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 …
An automatic identification framework for complex power quality disturbances based on multifusion convolutional neural network
Intelligent identification of multiple power quality (PQ) disturbances is very useful for
pollution control of power systems. In this paper, we propose a novel detection framework for …
pollution control of power systems. In this paper, we propose a novel detection framework for …
A new protection scheme for PV-wind based DC-ring microgrid by using modified multifractal detrended fluctuation analysis
This paper presents fault detection, classification, and location for a PV-Wind-based DC ring
microgrid in the MATLABI/SIMULINK platform. Initially, DC fault signals are collected from …
microgrid in the MATLABI/SIMULINK platform. Initially, DC fault signals are collected from …
An improved automated PQD classification method for distributed generators with hybrid SVM-based approach using un-decimated wavelet transform
Artificial intelligence (AI) approaches are usually coupled with the wavelet transform (WT) for
feature extraction to classify the power quality disturbances (PQDs). Therefore, selecting a …
feature extraction to classify the power quality disturbances (PQDs). Therefore, selecting a …
Power quality disturbances recognition using modified s transform and parallel stack sparse auto-encoder
The effective automatic recognition and classification of power quality (PQ) disturbance is of
significance to the control of power grid pollution before any reasonable solution is taken. In …
significance to the control of power grid pollution before any reasonable solution is taken. In …
Multiple power quality disturbances analysis in photovoltaic integrated direct current microgrid using adaptive morphological filter with deep learning algorithm
In this paper, an adaptive multiscale enhanced average combination morphological filter is
proposed to analyze voltage signals captured at the point of common coupling of the …
proposed to analyze voltage signals captured at the point of common coupling of the …
Boosting performance of power quality event identification with KL Divergence measure and standard deviation
Power quality event identification is widely recognized as one of the most interesting
problems in electric engineering. It consists of two sub-problems: detection and …
problems in electric engineering. It consists of two sub-problems: detection and …
Classification of Power Quality Disturbances using Artificial Intelligence: A Review
K Nandi, B Chatterjee, S Dalai - 2023 IEEE 3rd Applied Signal …, 2023 - ieeexplore.ieee.org
A detail review on the processes and methods of automatic classification of power quality
disturbances is presented in this paper. The development of artificial intelligence techniques …
disturbances is presented in this paper. The development of artificial intelligence techniques …
Hyperbolic window S-transform aided deep neural network model-based power quality monitoring framework in electrical power system
With the fast development of power grid the usage of electrical equipments is increased
which led to importance of power quality disturbance sensing for reliable and smooth …
which led to importance of power quality disturbance sensing for reliable and smooth …
Estimation of contamination level of overhead insulators based on surface leakage current employing detrended fluctuation analysis
This article proposes an advanced technique for condition assessment of outdoor insulators
based on its surface leakage current through employing detrended fluctuation analysis …
based on its surface leakage current through employing detrended fluctuation analysis …