Fault Position Research Articles

Partial discharge fault detection method of switchgear based on signal aliasing spectrum separation model

At present, the detection nodes of partial discharge fault in switchgear are generally set in one direction, and the fault detection range is small, which leads to an increase in the false recognition rate of partial discharge fault detection. Therefore, the design and verification analysis of the detection method of partial discharge fault in switchgear is proposed. According to the current measurement requirements and standards, firstly, the characteristics of switchgear discharge faults are extracted, and the fault detection range is expanded by the multi-step method. Multi-step partial discharge fault detection nodes are deployed, and the partial discharge fault detection model with signal aliasing and spectrum separation is constructed. The fault detection is completed by hierarchical fuzzy automatic identification. The test results show that the final detection error rate of partial discharge fault is well controlled below 20% by comparing the seven selected test cycles and combining the signal aliasing spectrum separation model, which shows that the designed detection method of partial discharge fault is more flexible and changeable, and has strong pertinence and reliability. Facing the complex switchgear operating environment, it can also mark the fault position in the shortest time, strengthen the detection results and ensure the detection accuracy.

A First Approach on the Impact of Distributed Generation on Voltage Sags

An analysis of the distributed generation (DG) impact on studies of voltage sags caused by system faults is presented. The simulation of 62 case studies of phase-to-ground faults on 13.8, 69, 138 and 230 kV transmission lines were performed and the voltage of a 380 V sensitive industrial busbar client was monitored. These lines are part of the electrical system of the city of Goiania, Brazil. For each case study, different fault positions were simulated by considering different DG levels connected to the consumer busbar. Long-term simulation scenarios were obtained by the Monte Carlo method and analyzed based on their cumulative distribution functions and probability density curves of voltage sags. This is one major contribution of this work.

CUSUM based Fault Detection of Stator Winding Short Circuits in Doubly-Fed Induction Generator based Wind Energy Conversion Systems

This paper investigates the detection of short-circuit faults in the stator winding of a Wind Energy Conversion System (WECS) based on a Doubly-Fed Induction Generator (DFIG). The Cumulative Sum (CUSUM) algorithm is used to detect the change in the stator negative-sequence current magnitude which is used as the fault residual. The grid voltage unbalance is considered along with the fault position and its severity to evaluate the effect on the residual. The generator is modeled using the winding-function approach. Simulation results are presented for a 15 kW system operated, under a power control strategy, at rated conditions. It is shown that the fault-detection method is able to detect the fault rapidly and is not influenced by the grid voltage unbalance within normal limits.

A First Approach on the Impact of Distributed Generation and network topology on Studies of Voltage Sags

An analysis of the distributed generation (DG) and network topology impact on studies of voltage sags caused by system faults is presented. The simulation of 62 case studies of phase-to-ground faults on 13.8, 69, 138 and 230 kV transmission lines were performed and the voltage of a 380 V sensitive industrial busbar client was monitored. These lines are part of the electrical system of the city of Goiania, Brazil. For each case study, different fault positions were simulated by considering different DG levels connected to the consumer busbar. Long-term simulation scenarios were obtained by the Monte Carlo method and analyzed based on their cumulative distribution functions and probability density curves of voltage sags. This is one major contribution of this work.

Tools for Assessing the Robustness of Electrical System against Voltage Dips in terms of Amplitude, Duration and Frequency

The method of fault position is useful for characterizing power-system performance in the presence of voltage dips due to faults. It is based on short-circuit simulations repeated for all the system nodes and for many points along the system lines: fault voltages that are below a preset threshold are the required voltage dips. These dips are stored in so-called dip matrices, which contain only the dips in all the system nodes when faults occur at points along the lines. Graphical presentation of dip matrices has been proposed as a valuable tool to ascertain the critical area for system performance; this graphical visualization immediately correlates dip severity in terms of amplitude with colours defined by a proper scale. This paper proposes a new graphical representation of the During Fault Voltage matrices that allow accounting for also the dip frequency that is a very important aspect for assessing the voltage dip severity. New robustness indices are also proposed to synthesize bus performance in terms of affected and exposed areas able to account for not only the amplitude of the residual voltage but also the frequency. All the concepts are introduced and illustrated with reference to a real distribution systems.

