Artificial intelligence techniques in smart grid: A survey

OA Omitaomu, H Niu - Smart Cities, 2021 - mdpi.com
The smart grid is enabling the collection of massive amounts of high-dimensional and multi-
type data about the electric power grid operations, by integrating advanced metering …

Integrating artificial intelligence Internet of Things and 5G for next-generation smartgrid: A survey of trends challenges and prospect

E Esenogho, K Djouani, AM Kurien - Ieee Access, 2022 - ieeexplore.ieee.org
Smartgrid is a paradigm that was introduced into the conventional electricity network to
enhance the way generation, transmission, and distribution networks interrelate. It involves …

Grey wolf optimizer-based machine learning algorithm to predict electric vehicle charging duration time

I Ullah, K Liu, T Yamamoto, M Shafiullah… - Transportation …, 2023 - Taylor & Francis
Precise charging time prediction can effectively mitigate the inconvenience to drivers
induced by inevitable charging behavior throughout trips. Although the effectiveness of the …

A critical and comprehensive review on power quality disturbance detection and classification

P Khetarpal, MM Tripathi - Sustainable Computing: Informatics and …, 2020 - Elsevier
With an elevating demand and use of power electronics equipment, green energy and the
development of smart grids, power quality disturbance detection and classification holds …

Fault detection through discrete wavelet transform in overhead power transmission lines

N Ahmed, AA Hashmani, S Khokhar… - Energy Science & …, 2023 - Wiley Online Library
Transmission lines are a very important and vulnerable part of the power system. Power
supply to the consumers depends on the fault‐free status of transmission lines. If the normal …

An identification method for anomaly types of active distribution network based on data mining

S Wang, T Lu, R Hao, F Wang, T Ding… - … on Power Systems, 2023 - ieeexplore.ieee.org
With the increasing penetration of distributed generators (DGs) and the growing demand for
reliable power sources, it has become imperative to promptly identify anomalies in active …

[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 tools for active distribution grid fault diagnosis

M Shafiullah, KA AlShumayri, MS Alam - Advances in engineering software, 2022 - Elsevier
Faults in power distribution networks cause customer minute and economic losses. A crucial
part of the protection system of such grids is effective fault diagnosis for the acceleration of …

Centrifugal Pump Fault Diagnosis Based on a Novel SobelEdge Scalogram and CNN

W Zaman, Z Ahmad, MF Siddique, N Ullah, JM Kim - Sensors, 2023 - mdpi.com
This paper presents a novel framework for classifying ongoing conditions in centrifugal
pumps based on signal processing and deep learning techniques. First, vibration signals …

Local demagnetization fault recognition of permanent magnet synchronous linear motor based on S-transform and PSO–LSSVM

X Song, J Zhao, J Song, F Dong, L Xu… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This article focuses on the local demagnetization fault recognition research of permanent
magnet synchronous linear motor (PMSLM) and realizes the accurate identification of the …