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
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;
Conference_Titel :
Power Electronics (IICPE), 2012 IEEE 5th India International Conference on
Conference_Location :
Delhi
Print_ISBN :
978-1-4673-0931-8
DOI :
10.1109/IICPE.2012.6450459