Fault Point Research Articles

Localization of Dual Partial Discharge in Transformer Windings Using Fabry–Pérot Optical Fiber Sensor Array

The power transformer is one of the most critical core devices for energy exchange in power systems, and its safe and stable operation is directly related to the reliability of the power grid. Partial discharge is the main cause of insulation degradation and failure of high-voltage electrical equipment. Online monitoring and accurate localization of partial discharge can provide information on the aging of power equipment, which is of great value for improving the safe operation and maintenance of the power grid. Internal dual partial discharge in transformer windings is a more complex type of fault. Since it is located inside the windings, the signal is attenuated and distorted, making it difficult for traditional monitoring methods to capture such partial discharge signal The Fabry–Perot optical fiber sensor is an ultrasonic detection method that can be built into the transformer interior. This sensor has high sensitivity and a small size, enabling flexible placement at different locations inside the transformer for precise partial discharge detection. Especially for the narrow space inside the high and low voltage windings, F–P sensors can form an array, utilizing the array’s directivity to locate the fault points. In this study, an ultrasonic detection system based on the F–P optical fiber sensor array was developed. The system utilizes a directional cross-localization algorithm based on the multiple signal classification (MUSIC) algorithm to accurately locate dual partial discharge sources. This partial discharge detection system was applied to a 35 kV single-phase transformer, enabling the localization of dual partial discharge sources within the high and low voltage windings. Combined with experimental results, this method exhibits high localization accuracy and is particularly suitable for detecting partial discharge phenomena that occur within or between transformer windings.

Enhanced distance-based protection for high impedance faults considering dynamic load modelling

The load can be represented by different models, including static and dynamic representations; each has different responses when analysing a power system, which also impacts the protection system's performance. For instance, in the distance relay, the estimated impedance can present overreach or underreach, affecting the selectivity of the protection and causing malfunction of triggering schemes. Under fault conditions, the load modelling effect can be magnified by the fault resistance effect, where the combination of both effects has not been addressed in the revisited bibliography. The present paper analyses the effect of load modelling for non-bolted faults in the distance relay impedance estimation. Distance relays are of interest due to their wide use in transmission systems and the emerging applications in distribution systems and microgrids. The fundamental contribution of the present paper is to propose a countermeasure for the effects of four different load types and fault resistance. The results demonstrate that the distance estimation is correctly enhanced, and then a close to the real positive sequence impedance is estimated from the relay point to the fault point. The proposal can be included in distance relays without requiring additional hardware, allowing countermeasure of the load type and fault resistance effects.

Active Fault-Locating Scheme for Hybrid Distribution Line Based on Mutation of Aerial-Mode Injected Pulse

Due to the overlap of initial traveling wave signals, the traveling wave propagation process in hybrid distribution lines is complicated to analyze. The most significant challenge posed by the traditional passive traveling wave-locating method for hybrid distribution lines lies in identifying the fault section and distinguishing the reflected wave from the fault point or the hybrid connection points. Based on this approach, with the application of the aerial-mode component of the pulse signal generated at the fault point, a fault-section-identification and fault-locating scheme for hybrid distribution feeders with active pulse injection is proposed. When power in a line is cut after a single-to-line ground (SLG) fault occurs, the same pulse is injected into the three phases from the neutral point of the coupling capacitor bank to construct the zero-mode component, which propagates to the SLG fault three-phase asymmetrical point, producing an aerial-mode component that is reflected back to the first end of the line. With the application of the arrival time of an aerial-mode wavefront, it is simple to locate the SLG fault for arbitrary forms of hybrid lines. The simulation results confirm the feasibility of the fault-locating scheme under different feeders, different fault locations, and fault resistances. The results of the experiments confirm the high practical value of the proposed method.

A Simple Magnetic-Flux-Based Method for Localizing High-Resistance Stator Ground Faults in Synchronous Machines

This paper presents a new offline method based on the analysis of the magnetic flux to determine the location of stator ground faults in synchronous machines. First, the defective phase is identified via the insulation resistance (Megger) test, and then the longitudinal axis of the rotor is aligned with the faulty phase winding. During two measuring modes, a voltage is applied separately to each end of the faulty phase while the other end is floating and the core is grounded. The application of the voltage between each terminal of the faulty phase and ground will lead to the circulation of a current through the stator winding to the fault point, being its path closed by the grounded core. A magnetic flux will then be created, which can be sensed indirectly by measuring the induced voltage in the rotor field winding. The fault point can be identified by measuring the applied current or voltage and the magnetic flux created in both measuring modes. Since stator ground faults usually occur via high resistances, the method is extended for the detection of such faults by processing the data using the stationary wavelet transform. The experimental results show that the proposed method is very sensitive and is able to identify the ground fault location for fault resistances up to a few hundred of k-Ohms.

