• DocumentCode
    1785634
  • Title

    Multi objective design of stand-alone PV/wind energy system by using hybrid GA and PSO

  • Author

    Amereh, Mohammad ; Khozani, Zahra Shiravi ; Kazemi, A.

  • Author_Institution
    Dept. of Electr. Eng., Iran Univ. of Sci. & Technol., Tehran, Iran
  • fYear
    2014
  • fDate
    20-22 May 2014
  • Firstpage
    695
  • Lastpage
    699
  • Abstract
    In recent years, hybrid renewable energy systems have been considered much more for stand-alone applications. In this paper, a new method has been introduced to obtain optimal size of hybrid energy system, including wind turbine (WT), photovoltaic (PV) panels and storage battery (SB). Optimization has considered two objective functions; total net present worth (TNPW) as cost function and energy index of reliability (EIR) as technical criteria. Because of complexity of problem and possibility of local minimum, a hybrid genetic algorithm (GA) and particle swarm optimization (PSO) is employed. First of all, by using GA, the possibility of local minimum reduces and after specified iterations, PSO is used to improve optimization´s speed and local tuning ability.
  • Keywords
    genetic algorithms; hybrid power systems; particle swarm optimisation; photovoltaic power systems; wind turbines; EIR; GA; PSO; PV panels; SB; TNPW; cost function; energy index of reliability; hybrid energy system; hybrid genetic algorithm; multiobjective design; particle swarm optimization; photovoltaic panels; stand-alone PV/wind energy system; storage battery; total net present worth; wind turbine; Batteries; Genetic algorithms; Hybrid power systems; Optimization; Particle swarm optimization; Reliability; Wind turbines; genetic algorithm; hybrid algorithm; multiobjective optimization; particle swarm optimization; photovoltaic panel; renewable energy; wind turbine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering (ICEE), 2014 22nd Iranian Conference on
  • Conference_Location
    Tehran
  • Type

    conf

  • DOI
    10.1109/IranianCEE.2014.6999628
  • Filename
    6999628