Fault Location Scheme Research Articles

A subsystem‐based fault location method in distribution grids by sparse measurement

AbstractWith the development of smart meters and other intelligent electronic devices, more and more data‐driven fault location methods based on wide area measurement are emerging. However, these diagnostic methods for dealing with the whole tested system often appear complex. This paper presents an innovative subsystems‐based fault location strategy in distribution grid by the sparsity promoted Bayesian learning algorithm. To avoid taking measurement for the whole distribution system, the fault‐included subsystem is selected according to the distribution characteristics of negative sequence voltage. Then the data for fault location is measured by allocating meters in subsystem, which can reduce the number of required meters. For accurately estimating the fault location, a sparse prior is proposed for the Bayesian learning, which could improve the accuracy of the fault location algorithm by about 4%. The performance is tested on a 12.66‐kV, 69‐bus distribution system in response to various fault scenarios. The results show that the accuracy of the proposed method for the fault section location can reach 90%. It also verifies the robustness and accuracy for fault line location, faced different fault types, fault resistance, noise, etc.

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.

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.

Study on sound transmission characteristics and positioning strategy of gas insulated transmission line shell

Gas insulated transmission line (GIL) is widely used for large-capacity power transmission in complex environment, and has the characteristics of long distance and totally enclosed structure. When the insulation fault occurs inside GIL, its metal shell structure makes it more difficult to monitor through optical, electrical and other physical quantities. Considering the rapidity and accuracy of positioning, the propagation of sound waves along the GIL sheath is a commonly used method in GIL on-site PD testing and running state online monitoring for fault positioning. This paper establishes a high-pressure GIL acoustic propagation simulation model based on pipe acoustics theory, analyzes the frequency dispersion and mode distribution of acoustic waves along the GIL shell, determines an appropriate fault location strategy based on the propagation velocity and attenuation of the selected acoustic wave mode, and carries out experiments to verify it. The results of the research show that the low order bending wave F(1,1) propagated along the GIL shell has good positioning characteristics, and the propagation velocity conforms to the dispersion curve distribution. By taking into account the attenuation and delay of the acoustic wave passing through epoxy insulators or expansion joints in the fault localization strategy, the localization accuracy can be improved by 60%. And this positioning strategy was verified to be effective in the GIL insulation fault localization test conducted in the field.

An active pole-to-ground fault location scheme for FB-MMC-MTDC system using the short-time blocking of sub-modules

The pole-to-ground (PTG) fault current is small in the multi-terminal direct current (MTDC) system, which cannot be used to locate the fault. This paper proposes a PTG fault location scheme for MTDC based on full bridge modular multilevel converter (FB-MMC), by actively blocking the sub-modules (SMs). The SMs blocking generates a voltage pulse wave which travels between the MMC and the fault point. By using the wave polarity analysis method, the reflected wave from fault point can be identified. The improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is used to detect the reflected wave arrival time. The time difference between pulse start time and reflection arrival time is processed for fault location. A four-terminal MMC-MTDC simulation model established in PSCAD/EMTDC validates the proposed method have not affected the power transmission. Afterwards, the fault location accuracy under the influences of fault type, fault location and fault impedance issues are also confirmed.

Fault properties identification scheme for hybrid MTDC system based on LCC signal injection and distributed parameter line model

AbstractA fault properties identification scheme for a hybrid multi‐terminal DC (MTDC) system is proposed to improve the power supply reliability in the system recovery stage. Firstly, a current signal injection strategy based on line commutated converter (LCC) is proposed using the fault control capability. Secondly, the difference between the calculated value (CV) and the measured value (MV) of the current signal under permanent and temporary faults is analyzed for the distributed parameter line model. By introducing the dynamic time warping (DWT) algorithm to represent the difference between CV and MV, a fault properties identification scheme for permanent fault identification is constructed. Finally, the proposed scheme for permanent fault location with the distributed parameter model is obtained by introducing the trust region reflection (TRR) algorithm. The simulation results show that the proposed fault properties identification scheme has the function of permanent fault identification and location. The proposed scheme fully considers the effects of fault impedance, sampling rate, noise, and data loss. It can be applied to high voltage DC long‐distance transmission lines with LCC.