A nondestructive high-resistance fault diagnosis method of XLPE medium voltage cables based on Chirp-TDR

Diagnosing and locating the high resistance fault (HIF) of XLPE medium voltage cables without causing secondary damage has been a trouble for power maintainers. Among the previous methods proposed by researchers, the frequency domain reflection method has the strongest sensitivity, which still cannot meet the broad dynamic range requirement of HIF detection. This paper proposes a chirp-TDR high resistance fault detection method, which fully taps the signal processing gain of the chirp signal after pulse compression. The method increases the practical detection limit to hundreds of kΩ. A prototype is implemented, and the performance is simulated. The influence of incidence and terminal reflection signals on fault point reflection signal detection is reduced by common mode filtering and access matching impedances. The selected detection signal with 5 ms duration and 20 MHz bandwidth can produce a signal processing gain of 50 dB. A signal coaxial cable and an XLPE power cable with artificial simulated defects were installed as test specimens. The test results show that the method is feasible and has strong anti-noise ability. The technology is compared with FDR, which also uses the chirp signal. The proposed method has a performance improvement of about 12 dB, showing better fault point resolution ability.

A Section Location Method of Single-Phase Short-Circuit Faults for Distribution Networks Containing Distributed Generators Based on Fusion Fault Confidence of Short-Circuit Current Vectors

A Section Location Method of Single-Phase Short-Circuit Faults for Distribution Networks Containing Distributed Generators Based on Fusion Fault Confidence of Short-Circuit Current Vectors

Performance Evaluation of Overcurrent Relay and Ground Fault Relay Coordination in Distribution Feeder

Reliable and sustainable electrical distribution systems require effective protection measures against internal and external disturbances, especially short-circuit disturbances, to avoid damage to the equipment. Overcurrent relays (OCR) and ground fault relays (GFR) play an important role in the safety of the distribution network. To improve performance, evaluation of relay coordination is essential. During the short circuit, the nearest relay to the fault point is activated first and the backup relay is activated if the fault current exceeds the adjustment of the main relay. Coordination ensures that timely signaling is sent to interrupt the circuit. Inspection of the OCR relay revealed that it did not comply with the IEC 60255 standard and consequently adjusted the classification time to 0.402 seconds. Similarly, the results of the GFR relay inspection did not meet the standards and required an adjustment of the evaluation time to 0.492 seconds. Resolving these deviations is crucial to maintaining the reliability and compliance of the distribution network with industry standards, ensuring that the protection relays respond quickly and effectively to disturbances, thereby preventing possible damage to equipment

Identification System for Short-Circuit Fault Points in Concentrated Stator Windings of Motors

Motors serve as the primary power sources in a wide range of industrial fields. In recent years, their application has been expanded to electric and hybrid electric vehicles. As the performance of the motors installed in electric vehicles directly affects human life, it is critical to diagnose the condition of the windings. The objective of this article is to establish a method to identify the short-circuit fault points in concentrated stator windings based on the magnetic flux density distribution near the stator windings. Unlike with distributed windings, the coils are wound around the teeth in concentrated windings. Thus, it is expected that the accurate position specification of the short circuit can be realized if a detailed magnetic flux density distribution over the teeth is obtained with an appropriate magnetic field sensor. The problem of sensor positioning is solved with two stepper motors moving the search coil in the rotational and longitudinal directions independently at specified intervals. The excellent capability of the proposed system is verified through experiments using the stator winding employed in hybrid electric vehicles. The accuracy and sensitivity of the proposed identification system for short-circuit fault points may enable its practical application in industries, for example, shipping and periodic inspections as well as the production management of motors with concentrated stator windings.

Application of SSA-KNN Algorithm in Fault Analysis of Power Metering Automation System

In view of the great pressure of operation and maintenance of power energy data collection terminal after putting into operation, an intelligent fault diagnosis system for power equipment terminal based on computer was developed. This paper proposes an Agent based on autonomy, promotility, cooperation and interactivity. It also provides a flexible interactive communication interface and load balancing optimization method. It can meet a variety of data transmission specifications and a large number of data service transmission requirements. The SA-KNN algorithm is used to analyze the power quality. Methods The operation data of maintenance electricity were collected. Learning and cluster analysis are carried out by using relevant data, and the calculation model of automatic check device failure is established. At the same time, the outlier points in the collected data are used to accurately locate the fault points of the power grid. This method can realize the comprehensive fault diagnosis of the power grid by using the interaction between the power grid and each component.

