• DocumentCode
    645716
  • Title

    Optimal location and sizing of distributed generators in distribution networks

  • Author

    Dahal, Sangeet ; Salehfar, H.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of North Dakota, Grand Forks, ND, USA
  • fYear
    2013
  • fDate
    22-24 Sept. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Using a combination of Particle Swarm Optimization (PSO) and Newton-Raphson load flow methods this paper investigates the impact of location and size of distributed generators on distribution systems. Similar to the existing improved analytical (IA) method, the proposed approach optimizes the size and location of distributed generators with both real and reactive power capabilities. However, studies show that the proposed method yields much better results than the IA technique and with less computation times. In addition, compared to other evolutionary algorithms such as artificial bee colony (ABC), the proposed method achieves a better distribution system voltage profile with smaller DG sizes. To show the advantages of the proposed method, the IEEE 69-bus distribution system is used as a test bed and the results are compared with those from IA and ABC approaches.
  • Keywords
    IEEE standards; Newton-Raphson method; distributed power generation; distribution networks; evolutionary computation; load flow; particle swarm optimisation; reactive power; ABC; DG; IA method; IEEE 69-bus distribution system; Newton-Raphson load flow method; PSO; artificial bee colony; distributed generator; distribution network; evolutionary algorithm; improved analytical method; particle swarm optimization; reactive power capability; Capacitors; Distributed power generation; Generators; Load flow; Particle swarm optimization; Reactive power; Resource management; Distributed generation; Improved analytical method; Particle swarm optimization; optimal location; optimal size; power loss; voltage profile;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    North American Power Symposium (NAPS), 2013
  • Conference_Location
    Manhattan, KS
  • Type

    conf

  • DOI
    10.1109/NAPS.2013.6666866
  • Filename
    6666866