Determination Of Fault Location Research Articles

Application of Digital Signal Processing to Improve the Accuracy of Fault Location Determination in Power Transmission Lines on the Basis of Fault Regime Parameters

Remote means for fault location determination are intended for finding the most likely fault point and reducing the bypass zone of the line. Methods of improving the accuracy of the calculation of the distance to the fault location (and reducing the inspection zone of the OHL) owing to the use of special digital processing of fault regime oscillogram signals are examined.

Detection of Fault Direction and Location in Compensated System using Sequence Component

Objectives: The proposed scheme presents a fault direction estimation as well as fault location determination technique for short transmission line using positive sequence component. An objective of the suggested work is to recognize direction of fault and locate it in short transmission line using positive sequence component. Methods/Analysis: Solution is given based on difference between positive sequence post-fault and steady state current phasor and difference of magnitude among post-fault and steady state positive sequence voltage phasor for fault direction estimation. Fault location is estimated by two-terminal method. Fast Fourier Transform is considered to detect the direction of fault and Discrete Fourier Transform is used to find the location of fault. The proposed work is estimated by simulated data in PSCAD and MATLAB/SIMULINK for a compensated line. Findings: Fault detection as well as fault location estimation in both sections of compensated line considering transmission line issues is identified properly. Many techniques are available for fault direction estimation and fault location determination. Sometimes available methods do not provide proper result of different issues which are present in compensated system. The proposed method is tested for forward power flow, reverse power flow, voltage inversion and current inversion cases. Simulation results show that proposed technique properly detects the direction of fault and locating the exact location of fault. Novelty/ Improvement: This approach deals with detection as well as location identification of fault in compensated system, so it is computationally efficient.

Differential Principle in the Traveling Wave Method of Determining Fault Locations in Overhead Lines with Branches1

The application of the differential principle in the traveling wave method of determining fault locations in overhead lines with branches by using the navigational approach is examined. The least-squares method is used to determine the wave propagation velocity. Results characterizing the accuracy of fault location determination by means of the proposed principle are presented.

Fault-location Observability Analysis on Power Distribution Systems

Most of the fault-location methods developed in the past employed measurements obtained from a limited number of meters installed in a power system. Optimal meter placement in power systems is to make the best use of a limited number of meters available to keep the entire network observable. This article presents the fault-location observability analysis for distribution systems and proposes a novel optimal meter placement algorithm to keep the system observable in terms of fault-location determination. First, the observability of fault location in power systems is defined. Then analysis of the whole system is performed to determine the fewest number of meters needed and the best locations to place those meters to achieve fault-location observability. Case studies based on a 16-bus distribution system have been carried out to illustrate the proposed algorithms.

Fault diagnosis based on PCA for sensors of laboratorial wastewater treatment process

This paper presents a PCA (principal component analysis)-based diagnostic approach, combining the principal component scores with the principal component loadings, to determine the fault location of sensors in a pilot-scale SBR (sequencing batch reactor activated sludge process) wastewater treatment process. The PCA diagnostic model is firstly built with the historical normal data, and the determination of fault location of sensors in wastewater treatment process is further achieved through the combination of the scores with the loadings of principal components. The study results reveal that PCA model can be used to detect faults; the loadings of principal components can well represent the contributions of variables to the principal components; and the scores of principal components give a clear indication of the faulty samples. The feasibility and effectiveness of the application of the combination of score plots with loading plots for sensor fault diagnosis in the wastewater treatment process are well demonstrated in the study.

Fault Location of Uncompensated/Series-compensated Lines Using Two-end Synchronized Measurements

Phasor measurement units have gained great popularity in the field of control and wide-area protection during the last decade. One of the major protection applications based on phasor measurement unit technology is to determine the fault location in a transmission line. Therefore, research has been developed in the field of fault location. This article introduces a generalized model of fault-location algorithm for both uncompensated and series-compensated transmission lines. The proposed algorithm is based on the distributed parameters of the transmission line in the determination of fault location. Moreover, the proposed algorithm utilizes the synchronized measurements of voltages and currents at both ends of the line. The proposed algorithm is general for any allocation of series-compensation elements. The proposed algorithm is tested through the PSCAD offline simulation program (Manitoba Research Center, Manitoba, Canada) and mathematical analysis with the aid of MATLAB (The MathWorks, Natick, Massachusetts, USA).

Determination of Fault Location and Type in Distribution Systems using Clark Transformation and Neural Network

In this paper, an accurate method for determination of fault location and fault type in power distribution systems by neural network is proposed. This method uses neural network to classify and locate normal and composite types of faults as phase to earth, two phases to earth, phase to phase. Also this method can distinguish three phase short circuit from normal network position. In the presented method, neural network is trained by αβ space vector parameters. These parameters are obtained using clarke transformation. Simulation results are presented in the MATLAB software. Two neural networks (MLP and RBF) are investigated and their results are compared with each other. The accuracy and benefit of the proposed method for determination of fault type and location in distribution power systems has been shown in simulation results.

