Proceedings of the Third International Conference on Control, Automation and Systems Engineering (CASE-13)

Real-Time Prediction of the Wind Power Based on Improved Sustainable Model

Authors
Yang Mao, Yunpeng Jia
Corresponding Author
Yang Mao
Available Online August 2013.
DOI
https://doi.org/10.2991/case-13.2013.29How to use a DOI?
Keywords
time series models; sustainable model; real-time prediction; evaluation of prediction
Abstract
Accurate prediction of wind power is an effective technology to achieve the large-scale utilization of wind energy. This article conducts in-depth research on real-time prediction of wind power based on the interim measures for the management of power prediction and prediction of wind farm published by the National Energy Board. It begins with an analysis of several typical prediction methods on single step, and gives the recommended modeling domain length, and puts forward the improved sustainable model which combines a time series model with sustainable model. We conduct several real-time predictions under different conditions with the data of wind power measured in a wind farm in Northeast China, evaluate different models combined with the corresponding marks in the files published by the National Energy Board. It proves that the improved sustainable method can improve the accuracy of prediction effectively.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
Third International Conference on Control, Automation and Systems Engineering (CASE-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
August 2013
ISBN
978-90786-77-81-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/case-13.2013.29How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yang Mao
AU  - Yunpeng Jia
PY  - 2013/08
DA  - 2013/08
TI  - Real-Time Prediction of the Wind Power Based on Improved Sustainable Model
BT  - Third International Conference on Control, Automation and Systems Engineering (CASE-13)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/case-13.2013.29
DO  - https://doi.org/10.2991/case-13.2013.29
ID  - Mao2013/08
ER  -