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
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;
Conference_Titel :
Power Electronics (IICPE), 2014 IEEE 6th India International Conference on
Print_ISBN :
978-1-4799-6045-3
DOI :
10.1109/IICPE.2014.7115784
