• DocumentCode
    1871430
  • Title

    Economic dispatch solution using a genetic algorithm based on arithmetic crossover

  • Author

    Yalcinoz, T. ; Altun, H. ; Uzam, M.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Nigde Univ., Turkey
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Abstract
    In this paper, a new genetic approach based on arithmetic crossover for solving the economic dispatch problem is proposed. Elitism, arithmetic crossover and mutation are used in the genetic algorithm to generate successive sets of possible operating policies. The proposed technique improves the quality of the solution. The new genetic approach is compared with an improved Hopfield NN approach (IHN), a fuzzy logic controlled genetic algorithm (FLCGA), an advance engineered-conditioning genetic approach (AECGA) and an advance Hopfield NN approach (AHNN)
  • Keywords
    Hopfield neural nets; control system synthesis; fuzzy control; genetic algorithms; load dispatching; neurocontrollers; optimal control; power system control; power system economics; advance engineered-conditioning genetic approach; arithmetic crossover; economic dispatch solution; elitism; fuzzy logic control; genetic algorithm; improved Hopfield NN approach; mutation; operating policies; solution quality; Arithmetic; Costs; Environmental economics; Fuel economy; Fuzzy logic; Genetic algorithms; Power generation economics; Power system economics; Power system modeling; Power system reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Tech Proceedings, 2001 IEEE Porto
  • Conference_Location
    Porto
  • Print_ISBN
    0-7803-7139-9
  • Type

    conf

  • DOI
    10.1109/PTC.2001.964734
  • Filename
    964734