Fault Location In Distribution Networks Research Articles

Fault Location in Active Distribution Networks Containing Distributed Energy Resources (DERs)

This paper presents a simple yet effective method for locating faults in radial distribution networks where impedance-based methods are known to have limitations, especially in the presence of inverter-based power sources (IBPS). The proposed approach utilizes the Discrete Wavelet Transform (DWT) to capture the first arrival times of the fault-generated traveling waves. It is assumed that a digital fault recorder (DFR) exists at the terminal node of every lateral, as well as the beginning and end of the main feeder. The detailed derivation of the fault location method is presented, and illustrative fault scenarios are simulated to experimentally verify the proposed algorithm's performance under very diverse conditions. It is shown that the proposed approach performs successfully irrespective of the unknown fault impedance, inception angle, and type.

Method for fault location in a low-resistance grounded distribution network based on multi-source information fusion

Several uncertain factors, such as the protection and circuit breaker refusing operation and misoperation, make it difficult to obtain accurate results based on a single fault location using the switching quantity. So this study proposes a power grid fault location method via multi-data source information fusion. The compressed sensing algorithm is used to reconstruct the electrical signal twice, and the rough fault range and electrical quantity fault degree are obtained respectively. Subsequently, the Bayesian network is used to obtain the switching fault degree of each element in the rough fault range. Finally, DS evidence theory fuses these two fault degrees to obtain the location result. PSCAD software builds an IEEE 14 node system, and the effectiveness of the proposed method is verified by simulation. Furthermore, it can quickly and accurately locate the fault after its occurrence and has good application prospects with respect to the fault location of a low-resistance grounded distribution network.

Analysis of Distributed Power Access on Distribution Network Fault Location and Voltage Quality

Distributed Generation (DG) has a certain impact on distribution network fault location and voltage quality during the access process, which is worth studying. In this paper, the impact of distributed power on the two is discussed separately, and further technical analysis is carried out with an example.

Research on IACA of distribution network fault location

In power system, the probability of distribution network failure is the highest, which will directly affect the power consumption experience of customers. The timely and accurate fault location of distribution network is very important to improve the reliability of power supply. In this paper, firstly, the switch function and evaluation function of distribution network fault location are discussed. ACA(Ant Colony Algorithm) algorithm has some defects such as premature convergence. In order to solve this problem, the IACA(Improvement Ant Colony Algorithm) method is proposed. Finally, the feasibility and effectiveness of the new method are verified by establishing a simple distribution network model.

Hybrid classifier for fault location in active distribution networks

This paper presents a fast hybrid fault location method for active distribution networks with distributed generation (DG) and microgrids. The method uses the voltage and current data from the measurement points at the main substation, and the connection points of DG and microgrids. The data is used in a single feedforward artificial neural network (ANN) to estimate the distances to fault from all the measuring points. A k-nearest neighbors (KNN) classifier then interprets the ANN outputs and estimates a single fault location. Simulation results validate the accuracy of the fault location method under different fault conditions including fault types, fault points, and fault resistances. The performance is also validated for non-synchronized measurements and measurement errors.

An edge computing method using a novel mode component for power transmission line fault diagnosis in distribution network

The commonly used fault diagnosis method of the power transmission line (PTL) is the traveling wave method which uses the traditional mode components $$\alpha $$ , $$\beta $$ and o to realize the fault type recognizing and the fault location in distribution network. However, the traditional mode components of the traveling wave method may take the value of zero that cannot provide the effective fault feature for the A-phase ground fault, or the A and B double phases short-circuit fault. Moreover, a single traditional mode component cannot recognize all the types of the faults, and the fault recognition has to use the multiple mode components that increases the complexity. To address the aforementioned issues, this paper proposes an edge computing scheme based on a novel mode component $$\gamma $$ for PTL fault diagnosis in distribution network. Firstly, the novel mode component $$\gamma $$ is fused according to the traditional mode components $$\alpha $$ and $$\beta $$ , then the propagation property of the traveling wave- $$\gamma $$ is derived. Secondly, the edge computing scheme and the PTL fault diagnosis method are designed for distribution network by using the only novel mode component $$\gamma $$ . Thirdly, the relationship table of the fault type and the boundary conditions as well as the component $$\gamma $$ expressions is derived for the fault recognition using the only traveling wave- $$\gamma $$ . In addition, the fault distance computing is explored by using the traveling wave- $$\gamma $$ . The computing is composed with the wave- $$\gamma $$ head identification using the optimal Wavelet vanishing moment parameter, and the arrival time determination, and the fault location method. To evaluate the efficiency of the proposed edge computing scheme, the simulation experiment and the laboratory tests are conducted. The simulation experiment results show that, the novel mode component $$\gamma $$ not only provides the effective fault features for all the ten types of the power transmission line faults, but also increases fault locating accuracy by the average 2.08 % compared with the methods using the traditional mode component $$\alpha $$ , $$\beta $$ and o. Meanwhile, the laboratory tests show that the edge computing method is practical.

