Real-time smart grid monitoring is critical to enhancing resiliency and operational efficiency
of power equipment. Cloud-based and edge-based fault detection systems integrating deep …

This paper provides a systematic, comprehensive, up-to-date study of the various artificial
intelligence (AI) techniques on the detection and classification of faults on power …

Fault detection and protection of Superconducting Cables (SCs) is considered a challenging
task due to the effects of the quenching phenomenon of High Temperature Superconducting …

One of the most critical concerns in power system reliability is the timely and accurate
detection of transmission line faults. Therefore, accurate detection and localisation of these …

This study develops a hybrid method to identify, classify, and locate electrical faults on
transmission lines based on Machine Learning (ML) methods. Firstly, Wavelet Transform …

The Artificial Neural Network (ANN) has become popular in the past few years for its great
performance. It is suitable for the nonlinear nature of dynamic systems. The literature …

Fault detection continues to be a relevant and ongoing topic in multiterminal High Voltage
Direct Current (MT-HVDC) grid protection. In MT-HVDC grids, however, high DC-fault …

This paper presents tree-based machine learning techniques like decision trees, and
random forest algorithms to categorize various permanent faults such as a line to ground …

The wavelet transform has received great importance in the last years on the power system
analysis because the multi-resolution analysis presents proprieties good for the transient …

This research proposes a comparison study on different artificial intelligence (AI) methods
for classifying faults in hybrid transmission line systems. The 115-kV hybrid transmission line …