Accurate Fault Location Research Articles

Fault Location of Grid-connected Microgrid Lines Based on AVMD and Double-ended Traveling Wave Ranging

To enhance the accuracy of fault location in microgrid lines, a fault location method based on adaptive variational mode decomposition (AVMD) and double-ended traveling wave ranging is proposed. Firstly, a microgrid radial structure model, incorporating wind, light, and water systems, is established. The parameters of variational mode decomposition are optimized by using the Aquila optimizer (AO) algorithm, allowing the original fault signal to be decomposed into multiple modal components using AVMD. Only a limited number of modal components retain the fault signal information. The effective weighted peak relevance index (EWPR) is employed to select the sensitive modal components, identified as the four modes that best preserve the fault information, for signal reconstruction. Finally, the reconstructed signal is applied for fault localization. Simulation results indicate that the proposed method is scarcely influenced by the fault type, exhibiting superior accuracy compared to the single-ended traveling wave method.

Ground fault identification and location of autotransformer traction network for high‐speed railway based on multi‐terminals synchronous measure information

AbstractWith the rapid development of high‐speed railway, the auto‐transformer traction network (ATN) is also expanding. However, due to the improved performance of electric multiple units (EMUs) and the non‐linear relationship between impedance and ground fault distance, distance protection has limited coverage and cannot accurately locate the fault distance by measuring impedance. This paper presents a model of the ATN considering the presence of EMUs, which effectively demonstrates the characteristics of current distribution under the ground faults. Furthermore, a ground fault identification method based on multi‐terminal currents is proposed to enhance the accuracy of fault identification and differentiate faults and EMUs. The mapping relationship between current distribution and fault location is derived, and an accurate fault location method is proposed. Compared to existing methods, this method is not affected by EMUs and AT parameters. The fault identification and location scheme for ATN employs multi‐terminal synchronous information. Finally, through simulation and experimental setups, case studies have been conducted to verify the accuracy and robustness of the proposed method in various fault scenarios. Certainly, this research has significant application prospects in fault analysis and detection for HSR.

A Fault Location Method for Medium Voltage Distribution Network Based on Ground Fault Transfer Device

The arc suppression device based on ground fault transfer (GFT) has been preliminarily applied in the medium voltage distribution network (MVDN). An accurate travelling wave (TW) fault location method is proposed to extend the use of the ground fault transfer device. D-PMU is used as a travelling wave detection tool to record the transient voltage travelling waves of fault grounding and bus active grounding during arc suppression. Then, the faulty section is identified through the time difference of travelling wave arrival at the upstream and downstream measurement points. On this basis, the fault location equations of the arrival time and distance of the upstream travelling wave are established, and an accurate fault location method based on the arrival time difference of the travelling wave is proposed. The simulation model is established by PSCAD/EMTDC, and the results show that the method has high location accuracy, and the absolute error is less than 30 m. It is not affected by the TW velocity, the fault conditions, or the distributed power sources.

End Face Attitude Detection of Special Steel Bars Based on Improved DBSCAN

An end face attitude detection system for special steel bars is designed to solve the problem of defect localization for steel bar grinding. A circle detection method based on improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is proposed for calculating special steel bars’ end face attitude. Firstly, the images are subjected to edge detection, connected region marking, and improved DBSCAN in accordance with the image characteristics. After that, the arcs belonging to the same circle are clustered into the same category to create virtual connected regions. Then, circle parameters of a virtual connected region are clustered using an improved DBSCAN algorithm. The actual circle parameter is obtained by calculating the centroid of each category. Finally, the vector is generated under the set coordinate system, passing through the center of the circumcircle of the steel bar end and one endpoint of the two-dimensional code, and the angle of the vector is calculated to determine the attitude of the special steel bar’s end face. The experimental results demonstrate that the method can obtain an attitude angle resolution of 0.2 degrees with an error range of ±0.1 degrees. This will provide accurate defect localization support for the digitization and intelligence of the grinding platform on the special steel bar production line.

Accurate Fault Location Method Based on Time-Domain Information Estimation for Medium-Voltage Distribution Network

The sampling rate of the wide-area synchronous phasor measuring device (D-PMU) in the distribution network is insufficient, and the localization sensitivity of the traditional localization method based on the time-domain Bergeron equation in the distribution network is insufficient. In this paper, an accurate location method of the distribution line grounding fault based on the time-domain’ synchronous information calculation is proposed to solve the problem of limited location accuracy caused by a low sampling rate and the insufficient sensitivity of traditional methods. The method preprocesses the measurement data through low-frequency time-domain signal reconstruction and cubic spline interpolation. The fault current’s different location criterion is constructed by using the voltage and current constraints at the fault point. By calculating the fault current difference at a limited number of calculated points, the accurate fault location under a low sampling rate is realized, which is beneficial to the rapid maintenance of faults and the shortening of the power outage time.

