• DocumentCode
    605453
  • Title

    Distributed generation siting and sizing with implementation feasibility analysis

  • Author

    Eroshenko, S.A. ; Khalyasmaa, A.I. ; Dmitriev, S.A. ; Pazderin, A.V. ; Karpenko, A.A.

  • Author_Institution
    Ural Fed. Univ., Ekaterinburg, Russia
  • fYear
    2013
  • fDate
    6-8 Feb. 2013
  • Firstpage
    717
  • Lastpage
    721
  • Abstract
    This paper addresses the problem of distributed generation siting and sizing optimization with subsequent equipment configuration assessment. The proposed methodology is based on the combination of genetic algorithms and indicative analysis, which gives an opportunity to assess power system interaction with incident infrastructures and take into account technical, economical, regulatory, ecological and other criteria. Two-step algorithm implementation makes the decision process more flexible and comprehensive. The case study is provided for proposed approach verification.
  • Keywords
    distributed power generation; genetic algorithms; power distribution planning; power generation planning; distributed generation siting; distributed generation sizing; equipment configuration assessment; genetic algorithm; incident infrastructure; indicative analysis; Distributed power generation; Engines; Estimation; Genetic algorithms; Optimization; Power systems; distributed generation; distribution network; genetic algorithm; indicative analysis; optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power, Energy and Control (ICPEC), 2013 International Conference on
  • Conference_Location
    Sri Rangalatchum Dindigul
  • Print_ISBN
    978-1-4673-6027-2
  • Type

    conf

  • DOI
    10.1109/ICPEC.2013.6527749
  • Filename
    6527749