• DocumentCode
    3157154
  • Title

    A new genetic algorithm for unit commitment

  • Author

    Hongwei, Zhao ; Liangting, Yi ; Buyun, Wang ; Gang, Cheng ; Haiping, Yang

  • Author_Institution
    Dept. of Autom. Eng., Chongqing Logistic Eng. Univ., Chongqing, China
  • Volume
    1
  • fYear
    1997
  • fDate
    28-31 Oct 1997
  • Firstpage
    606
  • Abstract
    This paper presents a revised genetic algorithm (RGA) for unit commitment (UC). A model to adjust the parameters of the GA automatically with the population evolution and different chromosomes is built. A new stop-rule is also given. In order to examine the proposed method, an example is employed for UC which yields several promising results
  • Keywords
    genetic algorithms; load distribution; power engineering computing; scheduling; chromosomes; load demand; optimum schedule; parameter adjustment; population evolution; revised genetic algorithm; stop rule; unit commitment; Acceleration; Artificial intelligence; Biological cells; Convergence; Delay; Genetic algorithms; Genetic mutations; Power systems; Robustness; Spinning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-4253-4
  • Type

    conf

  • DOI
    10.1109/ICIPS.1997.672856
  • Filename
    672856
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3157154