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Proceedings ArticleDOI

Wavelet Based Fault Detection, Classification and Location in Transmission Lines

TL;DR: In this paper, a global positioning system synchronizing clock is used to sample three phase voltage and current signals at both the ends of the transmission line over a moving window length of half cycle.
Abstract: This paper deals with the application of wavelet transforms for the detection, classification and location of faults on transmission lines. A global positioning system synchronizing clock is used to sample three phase voltage and current signals at both the ends of the transmission line over a moving window length of half cycle. The current signals are analyzed with Bior2.2 wavelet to obtain detail coefficients of single decompositions. Fault indices are calculated based on the sum of local and remote end detail coefficients, and compared with threshold values to detect and classify the faults. For estimation of fault location feed forward artificial neural networks are employed, which make use of third level approximate decompositions of the voltages and currents of local end obtained with Bior4.4 wavelet. Two types of neural networks are proposed, one for locating phase faults and the other for ground faults. The proposed algorithm is tested for different locations and types of faults as well as for various incidence angles and fault impedances. The algorithm is proved to be efficient and effective in detecting, classifying and locating faults.
Citations
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Journal ArticleDOI
TL;DR: D discrete wavelet transform of voltage signals at the two ends of the transmission lines have been analyzed and four layer feed forward back propagation neural networks are designed to classify and locate the fault at different single line to ground fault conditions.
Abstract: and distribution lines are vital links between generating units and consumers. They are exposed to atmosphere, hence chances of occurrence of fault in transmission line is very high, which has to be immediately taken care of in order to minimize damage caused by it. In this paper discrete wavelet transform of voltage signals at the two ends of the transmission lines have been analyzed. Transient energies of detail information for two consecutive data windows at fault are used for analysis. Four layer feed forward back propagation neural networks are designed to classify and locate the fault at different single line to ground fault conditions.

40 citations

Journal ArticleDOI
TL;DR: A new morphological edge detection (MED) filter to extract the transient features from the original fault signal is designed and can fast and accurately detect the arrival time and polarity of travelling waves in all conditions.
Abstract: In this study, a novel algorithm for detecting and classifying faults in transmission lines is proposed. The algorithm is based on mathematical morphology and initial current travelling waves. A new morphological edge detection (MED) filter to extract the transient features from the original fault signal is designed. This MED filter can fast and accurately detect the arrival time and polarity of travelling waves in all conditions. The appropriate criteria of fault classification and faulted-phase selection are introduced based on polarity of initial current travelling waves. The simulations based on the electromagnetic transients program and MATLAB have been done to evaluate the validity of the proposed algorithm.

38 citations

Journal ArticleDOI
TL;DR: In this article, a real-time simulation of a 20 V, 200 km transmission line, representing a 400 kV extra-high voltage transmission line is presented, where a National Instruments based data acquisition system in conjunction with LabVIEW has been incorporated to acquire the best possible representative data.
Abstract: In a power system, transmission lines are prone to faults of different nature, which challenge the system stability and reliability. Thus system performance analysis under such fault conditions has drawn attention of researchers. Particularly, the advent of fast and efficient data acquisition using higher sampling rates combined with high speed digital signal processors has paved the way for efficient digital real-time simulations. Though sustained efforts have been made by different researchers to develop some good real-time digital simulators, this study is an attempt to implement a laboratory prototype model of a 20 V, 200 km transmission line, representing a 400 kV extra-high voltage transmission line, so as to improve the real time performance. In addition, efficient National Instruments based data acquisition system in conjunction with LabVIEW has been incorporated to acquire the best possible representative data with commensurate characterisation and transmission with fidelity. The unique contributions of this real-time fault analysis laboratory hybrid model are accurate fault detection and classification using a frequency-domain approach having immunity to fault impedance and fault inception angle, which affect the time-domain analyses severely. It is also equipped with visual displays so that even non-experts can use it for planning and decision-making purposes.

33 citations

Proceedings ArticleDOI
23 Jun 2010
TL;DR: In this paper, a new technique is discussed by which avoiding noise in fault detection in high voltage transmission lines is achieved, and a comparative study of the performance of Fourier transform and wavelet transform based methods combined with protective relaying pattern classifier algorithm Neural Network for classification of faults is presented.
Abstract: Nowadays, power supply has become a business asset. The quality and reliability of power system needs to be maintained in order to obtain optimum performance. Therefore, it is extremely important that transmission line faults from various sources to be identified accurately, reliably and be corrected as soon as possible. In this paper, a new technique is discussed by which avoiding noise in fault detection in high voltage transmission lines is achieved. Later, a comparative study of the performance of Fourier transform and wavelet transform based methods combined with protective relaying pattern classifier algorithm Neural Network for classification of faults is presented. A new classification method is proposed for decreasing training time and dimensions of NN. The proposed algorithms are based on Fourier transform analysis of fundamental frequency of current signals in the event of a short circuit. Similar analysis is performed on transient current signals using multi-resolution Haar wavelet transform, and comparative characteristics of the two methods are discussed.