Deep‐Belief‐Networks Based Fault Classification in Power Distribution Networks

Accurate fault classification is the premise of fault location and management study in a power distribution network. In most of the traditional fault classification methods used in power distribution network, the characteristic quantities are selected by experience, which will increase the uncertainty of fault classification results. A novel fault classification method based on deep belief networks (DBN) is proposed in this paper. Samples of fault current and voltage are preprocessed by min–max standardization and waveform splicing firstly, then they are used to train the DBN together with fault type label. Characteristic quantities of the current and voltage will be automatically extracted by the well‐trained DBN model, and the reliable fault type classification of distribution network can be realized. Simulation and experimental results show that the fault classification method is suitable for distribution network, and it has not only characteristics of obvious fault feature extraction and high fault classification accuracy, but also has good adaptability while the neutral grounding modes changing or used in power distribution network with distributed generator. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

A random forest-based approach for fault location detection in distribution systems

Finding the fault location in distribution network is difficult in comparison to transmission network based upon high branching and high impedances composed of the contact with environmental factors when a fault occurs. For this matter, the possible faulty section is identified and then the fault location is determined with the proposed algorithms in this study. Wavelet transform is applied to the current–voltage data along with feature extraction methods, and then, Random Forest is used for identifying the faulty section and estimating the fault location. To approve the validation, the algorithms are applied to IEEE-34 node test feeder. Single-phase to ground faults regarding different impedance values at different points of the feeder have been effectively detected by using single measurement point data from the sending end of the feeder.

Reflected Traveling Wave Based Single-Ended Fault Location in Distribution Networks

Traveling wave (TW)-based fault-location methods have been used to determine single-phase-to-ground fault distance in power-distribution networks. The previous approaches detected the arrival time of the initial traveling wave via single ended or multi-terminal measurements. Regarding the multi-branch effect, this paper utilized the reflected waves to obtain multiple arriving times through single ended measurement. Potential fault sections were estimated by searching for the possible traveling wave propagation paths in accordance with the structure of the distribution network. This approach used the entire propagation of a traveling wave measured at a single end without any prerequisite of synchronization, which is a must in multi-terminal measurements. The uniqueness of the fault section was guaranteed by several independent single-ended measurements. Traveling waves obtained in a real 10 kV distribution network were used to determine the fault section, and the results demonstrate the significant effectiveness of the proposed method.

Physics-based analytical model for high impedance fault location in distribution networks

This paper presents a physics-based analytical model for high impedance fault location in power distribution systems. The presented analytical solution is composed by two interdependent processes. First, fault distance is estimated through a Weighted Least Square approach applied to solve an overdetermined and nonlinear algebraic system of equations. Second, an analytical method based on the statistical behavior of the estimates obtained from the frequency domain system model solution is presented to address the multiple estimates problem, identifying the faulted section. The presented fault location physics-based analytical model considers the capacitive effect of distribution lines. Furthermore, voltages and currents measured from only one terminal are used. The formulation is evaluated using the IEEE 13-bus and a modified version of the IEEE 34-bus test feeders. Comparative analysis with state-of-the-art methods is presented. Average errors of 1.95% are obtained. Easy to implement analytical model, without hard to derive parameters, built on the weighted least squares state estimator, highlight potential aspects for real-life applications.