Off-line location strategy for single-phase ground fault of distribution line

This paper adopts off-line location strategy of single-phase grounding fault of distribution lines, determines size and frequency of injected AC signal by analyzing distribution parameters of lines, and then develops portable small current signal source with adjustable frequency through power conversion control technology, and develops signal detector by analyzing noise correlation and adaptive morphological filtering. Then off-line location strategy is developed according to above two signal devices. Finally, it is verified that the strategy can accurately locate fault point of distribution line.

A New Approach for Single-Phase-to-Ground Fault Detection in Mid-Voltage Systems Using Low-Voltage Sensors

Single-phase-to-ground fault in low-current grounding systems represents a serious public safety concern. Low-voltage (LV) sensors, with their growing maturity, can now monitor multiple points of the mid-voltage (MV) distribution network. This paper proposes a new method for identifying single-phase-to-ground line faults and locating them using LV sensors deployed on the LV side of distribution transformers. We analyze the characteristics of the negative-sequence signal on the LV side after a single-phase grounding fault occurs on the MV side. The negative-sequence current can distinguish between fault and non-fault lines. By setting the ratio coefficient of negative-sequence voltage and positive-sequence voltage, we can use multi-point collaborative calculation and comparison to determine the section of the fault point. We consider the unbalanced load on the LV side and the special case of a fault point on one end of the line. Through simulation of combined MV and LV distribution systems in MATLAB software and dynamic model experiments, we verify that the proposed method has good robustness and accuracy. Monitoring the status information of the MV distribution network through LV sensors has great potential in practical application and implementation for realizing the fault detection of low-current grounding systems.

A ground fault location algorithm in double‐circuit transmission lines with T‐off connection to an industrial microgrid by using current and voltage phasors information of a single terminal

AbstractThe paper presents a ground fault location algorithm (GFLA) in double‐circuit transmission lines (DCTL) with a T‐off connection to an industrial microgrid (IMG) containing electric arc furnaces (EAF), renewable distributed generations (RDG), and static VAR compensator (SVC). The design presented utilizes the information on the current and voltage phasors of one side of the transmission lines (TL) during the fault period, and there is no need for the availability of information on the type of faulty phase(s) and even the faulty section. To find the exact location of the fault in this design, the voltage phasor equations governing the fault point in positive, negative, and zero‐sequence (PNZS) domains, the zero‐sequence current (ZSC) equation of the fault point, and the boundary condition equation of the fault point have been used. The simulation system is implemented in Simulink/MATLAB using accurate modelling of all network components. The algorithm has been tested and evaluated in different fault conditions, including various locations, phase types, phase‐to‐ground connection resistance, occurrence time, and microgrid (MG) operation modes. The successful results of various tests of the proposed design as well as the analysis of various sensitivities confirm the satisfying performance of the suggested algorithm.

New energy transmission line fault location method based on Pearson correlation coefficient

The access of new energy power source makes the traditional transmission line structure become complex, and due to the influence of power electronic device control strategy, the fault characteristics have been fundamentally changed, resulting in the traditional transmission line fault localization method can not be applied to the new energy sending line. To address the above problems, this paper analyzes the transient current characteristics of different power supply faults, and learns that there are obvious differences in the transient currents on both sides of the fault point inside and outside the transmission line area, and then proposes a new energy transmission line fault localization method based on the Pearson correlation coefficient, which determines the fault location by calculating the correlation coefficients of the fault waveforms of the neighboring monitoring points. Finally, comparative experiments are carried out under different fault types and fault locations to further verify the applicability of the proposed method.

Regional tectonic dynamics in Central Iran: Unveiling the interplay of fault systems through morphotectonic and seismological analyses in the Shotori mountains