A First Approach on the Fault Impedance Impact on Voltage Sags Studies

An analysis of the fault impedance impact on studies of voltage sags caused by system faults is presented. The simulation of 62 case studies of phase-to-ground faults on 13.8, 69, 138 and 230 kV transmission lines were performed and the voltage of a 380 V sensitive industrial busbar consumer was monitored. These lines are part of the electrical system of the city of Goiania, Brazil. For each case study, different fault positions were simulated by considering resistive fault impedances of 0, 2, 5, 10, 15 Ω or a random fault impedance with a specific distribution function. Long-term simulation scenarios were obtained by the Monte Carlo method and analyzed based on their cumulative distribution functions and probability density curves of voltage sags. This is one major contribution of this work. We found that, the greater the fault impedance, the smaller the average number of voltage sags expected per year at the end-user busbar. However, the behavior of the average number of voltage sags of a given class of magnitude with the fault impedance does not follow a general law.

A First Approach on the Impact of Distributed Generation and Fault Impedance on Studies of Voltage Sags

An analysis of the distributed generation (DG) and fault impedance on studies of voltage sags caused by system faults is presented. The simulation of 62 case studies of phase-to-ground faults on 13.8, 69, 138 and 230 kV transmission lines were performed and the voltage of a 380 V sensitive industrial busbar client was monitored. These lines are part of the electrical system of the city of Goiania, Brazil. For each case study, different fault positions and impedance fault were simulated by considering different DG levels connected to the consumer busbar. Long-term simulation scenarios were obtained by the Monte Carlo method and analyzed based on their cumulative distribution functions and probability density curves of voltage sags. This is one major contribution of this work.

Wave-based fault detection in concrete by the Full Waveform Inversion considering noise

In the field of non-destructive testing of concrete, the use of ultrasonic waves became state of the art, among other techniques. Nevertheless, there is still room for improvement, in particular concerning the resolution and robustness of the monitoring results.One approach is the application of the Full Waveform Inversion (FWI) originating from geotechnical engineering, known here as seismic tomography. The forward and backpropagation of waves within a numerical model are deployed to identify material parameters, like the primary and secondary wave velocity as well as density. This approach forms a non-linear, and ill-posed mathematical problem. Its solution is computationally demanding and time-consuming.Within the presented approach, the Full Waveform Inversion is used on a numerically simulated artificial concrete specimen of relatively large dimensions. Here, the synthetic ultrasound data is compromised by the consideration of different levels of Gaussian white noise. Additionally, several sizes and positions of faults are computed to simulate a variety of possible defects within the concrete material as in reality. Subsequently, the identifiability of the fault together with its recognition quality are investigated. Additionally, recommendations on sensor positioning and layout are given.

Novo ispitivanje korišćeno za predviđanje pritiska prskanja prave korodirane cevi pod unutrašnjim pritiskom

Introduction/purpose: There is a growing interest in pipeline integrity and its effects on economic and safety aspects. This study examines the process of corrosion evaluation in order to identify the remaining structural integrity of thin-walled pipelines with corrosion problems. Methods: This work aims to create a corrosion evaluation model that can analyse the deterioration of steel pipes caused by internal pressure. A study utilised the finite element approach to build models for predicting the burst pressure of defect-free straight pipes. The study involved analytical and numerical analysis and used the mathematical extrapolation method. Results: This paper discusses the impact of several factors on the integrity of a pipe, including the depth of defects, the thickness of the pipe, the shape, the size, and the position of faults, as well as the interaction between internal and external defects. Additionally, the influence of external defects on the overall integrity is discussed. Conclusion: It is concluded that the pipeline corrosion failure criterion (PCORRC) model and the presented model align with the analytical solution documented in the literature. This holds immense importance in the field of structural design and safety evaluation.

