• DocumentCode
    3470207
  • Title

    Optimal algorithm of distribution network planning including distributed generation

  • Author

    Wang, Yanjun ; Zhang, Yun

  • Author_Institution
    Sch. of Electr. Eng. & Autom., Tanjin Univ., Tianjin
  • fYear
    2008
  • fDate
    6-9 April 2008
  • Firstpage
    872
  • Lastpage
    876
  • Abstract
    The genetic algorithm has some defects for optimizing multi-objective, such as slow convergent speed and easy to premature. So this article proposes an improved self- adaptive genetic algorithm, improving terminal criterion and method of selection, make a self-adaptive disposal in crossover and mutation probability. Considering multi-objective of distribution network planning including distributed generation, this article introduces total satisfied degree by employing the fuzzy optimal theory, which makes a good way to transform multi-objective into single objective. Results of a system simulation show that this algorithm can seek the best result of overall situation effectively, increase the convergence speed obviously, also has favorable self-adaptive characteristic.
  • Keywords
    distributed power generation; fuzzy set theory; genetic algorithms; power distribution planning; crossover probability; distributed generation; distribution network planning; fuzzy theory; genetic algorithm; mutation probability; optimal algorithm; self-adaptive disposal; terminal criterion; Cost function; Distributed control; Genetic algorithms; Genetic mutations; Investments; Power system reliability; Power system security; Reactive power; Stability; Voltage; Distributed generation; distribution network planning; fuzzy optimization; improved self-adaptive genetic algorithm; multi-objective optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008. Third International Conference on
  • Conference_Location
    Nanjuing
  • Print_ISBN
    978-7-900714-13-8
  • Electronic_ISBN
    978-7-900714-13-8
  • Type

    conf

  • DOI
    10.1109/DRPT.2008.4523529
  • Filename
    4523529