Fast Fault Location Research Articles

Fault Location Method of Distribution Network Based on VGAE-GraphSAGE

The distribution network is the main component of the power system, which undertakes the important function of power transmission and distribution. Fast and accurate distribution network fault location is one of the important means to ensure the safe and stable operation of the power system and is helpful in guiding troubleshooting, shortening the power outage time, reducing the workload of manual inspection, and reducing the social and economic losses caused by faults. Due to the development of the new distribution network, the comprehensive influence of many factors has put forward new challenges to the traditional distribution network fault location methods. In this paper, a distribution network fault location method based on the graph neural network is proposed. Firstly, the distribution network is treated as non-Euclidean graph data; secondly, variational graph auto-encoders (VGAE) are used to mine the underlying information of nodes and improve the overall anti-noise performance of the fault location method. Then the GraphSAGE model is used to aggregate the neighbor information of nodes, fully consider the influence of the surrounding lines on the target lines, and improve the output of the model to locate the distribution network line where the fault occurred. The experimental example analysis based on OpenDSS simulation software (version 9.8) proves that the proposed method has high accuracy and anti-interference, and the accuracy reached 97.81%. Moreover, the positioning result is still good in the new intelligent distribution network scenario with distributed power access, with an accuracy of 95.07% in the hybrid power generation scenario.

Combination of Matrix and Genetic Algorithms for Fault Location of Active Distribution Network

Abstract Timely and effective location of faults in distribution networks is important for restoring power supply and dealing with faults. In this paper, a method combining matrix algorithm and genetic algorithm (GA) is proposed to determine the fault section. Firstly, the matrix algorithm is applied to locate the fault section initially by combining the alarm information uploaded from the feeder terminal unit (FTU). Secondly, in order to deal with the problem of outputting wrong location results, the switching function of the active distribution network is constructed to check the location results calculated by the matrix, and the results that do not meet the checking will be treated as a suspicious fault set, and the relevant evaluation function is constructed and optimized using the genetic algorithm, so as to arrive at the correct fault zone location results. The results of the example simulation show that the method used in this paper can achieve fast and fault-tolerant fault location in active distribution networks.

Fault indicator placement in distribution systems: Improving the criteria of quality of service

Distribution utilities need to ensure fast fault location to improve the energy supply service, given that, in the event of an outage scenario, the service restoration process starts after the fault has been localized. Minimizing the time required for fault location leads to a reduction in the system average interruption duration index (SAIDI), a crucial metric that all utilities strive to meet. The use of fault indicators can facilitate the fault location process in distribution systems. The challenge lies in determining the optimal placement of these fault indicators to facilitate the fault location process effectively. This paper presents a metaheuristic-based framework that takes into account both commercial and operational criteria to optimize the placement of fault indicators in distribution systems. This tool considers essential practical factors to assist utilities in achieving minimal SAIDI by optimizing the allocation of fault indicators. The method is tested for a 135-bus distribution feeder to verify its practicability. The numerical results demonstrate that the proposed methodology improves the expected SAIDI, leading to better energy supply service for customers.

A fast data-driven fault detection and location method for unknown distributed thermal processes

The distributed thermal processes are widely present in various industrial operations, but the presence of time delay effect and unknown model information make achieving fast and timely fault detection challenging. Furthermore, the involvement of spatiotemporal coupled data in measurement processes further exacerbates the situation. To solve these problems, this paper proposes a data-driven fault detection and location method for thermal processes described by distributed parameter systems (DPS). Firstly, a Time/Space separation is employed to decoupling the spatio-temporal data into spatial basis functions and temporal coefficients. Subsequently, dynamic partial least squares (DPLS) is employed to obtain the temporal information of the model with fault-free data. Monitoring statistics in both the temporal and spatial domains are then constructed, and their thresholds are estimated by kernel density function. Finally, an online strategy for fault detection and location is presented. The method was validated on the catalytic rod, and an experimental snap curing oven.