A two-terminal fault location method for gas switch prefire in linear transformer driver.

Large-scale linear transformer drivers (LTDs) are composed of numerous high-power gas switches, and switch prefire is a frequent operational fault. To detect and locate the faulty switch accurately and efficiently, a two-terminal location method is proposed. A B-dot sensor is integrated on the gas switch's shell to collect the discharging signal. All the B-dot sensors are connected in parallel through cables of equal length. The fault position can be determined by the time delay of the signals at the two terminals. A diode is inserted between the B-dot sensor's coil and the cable core to ensure low-loss transmission of the signal. Two methods are applied in fault location, including time-of-arrival (TOA) and time reversal (TR). For the TOA method, an energy criterion and a phase criterion are applied and compared. The accuracy of the energy criterion is greatly influenced by the signal-to-noise ratio, while the phase criterion requires a reasonable estimate of the actual delay to account for the impact of phase periodicity. The TR method based on a precise simulation model is established, which demonstrates high precision in location. The TR method has been tested and validated on a single stage LTD module. Moreover, the location method for double switches prefire is discussed theoretically. The method proposed in this paper will be helpful to improve the efficiency of the commissioning, operation, and maintenance of the large-scale LTD devices.

A Hierarchical Identification Method of Commutation Failure Risk Areas in Multi-Infeed LCC-HVDC Systems

In the multi-infeed LCC-HVDC system, the concurrent commutation failure (CCF) caused by the AC fault of the receiving-end system may lead to the blocking of multiple converter stations, which challenges power grid security and stability. This paper proposes a novel method to quickly and accurately identify the CF risk areas, considering the CF probability (CFP) during the single-line-to-ground (SLG) fault. First, an AC-DC voltage asymmetry factor (ADVAF) and its theoretical derivation are proposed to quantify the influence of the fault position on the CF. Second, the critical ADVAF (CADVAF) is derived based on the equivalent method. By comparing ADVAF and CADVAF, the CF risk areas can be quickly divided into non-, possible- and inevitable-concurrent CF risk areas. Third, the relationship between local CFP (LCFP) and fault position is established, and the concurrent CFP (CCFP) is calculated. The proposed method has improved the accuracy and computational efficiency of theoretical analysis than earlier methods. Finally, the validity and accuracy of the proposed method are verified in dual-infeed and five-infeed LCC-HVDC systems built based on the IEEE 39-bus and IEEE 118-bus models, respectively.

Prediction of Inter-Well Petrophysical Properties from Seismic Model: A Case of Egbem Field, Niger Delta, Nigeria

We have generated a seismic model for the prediction of inter-well petrophysical properties of Egbem Field; in the Niger Delta, Nigeria. Acoustic Impedances (AI) were calculated from sonic and density logs in the available 24 wells. Reflection Coefficients (RC) determined from the acoustic impedances were convolved with modelled wavelet to produce synthetic seismograms at various well locations. A top structure map of a reservoir from the field was used to define the position of faults, which served as key pillars in gridding the reservoirs of the field into geocellular blocks of 50 x 50 meters each. Petrophysical analysis of the field showed an average porosity of 24.8% and volume of shale of 19.9%. Petrophysical parameters were geostatistically distributed on the generated framework model using Sequential Gaussian Simulation (SGS). The result of the Acoustic Impedance classification reveals four lithologic facies namely, shale, sandy shale, shaley sand and sand facies. The facies model indicates high and low acoustic impedances for sand and shale respectively. This model indicates that sand which is a good reservoir is concentrated in the central part of the field. The result of synthetic seismic generation showed a very good match between acoustic impedance and lithology. Comparison of porosity obtained from the porosity model with conventional well log porosity showed similarities in their histogram distribution. Finally, Three-dimensional seismic model of Egbem Field has been constructed using log data from twenty four wells. The application of geostatistical analyses extrapolated and interpolated these log data to cover the entire field.

