Artículo

Fault Detection Method based on Artificial Neural Network for 330kV Nigerian Transmission Line

Resumen

This research focused on identifying various types of faults occurring on 330kV transmission lines through the use of artificial neural networks (ANN). A MATLAB model for the Gwagwalada-Katampe 330kV transmission line in Nigeria was implemented to generate fault datasets. Voltage and current fault parameters were utilized to train and simulate the ANN network architecture selected for each stage of fault detection. Four types of faults were considered, along with a fifth condition representing no fault. The results illustrated the success of the developed model in identifying various fault conditions and system parameters on the Gwagwalada-Katampe 330kV transmission line, modelled using MATLAB Simulink.
Herrera, Claudio Díaz (57200793587); Díaz, Emilio Moyano (58418447500)
Bibliometrics and semantics in XXI century Chilean social science journals; [Bibliometría y semântica em revistas de ciências sociales chilenas del siglo XXI]
2023
10.5209/rgid.89226
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163831993&doi=10.5209%2frgid.89226&partnerID=40&md5=bb91170f872406e2cf2e48f5dbaf538b
Universidad Católica del Maule, Facultad de Ciencias Sociales y Económicas, Departamento de Ciencias Sociales, Escuela de Trabajo Social, Chile; Universidad de Talca, Facultad de Psicología, Campus Talca, Chile
All Open Access; Gold Open Access
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