This paper focuses on a powerful and comprehensive overview of Deep Learning (DL)
techniques on Distribution Automation System (DAS) applications to provide a complete …

One of the many issues with the availability of usable power is constant faults in power
distribution network (PDN). Fault in distribution network is an anomaly situation that prevents …

Early detection of electrical faults is a very essential research area due to its positive
influence on network stability and customer satisfaction. Despite of the electrical fault …

This study proposes a new method for detecting and classifying faults in distribution lines.
The physical principle of classification is based on time-domain pulse reflectometry (TDR) …

Power outage prediction and fault detection play crucial roles in ensuring the reliability and
stability of electrical power systems. Traditional methods for predicting power outages and …

Faults are becoming more common as the number of transmission lines grows
progressively. The detection of faults must be quick and precise to do the least amount of …

Artificial intelligence (AI) plays a key role in the distribution automation system (DAS). By
using artificial intelligence technology, it is possible to intelligently verify and monitor …

Faults in transmission lines cause instability of power system and result in degrading end
users sophisticated equipment. Therefore, in case of fault and for the quick restoration of …

Shipboard microgrids (SMGs) have played a significant role in the concept of all-electric
ships (AES), with increasing power demand from loads during operation. The system …

This paper introduces a performance comparison of deep-learning and fuzzy-logic
algorithms for power system fault detection. The interconnected IEEE 14-bus transmission …