Tetrahedral Clusters Stabilized by Alloying.

A family of nanoclusters of tetrahedral symmetry is proposed. These clusters consist of symmetrically truncated tetrahedra with additional hexagonal islands on the four facets of the starting tetrahedron. The islands are placed in stacking fault positions. The geometric magic numbers of these clusters are derived. Global optimization searches within an atomistic potential model of Pt-Pd show that the tetrahedral structures can be stabilized for intermediate compositions of these nanoalloys, even when they are not the most stable structures of the elemental clusters. These results are also confirmed by density functional theory calculations for the magic sizes 59, 100, and 180. A thermodynamic analysis by the harmonic superposition approximation shows that Pt-Pd tetrahedral nanoalloys can be stable even above room temperature.

Research on neural network-based fault diagnosis and prediction method for power communication equipment

Abstract In this paper, facing the digital development of the power grid and the status quo of massive power communication equipment access and targeting the demand for highly intelligent operation and maintenance management of the power grid, combined with neural network technology, we propose an intelligent diagnosis model of power communication equipment faults. Adopting BERT as the vector embedding layer to obtain the vector sequence of fault text, designing a fault entity recognition model for power communication equipment based on BERT-BiGRU-CRF, and completing the construction of the relationship set of fault text. The proposed knowledge graph-based power communication equipment fault intelligent diagnosis model combined with the WBLA-based power communication equipment fault severity level recognition algorithm to obtain different severity fault information, from which a TFIDF-COS-based power communication equipment fault intelligent diagnosis algorithm is designed to realize intelligent diagnosis of power communication equipment faults. After testing, the TFIDF-COS algorithm can get the best optimization effect when the number of hidden layers of the selected algorithm is 1, and the initial learning rate is 0.05, and its accuracy rate can be kept above 98%. Compared with the traditional fault diagnosis system, in terms of the order of magnitude 100M, 500M, 1G, and 5G, the running time is reduced by 322s, 1874s, 4617s, and 7467s, and the accuracy rate is increased by 2.33%, 2.6%, 32.02%, and 61.4%, respectively. Therefore, this paper realizes the accurate positioning of power communication equipment faults and provides technical support for intelligent operation and maintenance of the power grid.

Hybrid diagnostic approach for the diagnosis of district heating networks

Decarbonization of the heating sector is a mandatory target towards climate neutrality by 2050. In this framework, District Heating Networks (DHNs) do play an important role since the heat carrier is dispatched from a heat source to end-users.Reliability of DHNs can be affected by several faults, of which the negative consequences can be prevented by employing diagnostic methodologies to evaluate the health state of the DHN and promptly localize the fault cause.In the literature, DHN faults are usually detected by means of physics-based and data-driven methodologies, but their drawbacks may hinder their application. Thus, this paper proposes a hybrid approach composed of two steps aimed at detecting the most common faults occurring in DHNs, i.e., water leakages as well as anomalous heat and pressure losses. First, a data-driven diagnostic methodology is employed to assess whether a fault is occurring. Then, a physics-based diagnostic approach identifies the health indices of each pipe of the DHN, the fault position, its type and magnitude. In this paper, the hybrid diagnostic approach is applied to the DHN of the campus of the University of Parma, where different faults were artificially implanted.The diagnostic approach proves to correctly detect and identify the implanted faults, by also correctly estimating their magnitude even in the most challenging scenarios.

Improving fault identification in smart transmission line using machine learning technique

<span lang="EN-US">In this work inevitable for power transmission boards such as Tamil Nadu Generation and Distribution Corporation Limited (TANGEDCO) to look for a low-cost communication system with low power usage and to improve supply reliability, to transmit reliable fault information back to the control centre in real time. This work aims to design an automated and effective fault identification and position system for all overhead power transmission network networks using all current fault indicator technologies, machine learning methods, and commercially tested communication technology to easily and reliably pin a transmission system's flawed point parts. This will help to people avoid touching the electrical wire and prevent electrical shocks and current wastage as well. Smart transmission lines have played a decisive role in developing human protection and preventing current wastage. The transmission line is opened and the state of the line is evaluated, and the information goes to electrical board (EB) office. The system monitors the data by sending the alert message to the person responsible for the GPS location, either via SMS or BUZZER, or by displaying the alert message lives. Transmission line distribution is broad and most of them are spread around the geographical environment.</span>

