2nd International Conference On Systems Engineering and Modeling (ICSEM-13)

Wind Power Forecasting Based on the BP Neural Network

Authors
Jiandong Mao, Xiaojing Zhang, Juan Li
Corresponding Author
Jiandong Mao
Available Online April 2013.
DOI
https://doi.org/10.2991/icsem.2013.3How to use a DOI?
Keywords
wind power, BP neural network, short-term forecast
Abstract
Accurate short-term wind power forecasting has important significance to safety, stability and economy of power system dispatching and also it is a difficult problem in practical engineering application. In this paper, by use of the data of numerical weather forecast, such as wind speed, wind direction, temperature, relative humidity and pressure of atmosphere, a short-term wind power forecasting system based on BP neural network has been developed. For verifying the feasibility of the system, some experiments have been were carried out. The results show that the system is capable of predicting accurately the wind power of future 24 hours and the forecasting accuracy of 85.6% is obtained. The work of this paper has important engineering directive significance to the similar wind power forecasting system.
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Proceedings
2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
April 2013
ISBN
978-94-91216-42-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/icsem.2013.3How 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  - Jiandong Mao
AU  - Xiaojing Zhang
AU  - Juan Li
PY  - 2013/04
DA  - 2013/04
TI  - Wind Power Forecasting Based on the BP Neural Network
BT  - 2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.3
DO  - https://doi.org/10.2991/icsem.2013.3
ID  - Mao2013/04
ER  -