Title :
Short and mid-term wind power plants forecasting with ANN
Author :
Mahmoudi, Javad ; Jamil, Majid ; Balaghi, Hossein
Author_Institution :
Electr. Eng., Sharif Univ., Tehran, Iran
Abstract :
In recent years, wind energy has a remarkable growth in the world, but one of the important problems of power generated from wind is its uncertainty and corresponding power. For solving this problem, some approaches have been presented. Recently, the Artificial Neural Networks (ANN) as a heuristic method has more applications for this propose. In this paper, short-term (1 hour) and mid-term (24 hours) power forecasting are presented for a sample wind power plant by multilayer ANN. The needed inputs data are temperature and wind speed for forecasting the power. A case study has presented.
Keywords :
load forecasting; neural nets; power engineering computing; wind power plants; artificial neural networks; mid-term wind power plant forecasting; multilayer ANN; short-term power forecasting; time 1 hour; time 24 hour; wind energy; wind speed; Artificial neural networks; Forecasting; Power generation; Training; Wind forecasting; Wind speed; artificial neural network; power prediction; wind power forecasting;
Conference_Titel :
Renewable Energy and Distributed Generation (ICREDG), 2012 Second Iranian Conference on
Conference_Location :
Tehran
Print_ISBN :
978-1-4673-0663-8
Electronic_ISBN :
978-1-4673-0664-5
DOI :
10.1109/ICREDG.2012.6190456