• DocumentCode
    3250218
  • Title

    Prediction of wind energy using intelligent approach

  • Author

    Rizwan, M. ; Saini, Shrikant ; Singh, Upendra

  • Author_Institution
    Dept. of Electr. Eng., Delhi Technol. Univ., New Delhi, India
  • fYear
    2012
  • fDate
    6-8 Dec. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Wind energy is one of the most promising renewable energy sources for power generation. As India has wind energy potential of around 45195 MW and the installed capacity is 17967 MW only. Keeping in view of the aforesaid prediction of wind energy is an important study for harnessing the wind energy potential. Various conventional and intelligent models are available in the literature for the prediction of wind Power. In this paper fuzzy logic and ANN based models have been developed and presented for the prediction of wind power using wind speed and air density as input parameters. Obtained results are compared with the available models and found better. Therefore, the proposed ANN model may be useful for the prediction of wind power.
  • Keywords
    fuzzy logic; neural nets; power engineering computing; renewable energy sources; wind power plants; ANN based models; India; air density; fuzzy logic based models; intelligent models; power 17967 MW; power generation; renewable energy sources; wind energy potential; wind energy prediction; wind power prediction; wind speed; Artificial neural networks; Atmospheric modeling; Fuzzy logic; Predictive models; Wind energy; Wind power generation; Wind speed; Wind Energy; artificial neural network; fuzzy logic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics (IICPE), 2012 IEEE 5th India International Conference on
  • Conference_Location
    Delhi
  • ISSN
    2160-3162
  • Print_ISBN
    978-1-4673-0931-8
  • Type

    conf

  • DOI
    10.1109/IICPE.2012.6450459
  • Filename
    6450459