• DocumentCode
    3349692
  • Title

    Genetic algorithm for power load dispatch

  • Author

    Chiang, Chao-Lung

  • Author_Institution
    Dept. of Electron. Eng., Nan-Kai Inst. of Technol., Nantou
  • fYear
    2008
  • fDate
    21-24 Sept. 2008
  • Firstpage
    347
  • Lastpage
    352
  • Abstract
    Few investigations of the genetic algorithm (GA) have been studied for the real-world power economic load dispatch (PELD) problem. This paper proposes an improved genetic algorithm with multiplier updating (IGAMU) to solve practical PELD problems of complexity having nonconvex cost curves where conventional mathematical methods are inapplicable. The proposed IGAMU integrates the improved genetic algorithm (IGA) and the multiplier updating (MU). A practical example is employed to demonstrate that the proposed algorithm has merits of straightforward concept; easy implementation; better effectiveness than previous methods; better effectiveness and efficiency than the GA with MU (GA-MU); automatic adjustment of the randomly assigned penalty to an appropriate value, and the requirement for only a small population in applications of real life PELD operations.
  • Keywords
    concave programming; genetic algorithms; power generation dispatch; power generation economics; IGAMU; improved genetic algorithm; multiplier updating; nonconvex cost curves; power load dispatch; randomly assigned penalty; real-world power economic load dispatch; Chaos; Constraint optimization; Cost function; Evolutionary computation; Fuels; Genetic algorithms; Genetic engineering; Power engineering and energy; Power generation; Power systems; economic load dispatch; nonconvex function;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cybernetics and Intelligent Systems, 2008 IEEE Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-1673-8
  • Electronic_ISBN
    978-1-4244-1674-5
  • Type

    conf

  • DOI
    10.1109/ICCIS.2008.4670767
  • Filename
    4670767