Research on Belt Deviation Fault Detection Technology of Belt Conveyors Based on Machine Vision

Traditional belt deflection detection devices for underground belt conveyors in coal mines have problems, such as their single function, poor fault location and analysis accuracy, low automation level, and low reliability. In order to solve the defects of traditional detection devices, the belt deviation faults of the underground belt conveyor transport process require to be detected effectively and reliably. This paper proposes a belt deviation detection method based on machine vision. This method makes use of a global adaptive high dynamic range imaging method to complete the brightness enhancement processing of the underground image. Then the straight-line features of the conveyor belt edges are extracted using Canny edge detection and the Hough transform algorithm. In addition, a dual-baseline localization judgment method is proposed to realize the identification of band bias faults. Finally, a test bench for belt conveyor deviation was built. Testing experiments for different deviations were conducted. The accuracy of the tape deviation detection reached 99.45%. The method proposed in this study improves the reliability of belt deviation fault detection of underground belt conveyors in coal mines and has wide application prospects in the field of coal mining.

High pass filter based traveling wave method for fault location in VSC-Interfaced HVDC system

Due to the difficult topography and bad weather conditions across large distances, dc line breakdown is a serious danger to the safety of high-voltage direct-current systems (HVDC). Thus, there is a need of an accurate and reliable fault location method to safely isolate the dc grid in the occurrence of a dc fault. Traveling wave (TW) fault location techniques have gained in popularity over the decades, with the expectation that power networks will become considerably more credible and accurate throughout. However, in the existing traveling wave based location, the signal processing methodology for extracting the wave front consumes too many computer resources, necessitating the development of a new location method with a fast response and high accuracy. In this paper, a new algorithm of TW based on high pass filter is proposed, it can differentiate the TW peak more easily by removing the oscillation in a signal. To ensure more accuracy double ended method (Type D) is used to obtain the location for the fault. The theory behind this new algorithm is presented in detail. High pass filter is designed for this purpose and its validity tested on point to point (P2P) dc simulation model which is created in PSCAD software to gather the voltage data from both terminals during transient. Following that the proposed fault location algorithm is executed in the MATLAB environment to get the fault location results. A comparison of the proposed algorithm with two popular methods namely the wavelet transforms (WT) and the single ended method highlights the superiority.

Enhancing Resilience and Reliability of Active Distribution Networks through Accurate Fault Location and Novel Pilot Protection Method

The integration of distributed generation (DG) into the decentralized access of the distribution network transforms the existing structure into an active distribution network. The alteration in fault characteristics poses significant challenges to the coordinated operation of relay protection. Fault location within the distribution network plays a vital role in facilitating fault recovery and enhancing the resilience of the power system. It proves instrumental in improving the network’s ability to withstand extreme disasters, thereby enhancing the reliability of power distribution. Therefore, this paper provides a detailed analysis of the voltage fault components occurring during various fault types within an active distribution network. Building upon the identified characteristics of voltage fault components, a novel approach for the longitudinal protection of active distribution networks is proposed. This method involves comparing the calculated values of voltage fault components with their actual values. The proposed approach is applicable to various fault scenarios, including short-circuit faults, line break faults, and recurring faults. It exhibits advantages such as insensitivity to the penetration of distributed power supplies and robustness in withstanding transition resistance. The simulation results validate the effectiveness of the proposed method, affirming its applicability to diverse protection requirements within active distribution networks.

Novel travelling wave fault location approach for overhead transmission lines

Travelling wave fault location approach for overhead transmission line is widely applied in actual power grid, which has better fault location accuracy comparing with conventional power frequency data based method. However, travelling wave fault location approach is highly related to the frequency distortion phenomenon of travelling wave propagation velocity, which includes two parts: (i) the distortion caused by reflection and refraction phenomena of transformer substation and (ii) the attenuation caused by distributed resistance of transmission line. Therefore, aiming to improve the fault location accuracy, the paper contributes to two aspects: (i) the complete theoretical analysis of the distortion phenomenon of travelling wave signal and (ii) the improved travelling wave fault location approach considering distortion phenomenon. Eventually, based on PSCAD/EMTDC simulation tool, a typical 500 kV case study model is established to verify the fault location accuracy of proposed travelling wave fault location approach under the influences of fault type issue, fault location issue and grounding resistance issue.