31 citations

Proceedings ArticleDOI
23 Jun 2010
TL;DR: In this paper, a comparative study of the performance of Fourier transform and wavelet transform based methods combined with Neural Network (NN) for location estimation of faults on high voltage transmission lines is presented.
Abstract: Nowadays, power supply has become a business commodity. The quality and reliability of power needs to be maintained in order to obtain optimum performance. Therefore, it is extremely important that transmission line faults from various sources be identified accurately, reliably and be corrected as soon as possible. In this paper, a comparative study of the performance of Fourier transform and wavelet transform based methods combined with Neural Network (NN) for location estimation of faults on high voltage transmission lines is presented. A new location method is proposed for decreasing training time and dimensions of NN. The proposed algorithms are based on Fourier transform analysis of fundamental frequency of current and voltage signals in the event of a short circuit on a transmission line. Similar analysis is performed on transient current and voltage signals using multi-resolution Daubchies-9 wavelet transform, and comparative characteristics of the two methods are discussed.

30 citations


Cites methods from "Wavelet Based Fault Detection, Clas..."

  • ...Transform (WT) [ 5 ]-[6] or a combination of these techniques [ 7]-[8]....

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References
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Book
01 Jul 1988
TL;DR: In this paper, the authors present a comprehensive, up-to-date account of computer relaying in power systems, based in part on the author's extensive experience in the field.
Abstract: This text/reference presents a comprehensive, up-to-date account of computer relaying in power systems, based in part on the author's extensive experience in the field. Provides background material on current relaying practices, and covers the mathematical foundations for relaying algorithms. Each chapter contains helpful illustrations, examples, and problems.

880 citations

Journal ArticleDOI
TL;DR: In this paper, a digital distance-protection scheme for transmission lines based on analyzing the measured voltage and current signals at the relay location using wavelet transform with multiresolution analysis (MRA) is presented.
Abstract: Wavelet transform (WT) has the ability to decompose signals into different frequency bands using multiresolution analysis (MRA). It can be utilized in detecting faults and to estimate the phasors of the voltage and current signals, which are essential for transmission line distance protection. A digital distance-protection scheme for transmission lines based on analyzing the measured voltage and current signals at the relay location using WT with MRA is presented in this paper. The scheme has been tested by both computer simulation and experimentally. The tests presented include solid ground faults, phase faults, high impedance and nonlinear ground faults, and line charging.

185 citations


"Wavelet Based Fault Detection, Clas..." refers methods in this paper

  • ...Distance protection schemes using WT based phasor estimation are reported in [3]&[4]....

    [...]

Journal ArticleDOI
TL;DR: In this paper, a fault detection technique of high impedance faults (HIFs) in high voltage transmission lines using the wavelet transform has been described, which is based on utilising the absolute sum value of coefficients in multiresolution signal decomposition (MSD) based on the discrete Wavelet transform (DWT).
Abstract: This paper describes a novel fault detection technique of high impedance faults (HIFs) in high voltage transmission lines using the wavelet transform. Recently, the wavelet transform (WT) has been successfully applied in many fields. The technique is based on utilising the absolute sum value of coefficients in multiresolution signal decomposition (MSD) based on the discrete wavelet transform (DWT). A fault indicator and fault criteria are then used to detect the HIF in transmission line. In order to discriminate between HIF and non-fault transient phenomena such as capacitor and line switching and arc furnace loads, the concept of duration time, i.e. the transient time period, is presented. On the basis of extensive investigations, optimal mother wavelets for the detection of HIF are chosen. It is shown that the technique developed is robust to fault type, fault-inception angle, fault resistance and fault location. The paper demonstrates a new concept and methodology in HIT in transmission lines. The performance of the proposed technique is tested under a variety of fault conditions on a typical 154kV Korean transmission line system.

179 citations


"Wavelet Based Fault Detection, Clas..." refers methods in this paper

  • ...Chul-Hwan Kim, et al [1] have used Wavelet Transforms to detect the high impedance arcing faults....

    [...]

Journal ArticleDOI
TL;DR: In this paper, a new adaptive fault protection scheme for transmission lines using synchronized phasor measurements is presented, which includes fault detection, direction discrimination, classification and location, and fault location indices are derived by using two-terminal synchronized measurements incorporated with distributed line model and modal transformation theory.
Abstract: This paper presents a new adaptive fault protection scheme for transmission lines using synchronized phasor measurements. The work includes fault detection, direction discrimination, classification and location. Both fault detection and fault location indices are derived by using two-terminal synchronized measurements incorporated with distributed line model and modal transformation theory. The fault detection index is composed of two complex phasors and the angle difference between the two phasors determines whether the fault is intemal or external to the protected zone. The fault types can be classified by the modal fault detection index. The proposed scheme also combines on-line parameter estimation to assure protection scheme performance and to achieve adaptive protection. Extensive simulation studies show that the proposed scheme provides a fast relay response and high accuracy in fault location under various system and fault conditions. The proposed method responds very well with regard to dependability, security and sensitivity (high-resistance fault coverage).

116 citations