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W. C. Santos

Bio: W. C. Santos is an academic researcher from Federal University of Campina Grande. The author has contributed to research in topics: Fault (power engineering) & Wavelet transform. The author has an hindex of 8, co-authored 9 publications receiving 291 citations.

Papers
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Journal ArticleDOI
TL;DR: A transient-based algorithm that uses the discrete wavelet transform to monitor high- and low-frequency voltage components at several points of the power system, being able to indicate the most likely area within which the disturbance has occurred, without requiring data synchronization nor the knowledge of feeder or load parameters.
Abstract: This paper presents a transient-based algorithm for high-impedance fault identification on distribution networks. It uses the discrete wavelet transform to monitor high- and low-frequency voltage components at several points of the power system, being able to indicate the most likely area within which the disturbance has occurred, without requiring data synchronization nor the knowledge of feeder or load parameters. The proposed algorithm is evaluated through electromagnetic transients program simulations of high-impedance faults in a 13.8 kV system modeled from actual Brazilian distribution grid data. Solid faults, capacitor bank switching, and feeder energization are also simulated, considering the system with and without distributed generation. Obtained results show that the algorithm significantly reduces the search field of the high-impedance fault, reliably distinguishing it from other disturbances.

155 citations

Journal ArticleDOI
TL;DR: In this paper, the wavelet coefficient energy with border distortions of a one-cycle sliding window designed for the real-time detection of transients induced by HIFs is presented.
Abstract: The development of modern protection functions is a challenge in the emerging environment of smart grids because the current protection system technology still has several limitations, such as the reliable high-impedance fault (HIF) detection in multigrounded distribution networks, which poses a danger to the public when the protection system fails. This paper presents the wavelet coefficient energy with border distortions of a one-cycle sliding window designed for the real-time detection of transients induced by HIFs. By using the border distortions, the proposed wavelet-based methodology presents a reliable detection of transients generated by HIFs with no time delay and energy peaks scarcely affected by the choice of the mother wavelet. The signatures of different HIFs are presented in both time and wavelet domains. The performance of the proposed wavelet-based method was assessed with compact and long mother wavelets by using data from staged HIFs on an actual energized power system, taking into account different fault surfaces, as well as simulated HIFs. The proposed method presented a more reliable and accurate performance than other evaluated wavelet-based algorithms.

130 citations

Journal ArticleDOI
TL;DR: In this article, a literature review of models of high impedance faults was made and it was proposed to use a model known in the literature with some adjustments, based on actual records obtained at different contact surfaces, it was possible to obtain a set of simulated records representing the most important features found in most of the HIF.
Abstract: High impedance faults (HIFs) are serious and troubling disturbances on power distribution systems because the main power system protection devices are usually not able to diagnose them accurately due to the low fault current levels. This paper presents the detailing of field experiments and modeling of HIF. A literature review of models of HIF was made and it was proposed to use a model known in the literature with some adjustments. With the model, based on actual records obtained at different contact surfaces, it was possible to obtain a set of simulated records representing the most important features found in most of the HIF.

49 citations

Proceedings ArticleDOI
15 Apr 2013
TL;DR: In this article, a transient based approach to diagnose high impedance faults (HIFs) on smart distribution grids is presented, which does not require the knowledge of the feeder parameters and uses the discrete wavelet transform (DWT) to monitor fault-induced transients at strategic points of the power system, taking advantage of available Smart Grid communication channels.
Abstract: This paper presents a transient based approach to diagnose high impedance faults (HIFs) on smart distribution grids. The algorithm does not require the knowledge of the feeder parameters and uses the discrete wavelet transform (DWT) to monitor fault-induced transients at strategic points of the power system, taking advantages of available Smart Grid communication channels. It allows the HIF detection and then the identification of the area in which the fault occurred. The proposed methodology is evaluated through Electromagnetic Transients Program (EMTP) simulations of HIFs in a 13.8 kV system, which was modeled using actual data of a Brazilian distribution network. Obtained results show that the method is able to detect HIFs practically at the disturbance inception as well as to provide a great reduction of the fault search field using a small computational burden.

16 citations

07 Jul 2011
TL;DR: In this paper, the authors present a useful tool to support the development of wavelet-based methods for: fault detection; power quality disturbance detection (voltage sags, transmission line energization and deenergization, capacitor bank switching, etc.).
Abstract: This paper presents a useful tool to support the development of wavelet-based methods for: fault detection; power quality disturbance detection (voltage sags, transmission line energization and deenergization, capacitor bank switching, etc.); fault classification; and fault location. The disturbance features can be graphically identified by means of the voltage and current waveform analysis (phase A, B, C, and/or neutral) and their related wavelet coefficients, approximation coefficients, energies of the wavelet coefficients, and other wavelet features at various scales. The features of some actual records extracted by means of this tool and how it can be used in order to perform wavelet-based diagnostic methods are also addressed in the paper.