A Novel Machine Learning-Based Approach for Fault Detection and Location in Low-Voltage DC Microgrids

DC microgrids have gained significant attention in recent years due to their potential to enhance energy efficiency, integrate renewable energy sources, and improve the resilience of power distribution systems. However, the reliable operation of DC microgrids relies on the early detection and location of faults to ensure an uninterrupted power supply. This paper aims to develop fast and reliable fault detection and location mechanisms for DC microgrids, thereby enhancing operational efficiency, minimizing environmental impact, and contributing to resource conservation and sustainability goals. The fault detection method is based on compressed sensing (CS) and Regression Tree (RT) techniques. Besides, an accurate fault location method using the feature matrix and long short-term memory (LSTM) model combination has been provided. To implement the proposed fault detection and location method, a DC microgrid equipped with photovoltaic (PV) panels, the vehicle-to-grid (V2G) charging station, and a hybrid energy storage system (ESS) are used. The simulation results represent the proposed methods’ superiority over the recent studies. The fault occurrence in the studied DC microgrid is detected in 1 ms, and the proposed fault location method locates the fault with an accuracy of more than 93%. The presented techniques enhance DC microgrid reliability while conserving renewable resources, vital to promoting a greener and more sustainable power grid.

Neural Network based Transmission Line Fault Classifier and Locator using Sequence Values

Faults can easily occur at transmission line because the line is exposed to the environment. The fast fault location after a fault occurrence will minimize the time to repair the faulty part thus reduce the stress of power system due to long outage time. This paper demonstrates the development of fault classifier and fault locator using neural network. The positive, negative and zero sequence values of three-phase voltage and current during fault time were used as the inputs to train the neural networks. Various fault conditions which have different fault types, fault resistance values and fault locations have been simulated to generate the training data for both neural network based fault classifier and fault locator. From the results, the fault classifier and locator successfully classified and located all the simulated fault conditions. One of the advantages of using sequence values as the inputs for the neural networks is only one fault type need to be simulated and used as the training data for single line-to-ground fault (RG, YG and BG), line-to-line fault (RY, YB, BR) and double line-to-ground fault (RYG, YBG, BRG).

A novel noniterative single-ended fault location method with distributed parameter model for AC transmission lines

Fast and accurate fault location methods can save costs and ensure power supply reliability. This paper proposes a novel noniterative single-ended phasor domain fault location method with distributed parameter model for AC transmission lines. Due to the limitation of information, the legacy impedance-based single-ended fault location methods usually are based on assumptions on the line or system to obtain more information. The method proposed in this paper takes advantage of the additional information brought by the operation mode of circuit breakers. The proposed method only needs the local measurements and does not need the measurements and the equivalent source parameters of the remote system. The proposed method only uses single-ended data and is not affected by communication and synchronization. The proposed method is noniterative and there is no risk of non-convergence. In addition, the method proposed in this paper does not rely on the assumptions of legacy methods and considers the distributed parameters, avoiding the disadvantages of the legacy methods. The effectiveness of the proposed method is verified through a lot of case studies in PSCAD/EMTDC, with different fault types, fault locations and resistances.© 2017 Elsevier Inc. All rights reserved.

A physics‐informed learning technique for fault location of DC microgrids using traveling waves

Fast and accurate fault location in DC power systems is of particular importance to ensure their reliable operation. One of the approaches for implementing a fast-tripping protection scheme is to use Traveling waves (TW) initiated by a fault scenario. This paper proposes a physics-informed machine learning approach that utilizes TWs for fault location in DC microgrids. TWs are extracted by the so-called multiresolution analysis which identifies the TW's wavelet coefficients for multiple frequency ranges. This paper deploys Parseval's theorem to find the energy of wavelet coefficients as a quantitative metric for describing TWs. The hypothesis of this paper is that once the Parseval energy curves for a specific cable are extracted, they can be utilized to locate faults along with that cable regardless of the DC system in which the cable is deployed. The fault location algorithm uses Parseval energy curves to train a Gaussian Process (GP) estimator. With the Parseval energy values of measured current at the protection device location, the GP estimator is able to estimate fault locations with high accuracy. The effectiveness of the proposed algorithm is verified by simulating a DC microgrid system in PSCAD/EMTDC.

