• DocumentCode
    3508763
  • Title

    Optimal VAr allocation by genetic algorithm

  • Author

    Iba, Kenji

  • Author_Institution
    Mitsubishi Electric Corp., Hyogo, Japan
  • fYear
    1993
  • fDate
    1993
  • Firstpage
    163
  • Lastpage
    168
  • Abstract
    Keeping up with the times and computer technology, many researchers have applied new mathematical approaches extensively to solve various problems in power systems. AI technology, fuzzy theory and artificial neural networks are recent trends. This paper presents a new optimization method for reactive power planning using genetic algorithms. The genetic algorithm (GA) is a kind of search algorithm based on the mechanics of natural selection and genetics. This algorithm can search for a global solution using a multiple path and have a structure fit to integer problems. The proposed method was applied to practical 51-bus and 224-bus systems to show its feasibility and capabilities.
  • Keywords
    genetic algorithms; power engineering computing; power system planning; reactive power; AI; artificial neural networks; fuzzy theory; genetic algorithm; global solution; natural selection; optimisation; power engineering computing; power system planning; reactive power; search algorithm; Artificial intelligence; Capacitors; Genetic algorithms; Inductors; Linear programming; Load flow; Power system control; Power system planning; Reactive power; Shunt (electrical);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks to Power Systems, 1993. ANNPS '93., Proceedings of the Second International Forum on Applications of
  • Conference_Location
    Yokohama, Japan
  • Print_ISBN
    0-7803-1217-1
  • Type

    conf

  • DOI
    10.1109/ANN.1993.264296
  • Filename
    264296