DocumentCode
3590825
Title
Comparative study of stochastic wind speed prediction models
Author
Agrawal, Alok ; Sandhu, K.S.
Author_Institution
Dept. of Electr. Eng., NIT Kurukshetra, Kurukshetra, India
fYear
2014
Firstpage
1
Lastpage
6
Abstract
Global weather concerns have diverted the researchers to look out for clean and green energy sources. The wind power has been utilized since old days for applications such as pumping water, grain grinding mills, driving ships, etc. However, due to its uneven nature, wind energy has never been a choice of power engineers. With the inherent variability of wind due to fluctuating weather conditions, wind speed prediction techniques play a vital role in determining the feasibility of esteemed wind power projects. Modern weather forecasting involves a combination of analyzed data, computer models, knowledge of trends and patterns. In this paper various short-term statistical wind speed forecasting techniques have been analyzed and focused upon.
Keywords
weather forecasting; wind; wind power; global weather; grain grinding mills; green energy sources; power engineers; pumping water; short-term statistical wind speed forecasting techniques; stochastic wind speed prediction models; wind power projects feasibility; Autoregressive processes; Polynomials; Predictive models; Time series analysis; Wavelet transforms; Wind forecasting; Wind speed; Artificial Neural Network(ANN); Auto-regressive Moving average(ARMA); Markov chain; Mortimer method; Numerical Weather Prediction(NWP); Polynomial Curve Fitting(PCF); Variance ratio(VR) method; Wavelet transformation;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Electronics (IICPE), 2014 IEEE 6th India International Conference on
Print_ISBN
978-1-4799-6045-3
Type
conf
DOI
10.1109/IICPE.2014.7115784
Filename
7115784
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