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.

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Fault detection, classification and location for transmission lines and distribution systems: a review on the methods

This paper presents a combined wavelet-support vector machine (SVM) technique for fault zone identification in a series compensated transmission line. The proposed method uses the samples of three line currents for one cycle duration to accomplish this task. Initially, the features of the line currents are extracted by first level decomposition of the current samples using discrete wavelet transform (DWT). Subsequently, the extracted features are applied as inputs to a SVM for determining the fault zone (whether the fault is before or after the series capacitor, as observed from the relay point). The feasibility of the proposed algorithm has been tested on a 300-km, 400-kV series compensated transmission line for all the ten types of faults through detailed digital simulation using PSCAD/EMTDC. Upon testing on more than 25000 fault cases with varying fault resistance, fault inception angle, prefault power transfer level, percentage compensation level, and source impedances, the performance of the developed method has been found to be quite promising.

Combined Wavelet-SVM Technique for Fault Zone Detection in a Series Compensated Transmission Line

A novel technique for fault detection and classification in the extremely high-voltage transmission line using the fault transients is proposed in this paper. The novel technique, called wavelet singular entropy (WSE), incorporates the advantages of the wavelet transform, singular value decomposition, and Shannon entropy. WSE is capable of being immune to the noise in the fault transient and not being affected by the transient magnitude so it can be used to extract features automatically from fault transients and express the fault features intuitively and quantitatively even in the case of high-noise and low-magnitude fault transients. The WSE-based fault detection is performed in this paper, which proves the availability and superiority of WSE technique in fault detection. A novel algorithm based on WSE is put forward for fault classification and it is verified to be effective and reliable under various fault conditions, such as fault type, fault inception time, fault resistance, and fault location. Therefore, the proposed WSE-based fault detection and classification is feasible and has great potential in practical applications.

Fault Detection and Classification in EHV Transmission Line Based on Wavelet Singular Entropy

This first chapter summarizes the motivation for holding the November 2003 National Science Foundation Workshop, and provides a listing of the Workshop speakers and their presentations. It also contains an overview of the articles contained in this compilation.

Applied Mathematics for Restructured Electric Power Systems

In the few years, wavelet-based methodologies have been proposed as a good alternative for real-time fault detection. However, these methodologies usually fail to detect faults with overdamped transients and they are highly influenced by the choice of the mother wavelet, presenting time delay in the real-time analysis. By using the discrete wavelet transform (DWT) or the maximal overlap discrete wavelet transform (MODWT), the wavelet coefficient energy has been also used for fault analysis and presents the same drawbacks of the wavelet coefficient analysis. However, this paper presents a novel wavelet-based methodology for real-time detection of fault-induced transients in transmission lines, where the wavelet coefficient energy takes into account the border effects of the sliding windows. As a consequence, the performance of the proposed energy analysis is not affected by the choice of the mother wavelet, presenting no time delay in real-time fault detection, and the fault detection is scarcely influenced to the fault inception angle, fault resistance, and fault location, even if in critical situations where there are no fault-induced transients. The performance of the proposed methodology was assessed by using actual and simulated data. Some records were reproduced to be analyzed in real time with a digital signal processor.

Fault-Induced Transient Detection Based on Real-Time Analysis of the Wavelet Coefficient Energy

This paper presents a new method for the boundary protection of series-compensated transmission lines, as well as fault classification. The boundary protection is based on detecting distinct frequency bands contained in the transient fault current wave. Discrete wavelet transform, using db4 as a mother wavelet, is used to capture two bands of frequencies in the transient current signal. The spectral energies of these two bands are obtained and used to determine if the fault is internal or external to the protected zone. Fault classification is done using the discrete wavelet transform. Using Haar as the mother wavelet, the coefficients of a frequency band in the range of 1 kHz-3 kHz are obtained for the three phase and ground currents. The average value of the coefficients of each current wave is then computed and used to classify the faulted phases. The basic principle of the protection scheme is described and its response to the series-compensated transmission lines is studied for a wide range of compensation levels, fault conditions, fault types, and fault locations. The stability of the algorithm under various load switching cases is also tested. Fault simulations are performed using power system computer-aided design/electromagnetic transient and direct current program and the results are then interfaced to MATLAB, where the algorithm is implemented. It is found that the proposed method gives reliable results in the boundary protection and fault classification of series-compensated lines.

Usage of wavelet transform in the protection of series-compensated transmission lines

In the literature, wavelet techniques are proposed for the analysis of power system transients. Many mother wavelets have been used for this analysis such as Haar, Daubechies (db), Symlets, and Coiflets. This paper describes a strategy to choose a suitable mother wavelet for this analysis. It also shows the deviation between Matlab and theoretical (mathematically calculated) db-wavelets when they are used for the analysis of power system transient. The simulation study is carried out using PSCAD simulation program and Matlab wavelet toolbox. The simulation results show that the theoretical db wavelet is more suitable for analyzing power system fault transients than the Matlab db wavelet.

Selection of a suitable mother wavelet for analyzing power system fault transients

This paper describes the laboratory implementation and real-time test results of a new neural network (NN) based digital differential relay used for detecting faults and classifying internal faults in the stator winding of synchronous generators. Details of the software written to enable the operation of the relay are described. Behavior of the NN based relay is observed and the experimental results are presented.

Experimental testing of a neural network based digital differential relay for synchronous generators

Recently, numerical relays with communication capabilities have been employed to provide adaptive solutions for Distributed Generations (DGs) protection issues. This paper presents an adaptive protection scheme based on centralized and decentralized communication to address DG protection problems. The proposed method uses two directional relays in each feeder, one at the beginning (called forward relay) and one at the end (called reverse relay). These relays can communicate with each other and the central unit. The centralized communication occurs between the central unit and the relays in the system when any relay’s status changes from connected to disconnected or vice versa. It aims to define the operation mode, islanding detection, and activate the relays settings to achieve proper coordination. Protective relays are coordinated using a Genetic Algorithm (GA) to optimize protection time. The optimization problem considers pick up current (Ipu), Time Multiplier Setting (TMS), Plug Setting Multiplier (PSM), and curve type. Decentralized communication, which occurs when any relay detects a fault, increases relays’ accuracy and speed of decision-making. This paper also proposes a novel method for detecting High Impedance Faults (HIF), a significant difficulty for protecting engineers as it draws a very low current that conventional overcurrent relays fail to detect in most cases. HIF is detected using wavelet transform, symlet 8, detail 2 (d2), and relay communication. On the IEC benchmark microgrid, the suggested algorithm is tested. ETAP is used for load flow analysis and short circuit analysis, whereas MATLAB is used for GA optimization, HIF modelling, and wavelet transform routines.

A.I. Megahed

Papers

Usage of wavelet transform in the protection of series-compensated transmission lines

Selection of a suitable mother wavelet for analyzing power system fault transients

Experimental testing of a neural network based digital differential relay for synchronous generators

Improved Adaptive Protection Scheme Based Combined Centralized/Decentralized Communications for Power Systems Equipped With Distributed Generation