Edge Computing-Based Fault Location in Distribution Networks by Using Asynchronous Transient Amplitudes at Limited Nodes

The feeders in distribution networks can be generally classified into two types: homogenous and hybrid feeders. Hybrid feeders consist of non-homogeneous line segments. In this paper, a fault location scheme is proposed for distribution grids with both homogenous and hybrid feeders using the edge computing. The standard transient amplitude ratio arrays of the hybrid feeders are first constructed and stored at the edge nodes. Then, an accurate fault location model is trained by the radial basis function neural network and stored in the substation server. To achieve this goal, the transients are first sampled at the measurement nodes and transmitted to the edge nodes nearby. The amplitudes are then extracted to determine the faulty branch. For a hybrid feeder, the actual amplitude ratio array is compared with the standard one to identify the faulty line segment. Finally, the amplitude ratio of the two transient components with different frequencies at one terminal of the faulty section is computed and transmitted to the server. Based on the model of a distribution network built by PSCAD/EMTDC, extensive fault simulations are studied. The results demonstrate the effectiveness of the scheme.

A Model-Based Design of Distributed Automation Systems for the Smart Grid: Implementation and Validation

The paper aims at describing a model-based approach to design automation logics for fault location and supply restoration in medium voltage distribution networks. The application of automation functions along medium voltage feeders and, in particular, the installation of protection devices in secondary substations mandates the design and the implementation of complex logics to coordinate the operations of this hardware in case of fault occurrences. This synchronization is realized with the exchange of IEC 61850 GOOSE messages, but the correct usage of this information must be implemented in each protection device through dedicated logics, which are not in the common out-of-the-box system configurations. To support the introduction and the design of these logics, an automata-based approach has been proposed and successfully demonstrated in a real environment in the European research project IDE4L. This formal methodology has been introduced to simplify the design phase and to standardize the logics implemented in the protection prototypes realized in the project. The same models have also been used in the implementation phase with a semi-automatic code generation procedure, considering as a target system the software programmable logic controllers (soft-PLCs), available on the protection devices. Based on the test results and the short time to set up the test bench, this approach proved to be a reliable and effective way to implement complex medium voltage (MV) automation logics such those needed in modern smart grids.

A Novel Fault Let-Through Energy Based Fault Location for LVDC Distribution Networks

Low Voltage Direct Current (LVDC) distribution systems have recently been considered as an alternative approach to electrical system infrastructure as they provide the additional flexibility and controllability required to facilitate the integration of more low carbon technologies (LCTs). However, DC protection systems and, more specifically high accuracy DC fault location, have been recognised as a key challenge to facilitating post-fault network maintenance. Most of the existing fault location techniques rely on current derivative or communications-based methods that are either very sensitive to noise or require a high level of data synchronisation. Fault energy has been recognized as a reliable indicator of more accurate fault location estimations. Therefore, this paper develops a mathematical model for describing fault energy during the transient period of DC faults. The method subsequently proposes a new fault let-through energy based DC fault location working strategy to facilitate post-fault network maintenance. The proposed method does not require data synchronisation regardless of the voltage, current, and the size of the converters connected to the LVDC feeder. The capabilities of the proposed fault location strategy are validated against different faults applied on an LVDC test network in PSCAD/EMTDC and shown to be more reliable and accurate than existing methods.

Impact of Resistive Superconducting Fault Current Limiter and Distributed Generation on Fault Location in Distribution Networks

Resistive Superconducting Fault-Current limiters (r-SFCL) appear as a new attractive technology to address faults in power grids. Based on a new generation of superconductors, referred to as High-Temperature Superconductors (HTS), they could offer economical benefits compared to more conventional technologies. To understand their impact on the electrical networks, two models of r-SFCL, differing by their complexity, were built to conduct short-circuit analysis. Different fault locations in distribution networks were studied in the standard IEEE 13-node and 34-node test feeders. Both models were validated against experimental data and then cross-checked in the IEEE 13-bus distribution system to determine their relative accuracy when used in practical power grids. Subsequently, using the simplest electrical model of r-SFCL, the 34-bus test system incorporating Distributed Generation (DG) was used to analyze short circuits. It was found that the presence of r-SFCL increases the error of the fault location algorithm. However, it was also demonstrated that a single r-SFCL enables the incorporation of several additional DG in a distribution network by reducing the fault current level by at least 45% depending on its design characteristics and the number of added DG. Finally, an improved algorithm is presented. This algorithm takes into account the r-SFCL resistance in order to reduce the fault location error.

Fault Location in Low-Voltage Distribution Networks based on Reflectometry – A Case Study

This research was funded by the “Ministerio de Ciencia, Innovacion y Universidades – Agencia Estatal de Investigacion” grant number “RTC-2017-6782-3” and the European Union FEDER funds with name “LOcalizacion de averias, monitorizacion de estado y Control en redes de bAja TEnsion—LOCATE”.

