• DocumentCode
    2635633
  • Title

    Genetic Algorithm for Static Power Economic Dispatch

  • Author

    Chiang, Chao-Lung

  • Author_Institution
    Electron. Eng. Dept., Nan Kai Univ. of Technol., Nan Ton, Taiwan
  • Volume
    4
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    646
  • Lastpage
    650
  • Abstract
    This research presents an improved genetic algorithm (IGA) to solve static power economic dispatch (SPED) problems of units with valve-point effects and multiple fuels. Few SPED problems related studies have seldom addressed both valve-point loadings and change fuels. The proposed algorithm was compared with the conventional genetic algorithm (CGA), revealing that the proposed IGA is more effective than the CGA, and applies the realistic SPED problem more efficiently than does the CGA.
  • Keywords
    genetic algorithms; power system economics; change fuels; conventional genetic algorithm; improved genetic algorithm; power system; static power economic dispatch; valve-point loadings; Constraint optimization; Cost function; Dynamic programming; Fuel economy; Genetic algorithms; Genetic engineering; Hopfield neural networks; Power engineering and energy; Power generation economics; Power systems; Genetic algorithm; Power system; economic dispatch;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Engineering, 2009 WRI World Congress on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-0-7695-3507-4
  • Type

    conf

  • DOI
    10.1109/CSIE.2009.440
  • Filename
    5171075
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2635633