Wind Power Forecasting Based on the BP Neural Network

DOI

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.

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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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  - Proceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)
PB  - Atlantis Press
SP  - 13
EP  - 17
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.3
DO  - 10.2991/icsem.2013.3
ID  - Mao2013/04
ER  -