• DocumentCode
    3162910
  • Title

    Soving unit commitment problem by combining of continuous relaxation method and genetic algorithm

  • Author

    Tokoro, K.-i. ; Masuda, Yasushi ; Nishino, Hiroaki

  • Author_Institution
    Central Res. Inst. of Electr. Power Ind., Tokyo
  • fYear
    2008
  • fDate
    20-22 Aug. 2008
  • Firstpage
    3474
  • Lastpage
    3478
  • Abstract
    This paper proposes a genetic algorithm for solving a unit commitment problem of electric generators, which formally is a mixed integer nonlinear programming problem. The proposed algorithm finds the optimal ON/OFF status of units by a combination of genetic algorithm and continuous relaxation method. In the proposed algorithm, a chromosome encodes a partial solution, in which the values of some variables are unfixed. The fitness of an individual is evaluated based upon a solution of the problem where all unfixed variables in the chromosome are relaxed to be continuous. Numerical experiments show the satisfactory performance of the proposed algorithm with respect to the solution quality for planning the actual unit commitment schedule.
  • Keywords
    genetic algorithms; integer programming; nonlinear programming; power generation dispatch; power generation scheduling; relaxation theory; continuous relaxation method; electric power generator; genetic algorithm; mixed integer nonlinear programming problem; optimal ON/OFF status; unit commitment problem; Biological cells; Costs; Electronic mail; Fuels; Generators; Genetic algorithms; Power generation; Relaxation methods; Scheduling algorithm; Spinning; Optimization; genetic algorithm mixed integer nonlinear optimization; unit commitment problem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE Annual Conference, 2008
  • Conference_Location
    Tokyo
  • Print_ISBN
    978-4-907764-30-2
  • Electronic_ISBN
    978-4-907764-29-6
  • Type

    conf

  • DOI
    10.1109/SICE.2008.4655263
  • Filename
    4655263