• DocumentCode
    1181897
  • Title

    Optimal Power Flow by Enhanced Genetic Algorithm

  • Author

    Bakirtzis, Anastasios G. ; Biskas, P. N. ; Zoumas, C. E. ; Petridis, V.

  • Author_Institution
    Aristotle University, Greece
  • Volume
    22
  • Issue
    2
  • fYear
    2002
  • Firstpage
    60
  • Lastpage
    60
  • Abstract
    This paper presents an enhanced genetic algorithm for the solution of the optimal power flow with both continuous and discrete control variables. The continuous control variables modeled are unit active power outputs and generator-bus voltage magnitudes, while the discrete ones are transformer-tap settings and switchable shunt devices. A number of functional operating constraints, such as branch flow limits, load bus voltage magnitude limits, and generator reactive capabilities are included as penalties in the genetic algorithm fitness function. Advanced and problem-specific operators are introduced in order to enhance the algorithm´s efficiency and accuracy. Numerical results on two test systems are presented and compared with results of other approaches.
  • Keywords
    Costs; Data analysis; Dictionaries; Genetic algorithms; Information analysis; Load flow; Power generation; Power system analysis computing; Power system dynamics; Protocols; Optimal power flow; genetic algorithms;
  • fLanguage
    English
  • Journal_Title
    Power Engineering Review, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1724
  • Type

    jour

  • DOI
    10.1109/MPER.2002.4311997
  • Filename
    4311997