DocumentCode :
551221
Title :
Time series prediction for icing process of overhead power transmission line based on BP neural networks
Author :
Li Peng ; Li Qimao ; Cao Min ; Gao Shangfei ; Huang Haiyan
Author_Institution :
Sch. of Inf. Sci. & Eng., Yunnan Univ., Kunming, China
fYear :
2011
fDate :
22-24 July 2011
Firstpage :
5315
Lastpage :
5318
Abstract :
Monitoring and prediction icing load of overhead power transmission lines are important problems for the reliability of power grid. A method based on BP neural networks is presented here to predict the time series of icing load for transmission line, which is complexity, nonlinear and fitful, not easy to find the mechanism model for prediction. According to the results of simulation, this model has a good accuracy of prediction whether in the same icing process or in the different.
Keywords :
backpropagation; neural nets; power engineering computing; power grids; power overhead lines; power transmission reliability; time series; BP neural networks; icing load monitoring; icing load prediction; icing process; mechanism model; overhead power transmission line; power grid reliability; time series prediction; Data models; Load modeling; Meteorology; Power transmission lines; Predictive models; Time series analysis; Training; Bp Neural Networks; Prediction Model; Time Series; Transmission Line Icing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
ISSN :
1934-1768
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
Type :
conf
Filename :
6001566
Link To Document :
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