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Artificial intelligence techniques in smart grid: A survey
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 …
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
Smartgrid is a paradigm that was introduced into the conventional electricity network to
enhance the way generation, transmission, and distribution networks interrelate. It involves …
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
Precise charging time prediction can effectively mitigate the inconvenience to drivers
induced by inevitable charging behavior throughout trips. Although the effectiveness of the …
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 …
development of smart grids, power quality disturbance detection and classification holds …
Fault detection through discrete wavelet transform in overhead power transmission lines
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 …
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 …
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)
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 …
operation of electric power distribution networks. However, the integration of intermittent …
Machine learning tools for active distribution grid fault diagnosis
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 …
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
This paper presents a novel framework for classifying ongoing conditions in centrifugal
pumps based on signal processing and deep learning techniques. First, vibration signals …
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
This article focuses on the local demagnetization fault recognition research of permanent
magnet synchronous linear motor (PMSLM) and realizes the accurate identification of the …
magnet synchronous linear motor (PMSLM) and realizes the accurate identification of the …