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

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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

Estimation of Single-Phase and Three-Phase Power-Quality Indices Using Empirical Wavelet Transform

TL;DR: In this paper, an empirical wavelet transform (EWT)-based time-frequency technique is proposed for the estimation of power-quality indices (PQIs), which first estimates the frequency components present in the distorted signal, computes the boundaries, and then filtering is done based on the boundaries computed.
Journal ArticleDOI

Classification of Power Quality Disturbances Due to Environmental Characteristics in Distributed Generation System

TL;DR: In this paper, the power quality disturbances in terms of statistical features are classified distinctly by use of modular probabilistic neural network (MPNN), support vector machines (SVMs), and least square support vector machine (LS-SVM) techniques.
Journal ArticleDOI

A review on performance of artificial intelligence and conventional method in mitigating PV grid-tied related power quality events

TL;DR: In this article, the authors investigate negative impacts of photovoltaic (PV) grid-tied system to the power networks, and study on performance of artificial intelligence (AI) and conventional methods in mitigating power quality event.
Journal ArticleDOI

PQ Monitoring System for Real-Time Detection and Classification of Disturbances in a Single-Phase Power System

TL;DR: The proposed combined approach identifies the type of disturbance and its parameters such as time localization, duration, and magnitude and is suitable for real-time monitoring of the power system and implementation on a digital signal processor (DSP).
Journal ArticleDOI

Performance Comparison of Variational Mode Decomposition over Empirical Wavelet Transform for the Classification of Power Quality Disturbances Using Support Vector Machine

TL;DR: In this article, the classification of power quality disturbances based on VMD (Variational Mode Decomposition) and EWT (Empirical Wavelet Transform) using SVM (Support Vector Machine) is done for producing feature vectors that can extract salient and unique nature of these disturbances.
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