An Innovative Hybrid Algorithm for Very Short-Term Wind Speed Prediction Using Linear Prediction and Markov Chain Approach

A new hybrid algorithm using linear prediction and Markov chain is proposed in order to facilitate very short-term wind speed prediction. First, the Markov chain transition probability matrix is calculated. Then, linear prediction method is applied to predict very short-term values. Finally, the res...

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Bibliographic Details
Published in:International journal of green energy 2011-01, Vol.8 (2), p.147-162
Main Authors: Kani, S. A. Pourmousavi, Riahy, G. H., Mazhari, D.
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Energy
Errors
Exact sciences and technology
Linear prediction
Markov chain
Markov chains
Mathematical analysis
Maximum percentage error
Mean absolute percentage error
Natural energy
Nonlinear filters
Uncertainty
Wind energy
Wind speed
Wind speed prediction
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Summary:A new hybrid algorithm using linear prediction and Markov chain is proposed in order to facilitate very short-term wind speed prediction. First, the Markov chain transition probability matrix is calculated. Then, linear prediction method is applied to predict very short-term values. Finally, the results are modified according to the long-term pattern by a nonlinear filter. The results from proposed method are compared by linear prediction method, persistent method and actual values. It is shown that the prediction-modification processes improves very short-term predictions, by reducing the maximum percentage error and mean absolute percentage error, while it retains simplicity and low CPU time and improvement in uncertainty of prediction.
ISSN:1543-5075
1543-5083
DOI:10.1080/15435075.2010.548887