Iran, located at the convergence of the Eurasian and Arabian tectonic plates, is a region of significant geologic and tectonic interest. This setting gives rise to complex tectonic dynamics that are crucial for understanding the seismicity and geological evolution of the area. This study provides novel insights into the tectonic dynamics of Central Iran, with a particular focus on the Shotori Mountains. Employing a combination of satellite imagery, earthquake catalog analysis, and field observations, we have studied the complex interactions among active fault systems in this part of Iran. Our investigation highlights the significant interactivity of these faults, especially at the convergence point of the Nayband strike-slip fault with the Esfandiar and Shotori thrust faults. This area is characterized by a high frequency of reverse mechanism earthquakes, primarily occurring in shallower crustal layers. A notable aspect of our findings is the identification of a distinct pattern of seismic activity linked to the interaction between different fault types. The Nayband shear zone, for instance, is critically responsible for right-lateral, oblique reverse faulting, and strike-slip events. This study also reveals a novel aspect of tectonic behavior in Central Iran: the correlation between strike-slip fault systems and their thrust terminations, influenced by the rotational dynamics of these faults. Our analysis suggests that the activation of strike-slip faults can precipitate the activation of their thrust terminations, a phenomenon particularly evident at their intersection points. This insight is crucial for understanding regional tectonic processes and could significantly impact seismic hazard assessments in Central Iran. Furthermore, the interaction between the Nayband strike-slip fault and its thrust terminations, such as the Shotori and Esfandiar faults, highlights areas of heightened tectonic activity. This study not only advances our understanding of the seismic and tectonic landscape of Central Iran but also has broader implications for regional tectonic studies and seismic risk management.

FedRDR: Federated Reinforcement Distillation-Based Routing Algorithm in UAV-Assisted Networks for Communication Infrastructure Failures

Traditional Internet of Things (IoT) networks have limited coverage and may experience failures due to natural disasters affecting critical IoT devices, making it difficult for them to provide communication services. Therefore, how to establish network communication service more efficiently in the presence of fault points is the problem we solve in this paper. To address this issue, this study constructs a hierarchical multi-domain data transmission architecture for an emergency network with unmanned aerial vehicles (UAVs) employed as core communication devices. This architecture expands the functionality of UAVs as key network devices and provides a theoretical basis for their feasibility as intelligent network controllers and switches. Firstly, the UAV controllers perceive the network status and learn the spatio-temporal characteristics of air-to-ground network links. Secondly, a routing algorithm within the domain based on federated reinforcement distillation (FedRDR) is developed, which enhances the generalization capability of the routing decision model by increasing the training data samples. Simulation experiments are conducted, and the results show that the average communication data size between each domain controller and the server is approximately 45.3 KB when using the FedRDR algorithm. Compared to the transmission of parameters through federated reinforcement learning algorithms, FedRDR reduces the transmitted parameter size by approximately 29%. Therefore, the FedRDR routing algorithm helps to facilitate knowledge transfer, accelerate the training process of intelligent agents within the domain, and reduce communication costs in resource-constrained scenarios for UAV networks and has practical value.

Precise Lightning Strike Detection in Overhead Lines Using KL-VMD and PE-SGMD Innovations

When overhead lines are impacted by lightning, the traveling wave of the fault contains a wealth of fault information. The accurate extraction of feature quantities from transient components and their classification are fundamental to the identification of lightning faults. The extraction process may involve modal aliasing, optimal wavelet base issues, and inconsistencies between the lightning strike distance and the fault point. These factors have the potential to impact the effectiveness of recognition. This paper presents a method for identifying lightning strike faults by utilizing Kullback–Leibler (KL) divergence enhanced Variational Mode Decomposition (VMD) and Symmetric Geometry Mode Decomposition (SGMD) improved with Permutation Entropy (PE) to address the aforementioned issues. A model of a 220 kV overhead line is constructed using real faults to replicate scenarios of winding strike, counterstrike, and short circuit. The three-phase voltage is chosen and then subjected to Karenbaren decoupling in order to transform it into zero mode, line mode 1, and line mode 2. The zero-mode voltage is decomposed using KL-VMD and PE-SGMD methods, and the lightning identification criteria are developed based on various transient energy ratios. The research findings demonstrate that the criteria effectively differentiate between winding strike, counterstrike, and short-circuit faults, thus confirming the accuracy and efficacy of the lightning fault identification criteria utilizing KL-VMD and PE-SGMD.

A Two-Stage Registration Strategy for Thermal–Visible Images in Substations

The analysis of infrared video images is becoming one of the methods used to detect thermal hazards in many large-scale engineering sites. The fusion of infrared thermal imaging and visible image data in the target area can help people to identify and locate the fault points of thermal hazards. Among them, a very important step is the registration of thermally visible images. However, the direct registration of images with large-scale differences may lead to large registration errors or even failure. This paper presents a novel two-stage thermal–visible-image registration strategy specifically designed for exceptional scenes, such as a substation. Firstly, the original image pairs that occur after binarization are quickly and roughly registered. Secondly, the adaptive downsampling unit partial-intensity invariant feature descriptor (ADU-PIIFD) algorithm is proposed to correct the small-scale differences in details and achieve finer registration. Experiments are conducted on 30 data sets containing complex power station scenes and compared with several other methods. The results show that the proposed method exhibits an excellent and stable performance in thermal–visible-image registration, and the registration error on the entire data set is within five pixels. Especially for multimodal images with poor image quality and many detailed features, the robustness of the proposed method is far better than that of other methods, which provides a more reliable image registration scheme for the field of fire safety.

