NDLI: Time series prediction for icing process of overhead power transmission line based on BP neural networks

Content Provider	IEEE Xplore Digital Library
Author	Li Peng Li Qimao Cao Min Gao Shangfei Huang Haiyan
Copyright Year	2011
Description	Author affiliation: School of Information Science and Engineering, Yunnan University, Kunming 650091, China (Li Peng; Li Qimao) \|\| School of Urban Construction and Management, Yunnan University, Kunming 650091, China (Huang Haiyan) \|\| Yunnan Electric Power Research Institute, Kunming 650051, China (Cao Min; Gao Shangfei)
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.
Starting Page	5315
Ending Page	5318
File Size	133748
Page Count	4
File Format	PDF
ISBN	9781457706776
ISSN	21612927
e-ISBN	9789881725592
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Assoc of Automati
Subject Keyword	Training Power transmission lines Bp Neural Networks Prediction Model Time series analysis Predictive models Time Series Data models Transmission Line Icing Load modeling Meteorology
Content Type	Text
Resource Type	Article

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Time series prediction for icing process of overhead power transmission line based on BP neural networks