Automatic fault diagnostic methodology in primary feeders of spot networkdistribution system. / Metodologia de diagnóstico automático de falhas de curto-circuito em alimentadores primários de sistemas de distribuição reticulados tipo Spot.

AUTOR(ES)
DATA DE PUBLICAÇÃO

2006

RESUMO

This work presents the development of an automatic failure diagnostic methodology for low impedance short circuit in mid voltage feeders of distribution spot networks systems. The developed methodology has the feature to identify the type of short circuit and its location. An Artificial Neural Network technique was employed. The parameters used to train the Artificial Neural Networks are obtained based upon patterns in simulations of real cases for short circuit behavior in mono-phase, bi-phase and tri-phase to ground configuration. The input data for the simulation was based on a real distribution circuit belonging to the Power Utility CEB located in Brasília-Brazil. The simulation program ATP (Alternative Transient Program) was used to obtain the electric behavior of the circuit in the distribution network. As for the Artificial Neural Network simulation, trainings and tests Matlab was employed. As a main contribution the results of this work shows the technical feasibility to apply such methodology as a important real time diagnostic tool to support the system operation and maintenance departments of power utilities that uses spot network topologies. Furthermore, it is presented the possibilities to continue this research related to automatic diagnostics for network distribution systems based on Artificial Neural Networks technique.

ASSUNTO(S)

sistemas reticulados diagnóstico de falhas redes neurais artificiais localização de curto circuito fault diagnostic sistemas elétricos de distribuição electric distribution system fault location artificial neural networks spot network

ACESSO AO ARTIGO

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