Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration
TL;DR: 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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TL;DR: A fast protection algorithm based on Hilbert-Huang transform (HHT) is proposed in this article for islanding and fault detection, classification, and location in a distribution system penetrated by a solar renewable energy source.
9 citations
TL;DR: A novel hybrid method based on Stockwell transform (ST) and deep learning is proposed to detect and classify multiple PQDs (MPQDs) and it is compared with other existing methods to demonstrate its robustness under noisy environments.
Abstract: With the widespread access of nonlinear loads, enterprises and consumers are faced with the problem of power quality disturbance (PQD) in the grid. The detection and classification of multiple PQDs are considered to be a challenging task. In this article, a novel hybrid method based on Stockwell transform (ST) and deep learning is proposed to detect and classify multiple PQDs (MPQDs). Compared with previous cases where only single or dual PQDs are considered, this article fully considers the existence of MPQDs compounds in real situations and designs a more general and automated approach based on deep learning for automated feature selection and classification. First, the S-transform is used to extract the features of the 1-D signal and take the modulus of the result to obtain the ST matrix of the signal. In order to improve the antinoise performance of the system, the parameters for generating the time–frequency-domain contour are optimized, so that contour images with less noise can be drawn. Second, the above images are fed into the designed convolutional neural network (CNN) for training. A total of 37 PQDs detection and classification tasks including single and multiple disturbances were completed. It is compared with other existing methods to demonstrate its robustness under noisy environments. Finally, an experimental platform for MPQDs was built to verify the proposed method, and the results demonstrated that the method can effectively detect and classify MPQDS.
8 citations
TL;DR: In this paper, the recurrent wavelet fuzzy neural network (RWFNN)-based controller for the DVR is developed and, with positive-sequence voltage analysis, the reference signal for theDVR compensation can be accurately obtained.
Abstract: Dynamic voltage restorers (DVRs) are one of the effective solutions to regulate the voltage of power systems and protect sensitive loads against voltage disturbances, such as voltage sags, voltage fluctuations, et cetera. The performance of voltage compensation with DVRs relies on the robustness to the power quality disturbances and rapid detection of voltage disturbances. In this paper, the recurrent wavelet fuzzy neural network (RWFNN)-based controller for the DVR is developed. With positive-sequence voltage analysis, the reference signal for the DVR compensation can be accurately obtained. In order to enhance the response time for the DVR controller, the RWFNN is introduced due to the merits of rapid convergence and superior dynamic modeling behavior. From the experimental results with the OPAL-RT real-time simulator (OP4510, OPAL-RT Technologies Inc., Montreal, Quebec, Canada), the effectiveness of proposed controller can be verified.
8 citations
TL;DR: In this paper , the authors present the issues in the power quality of a variable speed wind farm synchronous generator located at Tamilnadu (India), according to IEC 61,400,21, power quality events such as voltage fluctuation, harmonics and flicker are measured by power quality analysers connected at the selected locations in the wind farm.
7 citations
TL;DR: In this article , the typical sources of generation of harmonics, their deleterious effects, available standards, and detection techniques for both grid-connected and islanded microgrids have been discussed in detail.
Abstract: A generational shift has led to the evolution of distributed generation (DG) and microgrids. The loads connected in a microgrid can be both linear and nonlinear. Nonlinear loads deteriorate the power quality by drawing harmonic currents. Drawing of nonlinear currents will make the voltage waveform nonsinusoidal, which may prove harmful for other loads connected to the system. Previously, passive and active filters were used to mitigate harmonics, but they are expensive and bulky. The state of the art is to exploit multifunctional capabilities of inverter-interfaced DGs to deal with the power quality issues. This article presents the typical sources of generation of the harmonics, their deleterious effects, available standards, and detection techniques. Harmonic mitigation strategies for both grid-connected and islanded microgrids have been discussed in detail. The aim is to review and categorize the various strategies adopted by authors in recent times to mitigate harmonics and bring out the research gaps so that further avenues can be explored in this area.
