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A new ANN-based methodology for very short-term wind speed prediction using Markov chain approach

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2 Author(s)
Kani, S.A.P. ; Dept. of Electr. Eng., Amirkabir Univ. of Technol., Tehran ; Riahy, G.H.

Since year 2000, the increase of the installed wind energy capacity all over the world (mainly in Europe and United States) attracted the attention of electricity companies, wind farm promoters and researchers towards the short term prediction, mainly motivated by the necessity of integration into the grid of an increasing dasiaunknownpsila (fluctuating) amount of wind power. Besides, in a deregulated system, the ability to trade efficiently, make the best use of transmission line capability and address concerns with system frequency, accurate very short-term forecasts are motivated more than ever. In this study, very short term wind speed forecasting is developed utilizing artificial neural networks (ANN) in conjunction with Markov chain approach. Artificial neural networks predict short term values and the results are modified according to the long term patterns due to applying Markov chain. For verification purposes, the integrated proposed method is compared with ANN. The results show the effectiveness of the integrated method.

Published in:

Electric Power Conference, 2008. EPEC 2008. IEEE Canada

Date of Conference:

6-7 Oct. 2008