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Proceedings ArticleDOI

High Impedance Fault detection using DWT for transmission and distribution networks

TL;DR: In this article, the authors proposed a fault detection method for high impedance faults (HIFs) using DWT. DWT is an effective method for HIF detection as it is capable of extracting transient information in both frequency and time domains simultaneously.
Abstract: The objective of intelligent electronic devices in grids running fault detection algorithm is to evaluate the special features in patterns of the voltages and currents samples taken at strategic points for transmission and distribution networks and detect if a fault has occurred. Fault detection is necessary to improve power grid reliability and efficiency for safe power supply transmission and distribution. High Impedance Faults (HIF) are an important type of power system faults that are difficult to be detected by conventional over-current protective relays because of their very low fault currents. High impedance faults (HIFs) creates lot of transients in the power system and can result in equipment damage and electrical shocks. Therefore special methods have to be developed and utilized in order to detect them quickly. DWT is an effective method for HIF detection as it is capable of extracting transient information in both frequency and time domains simultaneously. High frequency transient energies is shown to be useful for accurate fault detection and classification.
Citations
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Journal ArticleDOI
TL;DR: Results suggest that the proposed method is not affected by fault location or inception angle, system loading and topology changes in the distribution network, and can differentiate high impedance faults from other distribution network disturbances such as capacitor banks switching, feeder energizing and low-impedance faults.

34 citations

Journal ArticleDOI
TL;DR: A comprehensive review of HIF detection and its improvement techniques suggested by various authors are discussed in this paper.

26 citations

Journal ArticleDOI
TL;DR: In this article, an analytical model to analyze the interaction between the electric arc associated to HIFs and a transmission line is presented, which is validated by means of comparison between measured and calculated results.
Abstract: A high impedance fault (HIF) normally occurs when an overhead power line physically breaks and falls to the ground. Such faults are difficult to detect because they often draw small currents which cannot be detected by conventional overcurrent protection. Furthermore, an electric arc accompanies HIFs, resulting in fire hazard, damage to electrical devices, and risk with human life. This paper presents an analytical model to analyze the interaction between the electric arc associated to HIFs and a transmission line. A joint analytical solution to the wave equation for a transmission line and a nonlinear equation for the arc model is presented. The analytical model is validated by means of comparisons between measured and calculated results. Several cases of study are presented which support the foundation and accuracy of the proposed model.

11 citations

Journal ArticleDOI
TL;DR: An impedance-based method to estimate the fault location in transmission lines, which allows to generate synthetic high impedance faults by setting specific features of a HIF from simple input parameters, and an adjustable HIF model to validate its performance.

11 citations

Proceedings ArticleDOI
01 Oct 2018
TL;DR: The proposed PMU and wavelet-based fault detector has been tested with MATLAB Simulink-generated signals and proved to be robust against transients generated during normal events such as feeder energizing and de-energizing as well as capacitor bank switching.
Abstract: A new simple algorithm to detect high impedance high impedance fault (HIF) in grounded distribution networks with the combination of a wavelet transform and phasor measurement unit (PMU) techniques is presented in this paper. The protection algorithm observes the changing conditions of phase displacement between phase voltage and current signals and high frequency component present in the detail coefficient of zero sequence current of the specified measured terminal. The proposed method consists in three simple steps. The first step is checking whether the system is normal or abnormal by using the total sum of mean absolute values of phase displacements between phase voltages and currents. Then, the second step is whether system unbalance is fault or other load switching will be checked by using the sum of mean values of phase displacement between voltage and current. Finally, the algorithm will observe the present of high frequency transient components in the residual current signal to ensure that the system is under fault condition. The proposed PMU and wavelet-based fault detector has been tested with MATLAB Simulink-generated signals, more simple than conventional algorithms and methods. The scheme proved to be robust against transients generated during normal events such as feeder energizing and de-energizing as well as capacitor bank switching.

