• DocumentCode
    2530360
  • Title

    A solution to the unit commitment using hybrid genetic algorithm

  • Author

    Chang, Wenping ; Luo, Xianjue

  • Author_Institution
    Dept. of Electr. Eng., Henan Mech. & Electr. Eng. Coll., Xinxiang
  • fYear
    2008
  • fDate
    19-21 Nov. 2008
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    A hybrid genetic algorithm (HGA) is presented to solve the thermal unit commitment (UC). It effectively uses the binary-coded genetic algorithm incorporating a priority list ordering scheme to solve the unit commitment up/down problem and the lambda-iteration method to solve the power economic dispatch problem, This modification helps to explore the search space very effectively, It generates better solutions than the other methods. Problem formulation, representation and the simulation results with systems of up to 10 units and 24-h scheduling horizon are presented.
  • Keywords
    genetic algorithms; iterative methods; power generation dispatch; power generation scheduling; binary-coded genetic algorithm; hybrid genetic algorithm; lambda-iteration method; power economic dispatch problem; priority list ordering; thermal unit commitment; time 24 h; Artificial neural networks; Costs; Fuel economy; Genetic algorithms; Optimization methods; Power generation economics; Power system economics; Power system simulation; Power systems; Space exploration; Unit commitment; economic dispatch; genetic algorithm; lambda-iteration method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON 2008 - 2008 IEEE Region 10 Conference
  • Conference_Location
    Hyderabad
  • Print_ISBN
    978-1-4244-2408-5
  • Electronic_ISBN
    978-1-4244-2409-2
  • Type

    conf

  • DOI
    10.1109/TENCON.2008.4766718
  • Filename
    4766718