Abstract

A distinctive feature of a smart electrical network is the continuous monitoring of the state of overhead power lines (OHL). An important problem is the effective location of the damage to the OHL, as well as monitoring the external impact of the environment causing accidents. As the main factor that threatens the normal operation of the OHL, the risk of glaciation of the phase conductors, leading to their breakage, is considered. In order to minimize accidents in accordance with the geo-information approach to the analysis of reliability of electricity supply, the most dangerous sections of the lines are proposed to be performed on “smart” towers equipped with information and measuring equipment for detecting emergency modes by changed electromagnetic field of the OHL and also video registration of its sagging and deflections of the tower. An important feature of the “smart” tower is the use of the apparatus of artificial neural networks with the purpose of processing information about the current mode of the line and predicting its state. The combination of disparate sensing elements in a single information and measuring complex of a “smart” tower allows achieving a synergistic effect – increasing the reliability of the air line by simultaneously recording any potentially dangerous disturbances, as well as reducing the time spent on restoring the line after an accident.

Full Text
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