Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

Short-term wind power prediction based on time series analysis model

Authors
Xiaodan Wu, Wenying Liu, Ningbo Wang, Yanhong Ma
Corresponding Author
Xiaodan Wu
Available Online March 2013.
DOI
10.2991/iccsee.2013.111How to use a DOI?
Keywords
wind power, power forecast, time series method
Abstract

In this paper, three kinds of prediction models based on time series analysis method are studied. Largely the process of building the wind farm short-term power forecasting model is discussed, mainly including sequence preprocessing, model identification, model order judging, parameter estimation, model testing and so on. It focuses on wind power short-term generation forecasting combined with the specific example using time series method. The example demonstrates the effectiveness and usefulness of the model.

Copyright
© 2013, 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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Volume Title
Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
Series
Advances in Intelligent Systems Research
Publication Date
March 2013
ISBN
978-90-78677-61-1
ISSN
1951-6851
DOI
10.2991/iccsee.2013.111How to use a DOI?
Copyright
© 2013, 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/).

Cite this article

TY  - CONF
AU  - Xiaodan Wu
AU  - Wenying Liu
AU  - Ningbo Wang
AU  - Yanhong Ma
PY  - 2013/03
DA  - 2013/03
TI  - Short-term wind power prediction based on time series analysis model
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 434
EP  - 436
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.111
DO  - 10.2991/iccsee.2013.111
ID  - Wu2013/03
ER  -