• DocumentCode
    1896828
  • Title

    Optimal placement of hybrid PV-wind systems using genetic algorithm

  • Author

    Masoum, Mohammad A S ; Badejani, Seyed M Mousavi ; Kalantar, Mohsen

  • Author_Institution
    Curtin Univ. of Technol., Perth, WA, Australia
  • fYear
    2010
  • fDate
    19-21 Jan. 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Genetic algorithms are proposed for optimal placement of hybrid PV-wind system (HPWS) and for determining the optimal ratio of wind/solar power contributions. The total capacity of HPWS is determined based on estimated annual power demand, average wind speed and sun radiation. Each PV and wind unit is defined based on real environmental conditions. To improve HPWS performance under different operating and environmental conditions, maximum power point tracking of PV units and blade angle pitch control of wind turbines are considered. For each candidate location, cost functions corresponding to PV, wind and battery units, as well as surplus produced power are defined and genetically minimized to determine the best location of HPWS. The proposed algorithm is used for optimal placement of a 1MVA hybrid PV-wind system in United States (considering 265 candidate locations) and to compute the optimal number of 40kW-PV and 68.46kW-wind units.
  • Keywords
    blades; genetic algorithms; maximum power point trackers; photovoltaic power systems; solar power; solar radiation; wind power; wind power plants; wind turbines; HPWS; United States; average wind speed; blade angle pitch control; cost functions; estimated annual power demand; genetic algorithm; hybrid PV-Wind systems optimal placement; maximum power point tracking; optimal ratio; power 40 kW; power 68.46 kW; solar power; sun radiation; wind power; wind turbines; Batteries; Blades; Control systems; Cost function; Genetic algorithms; Hybrid power systems; Induction generators; Power system reliability; Wind energy generation; Wind turbines; Hybrid PV-wind systems; cost function; genetic algorithms; optimal location;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies (ISGT), 2010
  • Conference_Location
    Gaithersburg, MD
  • Print_ISBN
    978-1-4244-6264-3
  • Electronic_ISBN
    978-1-4244-6333-6
  • Type

    conf

  • DOI
    10.1109/ISGT.2010.5434746
  • Filename
    5434746