Research on motor rotation anomaly detection based on improved VMD algorithm

PurposeThe electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder. The tolerance leads to imprecise brake control, so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system. This paper aims to present improved variational mode decomposition (VMD) algorithm, which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system.Design/methodology/approachThe VMD algorithm plays a pivotal role in the preliminary phase, employing mode decomposition techniques to decompose the motor speed signals. Afterward, the error energy algorithm precision is utilized to extract abnormal features, leveraging the practical intrinsic mode functions, eliminating extraneous noise and enhancing the signal’s fidelity. This refined signal then becomes the basis for fault analysis. In the analytical step, the cepstrum is employed to calculate the formant and envelope of the reconstructed signal. By scrutinizing the formant and envelope, the fault point within the electromechanical brake system is precisely identified, contributing to a sophisticated and accurate fault diagnosis.FindingsThis paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake (EMB) motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction. The signal is reconstructed according to the effective intrinsic mode functions (IMFS) component of removing noise, and the formant and envelope are calculated by cepstrum to locate the fault point. Experiments show that the empirical mode decomposition (EMD) algorithm can effectively decompose the original speed signal. After feature extraction, signal enhancement and fault identification, the motor mechanical fault point can be accurately located. This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems.Originality/valueBy using this improved VMD algorithm, the electromechanical brake system can precisely identify the rotational anomaly of the motor. This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled. Compared with the conventional motor diagnosis method, this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs. Moreover, the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.

Research on fault localization method of transmission line based on distributed monitoring

Abstract Transmission lines are the arteries of power system operation, carrying the important task of conveying electric energy, which is the most fragile and fault-prone place in the power system. This paper first analyzes the traveling wave propagation characteristics of transmission lines. It builds a mathematical model for the refraction and reflection phenomena of traveling waves that occur in the process of readjustment and distribution of transmission lines. The three traveling wave monitoring points nearest to the fault point are used to localize the fault, and the principle of the phase difference of split-phase current is explored based on the fault component. By means of experimental analysis, the phase currents of the three measurement points are detected, and for the transient current waveforms at the time of lightning strikes and short-circuits, the lightning fault localization method of the transmission line based on wavelet transforms is proposed and analyzed for fault localization of the technique. The results of simulation experiments show that when a ground fault occurs in the L1 phase of the line, the current fault components of measurement point 2 and measurement point 3 increase rapidly, and the element between measurement points is more than 10kA. The phase difference of the components is 180°, so the fault interval of the transmission line is from measurement point 2 to measurement point 3, and the fault phase is the L1 phase. Upon analysis, it is apparent that the actual fault distance error of 0.838km is the measurement of the fault distance of the transmission line, and the method proposed in this paper has a high level of measurement accuracy.

Demonstration Application of Adaptive Intelligent Monitoring and Analyzing System for Distribution Networks Based on Distribution OCS System and Multiple Data Fusion

Abstract Electricity is a matter of national livelihood, and monitoring the operation status of the distribution network is an effective means to improve the quality of electricity service. In this paper, we design a distribution network intelligent monitoring and analysis system based on the distribution network OCS system, so as to realize real-time monitoring of the operation status of the distribution network. The system processes the collected three-phase current, three-phase voltage, and other multivariate data through the multivariate data fusion processing technology and adopts the adaptive weighted fusion algorithm based on the t-test criterion to eliminate the coarse error values and enhance the data fusion effect. The software and hardware facilities of the distribution network intelligent monitoring and analyzing system are designed with the distribution network OCS system as the core, and the functional modules such as power data calculation, reactive power compensation, and intelligent protection are designed according to the requirements of practical applications. In practical application, the intelligent monitoring and analysis system for distribution networks described in this paper can successfully monitor electricity load, reactive power compensation, and other conditions in the townships in area A. The system can be successfully used to monitor the electricity load and reactive power compensation of the townships in area A. After the application of the system, it accurately determined 10 faults, promptly located the fault points, and isolated the faults automatically. The cost saving of only part of the project after the use of the system amounted to RMB 912,100, and at the same time, it greatly improved the satisfaction level of the users in the distribution network.