• DocumentCode
    1611719
  • Title

    AI based reconfiguration technique for improving performance and operation of distribution power systems with distributed generators

  • Author

    Fayek, R.H. ; Sweif, R.A.

  • Author_Institution
    Electron. Eng., German Univ. in Cairo, Cairo, Egypt
  • fYear
    2013
  • Firstpage
    215
  • Lastpage
    221
  • Abstract
    This paper targets the enhancement of distribution power system´s performance and operation through reducing system´s real losses and improving overall voltage profile of the network taking into consideration topological and load constraints. For this target, two main techniques are employed in this paper; network reconfiguration and distributed generators installation. The paper proposes genetic algorithm (GA) along with an analytically developed load flow code to generate optimal network topology and find optimal sizing, locations and number of distributed generators to be installed considering different DG types. To demonstrate the effectiveness of the research, the IEEE 33 bus system is considered in this paper. This is a three phase radial balanced distribution system.
  • Keywords
    distributed power generation; distribution networks; genetic algorithms; load flow; AI based reconfiguration technique; IEEE 33 bus system; distributed generators installation; distribution power system performance; genetic algorithm; load constraints; load flow code; network reconfiguration; three phase radial balanced distribution system; topological constraints; voltage profile; Biological cells; Generators; Genetic algorithms; Load flow analysis; Optimization; Reactive power; Distribution system; distributed generators (DG); genetic algorithm optimization (GA); network reconfiguration; power loss reduction; voltage profile improvement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering, Energy and Electrical Drives (POWERENG), 2013 Fourth International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    2155-5516
  • Type

    conf

  • DOI
    10.1109/PowerEng.2013.6635609
  • Filename
    6635609