• DocumentCode
    2221474
  • Title

    Multi-objective optimal multiple reservoir operation

  • Author

    Scola, Luís A. ; Neto, Oriane Magela ; Takahashi, Ricardo H. C. ; Cerqueira, Sergio A. A. G.

  • Author_Institution
    Dept. of Thermal & Fluid Sci., Fed. Univ. of Sao Joao del Rei, Sao Joao del Rei, Brazil
  • fYear
    2011
  • fDate
    5-8 June 2011
  • Firstpage
    1927
  • Lastpage
    1933
  • Abstract
    Hydropower plants produce most of the electrical power generated in Brazil. Although the remaining potential is still large, most of it is located far from the industrialized south eastern states. In addition to that, the increasing opposition to the construction of new large reservoirs, for ecological and social reasons, highlights the need for the efficient operation of the existing system. In this work, a formulation recently developed by the authors, which has been shown to efficiently deal with the operational constraints of a single plant, is expanded to the multi-reservoir case. A multi-objective optimization of a system of five Brazilian hydropower plants is performed, with the objectives of increasing the mean power generation along a year and reducing the peak of demand of non-renewable energy sources. The optimization algorithm is taxed by the increase in the number of variables and by their unsual combination in the efficient solutions set, leading to problems that were found to be associated with the the simple Gaussian mutation operator employed.
  • Keywords
    Gaussian processes; hydroelectric power stations; optimisation; reservoirs; Brazilian hydropower plant; Gaussian mutation operator; electrical power generation; multiobjective optimal multiple reservoir operation; multiobjective optimization; Genetic algorithms; Hydroelectric power generation; Optimization; Reservoirs; Turbines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2011 IEEE Congress on
  • Conference_Location
    New Orleans, LA
  • ISSN
    Pending
  • Print_ISBN
    978-1-4244-7834-7
  • Type

    conf

  • DOI
    10.1109/CEC.2011.5949851
  • Filename
    5949851