Novel wavefront detection and fault location method based on Hilbert-Huang transform for long HVDC transmission lines

For the newly constructed ± 1 100 kV HVDC system with 3 324 km transmission lines in China, fast and accurate fault location is vitally important for its stable operation. This paper proposes a novel method based on Hilbert-Huang Transform (HHT) for detecting wavefronts and locating faults occurring on the HVDC transmission lines. False instantaneous frequency maximum points may reduce the accuracy and reliability of wavefront detection. The novel criterion, named the product of amplitude and frequency (PAF), has significant advantages and robustness in characterizing the singularity of the signal and precisely capturing the arrival time of wavefronts. A realistic model of the Changji-Guquan ± 1 100 kV transmission system is constructed using PSCAD/EMTDC to verify the effectiveness of the proposed method. The simulation results give the maximum location error of 0.843 km in given cases of different fault distance, fault impedance, sampling frequency, and other parameters. Noise conditions and the dynamic arc model are also considered in this paper. The comparison against other methods demonstrates the superior performance of the proposed method in terms of accuracy and robustness. The proposed method has broad application prospects and guiding significance for practical projects.

Fast Low Frequency Fault Location and Section Identification Scheme for VSC-Based Multi-Terminal HVDC Systems

Penetration of DC networks is rapidly increasing in modern power systems. As transient behavior of DC grids is different from that of AC ones, AC grid protection schemes might not be applicable to protect DC networks. Exact fault location is vital for protection of DC networks to reduce repair cost and achieve fast power recovery. This paper proposes a novel topology independent multi-terminal DC scheme to identify fault section and location for DC transmission systems. Voltage and current signals measured at the terminals are analyzed by the least squares error (LSE) algorithm. Then, the proposed scheme uses low frequency components of the signals to locate DC faults offline. Unlike some other methods, it does not require sophisticated sensors and hardware to capture very high frequency content of the signals. Hence, the proposed scheme can be implemented in practice without additional measuring infrastructure. The performance of the proposed scheme is evaluated under various fault conditions for different topologies of DC networks in both overhead lines and cables. Numerous simulations carried out demonstrate that the proposed scheme is quite accurate and provides excellent performance under different fault resistances, sections, and locations.

A fast and accurate Bi-level fault location method for transmission system using single ended phasor measurements

To guarantee continuous and reliable operation of power systems working near their stability margins, it is necessary to clear faults quickly. For this purpose, accurate and fast fault location methods are required. Single-ended phasor based methods are a category of fault location strategies which are favourable due to simplicity of their implementation. However, enhancing the accuracy of these methods is a challenging task due to unavailability of data from the remote end of the line. In this paper, a novel fault location method that requires the measured data of one end of the line is proposed. As a result, this method does not need communication links. The proposed method is bi-level and in its first level, fault characteristics such as current, voltage, and impedance of the fault are calculated for a given fault location obtained from Level-2. Then, based on the calculated fault characteristics, fault location is updated in the second level. The presented fault location method considers magnetic coupling between lines and it is also applicable for both transposed and un-transposed lines. Numerous simulation studies verify the accuracy of the proposed method in presence of uncertainties such as noise, fault impedance and error in input line parameters. Furthermore, although the proposed method is based on a bi-level iterative approach, the presented results confirm that it converges quickly in 2 or 3 iterations.

Fault section location in urban distribution network based on fault marking

The goal is to propose an effective method for locating a fault segment in urban power distribution networks. Urban distribution networks have multiple outgoing lines, switches with multiple connections and have variable topology characteristics. It is found that the fault location method based on matrix algorithm has low adaptive capability and fault tolerance when dealing with complex and variable topology. Therefore, this paper proposes an efficient fault segment location method based on special fault indicators, which can significantly improve the accuracy and reliability of fault location. Accordingly, to improve the accuracy and reliability of fault location, a fault segment location method based on fault marking is proposed. The approach proposed in the paper relies on the analysis of the incident matrix, which describes the relationship between nodes and branches, and allows the use of graph theory. The branch state vector is added to obtain the adjacency matrix, which allows to describe the state of change in the dynamics of the distribution network topology. In the next step, a set of nodes and branches, which reflect the incoming and outgoing interconnections of the nodes, is established based on the selected direction of the network binding. According to the direction of the node fault current, the suspicious branches are identified and labeled to indicate the fault. By cumulative calculation and analysis of the labels, the target branches are screened out and the faulty sections of the city power supply network are identified. The results of the case study conducted in the paper show that the proposed method has good adaptability to the variable topology and increases the fault tolerance and accuracy of the developed matrix algorithm. The topological operating state of the network can be changed by controlling the switches to optimize the operation and improve the reliability of the power supply. Thus, the algorithm for fast and accurate fault location is of great importance for improving the safety and quality of urban power supply.

