The modelling of low voltage arc flash based on artificial neural network

Dimas Anton Asfani*, Abdillah Fashiha Ilman, Nugroho Wisnu Ari Sanjaya, I. Made Yulistya Negara, Daniar Fahmi, Dian Retno Sawitri, Mochammad Wahyudi, Hadi Lizikri Al-Azmi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


This paper dealt with a dynamic modelling of arc flash phenomenon in low voltage installation system based on artificial neural network (ANN). There were two ANN models employed to this proposed model. The first one is dynamic resistance model and the second one is switch or short circuit contact model. The arc flash energy and the number of filaments are defined as the inputs of these ANN models, whereas the targets are the resistance value for dynamic resistance model and the switch value for switch model. The values used in modelling are obtained from experiment of arc flash initiated by phase to neutral short circuit. This fault location is parallel with the resistive load. The feed-forward back-propagation is selected as an algorithm of ANN. The result shows that the proposed model presented the level of accuracy up to 96.7%. In addition, the simulated model revealed that the lower cable impedance is and the higher load is, the greater current peak is and the shorter duration of arc flash is.

Original languageEnglish
Pages (from-to)1389-1405
Number of pages17
JournalInternational Journal of Innovative Computing, Information and Control
Issue number4
Publication statusPublished - Aug 2018


  • Arc flash energy
  • Dynamic resistance
  • Feed-forward back-propagation neural network
  • Low voltage installation system
  • Parallel arc flash
  • Phase to neutral fault


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