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Open AccessJournal ArticleDOI

Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration

TLDR
A critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration is presented, to provide various concepts utilized for extraction of the features to detect and classify the P Q disturbances even in the noisy environment.
Abstract
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 quality (PQ) disturbances are found to be more predominant with RE penetration due to the variable outputs and interfacing converters. There is a need to recognize and mitigate PQ disturbances to supply clean power to the consumer. This article presents a critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration. The broad perspective of this review paper is to provide various concepts utilized for extraction of the features to detect and classify the PQ disturbances even in the noisy environment. More than 220 research publications have been critically reviewed, classified and listed for quick reference of the engineers, scientists and academicians working in the power quality area.

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Citations
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Journal ArticleDOI

Sustainable development of renewable energy integrated power sector: Trends, environmental impacts, and recent challenges.

TL;DR: In this article , the authors provide an up-to-date review of the most recent global trend of various renewable energy integrations into the power sector and discuss the role of RE integration in sustainable development.
Journal ArticleDOI

Near-Optimal PI Controllers of STATCOM for Efficient Hybrid Renewable Power System

TL;DR: In this paper, the static synchronous compensator (STATCOM) is considered for both improving the performance of a hybrid system, which contains WECS and photovoltaics (PVs) against wind gusts and maintaining the continuous operations of RESs during three-phase fault occur at the point of common coupling (PCC) between the RESs and the grid.
Journal ArticleDOI

A Critical Analysis of Methodologies for Detection and Classification of Power Quality Events in Smart Grid

TL;DR: In this paper, the authors present an exhaustive survey of detection and classification of power quality disturbances by discussing signal processing techniques and artificial intelligence tools with their respective pros and cons, with the viewpoint of the types of power input signal (synthetic/real/noisy), preprocessing tools, feature selection methods, artificial intelligence techniques and modes of operation (online/offline).
Journal ArticleDOI

A novel hybrid deep learning approach including combination of 1D power signals and 2D signal images for power quality disturbance classification

TL;DR: The proposed hybrid convolutional neural network method is a novel approach that covers the steps of an expert examining a signal and its classification performance is relatively high compared to other methods, the computational complexity is almost the same.
Proceedings ArticleDOI

Optimal feature and decision tree based classification of power quality disturbances in distributed generation systems

TL;DR: In this paper, the authors provided an improved power quality (PQ) disturbances classification, which were associated with load changes and environmental factors, by employing support vector machines (SVM) and decision tree classifiers.
References
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Journal ArticleDOI

Covariance analysis of voltage waveform signature for power-quality event classification

TL;DR: C covariance behavior of several features that are determined from the voltage waveform within a time window for power-quality event detection and classification is analyzed and it is observed that the feature vectors corresponding to power quality event instances can be efficiently classified according to the event type using a covariance based classifier known as the common vector classifier.
Journal ArticleDOI

A New Convolutional Network Structure for Power Quality Disturbance Identification and Classification in Micro-Grids

TL;DR: A comparison of the results obtained by the proposed method with those obtained by several other methods reveals that the proposed methods attains a higher accuracy, higher convergence speed and stronger generalization ability.
Journal ArticleDOI

Detection and Characterization of Oscillatory Transients Using Matching Pursuits With a Damped Sinusoidal Dictionary

TL;DR: In this paper, the authors proposed a reliable method based on matching pursuits for detecting and characterizing power system oscillatory transients, which is based on comparing a portion of the time-domain signal with the damped sinusoidal functions of a redundant dictionary.
Journal ArticleDOI

Real-time cross-correlation-based technique for detection and classification of power quality disturbances

TL;DR: In this paper, a novel technique for automated power quality (PQ) disturbance detection and classification in power distribution system using cross-correlation-based approach in conjunction with fuzzy logic is presented.
Journal ArticleDOI

Method for classification of PQ events based on discrete Gabor transform with FIR window and T2FK-based SVM and its experimental verification

TL;DR: Use of this hybrid approach decreased the extracted features size, so the execution time and total required memory were optimized for the classification section, and the overall accuracy of the proposed method was comparable to other methods and the accuracy evaluated under noisy conditions.
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