Icing of transmission line has seriously impacted on the safe operation of power grid. Therefore, after analyzing meteorological factors which influence icing thickness, we proposed to construct an icing thickness prediction model based on a 3-layer BP neural network in this article. In order to solve problems that BP neural network converges slowly and is prone to local minimum values, the prediction speed and accuracy have been increased by using improved fruit fly algorithm to optimize BP neural network. Taking icing historical data on 500kV transmission line of Shenxin Line I in China as an example, the rationality and accuracy of this model have been proved, and the analyzing results could be provided to instruct the operation and maintenance of transmission lines.
Transmission lines, icing, BP neural network, fruit fly algorithm
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