• DocumentCode
    696282
  • Title

    Novel approach to generation Portfolio Optimization by using genetic algorithms and stochastic methods

  • Author

    Di Giorgio, Alessandro ; Mercurio, Andrea ; Pimpinella, Laura

  • Author_Institution
    Dept. of Comput. & Syst. Sci., Univ. of Rome Sapienza, Rome, Italy
  • fYear
    2009
  • fDate
    23-26 Aug. 2009
  • Firstpage
    3196
  • Lastpage
    3201
  • Abstract
    In this paper we present the Portfolio Optimization Problem in the electricity generation framework. We consider traditional and fully controllable energy sources together with wind source, strongly supported by economical benefits but exposed to intermittent generation volatility. Due to the statistical uncertainty about parameters, we formalize the optimization problem in a probabilistic sense and solve it by using Genetic Algorithms.
  • Keywords
    genetic algorithms; investment; power generation economics; probability; stochastic processes; wind power plants; electricity generation portfolio optimization problem; energy sources; genetic algorithms; intermittent generation volatility; statistical uncertainty; stochastic methods; wind source; Coal; Genetic algorithms; Green products; Investment; Optimization; Portfolios; Power generation; Generation Company; Genetic Algorithms; Monte Carlo method; Net Present Value; Portfolio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 2009 European
  • Conference_Location
    Budapest
  • Print_ISBN
    978-3-9524173-9-3
  • Type

    conf

  • Filename
    7074897