Very Short-Term Wind Power Forecasting Based on SVM-Markov

DOI

10.2991/aeece-15.2015.27How to use a DOI?

Keywords

Very short-term forecasting; SVM; Markov chain model; the confidence interval.

Abstract

Very short-term forecasting of wind power is important to scheduling staff’s planning and wind turbine control. This paper has established a combined forecasting model based on Markov chain and support vector machine (SVM). Firstly, the SVM is used to model for wind power. Then, transition probability matrix is made based on Markov chain to modify for SVM prediction. Finally, the prediction confidence interval of combination forecasting model is given by method of fluctuation confidence interval. Verified by an example of a wind farm indicating that the combination forecasting model is better than a single SVM model on a variety of error indicators.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shunhui Jiang
AU  - Ruiming Fang
AU  - Li Wang
AU  - Changqing Peng
PY  - 2015/09
DA  - 2015/09
TI  - Very Short-Term Wind Power Forecasting Based on SVM-Markov
BT  - Proceedings of the International Conference on Advances in Energy, Environment and Chemical Engineering
PB  - Atlantis Press
SP  - 130
EP  - 134
SN  - 2352-5401
UR  - https://doi.org/10.2991/aeece-15.2015.27
DO  - 10.2991/aeece-15.2015.27
ID  - Jiang2015/09
ER  -