• DocumentCode
    2312355
  • Title

    Monte Carlo Planning Technique for Renewable Energy Sources

  • Author

    Indulkar, C.S.

  • Author_Institution
    IIT Delhi, Delhi
  • fYear
    2008
  • fDate
    12-15 Oct. 2008
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Distributed power generation provides electric power at a site closer to customers. This paper, formulates the problem of optimal utilization of renewable energy options to meet the peak load demand. A Monte Carlo apportioning technique of solar photovoltaic, co-generation, wind power, and small hydro, which considers specific techno-economic constraints, such as capital cost and generation cost constraints, and carbon dioxide emission factors, is described. The proposed method in a single study provides the proportion of the renewable energy sources for maximum generating capacity or lowest generation cost subject to lowest emission or to lowest capital cost.
  • Keywords
    Monte Carlo methods; distributed power generation; power generation economics; power generation planning; renewable energy sources; Monte Carlo planning technique; apportioning technique; carbon dioxide emission factors; co-generation; distributed power generation; electric power; generation cost constraints; peak load demand; renewable energy sources; solar photovoltaic system; techno-economic constraints; wind power; Costs; Distributed power generation; Monte Carlo methods; Photovoltaic systems; Power generation planning; Renewable energy resources; Solar power generation; Wind energy; Wind energy generation; Wind power generation; Linear programming; Operation strategies; Renewable energy technologies; Techno-economic constraints;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power System Technology and IEEE Power India Conference, 2008. POWERCON 2008. Joint International Conference on
  • Conference_Location
    New Delhi
  • Print_ISBN
    978-1-4244-1763-6
  • Electronic_ISBN
    978-1-4244-1762-9
  • Type

    conf

  • DOI
    10.1109/ICPST.2008.4745150
  • Filename
    4745150