12 citations


Cited by
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Journal ArticleDOI
01 Apr 2016
TL;DR: A comprehensive review on the methods used for fault detection, classification and location in transmission lines and distribution systems is presented in this article, where fault detection techniques are discussed on the basis of feature extraction.
Abstract: A comprehensive review on the methods used for fault detection, classification and location in transmission lines and distribution systems is presented in this study. Though the three topics are highly correlated, the authors try to discuss them separately, so that one may have a more logical and comprehensive understanding of the concepts without getting confused. Great significance is also attached to the feature extraction process, without which the majority of the methods may not be implemented properly. Fault detection techniques are discussed on the basis of feature extraction. After the overall concepts and general ideas are presented, representative works as well as new progress in the techniques are covered and discussed in detail. One may find the content of this study helpful as a detailed literature review or a practical technical guidance.

248 citations

Journal ArticleDOI
TL;DR: A review of the literature related to the HIF phenomenon can be found in this paper, where the authors categorized, evaluated, and compared the existing HIF detection techniques and HIF location techniques.
Abstract: Protection from the high impedance fault (HIF) has been one of the biggest challenges in the power distribution network HIF typically occurs when the conductors in distribution network break and touch the ground surface; or lean and touch a tree branch This fault, with current magnitude close to the load current level, is not detectable by over-current relays This paper aims to review the literature related to the HIF phenomenon In this work, the HIF detection techniques are categorized, evaluated, and compared with one another Furthermore, the existing HIF models and HIF location techniques are reviewed Finally, the shortcoming of the existing perspective toward the HIF phenomenon and the possible road to the future for HIF detection is discussed

200 citations

Journal ArticleDOI
TL;DR: A transient-based algorithm that uses the discrete wavelet transform to monitor high- and low-frequency voltage components at several points of the power system, being able to indicate the most likely area within which the disturbance has occurred, without requiring data synchronization nor the knowledge of feeder or load parameters.
Abstract: This paper presents a transient-based algorithm for high-impedance fault identification on distribution networks. It uses the discrete wavelet transform to monitor high- and low-frequency voltage components at several points of the power system, being able to indicate the most likely area within which the disturbance has occurred, without requiring data synchronization nor the knowledge of feeder or load parameters. The proposed algorithm is evaluated through electromagnetic transients program simulations of high-impedance faults in a 13.8 kV system modeled from actual Brazilian distribution grid data. Solid faults, capacitor bank switching, and feeder energization are also simulated, considering the system with and without distributed generation. Obtained results show that the algorithm significantly reduces the search field of the high-impedance fault, reliably distinguishing it from other disturbances.

155 citations

Journal ArticleDOI
TL;DR: In this paper, the wavelet coefficient energy with border distortions of a one-cycle sliding window designed for the real-time detection of transients induced by HIFs is presented.
Abstract: The development of modern protection functions is a challenge in the emerging environment of smart grids because the current protection system technology still has several limitations, such as the reliable high-impedance fault (HIF) detection in multigrounded distribution networks, which poses a danger to the public when the protection system fails. This paper presents the wavelet coefficient energy with border distortions of a one-cycle sliding window designed for the real-time detection of transients induced by HIFs. By using the border distortions, the proposed wavelet-based methodology presents a reliable detection of transients generated by HIFs with no time delay and energy peaks scarcely affected by the choice of the mother wavelet. The signatures of different HIFs are presented in both time and wavelet domains. The performance of the proposed wavelet-based method was assessed with compact and long mother wavelets by using data from staged HIFs on an actual energized power system, taking into account different fault surfaces, as well as simulated HIFs. The proposed method presented a more reliable and accurate performance than other evaluated wavelet-based algorithms.

130 citations

Journal ArticleDOI
TL;DR: In this article, a fault-location scheme for ungrounded photovoltaic (PV) systems is proposed, in which high frequency noise patterns are used to identify the fault location.
Abstract: Identifying ground faults is a significant problem in ungrounded photovoltaic (PV) systems because such earth faults do not provide sufficient fault currents for their detection and location during system operation. If such ground faults are not cleared quickly, a subsequent ground fault on the healthy phase will create a complete short circuit in the system. This paper proposes a novel fault-location scheme in which high frequency noise patterns are used to identify the fault location. The high-frequency noise is generated due to the switching transients of converters combined with the parasitic capacitance of PV panels and cables. Discrete wavelet transform is used for the decomposition of the monitored signal (midpoint voltage of the converters) and features are extracted. Norm values of the measured waveform at different frequency bands give unique features at different fault locations and are used as the feature vectors for pattern recognition. Then, a three-layer feedforward artificial neural networks classifier, which can automatically classify the fault locations according to the extracted features, is investigated. The proposed fault-location scheme has been primarily developed for fault location in the PV farm (PV panels and dc cables). The method is tested for ground faults as well as line–line faults. These faults are simulated with a real-time digital simulator and the data are then analyzed with wavelets. Finally, the effectiveness of the designed fault locator is tested with varying system parameters. The results demonstrate that the proposed approach has accurate and robust performance even with noisy measurements and changes in operating conditions.

113 citations