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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18 Jun 2021
TL;DR: In this article, a method using features computed from voltage by applying Hilbert transform (HT) and Stockwell transform (ST) for event recognition and power quality (PQ) estimation in distribution network (DN) interfaced to the solar photovoltaic (PV) generation is presented.
Abstract: A method using features computed from voltage by applying Hilbert transform (HT) and Stockwell transform (ST) for event recognition and power quality (PQ) estimation in distribution network (DN) interfaced to the solar photovoltaic (PV) generation is presented here. A PQ estimation factor (PEF) is proposed to recognize a PQ disturbances associated to an event in the DN with solar generation. Further, a time estimation factor (TEF) is also proposed which is effective for estimation of events and location of PQ issues. Features computed from the PEF and TEF are considered as input for rule based decision tree (RBDT) to classify the operational events. IEEE-13 buses test DN having an interfaced solar PV system is utilized for the proposed study. Performance of this technique is superior compared to approach using application of Discrete Wavelet transform (DWT).
7 citations
TL;DR: In this paper, a user-centric cooperative mechanism that enhances user participation in P2P energy trading is proposed to make it possible to conduct economic transactions while reflecting the preferences of the traders in the ordering process.
Abstract: Peer-to-peer (P2P) energy trading is gaining attention as a technology to effectively handle already existing distributed energy resources (DER). In order to manage a large number of DER, it is necessary to increase the number of P2P energy trading participants. For that, designing incentives for participants to engage in P2P energy trading is important. This paper describes a user-centric cooperative mechanism that enhances user participation in P2P energy trading. The key components of this incentive for participants to engage in P2P energy trading are described and evaluated in this study. The goal of the proposal is to make it possible to conduct economic transactions while reflecting the preferences of the traders in the ordering process, making it possible to conduct transactions with minimal effort. As a case study, the Higashi-Fuji demonstration experiment conducted in Japan verified the proposed mechanism. In this experiment, 19 households and 9 plugin hybrid vehicles (PHV) were evaluated. As a result, the study confirmed that prosumers were able to sell their surplus electricity, and consumers were able to preferentially purchase renewable energy when it was available. In addition, those trades were made economically. All trades were made automatically, and this efficiency allowed the users to continue using the P2P energy trading.
7 citations
TL;DR: In this paper , the authors developed a new approach to convolutional neural network (CNN) based which classifies a particular power signal into its respective power quality condition, based on the idea that the best solution will be taken from the newly produced data pool obtained by rescaling the available data according to the total number of pixels before the average data pool is created and then deep CNN processes will continue.
Abstract: Abstract Power quality is one of the most important research eras for the energy sector. Suddenly dropped voltages or suddenly rising voltages and harmonics in energy should be identified. All of these distortions are called power quality disturbances (PQDs). Deep learning based convolutional artificial neural networks with an attention model approach has been carried out. The main idea is to develop a new approach to convolutional neural network (CNN) based which classifies a particular power signal into its respective power quality condition. The attention model approach is based on the idea that the best solution will be taken from the newly produced data pool obtained by rescaling the available data according to the total number of pixels before the average data pool is created and then deep CNN processes will continue. In the attention model approach, all data is multiplied by the number of elements by the number of epoch time sixty-six tensors. The dataset used here contains signals which belong to one of the 9 classes. This means that each signal is characterized by 622 data points and 5600 data parameters. All signals provided are in time domain. Power quality (PQ) is directly depending on power disturbances’ absence or scarcity. The accuracy and error values of the developed model were obtained according to both the number of epochs and the number of iterations.
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
TL;DR: A broad review of signal processing and soft computing techniques used for the detection and recognition of the underlying cause of power quality disturbance is presented in this article , which will help the researcher, engineers, designers working in the field of detection, recognition, and monitoring of the power quality.
7 citations
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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.
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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.
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