Seismic attribute-assisted seismic fault interpretation

Fault mapping is one of the main tasks of 3D seismic interpretation, and seismic discontinuity attributes are often used to support fault mapping in vertical sections and time slices. The most commonly used fault mapping procedure involves three passes/generations. First, the approximate positions of faults (generation I) on some vertical sections are interpreted manually. Second, the generation I faults are projected on some time slices, and the individual fault traces (generation II) are picked on time slices. Finally, the generation II faults are projected onto the vertical sections and the fault sticks (generation III) are picked in the vertical sections. To speed up the fault mapping process, we use the seismic discontinuity attribute as input to automatically extract the generation III faults in the vertical sections under the generation I and II fault mapping conditions. A quality control (QC) step is essential to improve the accuracy of the automatically generated fault sticks. To reduce the time required for QC, we propose to output the fault sticks on the seismic vertical sections defined by the interpreters. The workflow is applied to a real seismic survey to demonstrate its effectiveness.

Implications for fault reactivation and seismicity induced by hydraulic fracturing

Evaluating the physical mechanisms that link hydraulic fracturing (HF) operations to induced earthquakes and the anticipated form of the resulting events is significant in informing subsurface fluid injection operations. Current understanding supports the overriding role of the effective stress magnitude in triggering earthquakes, while the impact of change rate of effective stress has not been systematically addressed. In this work, a modified critical stiffness was brought up to investigate the likelihood, impact, and mitigation of induced seismicity during and after hydraulic fracturing by developing a poroelastic model based on rate-and-state fraction law and linear stability analysis. In the new criterion, the change rate of effective stress was considered a key variable to explore the evolution of this criterion and hence the likelihood of instability slip of fault. A coupled fluid flow–deformation model was used to represent the entire hydraulic fracturing process in COMSOL Multiphysics. The possibility of triggering an earthquake throughout the entire hydraulic fracturing process, from fracturing to cessation, was investigated considering different fault locations, orientations, and positions along the fault. The competition between the effects of the magnitude and change rate of effective stress was notable at each fracturing stage. The effective stress magnitude is a significant controlling factor during fracturing events, with the change rate dominating when fracturing is suddenly started or stopped. Instability dominates when the magnitude of the effective stress increases (constant injection at each fracturing stage) and the change rate of effective stress decreases (the injection process is suddenly stopped). Fracturing with a high injection rate, a fault adjacent to the hydraulic fracturing location and the position of the junction between the reservoir and fault are important to reduce the Coulomb failure stress (CFS) and enhance the critical stiffness as the significant disturbance of stresses at these positions in the coupled process. Therefore, notable attention should be given to the injection rate during fracturing, fault position, and position along faults as important considerations to help reduce the potential for induced seismicity. Our model was verified and confirmed using the case of the Longmaxi Formation in the Sichuan Basin, China, in which the reported microseismic data were correlated with high critical stiffness values. This work supplies new thoughts of the seismic risk associated with HF engineering.

Adjustments for an HVDC link fault detector: practical considerations

In this work, practical considerations regarding the use of a fault diagnosis scheme based on a distributed adaptive estimator for the high-voltage direct current (HVDC) transmission line within a simplified model of the DC link are presented. Due to transients and steady-state ripple caused by unmodeled nonlinearities in the HVDC system's conversion part, parameter adjustments of the distributed estimator, including gains and thresholds, are performed to successfully determine the fault magnitude and position within the line through simulation studies. To validate the proposed scheme, numerical simulations of the diagnostic scheme are compared with two HVDC links: a simplified one and the CIGRE (International Council on Large Electric Systems).

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.