A Novel Machine Learning-Based Approach for Fault Detection and Location in Low-Voltage DC Microgrids

S Salehimehr, SM Miraftabzadeh, M Brenna - Sustainability, 2024 - mdpi.com
DC microgrids have gained significant attention in recent years due to their potential to
enhance energy efficiency, integrate renewable energy sources, and improve the resilience …

[HTML][HTML] A Deep Reinforcement Learning Optimization Method Considering Network Node Failures

X Ding, X Liao, W Cui, X Meng, R Liu, Q Ye, D Li - Energies, 2024 - mdpi.com
Nowadays, the microgrid system is characterized by a diversification of power factors and a
complex network structure. Existing studies on microgrid fault diagnosis and troubleshooting …

Detect, classify, and locate faults in DC microgrids based on support vector machines and bagged trees in the machine learning approach.

MH Ibrahim, EA Badran, MH Abdel-Rahman - IEEE Access, 2024 - ieeexplore.ieee.org
The DC microgrids possess numerous pros, including enhanced reliability, increased
efficiency, and a less complicated control system. Further, they provide a simplified system …

Enhanced Fault Detection and Localization Strategy for High-Speed Protection in Medium-Voltage DC Distribution Networks Using Extended Kalman Filtering …

NA Larik, MS Li, QH Wu - IEEE Access, 2024 - ieeexplore.ieee.org
Conventional strategies are not effective in addressing the complex protection challenges in
medium-voltage DC distribution networks (MVDCDN). The main challenge in MVDCDN is …

An advanced graph algorithm-based protection strategy for detecting kilometric and cross-country faults in DC microgrid

SF Fathima, L Premalatha, P Yuvaraj - Heliyon, 2024 - cell.com
Low voltage DC microgrids (LVDC) are on rise, because of increase in usage of electronics-
based utility loads. However, the protection and safety aspects of these grids remain …

Ultra High-Speed Fault Diagnosis Scheme for DC Distribution Systems based on Discrete Median filter and Mathematical Morphology

F Mumtaz, TS Khan, M Alqahtani, HA Sher… - IEEE …, 2024 - ieeexplore.ieee.org
In the modern world, the growing presence of renewable energy power near the consumer
end makes DC distribution systems more attractive than traditional AC ones. However …

An effective data-driven machine learning hybrid approach for fault detection and classification in a standalone low-voltage DC microgrid

A Deb, AK Jain - Electrical Engineering, 2024 - Springer
DC microgrids are gaining more importance in maritime, aerospace, telecom, and isolated
power plants for heightened reliability, efficiency, and control. Yet, designing a protective …

Detection and classification of faults in DC microgrids utilising artificial neural network with bidirectional gated recurrent units

R Dalai, SC Swain - International Journal of Power …, 2025 - inderscienceonline.com
This paper proposes a fault detection and classification method for DC-MG. This paper aims
to identify and categorise errors with increased precision. In order to improve the detection …

Study on Instability Mechanism and Compensation Strategy for Distributed Energy Storage Systems.

Y Ning, H Lin, X Wan, Y Huang, Z Yang… - Electronics (2079 …, 2024 - search.ebscohost.com
Distributed energy storage systems (DESSs), which would become key components in a
new power system, can flexibly deliver peak load shaving and demand management. With …

Providing a fault detection method for the occurrence of faults in DC microgrids, distributed generations, and electrical vehicles

A Sistani, SA Hosseini, VS Sadeghi… - AUT Journal of Electrical …, 2024 - eej.aut.ac.ir
DC microgrids have emerged as a promising solution to provide reliable and efficient power
for various applications. However, similar to any power system, DC microgrids are prone to …