Assessment of traveling wave-based functions in inverter-based resource interconnecting lines

In this paper, the behavior of traveling waves (TWs) on transmission lines which interconnect inverter-based resources (IBRs) is investigated, assessing the performance of well-known TW functions applied in protection and fault location schemes. To do so, traditional synchronous generators and wind turbine-based IBRs of types III and IV are investigated, allowing comparative studies regarding the shape of fault-induced transients measured at the monitored line terminals. Then, the impacts of typical terminations of IBR-interconnecting lines on the classical double-ended TW-based fault location method, as well as on directional, overcurrent and differential TW-based protections are analyzed, highlighting the effects of busbar and transformer stray capacitances on the performance of these functions. The obtained results reveal that TW solutions are promising for IBR-interconnecting lines. However, a significant influence of busbar and transformer stray capacitances on the performance of TW functions is also identified, revealing the need for taking these capacitances into account during the definition of settings used in TW protection and fault location schemes.

Permanent fault identification and location scheme for MTDC grid based on equivalent impedance phase characteristics and distributed parameter line

To ensure the reliability of the MTDC grid's recovery system during the reclosing stage, identifying permanent faults is crucial. Therefore, a permanent fault identification and location scheme is proposed based on equivalent impedance phase characteristics and distributed parameter lines. The equivalent impedances with distributed parameter lines in permanent and temporary faults are investigated. The proposed scheme for identifying a permanent fault is based on the phase characteristics of the equivalent impedances. The proposed scheme for permanent fault location is achieved by solving the fault location equation considering distributed parameter lines to determine the fault distance. Simulation results indicate that the proposed scheme is suitable for long-distance DC transmission lines and is less affected by the sampling rate, fault locations, fault resistance, and noise. The proposed scheme improves the reliability and sensitivity of permanent fault detection.

Analytical multi-section Bergeron model of transmission lines and application to accurate fault location for long HVDC lines

Line Bergeron model is widely adopted for various applications including line fault location. However, it models the line distributed series resistance using a very limited number of lumped resistors, resulting in modeling errors. For long HVDC lines, this modeling error will cause fault location errors. In addition, if high frequency components of measurements are adopted to mitigate the influence of the frequency dependent parameters, the modeling errors of the existing Bergeron model and the fault location errors will be further magnified. To this end, this paper proposes a multi-section Bergeron model to improve line modeling and fault location accuracy. First, the error of the existing Bergeron model is analytically derived to show its limitations. Then, with multiple Bergeron sections in series to well approximate the distributed series resistance, the analytical expression of the multi-section Bergeron model is proposed with rigorously derivations and proofs. Finally, based on the proposed multi-section Bergeron model, a novel fault location scheme for long HVDC lines is presented, where the 1-mode and high frequency components of measurements are utilized to minimize the impact of line frequency dependent characteristics. Numerical experimental results in both LCC and VSC HVDC systems show that the proposed method has higher line modeling accuracy and fault location accuracy than the existing method. The proposed multi-section Bergeron model can potentially be applied to other long transmission line related applications.

Fault-Tolerant Control Strategy for Sub-Modules Open-Circuit Fault of Modular Multilevel Converter

Modular multilevel converter (MMC) is a key device of high-voltage-direct circuit (HVDC) transmission system, the sub-module detection technology of which will directly influence the damage severity, and even the reliability of the whole system. In this paper, the open-circuit fault characteristics of an insulated gate bipolar transistor (IGBT) in a sub-module are analyzed, and a fault-tolerant optimal control strategy is proposed for the redundant hot-reserved MMC based on nearest-level modulation (NLM). A fault sub-module diagnosis and location strategy based on the deviation distance of the capacitor voltages is presented. After the faulty sub-module is removed, due to the asymmetric operation of the MMC, odd-order circulating currents are introduced in the faulty phase, in which the fundamental-frequency circulating current is the major component; the fundamental-frequency voltage related to the redundancy rate is injected into the faulty phase, which effectively suppresses the fundamental-frequency circulating current and harmonics in the faulty phase. The proposed method combines fault detection and fault ride-through steps, so it has the features of high reliability and high compatibility. Based on the Matlab/Simulink simulation model, the effectiveness of the proposed strategy is verified.

