quality of solution, voltage profile, convergence characteristics and time elapsed to complete optimization process.
  • Keywords
    IEEE standards; distribution networks; particle swarm optimisation; IEEE 69 bus system; SPSO algorithm; base loading condition; binary particle swarm optimization; electrical distribution network; heavy loading condition; light loading condition; medium loading condition; minimum system power loss; modified BPSO; optimal network reconfiguration; radial configuration; selective particle swarm optimization; selective search space; Convergence; Genetic algorithms; Loading; Minimization; Optimization; Particle swarm optimization; Switches; Binary Particle Swarm Optimization (BPSO); Distribution Networks; Network Reconfiguration (NR); Particle Swarm Optimization (PSO); Selective Particle Swarm Optimization (SPSO);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power, Control and Embedded Systems (ICPCES), 2014 International Conference on
  • Print_ISBN
    978-1-4799-5910-5
  • Type

    conf

  • DOI
    10.1109/ICPCES.2014.7062806
  • Filename
    7062806