Wind Power Forecasting Based on the BP Neural Network
Jiandong Mao, Xiaojing Zhang, Juan Li
Available Online April 2013.
- https://doi.org/10.2991/icsem.2013.3How to use a DOI?
- wind power, BP neural network, short-term forecast
- 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.
- 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 SP - 13 EP - 17 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 -