7 citations
References
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3,156 citations
"Comprehensive Review on Detection a..." refers background in this paper
...Fourier Transform (FT) has proved itself as a magical mathematical tool that breaks a function or signal into an alternate representation, characterized by sine and cosines [40]....
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Journal Article•
TL;DR: The S transform as discussed by the authors is an extension to the ideas of the Gabor transform and the Wavelet transform, based on a moving and scalable localising Gaussian window and is shown here to have characteristics that are superior to either of the transforms.
Abstract: The S transform, an extension to the ideas of the Gabor transform and the Wavelet transform, is based on a moving and scalable localising Gaussian window and is shown here to have characteristics that are superior to either of the transforms. The S transform is fully convertible both forward and inverse from the time domain to the 2-D frequency translation (time) domain and to the familiar Fourier frequency domain. Parallel to the translation (time) axis, the S transform collapses as the Fourier transform. The amplitude frequency-time spectrum and the phase frequency-time spectrum are both useful in defining local spectral characteristics. The superior properties of the S transform are due to the fact that the modulating sinusoids are fixed with respect to the time axis while the localising scalable Gaussian window dilates and translates. As a result, the phase spectrum is absolute in the sense that it is always referred to the origin of the time axis, the fixed reference point. The real and imaginary spectrum can be localised independently with a resolution in time corresponding to the period of the basis functions in question. Changes in the absolute phase ofa constituent frequency can be followed along the time axis and useful information can be extracted. An analysis of a sum of two oppositely progressing chirp signals provides a spectacular example of the power of the S transform. Other examples of the applications of the Stransform to synthetic as well as real data are provided.
2,323 citations
TL;DR: A survey on theoretical results on ant colony optimization, which highlights some open questions with a certain interest of being solved in the near future and discusses relations between ant colonies optimization algorithms and other approximate methods for optimization.
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TL;DR: In this paper, the authors present how renewable energy resources are currently being used, scientific developments to improve their use, their future prospects, and their deployment, and represent the impact of power electronics and smart grid technologies that can enable the proportionate share of renewable resources.
Abstract: Electric energy security is essential, yet the high cost and limited sources of fossil fuels, in addition to the need to reduce greenhouse gasses emission, have made renewable resources attractive in world energy-based economies. The potential for renewable energy resources is enormous because they can, in principle, exponentially exceed the world׳s energy demand; therefore, these types of resources will have a significant share in the future global energy portfolio, much of which is now concentrating on advancing their pool of renewable energy resources. Accordingly, this paper presents how renewable energy resources are currently being used, scientific developments to improve their use, their future prospects, and their deployment. Additionally, the paper represents the impact of power electronics and smart grid technologies that can enable the proportionate share of renewable energy resources.
1,990 citations
"Comprehensive Review on Detection a..." refers background in this paper
...Over 220 publications [1]–[222] are critically reviewed in this manuscript and it comprises six sections....
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TL;DR: This work presents a comprehensive survey of the advances with ABC and its applications and it is hoped that this survey would be very beneficial for the researchers studying on SI, particularly ABC algorithm.
Abstract: Swarm intelligence (SI) is briefly defined as the collective behaviour of decentralized and self-organized swarms. The well known examples for these swarms are bird flocks, fish schools and the colony of social insects such as termites, ants and bees. In 1990s, especially two approaches based on ant colony and on fish schooling/bird flocking introduced have highly attracted the interest of researchers. Although the self-organization features are required by SI are strongly and clearly seen in honey bee colonies, unfortunately the researchers have recently started to be interested in the behaviour of these swarm systems to describe new intelligent approaches, especially from the beginning of 2000s. During a decade, several algorithms have been developed depending on different intelligent behaviours of honey bee swarms. Among those, artificial bee colony (ABC) is the one which has been most widely studied on and applied to solve the real world problems, so far. Day by day the number of researchers being interested in ABC algorithm increases rapidly. This work presents a comprehensive survey of the advances with ABC and its applications. It is hoped that this survey would be very beneficial for the researchers studying on SI, particularly ABC algorithm.
1,645 citations
"Comprehensive Review on Detection a..." refers methods in this paper
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