Power supply station equipment status monitoring and evaluation system based on wireless network technology

With the continuous development of the power industry and the acceleration of the process of intelligence, monitoring and analyzing the status of power supply equipment is crucial for ensuring power supply and safety. Traditional power monitoring systems still have certain problems in data transmission. Using wireless network technology (WNT) to detect and analyze the status of power supply station equipment can not only achieve real-time monitoring and remote control, improve equipment operation and management efficiency, but also achieve automated monitoring and analysis of equipment status, providing technical support for the intelligence of power supply station equipment. In order to verify the effectiveness of the WNT-based power supply station equipment status monitoring and analysis system, a comparative experiment was conducted with traditional wired network monitoring methods. The final experimental results show that the average feedback time for testing the WNT power supply station equipment status monitoring and analysis system is 7.71 s, which is 38.22 s shorter than traditional methods. The average fault location accuracy is 95.98 %, which is 35.91 % higher than traditional methods. The average management efficiency is 92.88 %, which is 34.71 % higher than traditional methods. Through testing data, it can be concluded that the power supply station equipment status monitoring and analysis system based on WNT has greater advantages than traditional power equipment monitoring methods.

Fault-Location Accuracy of Natural Frequencies Using Incomplete HVDC Station Models

This paper investigates how the accuracy of fault location estimated from a transmission line's natural frequencies is affected by imperfect modeling of HVDC power-converter sta- tions. These systems include a large number of devices each with specific frequency-dependent characteristics, as filters, reactors and surge protection systems. While it is well-known that location errors may ensue from inaccurate termination models, it is not clear to what extent location accuracy is affected when neglecting one or more of these devices. Results show significant differences depending on the kind of transmission line and the reactor inductance. Including reactors is found not to completely avoid errors, proving the need to take into account the reactive behavior of the converter, which strongly varies according to the HVDC technology. A notable source of errors is level repulsion between station and line resonances, a phenomenon observed when the converter station presents self resonances, e.g., due to DC filters and stray capacitances in reactors. Significant loss of sensitivity to the fault position is found in these cases, impairing fault-location resolution. The first, or dominant, natural frequency of the line is more strongly affected by all these phenomena, suggesting that the standard choice of using the dominant resonance may not be an optimal strategy. Higher-order resonances are instead found to be more robust against inaccurate converter models, and appear to be more suitable for accurate fault location in case of uncertainties about the converter model.

Two-stage UHV GIL Fault Location Based on Ultrasonic Sensor Network

The failure of a long-distance Ultra-high voltage (UHV) Gas Insulated Transmission Line (GIL) during operation will cause great security risks to power transportation. How to locate GIL faults quickly and accurately and further carry out related operation and maintenance work is of great significance to the stable operation of the power grid. Based on this, this paper proposes a two-stage fault location method for UHV GIL based on an ultrasonic sensor network. In this method, ultrasonic sensors are configured in the shell of GIL to form an ultrasonic sensor network and internal faults are located by analyzing the signals collected from the network. The method is divided into two stages: 1) according to the collected signal data, the two sensors closest to the fault point are preliminarily identified, and then the fault point is roughly located, and obtain the data collected by the sensors; 2) we analyze sensor signal data, train and establish a network model based on recurrent neural network RNN for accurate fault location. The verification experiment shows that this method has fast location speed and high location accuracy, and can be effectively applied for quick maintenance, safe operation, and maintenance of GIL.

A novel fault location strategy based on Bi‐LSTM for MMC‐HVDC systems

AbstractThe integration of modular multilevel converters (MMCs) with high voltage direct current (HVDC) transmission systems is an efficient method for transporting electricity from distant renewable energy sources to demand centres. However, MMC‐HVDC systems face reliability challenges during DC overcurrent faults, often caused by component failures that can lead to HVDC network shutdowns. Consequently, a reliable fault location approach is crucial for grid protection and restoration, aiding in fault isolation and alternate power flow identification. Conventional fault location methods struggle with manual protective threshold setting, susceptibility to fault resistance and noise, and the need for communication channels, resulting in signal delays. In multi‐terminal HVDC networks, fault location becomes even more complex due to poor selectivity and sensitivity in traditional schemes. This study proposes a robust fault location approach based on bidirectional long short‐term memory (bi‐LSTM). The method offers a simplified decision‐making model with low computational requirements, utilizing fault features from one end of the network, eliminating the need for a communication channel. Remarkably, this approach achieves high fault location accuracy, even with varying fault types, resistances, and noise levels, as demonstrated by an MSE of 0.006 and a percentage error below 1% in simulations conducted using a real‐time simulator with MATLAB/Simulink.