Traveling Wave-Based Primary Protection and Fault Localization Scheme for MTDC Grid Considering IEC 61869-9 Measurement Standard

Traveling wave (TW) based protection and fault localization requires high sampling frequency measurements (500 kHz - 1 MHz) and are non-compliant to the IEC 61869-9 measurement standards, which allows maximum sampling frequency of 96 kHz for DC application. This work proposes a novel low sampling frequency (50 kHz) TW based primary protection and real-time DC fault localization technique for multi terminal high voltage DC (MTDC) grid which is compliant with the aforementioned measurement standard. In the proposed MTDC protection scheme, a TW arrival time (TWAT) is estimated under low sampling frequency measurement using cascaded combination of modified mathematical morphology gradient (MMG), sobel operator and linear regression tool. Subsequently, the TWAT information at both DC link terminals is communicated via dedicated communication channel compliant to IEC-61850-9-2 standard. And if the TWAT difference between DC terminals is less than the TW propagation threshold for the protected DC line, then a DC trip signal is issued to the associated hybrid DC circuit breaker (HDCCB). For fast power system restoration, the same TWAT information is also used for real-time fault localization in the faulted DC line, which is also compliant with IEC 61869-9 measurement standards. Finally, the practical feasibility of the proposed algorithm is demonstrated through control hardware-in-loop testing with real-time digital simulation setup and TI TMS320F28379d digital signal processor card.

Fault-Locator Scheme for Combined Taba-Aqaba Transmission System Based on New Faulted Segment Identification Method

Fault-Locator Scheme for Combined Taba-Aqaba Transmission System Based on New Faulted Segment Identification Method

Advanced fault location scheme for superconducting cables based on deep learning algorithms

This paper addresses the challenge of fault localization in power grids which incorporate Superconducting Cables (SCs) and presence of inverter-connected generation, by proposing a novel data-driven fault location scheme. The developed fault location algorithm utilizes the transformation of time domain fault current and voltage signatures, to time–frequency domain and exploits the advantages of a Convolutional Neural Network (CNN) to estimate the fault position along SCs. The proposed algorithm has been tested using a verified model of SC, and the results revealed that it can provide precise fault localization for a wide range of fault scenarios, including different fault types, fault resistance values and fault inception angles. Furthermore, the proposed scheme robustness has been verified against different influencing factors accounting for very small increments of fault location, additive noise and different value of sampling frequency. For validation purposes, the effectiveness of the CNN-based algorithm has been compared with other data-driven algorithms and the relevant advantages have been highlighted.

Intelligent Sensors for dc Fault Location Scheme Based on Optimized Intelligent Architecture for HVdc Systems

We develop a probabilistic model for determining the location of dc-link faults in MT-HVdc networks using discrete wavelet transforms (DWTs), Bayesian optimization, and multilayer artificial neural networks (ANNs) based on local information. Likewise, feedforward neural networks (FFNNs) are trained using the Levenberg-Marquardt backpropagation (LMBP) method, which multi-stage BO optimizes for efficiency. During training, the feature vectors at the sending terminal of the dc link are selected based on the norm values of the observed waveforms at various frequency bands. The multilayer ANN is trained using a comprehensive set of offline data that takes the denoising scheme into account. This choice not only helps to reduce the computational load but also provides better accuracy. An overall percentage error of 0.5144% is observed for the proposed algorithm when tested against fault resistances ranging from 10 to 485 Ω. The simulation results show that the proposed method can accurately estimate the fault site to a precision of 485 Ω and is more robust.

Fault identification and fault location methods for VSC-HVDC transmission lines based on the traveling waveform difference

Due to the low-damping characteristic of the voltage source converter based high voltage direct current (VSC-HVDC) transmission system, the line current will reach the peak value within a few milliseconds after DC fault, threatening the safety of power electronic devices. Therefore, a reliable and rapid protection scheme comprising fault identification and location is necessary. The detection time cost of traditional backup protections is high. Worse still, most existing methods cannot distinguish the double-pole-to-ground fault with unequal positive and negative pole fault resistances. To solve the issues, a backup protection based on the same/different-mode traveling wave, differential forward/backward current, and traveling waveform difference for VSC-HVDC lines is proposed in the paper. The fault characteristics of same/different-mode traveling wave and relationship between fault distance and differential forward/backward current are elaborated. The waveform differences in positive/negative-pole same/different-mode traveling waves and 1-mode differential forward/backward currents are summarized. According to these analyses, the protection is established and the VSC-HVDC is modeled in PSCAD. Based on the sufficient simulation tests, it is verified the proposed fault identification and location schemes have great performance, with superiority in fault resistance and distance tolerance (2,000 Ω and the whole line), strong anti-interference capability, fast fault distinguishment, and accurate fault location.

