• DocumentCode
    3478481
  • Title

    The generation expansion planning of the utility in a deregulated environment

  • Author

    Lin, Whei-Min ; Zhan, Tung-Sheng ; Tsay, Ming-Tong ; Hung, Wen-Cha

  • Author_Institution
    Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan
  • Volume
    2
  • fYear
    2004
  • fDate
    5-8 April 2004
  • Firstpage
    702
  • Abstract
    In this paper, an improved genetic algorithm (IGA) is presented to determine the generation expansion planning of the utility in a deregulated market. The utility has to take both the IPPs´ participation and environment impact into account when a new generation is expanded. The CO2emission also took into account, while satisfying all electrical constraints simultaneously. IGA was conducted by an improved crossover and mutation mechanism with a competition and autoadjust scheme to avoid prematurity. Tabu lists with heuristic rules were also employed in the searching process to enhance the performance. Testing results shows that IGA can offer an efficient way in determining the generation expansion planning. Results can offer utilities for determining the optimal expansion planning.
  • Keywords
    air pollution; carbon compounds; genetic algorithms; heuristic programming; power generation planning; power markets; search problems; CO2; IPPs participation; Tabu lists; autoadjust scheme; crossover mechanism; deregulated market; electrical constraints; environment impact; generation expansion planning; genetic algorithm; heuristic rules; mutation mechanism; optimal expansion planning; searching process; Artificial intelligence; Character generation; Costs; Dynamic programming; Genetic algorithms; Genetic mutations; Integer linear programming; Nuclear power generation; Petroleum; Power generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Utility Deregulation, Restructuring and Power Technologies, 2004. (DRPT 2004). Proceedings of the 2004 IEEE International Conference on
  • Print_ISBN
    0-7803-8237-4
  • Type

    conf

  • DOI
    10.1109/DRPT.2004.1338074
  • Filename
    1338074