Comprehensive review on detection and classification of power quality disturbances in utility grid with renewable energy penetration
The global concern with power quality is increasing due to the penetration of renewable
energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power …
energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power …
Classification of complex power quality disturbances using optimized S-transform and kernel SVM
Accurate power quality disturbance (PQD) classification is significantly important for power
grid pollution control. However, the use of nonlinear loads makes power system signals …
grid pollution control. However, the use of nonlinear loads makes power system signals …
A classification method for multiple power quality disturbances using EWT based adaptive filtering and multiclass SVM
This paper presents an automated recognition approach for the classification of power
quality (PQ) disturbances based on adaptive filtering and a multiclass support vector …
quality (PQ) disturbances based on adaptive filtering and a multiclass support vector …
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 modified S-transform and random forests-based power quality assessment framework
The proposed work aims at the accurate detection and classification of various single and
multiple power quality (PQ) disturbances. To this end, a modified optimal fast discrete …
multiple power quality (PQ) disturbances. To this end, a modified optimal fast discrete …
Automatic power quality events recognition based on Hilbert Huang transform and weighted bidirectional extreme learning machine
In this paper, Hilbert Huang transform (HHT) and weighted bidirectional extreme learning
machine (WBELM) are integrated to detect and classify power quality events (PQEs) in real …
machine (WBELM) are integrated to detect and classify power quality events (PQEs) in real …
Power quality disturbance classification under noisy conditions using adaptive wavelet threshold and DBN-ELM hybrid model
Y Gao, Y Li, Y Zhu, C Wu, D Gu - Electric power systems research, 2022 - Elsevier
To solve the problems of noise interference and artificial feature extraction in power quality
disturbance (PQD) classification, a new method combining adaptive wavelet threshold …
disturbance (PQD) classification, a new method combining adaptive wavelet threshold …
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 …
FPGA-based online power quality disturbances monitoring using reduced-sample HHT and class-specific weighted RVFLN
This paper proposes a new signal segmentation method, reduced-sample empirical mode
decomposition, to extract the highly correlated monocomponent mode of oscillations. The …
decomposition, to extract the highly correlated monocomponent mode of oscillations. The …
Optimal feature selection via NSGA-II for power quality disturbances classification
This paper presents an application of nondominated sorting genetic algorithm II (NSGA-II)
for multiobjective feature selection in power quality disturbances classification. Classification …
for multiobjective feature selection in power quality disturbances classification. Classification …