Title: SVM-based prediction method for icing process of overhead power lines

Authors: Peng Li; Qi-mao Li; Wen-Ping Ren; Min Cao

Addresses: School of Information Science and Engineering, Yunnan University, Kunming, 650091, China ' School of Information Science and Engineering, Yunnan University, Kunming, 650091, China ' School of Information Science and Engineering, Yunnan University, Kunming, 650091, China ' Yunnan Electric Power Research Institute, South Power Grid Corp., Kunming, Yunnan Province, China

Abstract: The icing of overhead transmission lines is a serious problem for the safety of power grid. A method based on support vector machine (SVM) is presented here to predict the icing load of power transmission line, which utilises the history meteorology data from the icing monitoring system, and takes account of time effects of meteorology factors. According to the results of simulation, the prediction of icing load on the power lines in Northeast of Yunnan province is close to the actual value and the ability of generalisation is better than the model based on BPNN.

Keywords: overhead power lines; icing load prediction; support vector machines; SVM; modelling; power grid; safety; historical data; meteorological data; icing monitoring; time effects; simulation.

DOI: 10.1504/IJMIC.2015.070646

International Journal of Modelling, Identification and Control, 2015 Vol.23 No.4, pp.362 - 370

Available online: 15 Jul 2015 *

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