Modeling and simulation of intermittent arc effects on traveling wave based fault location techniques for distribution network

With rapidly developing of the distribution networks the rate of the earth fault increases sharply. Aiming to fault location for distribution networks, many techniques are proposed and applied in distribution networks throughout the world. However, until now the technology for precise fault point location has not been successfully implemented in engineering practice. Traveling wave based methods as common techniques are widely applied in transmission line protection for locating fault point. However, these methods face severe challenge in fault location for distribution networks. The main reason is that the intermittent arc fault easily results in failure of detecting inceptive travelling wave and this intermittent arc is a common earth fault in distribution networks compared with transmission networks. In this paper, a simplified distribution line is built by making reference to the two parallel lossless transmission lines system. Then, the intermittent arc effects on traveling wave based method are modeled and discussed. Finally, the reason why these travelling wave based methods are hard to locate fault point precisely is illustrated.

Analysis of traveling wave based fault location method for distribution network with image processing

Laws of traveling wave data related to fault location for medium voltage distribution network are discussed and summarized. Given the tree structure of a distribution network, an image of nodes voltage is created combining the use of real-time traveling wave meters at all nodes of the tree. The novelty of this paper is that travelling wavefront are analyzed based on the dynamic changes of these images. Based on principle of the traditional fault location with traveling wave-based method for transmission networks, traveling wave data of fault location for medium voltage distribution networks are plotted in order to estimate propagation velocity and distance between the fault position and the reference node. The results indicate that taking advantage of the laws of data related to first wave front can improve the reliability of the fault location for medium voltage networks.

High Impedance Fault Detection and Location in Combined Overhead Line and Underground Cable Distribution Networks Equipped with Data Loggers

Power distribution networks are vulnerable to different faults, which compromise the grid performance and need to be managed effectively. Automatic and accurate fault detection and location are key components of effective fault management. This paper proposes a new framework for fault detection and location for smart distribution networks that are equipped with data loggers. The framework supports networks with mixed overhead lines and underground cables. The proposed framework consists of area detection, faulty section identification, and high impedance fault location. Firstly, the faulty zone and section are detected based on the operation of over-current relays and digital fault recorders. Then, by comparing the recorded traveling times at both ends of lines, which are related to the protection zone, the faulty line is identified. In the last step, the location of the fault is estimated based on discrete wavelet transform. The proposed method is tested on a 20 kV 13 node network, which is composed of overhead lines and underground cables. The method is tested in both balanced and unbalanced configurations. The obtained results confirm the advantages of the proposed method compared with the current state-of-the art.

A New Method for Fault Location in Distribution Networks Based on Voltage Sag Measurements

This paper presents an innovative method for fault location in distribution networks based on classical circuit analyses. Two synchronized and few nonsynchronized pre- and during-fault voltages are required at few buses along with the impedancematrix. A new impedance matrix manipulation procedure is proposed so that the distribution system is investigated in partitions across multiple subsystems. This procedure allows the fault location process to be performed by solving systems of determined equations, making the method more technically accessible. The fault is located by analyzing the voltage sag at the terminal-bus of each subsystem separately. The proposed method is validated on the IEEE 33-bus, 12.66 kV distribution system with/without distributed generation (DG). Simulation results show the robustness and accuracy of the method under several pre- and during-fault scenarios and measurements errors.

Fault Location in Radial Distribution Network Based on Fault Current Profile and the Artificial Neural Network

Abstract Electricity distribution systems are subject to a variety of faults such as permanent and transient short circuits due to the extent and multiplicity of equipment. In principle, short circuit fault causes the existing protective equipment to operate and to no electricity the various parts of the distribution network. Rapid and accurate determination of fault location, repair and recovery, it has not prevented the distribution of energy. This will satisfy consumers and prevent the losses of electricity companies. In this paper, the artificial neural network and fault current profiles are used to determine the distance of the fault, determine the type of fault and detect the short circuit. This method provides the information needed to locate the fault by sampling the current before and after the fault occurs from the SCADA system. The effect of connectivity local resistance changes and the effect of load changes on fault location were evaluated. The results show that this method is more accurate than the voltage droop profile variation method in determining the fault distance and short circuit breakdown. If only the net fault current changes profile is used, the effect of the load changes in determining the short-circuit breakdown is much less.