• DocumentCode
    176116
  • Title

    Research of immune algorithms for reconfiguration of distribution network with distributed generations

  • Author

    Cailian Gu ; Jianwei Ji ; Li Liu

  • Author_Institution
    Coll. of Electr. Eng., Shenyang Inst. of Eng., Shenyang, China
  • fYear
    2014
  • fDate
    May 31 2014-June 2 2014
  • Firstpage
    2156
  • Lastpage
    2160
  • Abstract
    The structure of traditional distribution network is changed from a single supply radial network to a more power ring network when grid is connected with distributed generations (DG), and island phenomenon occurs higher in the process of reconstruction, which becomes uncontrolled and high risk operation and increased the difficulty of distribution network reconstruction. The improved immune genetic algorithm introduced the principle of biological immune mechanism into standard genetic algorithm is put forward, the problem of genetic algorithm premature convergence in distribution network calculation is overcome, constraint conditions of preventing islanding phenomenon in the reconstructed model is added, encoding method based on the loop is used. The calculation results show that, in the case of a distributed power supply, the loss of network can be decreased and voltage quality is improved by using this method, what is the most that island phenomenon is avoided. IEEE33 node is an example to prove the feasibility of the method.
  • Keywords
    distributed power generation; genetic algorithms; power distribution faults; power supply quality; IEEE 33 node system; biological immune mechanism; constraint conditions; distributed generation; distributed power supply; distribution network reconfiguration; encoding method; genetic algorithm; immune algorithm; island phenomenon; voltage quality; Encoding; Genetic algorithms; Heuristic algorithms; Immune system; Load flow; Optimization; DG; Distribution Reconfiguration; Immune genetic algorithm; Islanding phenomenon;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (2014 CCDC), The 26th Chinese
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-3707-3
  • Type

    conf

  • DOI
    10.1109/CCDC.2014.6852524
  • Filename
    6852524