AC microgrids are being expanded due to their numerous advantages. However, the
execution of distributed energy resources near by the demand side may cause various …

The signal of rotating machinery is usually non-stationary, non-linear, and with noise
interference. The early fault signal is too weak to extract fault features and the accuracy …

A novel intelligent scheme using the wavelet packet transform (WPT) and extreme learning
machine (ELM) is proposed for fault event classification in the grid-connected photovoltaic …

Arc fault diagnosis methods based on traditional machine learning rely heavily on expert-
designed characteristics and are difficult to train models with strong generalization. Deep …

Unsafe electrical appliances can be hazardous to humans and can cause electrical fires if
not monitored, analyzed, and controlled. The purpose of this study is to monitor the system's …

Low level current and similarity of High Impedance Faults (HIF) in respect of characteristics
to other transient events have posed a critical challenge to the protection of distribution …

The dependence of high-impedance faults (HIFs) detection methods on a large amount of
training data has always been a fundamental problem in electrical distribution systems. This …

This work proposes a new algorithm to classify high impedance faults (HIFs) in distribution
systems. HIFs can be represented by small current magnitudes with non-linear variations …

This paper presents an evaluation of the impacts of simulation models for high impedance
faults detection in microgrids with distributed generators interfaced by voltage source …

Arc grounding faults commonly occur in power grids, causing extensive power outages and
significant economic losses. In this paper, we propose a novel method for detecting arc …