• DocumentCode
    167311
  • Title

    Hybrid Metaheuristic for Annual Hydropower Generation Optimization

  • Author

    Nakib, Amir ; Talbi, El-Ghazali ; Fuser, Alain

  • Author_Institution
    Lab. LISSI, Univ. Paris, Creteil, France
  • fYear
    2014
  • fDate
    19-23 May 2014
  • Firstpage
    412
  • Lastpage
    419
  • Abstract
    In this paper, an hybrid metaheuristic based solution is proposed to solve the annual optimal hydro generation scheduling problem. The problem of the hydro generation scheduling is formulated as a continuous non-linear optimization problem and solved using enhanced combination of metaheuristics: random greedy, evolutionnary algorithm and, pseudo dynamic programming. The obtained results upon one year of the application of the proposed method on the horizon of one year of hydropower generation (while in the literature most authors are limited to one week) demonstrate the efficiency of the proposed algorithm.
  • Keywords
    dynamic programming; evolutionary computation; greedy algorithms; hydroelectric generators; hydroelectric power; hydroelectric power stations; nonlinear programming; random processes; annual hydropower generation optimization; annual optimal hydro generation scheduling problem; continuous nonlinear optimization problem; evolutionnary algorithm; hybrid metaheuristic based solution; pseudodynamic programming; random greedy algorithm; Heuristic algorithms; Optimization; Production; Reservoirs; Security; Turbines; continuous optimization; evolutionary algorithm; hydropower; metaheuristics; scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel & Distributed Processing Symposium Workshops (IPDPSW), 2014 IEEE International
  • Conference_Location
    Phoenix, AZ
  • Print_ISBN
    978-1-4799-4117-9
  • Type

    conf

  • DOI
    10.1109/IPDPSW.2014.53
  • Filename
    6969417