• DocumentCode
    2369128
  • Title

    Optimal sizing of hybrid wind/photovoltaic/battery considering the uncertainty of wind and photovoltaic power using Monte Carlo

  • Author

    Bashir, M. ; Sadeh, J.

  • Author_Institution
    Islamic Azad Univ., Gonabad, Iran
  • fYear
    2012
  • fDate
    18-25 May 2012
  • Firstpage
    1081
  • Lastpage
    1086
  • Abstract
    Using hybrid renewable energy is one of the best alternatives to supply the electrical energy at remote areas. Renewable energy sources are depended to weather conditions or other factors, so for supplying load with renewable sources appropriate capacity of these sources should be selected. In determining the capacity of renewable energy such as wind and solar, considering the stochastic nature of wind speed and solar radiation is very impressive. In this paper, a new algorithm for determining the capacity of hybrid wind, photovoltaic and battery generation system with considering the uncertainty in wind and photovoltaic power production is proposed. The algorithm of determining capacity of wind, photovoltaic and battery for supplying certain load is formulated as an optimization problem that the objective function is the minimization of the cost and with constrain of having specific reliability. Probability density of wind speed and solar radiation and Mont Carlo simulation method is used to considered uncertainty in wind and photovoltaic power generation. Particle swarm optimization is used for optimal sizing of the system.
  • Keywords
    Monte Carlo methods; battery storage plants; hybrid power systems; particle swarm optimisation; photovoltaic power systems; power generation reliability; probability; renewable energy sources; stochastic processes; sunlight; wind power plants; Mont Carlo simulation method; cost minimization; electrical energy; hybrid renewable energy source; hybrid wind-photovoltaic-battery generation system; load supply; particle swarm optimization; photovoltaic power production; probability density; reliability; sizing optimisation problem; solar energy; solar radiation stochastic nature; wind power uncertainty; wind speed stochastic nature; Batteries; Photovoltaic systems; Renewable energy resources; Solar radiation; Wind speed; Wind turbines; Hybrid wind; Monte Carlo simulation; Particle swarm optimization; Reliability evaluation; Renewable energy; photovoltaic system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Environment and Electrical Engineering (EEEIC), 2012 11th International Conference on
  • Conference_Location
    Venice
  • Print_ISBN
    978-1-4577-1830-4
  • Type

    conf

  • DOI
    10.1109/EEEIC.2012.6221541
  • Filename
    6221541