Distance relaying for transmission line using support vector machine and radial basis function neural network

The proposed technique consists of preprocessing the fault current signal samples using discrete wavelet transform to yield the change in energy (ce) and standard deviation (sd) at the appropriate level of decomposition of fault current and voltage signal for faulty phase identification and fault location determination. After feature extraction (ce and sd) from fault current signal, support vector machine (SVM) is used for decision of fault or no-fault on any phase or multiple phases of the transmission line. The ground detection is done by a proposed indicator ‘index’ with a threshold value. Once the faulty phases are identified, the fault location from the relaying point can be accurately estimated using RBFNN (radial basis function neural network) with recursive least square algorithm. For fault location both current and voltage signals are preprocessed through wavelet transform to yield change in energy (ce) and standard deviation (sd) which are used to train and test the RBFNN to provide fault location from the relaying point accurately. The combined SVM and RBFNN based technique is tested for faults with wide range of operating conditions and provides accurate results for fault classification and location determination, respectively.

ANN applications in fault locators

Recent developments indicate that Artificial Neural Networks (ANNs) may be appropriate for assisting dispatchers in operating electric power systems. The fault location algorithm being a key element in the digital relay for power transmission line protection, this paper discusses the potential applicability of ANN techniques for determination of fault location and fault resistance on EHV transmission lines with remote end in-feed. Most of the applications make use of the conventional Multi Layer Perceptron (MLP) model based on back propagation algorithm. However, this model suffers from the problem of slow learning rate. A modified ANN learning technique for fault location and fault resistance determination is presented in this paper. A reasonably small NN is built automatically without guessing the size, depth, and connectivity pattern of the NN in advance. Results of study on a 400 kV transmission line are presented for illustration purposes. Performance of the modified ANN is compared with the analytical algorithms and conventional MLP algorithm for different combinations of pre-fault loading condition, fault resistance and fault location. The results are found to be encouraging.

Synchronized sampling improves fault location

Transmission line faults must be located accurately to allow maintenance crews to arrive at the scene and repair the faulted section as soon as possible. Rugged terrain and geographical layout cause some sections of power transmission lines to be difficult to reach. Therefore, robustness of the accurate fault location determination under a variety of power system operating constraints and fault conditions is an important requirement. This article introduces a unique concept of high-speed fault location that can be implemented either as a simple add-on to the digital fault recorders (DFRs) or as a stand-alone new relaying function. This advanced concept is based on the use of voltage and current samples that are synchronously taken at both ends of a transmission line. This sampling technique can be made readily available in some new DFR designs incorporating receivers for accurate sampling clock synchronization using the satellite Global Positioning System (GPS). >

Development of fault characterization equipment (FCAREC) for power transmission lines

The authors present fault characterization equipment (FCAREC) which detects fault resistances in a time sequence, in addition to the conventional determination of fault location. The objective of FCAREC is to offer improved functions to estimate causes of system faults. The equipment works by solving a circuit equation, using voltage and current data and line constants at each end of a particular line. To reduce the effects of data measurement errors, a high-precision calculation based on the least squares method is used. Since December 1989, the prototype FCAREC equipment has been used in feasibility tests on 154 kV parallel double transmission lines. During the tests, three power system faults were experienced and satisfactory results were obtained in all cases. >

Imaging discontinuities on seismic sections

In routine seismic processing, normal moveout (NMO) corrections are performed to enhance the reflected signals on common‐depth‐point or common‐midpoint stacked sections. However, when faults are present, reflection interference from the two blocks and the diffractions from their edges hinder fault location determination. Destruction of diffraction patterns by poststack migration further inhibits proper imaging of diffracting centers. This paper presents a new technique which helps in the interpretation of diffracting edges by concentrating the signal amplitudes from discontinuous diffracting points on seismic sections. It involves application to the data of moveout and amplitude corrections appropriate to an assumed diffractor location. The maximum diffraction amplitude occurs at the location of the receiver for which the diffracting discontinuity is beneath the source‐receiver midpoint. Since the amplitudes of these diffracted signals drop very rapidly on either side of the midpoint, an appropriate amplitude correction must be applied. Also, because the diffracted signals are present on all traces, one can use all of them to obtain a stacked trace for one possible diffractor location. Repetition of this procedure for diffractors assumed to be located beneath each surface point results in the common‐fault‐ point (CFP) stacked section, which shows diffractor locations by high amplitudes. The method was tested for synthetic data with and without noise. It proves to be quite effective, but is sensitive to the velocity model used for moveout corrections. Therefore, the velocity model obtained from NMO stacking is generally used for enhancing diffractor locations by stacking. Finally, the technique was applied to a field reflection data set from an area south of Princess well in Alberta.