3 citations

References
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Journal ArticleDOI
01 Apr 1996
TL;DR: In this article, the authors present a new approach to detect, localize, and investigate the feasibility of classifying various types of power quality disturbances using dyadic-orthonormal wavelet transform analysis.
Abstract: In this paper we present a new approach to detect, localize, and investigate the feasibility of classifying various types of power quality disturbances. The approach is based on wavelet transform analysis, particularly the dyadic-orthonormal wavelet transform. The key idea underlying the approach is to decompose a given disturbance signal into other signals which represent a smoothed version and a detailed version of the original signal. The decomposition is performed using multiresolution signal decomposition techniques. We demonstrate and test our proposed technique to detect and localize disturbances with actual power line disturbances. In order to enhance the detection outcomes, we utilize the squared wavelet transform coefficients of the analyzed power line signal. Based on the results of the detection and localization, we carry out an initial investigation of the ability to uniquely characterize various types of power quality disturbances. This investigation is based on characterizing the uniqueness of the squared wavelet transform coefficients for each power quality disturbance.

908 citations

Journal ArticleDOI
TL;DR: In this article, a novel method for high impedance fault (HIF) detection based on pattern recognition systems is presented, using this method, HIFs can be discriminated from insulator leakage current (ILC) and transients such as capacitor switching, load switching (high/low voltage), ground fault, inrush current and no load line switching.
Abstract: A novel method for high impedance fault (HIF) detection based on pattern recognition systems is presented in this paper. Using this method, HIFs can be discriminated from insulator leakage current (ILC) and transients such as capacitor switching, load switching (high/low voltage), ground fault, inrush current and no load line switching. Wavelet transform is used for the decomposition of signals and feature extraction, feature selection is done by principal component analysis and Bayes classifier is used for classification. HIF and ILC data was acquired from experimental tests and the data for transients was obtained by simulation using EMTP program. Results show that the proposed procedure is efficient in identifying HIFs from other events.

202 citations

Journal ArticleDOI
TL;DR: In this paper, a high impedance arcing fault due to a leaning tree in medium voltage (MV) networks is modeled and experimentally verified, where the fault is represented in two parts; an arc model and a high resistance.
Abstract: A high impedance arcing fault due to a leaning tree in medium voltage (MV) networks is modeled and experimentally verified. The fault is represented in two parts; an arc model and a high resistance. The arc is generated by a leaning tree towards the network conductor and the tree resistance limits the fault current. The arcing element is dynamically simulated using thermal equations. The arc model parameters and resistance values are determined using the experimental results. The fault behavior is simulated by the ATP/EMTP program, in which the arc model is realized using the universal arc representation. The experimental results have validated the system transient model. Discrete wavelet transform is used to extract the fault features and therefore localize the fault events. It is found that arc reignitions enhance fault detection when discrete wavelet transform is utilized

140 citations

Journal ArticleDOI
TL;DR: In this article, a new analytic approach to optimal coordination of directional overcurrent relays is presented, which is based on the selection of optimum pickup current and time dial setting, in order to obtain minimum operating time for the relays, while satisfying various coordination and boundary constraints.
Abstract: This study presents a new analytic approach to optimal coordination of directional overcurrent relays. This approach is based on the selection of optimum pickup current and time dial setting, in order to obtain minimum operating time for the relays, while satisfying various coordination and boundary constraints. Based on the new optimal relay setting procedure, an iterative numerical solution is proposed. The proposed numerical algorithm converges to the global optimum values, which are independent of initial values and the order of relay setting. The proposed method is applied to three different test systems. The new method is compared with some previously proposed analytic and evolutionary approaches. The results demonstrate the advantages of the proposed method over the previous works.

86 citations

Journal ArticleDOI
11 May 2006
TL;DR: In this paper, a novel method for high-impedance fault (HIF) detection in distribution systems is presented, which can be discriminated from isolator leakage current (ILC) and transients such as capacitor switching, load switching (high/low voltage), ground fault, inrush current and no load line switching.
Abstract: A novel method for high-impedance fault (HIF) detection in distribution systems is presented. Using this method HIFs can be discriminated from isolator leakage current (ILC) and transients such as capacitor switching, load switching (high/low voltage), ground fault, inrush current and no-load line switching. Wavelet transform and principal component analysis are used for feature extraction/selection. A fuzzy inference system is implemented for fault classification and a genetic algorithm is applied for input membership functions adjustment. HIF and ILC data was acquired from experimental tests and the data for other transients was obtained by simulation of a real 20 kV distribution feeder using EMTP. Results show that the proposed procedure is efficient in identifying HIFs from other events.

66 citations