An accurate unsynchronized fault location method on practically transposed transmission lines with closed-form solutions

This paper proposes an unsynchronized two-terminal fault location method on three phase practically transposed transmission lines.Compared to the existing fault location methods, the proposed method considers the asymmetry of the practically transposed transmission lines during the fault in practice. First, the proposed method constructs the practically transposed transmission lines by connecting three untransposed transmission line sections. For each section, the fully distributed parameters line model is adopted to ensure the modeling accuracy. According to the physical laws that the line should obey, the unsynchronized angle is estimated with analytical formulation before the fault. Next, the closed-form solutions of fault location are derived for different fault events, to avoid the risks of unconvergence using the iterative algorithms. In the numerical experiments, the proposed method shows higher accuracy of fault location than the existing fault location methods, regardless of fault types, locations and impedances. The proposed method also demonstrates robustness against various unsynchronized angles, loading conditions, measurement noises and line lengths.

UniLoc: Unified Fault Localization of Continuous Integration Failures

Continuous integration (CI) practices encourage developers to frequently integrate code into a shared repository. Each integration is validated by automatic build and testing such that errors are revealed as early as possible. When CI failures or integration errors are reported, existing techniques are insufficient to automatically locate the root causes for two reasons. First, a CI failure may be triggered by faults in source code and/or build scripts, whereas current approaches consider only source code. Second, a tentative integration can fail because of build failures and/or test failures, whereas existing tools focus on test failures only. This article presents UniLoc, the first unified technique to localize faults in both source code and build scripts given a CI failure log, without assuming the failure’s location (source code or build scripts) and nature (a test failure or not). Adopting the information retrieval (IR) strategy, UniLoc locates buggy files by treating source code and build scripts as documents to search and by considering build logs as search queries. However, instead of naïvely applying an off-the-shelf IR technique to these software artifacts, for more accurate fault localization, UniLoc applies various domain-specific heuristics to optimize the search queries, search space, and ranking formulas. To evaluate UniLoc, we gathered 700 CI failure fixes in 72 open source projects that are built with Gradle. UniLoc could effectively locate bugs with the average mean reciprocal rank value as 0.49, mean average precision value as 0.36, and normalized discounted cumulative gain value as 0.54. UniLoc outperformed the state-of-the-art IR-based tool BLUiR and Locus. UniLoc has the potential to help developers diagnose root causes for CI failures more accurately and efficiently.

Study on Single-phase Ground Fault Localisation in Distribution Networks Based on Transient Travelling Waves

China's low and medium voltage distribution networks are mostly grounded by small currents, and single-phase grounding faults are frequent and their fault characteristics are weak, so that the traditional fault localization schemes may fail. In order to effectively solve the problem of single-phase grounding fault localization in distribution networks, the traveling wave localization technology is applied in distribution networks, which is expected to realize fast and accurate fault localization in distribution networks. Firstly, the paper analyzes the characteristics of traveling wave signals in distribution networks and those in transmission networks, and proves the feasibility of the traveling wave localization method applied to distribution networks. Secondly, the transient electrical quantities after a single-phase ground fault occurs in the distribution network are characterized, and it is concluded that in the fault transient process, nonlinear and nonsmooth signals appear in the faulted and non-faulted lines, and effective information is extracted for fault localization using the traveling wave method. Finally, in the case of abnormal traveling wave data during fault localization, single-end localization is carried out using the initial wave head arrival moment and reflection wave arrival moment of the traveling wave signal of the side branch to ensure accurate localization, and simulation verification is carried out using PSCAD/EMPDC.

An Open-Circuit Fault Diagnosis Method Based on Adjacent Trend Line Relationship of Current Vector Trajectory for Motor Drive Inverter

This paper proposes a power switch open-circuit (OC) fault diagnosis method for a motor drive inverter system. This method utilizes adjacent trend lines to extract fault features from the current vector trajectory, enabling rapid fault diagnosis and localization. Firstly, the current vector trajectory is obtained by applying the Clark transformation to the three-phase currents, and trend line slopes are calculated using equidistant current signal nodes. Subsequently, the method determines fault by calculating changes in adjacent trend line slopes and quickly locates the faulty power switch by considering the average slope of adjacent trend lines and the beta-axis current direction in the alpha–beta coordinate system. Accurate OC fault localization can be achieved with just a few trend line data points calculated in each current cycle, reducing the extra hardware and computational burden. This method is not only suitable for load variations but also applicable to the diagnosis of both single-switch and multiple-switch faults. Finally, simulation and experimental results validate the effectiveness and robustness of the method.

