Title :
Optimized DHT-RBF model as replacement of ARMA-RBF model for wind power forecasting
Author :
Mukhopadhyay, Saibal ; Panigrahi, Pratap Kumar ; Mitra, Abhijit ; Bhattacharya, Pallab ; Sarkar, Mohanchur ; Das, Pritam
Author_Institution :
Phys. Sci. Dept., IISER, Kolkata, India
Abstract :
ARMA-Neural model is an established useful model for the Wind Power forecasting purpose. In the current work we introduced Discrete Hilbert Transform (DHT)-Neural Model which provides better result than the ARMA-Neural Model. We know that a signal and its´ DHT produces the same Energy Spectrum. Based on this concept in this paper DHT is used for Wind Speed forecasting purpose. Thereafter the RBF neural network is used on this to forecast wind power. Taking the data of measured wind speed from Weather Forecasting Bureau Report as example, we validate the method described above.
Keywords :
Hilbert transforms; load forecasting; radial basis function networks; weather forecasting; wind power; ARMA-RBF model replacement; ARMA-neural model; DHT-neural model; RBF neural network; Weather Forecasting Bureau report; discrete Hilbert transform-neural model; energy spectrum; optimized DHT-RBF model; wind power forecasting; wind speed forecasting; Forecasting; Neural networks; Transfer functions; Transforms; Wind power generation; Wind speed; ARMA Model; Discrete Hilbert Transform; RBF Neural Network; Wind Power;
Conference_Titel :
Emerging Trends in Computing, Communication and Nanotechnology (ICE-CCN), 2013 International Conference on
Conference_Location :
Tirunelveli
Print_ISBN :
978-1-4673-5037-2
DOI :
10.1109/ICE-CCN.2013.6528534
