Very short-term wind speed prediction: A new artificial neural network-Markov chain model

被引：148
|
作者：
Kani, S. A. Pourmousavi [1 ]
Ardehali, M. M. [2 ]
机构：
[1] Montana State Univ, Dept Elect & Comp Engn, Bozeman, MT 59717 USA
[2] Amirkabir Univ Technol, Dept Elect Engn, Energy Res Ctr, Tehran Polytech, Tehran 15914, Iran
来源：
ENERGY CONVERSION AND MANAGEMENT | 2011年 / 52卷 / 01期
关键词：
Artificial neural network; Markov chain approach; Very short-term prediction; Wind speed prediction; GENERATION; ANN;
D O I：
10.1016/j.enconman.2010.07.053
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
As the objective of this study, artificial neural network (ANN) and Markov chain (MC) are used to develop a new ANN-MC model for forecasting wind speed in very short-term time scale. For prediction of very short-term wind speed in a few seconds in the future, data patterns for short-term (about an hour) and very short-term (about minutes or seconds) recorded prior to current time are considered. In this study, the short-term patterns in wind speed data are captured by ANN and the long-term patterns are considered utilizing MC approach and four neighborhood indices. The results are validated and the effectiveness of the new ANN-MC model is demonstrated. It is found that the prediction errors can be decreased, while the uncertainty of the predictions and calculation time are reduced. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码：738 / 745
页数：8
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