Active Cable Sheath Current-Based Protection Scheme for an Offshore HVAC Wind Transmission System

Due to the complex sending terminal structure of offshore wind transmission systems, conventional on-line monitoring-based protection cannot work well. The electromagnetic transient faults are also difficult to locate due to a short time span with fast characteristics that are affected by various power electronic devices and control algorithms. To solve the aforementioned problems, a new offshore wind transmission line protection scheme based on active detection of submarine cable sheath current is proposed. This method uses a normalized coding cooperation to realize the risk levels and failure locations of the transient defects, and then the sheath currents become a characteristic input data source, which can build a clear system protection boundary. Case studies using MATLAB and ATP simulations are carried out, where three types of transient faults represented by sheath currents are studied, i.e., loss of electrical continuity of grounding device, short circuit of segmented metal sheath of cable joint, and water immersion of junction box. Testing results illustrated that the proposed method could achieve fast fault detection and precise fault location of the electromagnetic transients. Moreover, compared with conventional wind farm protection techniques, it only needs to add few signal injection modules with high sampling frequency into the submarine optical fibers.

A novel strategy for fault location in shunt-compensated double circuit transmission lines equipped by wind farms based on long short-term memory

Parallel lines are one of the main parts of the power systems due to their capability of increasing the transmitted power and reliability of the power network. However, due to their complexity, fault location in these transmission lines has always been a potential problem. Furthermore, when the wind farms are connected to the power networks, a new challenge is created for the fault location algorithms. The reason is that the impedance changes continuously in these wind power plants. Moreover, the Static Var Compensator (SVC), which is used for compensation in transmission lines, can cause problems in accurate calculation of the fault location in power transmission lines. Accordingly, this paper presents a new method based on Long Short-Term Memory (LSTM) networks for source impedance and other network parameters estimation, which are key parameters to calculate the fault location accurately. The simulations are accomplished using PSCAD and Python software on a sample two-circuit network. This network consists of two parallel lines, a wind farm, and a synchronous generator to supply the network's power. The double-fed induction generator (DFIG) model is considered as the wind farm in the studied network. The results obtained from the tests clearly illustrate the applicability of the proposed method to estimate fault location and source impedance with high accuracy. • A fast and accurate fault location algorithm is achieved using Long Short-Term Memory (LSTM) networks. • Determining the location of different fault types in two circuit transmission lines. • Accurate performance for the location of different fault types under nosy conditions. • Estimation of the source impedance with a much smaller error value.

Non-Human-Machine Interaction for Power Transmission Lines Protection Design and Enhancement of Under Voltage Relay

The continuous monitoring of transmission line protection relay is desirable to ensure the system disturbance such as fault inception is detected in transmission line. Therefore, fault on transmission line needs to be detected, classified, and located accurately to maintain the stability of system. This project presents design enhancement and development under voltage relay in power system protection using MATLAB/Simulink. The under-voltage relay is a relay that has contacts that operate when voltage drops below a set voltage which is used for protection against voltage drops to detect short circuit and others. This study is carried out for all types of faults which only related with one of the parallel lines. For the overall of operation conditions, the sample data were generated for the system by varying the different fault types and fault location. This design system proposes the use of MATLAB/ Simulink based method for fast and reliable fault classification and location for a various type of fault.

A Closed-Form Mathematical Model and Method for Fast Fault Location on a Low Voltage DC Feeder Using Single-Ended Measurements

Fault location on a dc microgrid feeder needs to be extremely fast to protect the circuit breaker and converter-source components. This paper develops a seminal theoretical foundation for fast fault location on a dc feeder that uses only single-ended local measurements in time domain. The theory provides a closed-form deterministic solution for fault location, making the resulting fault location method agnostic to system-topology and immune to fault resistance. The theory is developed with ideal dc voltage sources, and extended to practical converter-sources. The performance of the resulting method is demonstrated by simulating a dc feeder with converters connected at both ends, modeled in PSCAD.

