Remote monitoring of short circuits situations in a power distribution system via artificial neural networks

Abstract

The growing concern with energy efficiency, automation and integration of processes in the present scenario has been characterized by a considerable increase in the number of sensitive equipment and prone to generate quality problems of electricity. Thus, it is essential to ensure the supply of electricity within the quality standards that can only be ensured through effective and continuous monitoring of the quantities of interest, among which the three-phase voltage of the distribution system on several points. In this context, this work presents an alternative method of remote monitoring using artificial neural networks to estimate the values of the three-phase voltages in various parts of SD, taking into account different load profiles that the system can come forward. Obtaining these networks is made possible by modeling the real distribution system to provide the necessary data for training and validation of the results obtained during the search.