Classification of fault analysis of HVDC systems using artificial neural network

This paper presents the identification and classification of different faults that can occur in a LCC-HVDC system, with the help of artificial neural network (ANN) training algorithm technique. In particular, single-line to ground, double-line to ground, line-line, HVDC transmission line (dc link) and load side inverter faults are examined. A complete model of a 12-pulse LCC-HVDC system together with an ANN algorithm is modeled in numerical simulation software. The output of the ANN can predict the change in appropriate firing angle required for the HVDC rectifier unit under steady state normal operation and various fault conditions. A set of simulation results are provided to show the effectiveness of the ANN technique subjected to developed fault conditions.