Performance Comparison of Impedance-Based Fault Location Methods for Transmission Line

Electric transmission lines play a very essential role in transmitting power energy from generation centers to consumption regions. They can be exposed to fault occurrences due to various reasons, such as lightning strikes, malfunction of components, and human errors. Since fault is unpredictable, a fast fault location method is required to minimize the impact of fault in power systems. This paper presents a research work for comparing the performance of the impedance-based fault location methods, in which the impedance parameter of the faulted line section is calculated as a measure of the distance to the fault. To evaluate the capability of the methods for correctly detecting and locating the fault locations, comprehensive simulation results are carried out. This computation is based on modeling and simulating a three-phase 220kV overhead transmission line in the Matlab/Simulink software. Short circuits which occur in various fault resistances and locations along the transmission line are emulated to investigate several case studies and the accuracy of fault location determination is calculated to compare the performance among these fault location methods.

The improved fault location method based on natural frequency in MMC-HVDC grid by combining FFT and MUSIC algorithms

The fast and accurate fault location is extremely important for effective fault clearance in the power system. And in HVDC grid, the natural-frequency based fault location method is quite promising. Therefore, in this paper, the applicability of the traditional natural-frequency based method in MMC-HVDC grid is analyzed. Then the improved method suitable for MMC-HVDC grid is proposed. In the proposed method, the second natural frequency is discriminated and extracted to calculate the fault distance, because the first natural frequency is very low and used data window is very short in MMC-HVDC grid. In addition, the scheme combinedly utilizing FFT and MUSIC algorithms is designed, to avoid influence of traditional MUSIC false frequency phenomenon. A four-terminal meshed dc grid model is built based on PSCAD/EMTDC, and the simulation cases are carried out to verify the correctness of theoretical analysis and superiorities of proposed method. Compared with traditional method, the proposed one calculates fault distance based on a shorter data window, thus being more suitable for MMC-HVDC grid. And the influence of the MUSIC false frequency phenomenon is avoided, further guaranteeing the fault location accuracy.

An improved contact model considered the effect of boundary lubrication regime on piston ring-liner contact for the two-stroke marine engines from the perspective of the Stribeck curve

The prediction of lubrication performance is required to be the basement of friction optimization for marine engines. This paper simulates the lubrication performance of marine engines based on statistical models which have the advantages of fast, efficient, and macroscopic fault location. Boundary lubrication exists in the piston ring-cylinder liner (PRCL) of two-stroke marine engines because of the harsher load, lower speed, and larger structure. It has been proposed that there would be tribofilm under boundary lubrication which has a significant influence on the contact. To understand the boundary lubrication, it is necessary to study the lubrication regime transition. In this paper, firstly, the coefficient of friction curve combined with the thickness ratio embodies the lubrication regime transition process of two-stroke engines under work conditions. However, the phenomenon that the coefficients under boundary lubrication are smaller than that of other regimes shows the non-objectivity of this curve. Therefore, the Stribeck curve is introduced for objectively evaluating the transition. Then, the calculation of asperities contact pressure under boundary lubrication, which Wen proposed, is introduced into the classic Greenwood-Williamson model, the problem that the original model cannot reflect the boundary lubrication regime in the form of the Stribeck curve is improved. Finally, the results are compared before and after modifying the model to verify this study’s practicability. It provides more precise asperities contact pressure for the tribofilm growth calculation from the perspective of the Stribeck curve under the PRCL statistical model in future work.

Adaptive Fast Fault Location for Open-Switch Faults of Voltage Source Inverter

In this paper, the issue of open-switch faults of voltage source inverter (VSI) is studied, an adaptive fast voltage-based real-time open-switch fault location method is proposed. Firstly, for each switching period, the voltage deviation is calculated by the expected voltage and estimated actual voltage, they are obtained via the mixed logical dynamic model (MLDM) and measured currents, respectively. Then, the voltage deviation of each phase is employed as a fault variable. By this way, avoiding the use of additional hardware, and embedding easily in system. Furthermore, considering the impact of sampling error, parameter error, dead time, delay time, and transition time, the adaptive threshold is designed. Finally, simulations and experiments are executed to verify the effectiveness of the proposed method.