A survey of time-series prediction for digitally enabled maintenance of electrical grids

H Mirshekali, AQ Santos, HR Shaker - Energies, 2023 - mdpi.com
The maintenance of electrical grids is crucial for improving their reliability, performance, and
cost-effectiveness. It involves employing various strategies to ensure smooth operation and …

Machine learning-based fault location for smart distribution networks equipped with micro-PMU

H Mirshekali, R Dashti, A Keshavarz, HR Shaker - Sensors, 2022 - mdpi.com
Faults in distribution networks occur unpredictably, causing a threat to public safety and
resulting in power outages. Automated, efficient, and precise detection of faulty sections …

Deep learning-based fault classification and location for underground power cable of nuclear facilities

A Said, S Hashima, MM Fouda, MH Saad - Ieee Access, 2022 - ieeexplore.ieee.org
Worldwide, Nuclear Power Plants (NPPs) must have higher security protection and precise
fault detection systems, especially underground power cable faults, to avoid causing …

[HTML][HTML] Deep learning-based fault location framework in power distribution grids employing convolutional neural network based on capsule network

H Mirshekali, A Keshavarz, R Dashti, S Hafezi… - Electric Power Systems …, 2023 - Elsevier
Power distribution grids (PDGs) are one of the main parts of electrical logistic chains with the
task of transferring electricity to the consumers continually. Adverse weather conditions …

[HTML][HTML] Fault classification and location of a PMU-equipped active distribution network using deep convolution neural network (CNN)

MNI Siddique, M Shafiullah, S Mekhilef, H Pota… - Electric Power Systems …, 2024 - Elsevier
Accurate fault detection and localization play a pivotal role in the reliable and optimal
operation of electric power distribution networks. However, the integration of intermittent …

Machine learning-based fault diagnosis for research nuclear reactor medium voltage power cables in fraction Fourier domain

MH Saad, A Said - Electrical Engineering, 2023 - Springer
Abstract Fault diagnosis of Medium Voltage power Cables (MVCs) research nuclear reactor,
incredibly inaccessible/remote ones, has to be carefully identified, located, and fixed within a …

Identification of transmission line voltage sag sources based on multi‐location information convolutional transformer

Q Li, C Zheng, S Liu, S Dai, B Zhang… - IET Renewable …, 2024 - Wiley Online Library
Conventional methods for identifying voltage sag sources are difficult to categorize
accurately due to the complexity of transmission lines and the influence of noise. In order to …

Deep LSTM-RBM Framework for Fault Location and Classification in Power Distribution Networks

M Khodayar, AF Bavil… - 2024 IEEE Power & …, 2024 - ieeexplore.ieee.org
This paper introduces a novel deep learning-based framework for accurate fault localization
and classification in power distribution systems. The proposed approach combines a long …

The Application of Machine Learning and Deep Learning Techniques for Event Classification in Power Systems

MR Shadi, H Gharibi, MR Ebrahimi - … in the Operation and Control of …, 2024 - Springer
Maintaining stability and providing an uninterrupted supply of customers' demands are
crucial aspects of power systems. With the expansion of electrical networks, the complexity …

Protection and Communication Techniques in Modern Power Systems

K Kauhaniemi - Energies, 2023 - mdpi.com
The protection systems of modern grids are facing new challenges and opportunities due to
the development of future Smart Grids. The complexity of the system increases when the …