Fault Classification and Localization Scheme for Power Distribution Network

In this paper, a fault protection diagnostic scheme for a power distribution system is proposed. The scheme comprises a wavelet packet decomposition (WPD) for signal processing and analysis and a support vector machine (SMV) for fault classification and location. The scheme is tested on a reduced Eskom 132 kV power line. The WPD is used to extract fault signatures of interest and the SVM is subsequently used for fault classification and locating various fault conditions. Furthermore, we investigate the effectiveness of the SVM scheme using different samples of the cycles for fault classification and location. The results show that the fault classification and location on a distribution line can be determined rapidly and efficiently irrespective of the fault impedance and incipient angle with minimum estimation error. Lastly, the proposed scheme is tested on a grid-integrated system with renewable energy sources.

High speed fault detection and localization scheme for low voltage DC microgrid

In this paper, a new differential protection scheme based on the sensitivity of the relay is proposed for fault detection and location estimation in DC microgrid having different renewable energy sources (RESs) namely PV, wind and battery. The sensitivity of each relay, connected at the bus terminal of the microgrid, is determined by using the magnitude of currents flowing through the cables. Once, Sensitivity factor (S-factor) for each relay is calculated, proposed scheme detects the fault by comparing S-factor of each relay with predefined threshold value. Further, the fault location is determined by measuring voltage and current at both ends of the faulty cable. The effectiveness of the proposed scheme is validated on a 380 V ring-type DC microgrid simulated under various fault conditions with different fault resistance values and at different fault locations. The simulation results obtained under different operating conditions indicate high selectivity and high speed of operation (less than 1.2 ms) of the proposed scheme for fault detection and isolation of faulty part. The proposed scheme ensures the effectivness and reliability when compared with other schemes mentioned in the literature.

Open circuit fault diagnosis strategy of PMSM drive system based on grey prediction theory for industrial robot

Permanent magnet synchronous motor (PMSM) is widely used in industrial robot joints and machine tools due to its high torque density, good controllability, and compact structure. Automatic fault diagnosis and early warning of PMSM drive system of industrial robot is the key and difficult point for the smooth development of automatic production process. In view of the problems that the traditional open circuit fault diagnosis method is not fast enough, not intelligent enough, and prone to misdiagnosis in the case of load change, an open circuit fault diagnosis and location strategy for windings and power switches of PMSM drive system based on grey prediction theory is proposed. The grey prediction method only needs to collect a small amount of motor current data and uses the grey model to estimate and predict the rule of the system. It can still diagnose and locate faults accurately in the case of load change, and compared with the traditional current detection method, the diagnosis speed is fast, and the accuracy is high. Through the theoretical analysis, simulation, and experimental results, it is verified that proposed strategy can diagnose the power switch and winding open circuit faults accurately in real time, which improves the reliability of the electric drive system in the application of industrial robot.

Model and Data-Driven Combination: A Fault Diagnosis and Localization Method for Unknown Fault Size of Quadrotor UAV Actuator Based on Extended State Observer and Deep Forest.

The rotor is an essential actuator of quadrotor UAV, and is prone to failure due to high speed rotation and environmental disturbances. It is difficult to diagnose rotor faults and identify the fault localization simultaneously. In this paper, we propose a fault diagnosis and localization scheme based on the Extended State Observer (ESO) and Deep Forest (DF). This scheme can accurately complete the fault diagnosis and localization for the quadrotor UAV actuator without knowing the fault size by combining the model-based and the data-driven methods. First, we obtain the angular acceleration residual signal of the quadrotor UAV by using ESO. The residual signal is the difference between the observed state of ESO and the true fault state. Then, we design the residual feature analysis method by considering the position distribution of the quadrotor UAV actuator. This method can embed the actuator fault localization information into the fault data by simultaneously considering pitch and roll of the quadrotor UAV. Finally, we complete the fault diagnosis and localization of the quadrotor UAV actuator by processing the fault data by using DF. This scheme has the advantages of straightforward observer modeling, strong generalization ability, adaptability to small sample data, and few hyperparameters. Our simulation results indicate that the accuracy of the proposed scheme reaches more than 99% for the unknown size of the quadrotor UAV actuator fault.

Sliding DFT-Based Fault Location Scheme for DC Microgrid

Nowadays, the dc microgrid is getting much more attention due to its numerous advantages. However, accurate and timely detection of a fault and its location is still challenging. This article proposes a fast and effective fault identification and localization scheme for dc microgrids. This article implements the dc component concept to detect and locate the fault. The sliding discrete Fourier transform technique is used for the computation of dc components. At the first stage, the fault is identified by noticing the change in the direction of both the end current signals. In the second stage, the fault point resistance is estimated. Finally, in the third stage, the location of the fault is determined. The proposed methodology is implemented in real-time on the LabVIEW platform. The testing is performed for different types of faults at various fault locations considering distant topologies of the dc microgrid.