Engineering fault intelligent monitoring system based on Internet of Things and GIS

Abstract The power grid (referred to as PG for convenience) structure is becoming increasingly complex. Aiming at the problem that it is difficult for traditional PG monitoring methods to accurately detect PG faults, an intelligent PG fault monitoring system is constructed using Internet of Things (IoT) and geographic information system (GIS) to improve the effectiveness of fault monitoring. The sensor equipment is used to collect the current information in the circuit, and the change of induced current is used to judge the cause of the fault, and the fault information is transmitted to the monitoring center through communication technology. The staff can directly locate the geographical location of the fault in the visual interface. One hundred overhead lines of Xianyang Power Supply Company are selected for analysis, and the performance of the traditional PG monitoring method and intelligent PG fault monitoring system is compared. The average fault detection accuracy of the traditional PG monitoring method and the system proposed in this article is 72.0 and 94.8%, respectively. The average fault location accuracy of the traditional PG monitoring method and this system is 80.8 and 96.5%, respectively. The intelligent monitoring system of PG fault based on IoT and GIS has high accuracy in PG fault detection and fault location, which can improve the effectiveness of fault monitoring.

Fault location of untransposed double-circuit transmission lines based on an improved Karrenbauer matrix and the QPSO algorithm

Some double-circuit transmission lines are untransposed, which results in complex coupling relations between the parameters of the transmission lines. If the traditional modal transformation matrix is directly used to decouple the parameters, it can lead to large errors in the decoupled modal parameter, errors which will be amplified in the fault location equation. Consequently, it makes the fault location results of the untransposed double-circuit transmission lines less accurate. Therefore, a new modal transformation method is needed to decouple the parameter matrix of untransposed double-circuit transmission lines and realize the fault location according to the decoupled modal parameter. By improving the basis of the Karrenbauer matrix, a modal transformation matrix suitable for decoupling parameters of untransposed double-circuit transmission lines is obtained. To address the difficulties in solving the fault location equation of untransposed double-circuit transmission lines, a new fault location method based on an improved Karrenbauer matrix and the quantum-behaved particle swarm optimization (QPSO) algorithm is proposed. Firstly, the line parameter matrix is decomposed into identical and inverse sequence components using the identical-inverse sequence component transformation. The Karrenbauer matrix is then transformed to obtain the improved Karrenbauer matrix for untransposed double-circuit transmission lines and applied to identical and inverse sequence components to solve the decoupled modal parameter. Secondly, based on the principle that voltage magnitudes at both ends are equal, the fault location equation is expressed using sequence components at each end, and the QPSO algorithm is introduced to solve the equation. Finally, the feasibility and accuracy of the proposed method are verified by PSCAD simulation. The simulation results fully demonstrate that the innovative improvement on the basis of the traditional modal transformation matrix in this paper can realize the modal transformation of the complex coupling parameters of the untransposed double-circuit transmission lines. It causes almost no errors in the decoupling process. The QPSO algorithm can also solve the fault location equation more accurately. The new fault location method can realize the accurate fault location of untransposed double-circuit transmission lines.

A novel superimposed voltage energy‐based approach for single phase to ground fault detection and location in distribution networks

AbstractThe structure complexity and the extended geographical area are among the factors that create challenges in accurate fault location and detection in distribution networks. The single‐phase to ground (SPG) faults are considered as most frequent reasons for distribution network interruption, which can threaten the network's reliability. Signal processing methods are usually used as common approaches to distinguish and locate faults in distribution networks. This paper proposes a novel scenario to select optimal wavelet packet transform (WPT) coefficients for SPG fault location and a method based on superimposed voltage energy to distinguish the faulty phase according to these coefficients. Furthermore, employing the energies of the superimposed voltages helps to minimize the effects of high resistance faults (HRFs) and load encroachment on the efficiency of the faulty phase detection part. Comparing the obtained results with other scenarios demonstrates the considerable efficiency of the proposed scenario. Finally, with the help of general regression neural networks (GRNN) as machine‐learning tools, a new algorithm is derived for detecting and locating the SPG fault and capacitor bank switching overvoltage (COV). Simulation results are implemented on the IEEE 34‐bus standard distribution network, demonstrating the efficiency and superiority of the suggested method.