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The electrical power distribution system (EPDS) is an essential component of the power system. Electricity and its services have risen enormously in the recent period, and the primary task of EPDS is to distribute uninterrupted electricity to the consumer. The EPDS comprises numerous intricate, unpredictable, and interlinked components that are frequently susceptible to disruption or malfunction. Faults on EPDS are intended to be appropriately recognized and categorized before being eliminated as quickly as feasible. An efficient fault recognition mechanism makes relaying operations realistic, fast, safe, and dependable. In this article, we introduce a MATLAB simulation model based on the Electrical Fault Detection and Classification (EFDC) algorithm for shunt fault analysis in the EPDS and distinguish among heterogeneous types of shunt fault based on current and voltage waveform throughout the fault. The recommended fault scrutiny and isolation framework might aid in segregating malfunctioning sections from healthy EPDS. Numerous electrical shunt faults are modeled and simulated to detect such deficient behaviors. The suggested EFDC algorithm’s efficacy, including Digital Comparative Fault Classifier (DCFC), is examined by simulating different kinds of shunt faults throughout ring-main EPDS’s source and load regions to evaluate the proposed technique’s adaptability, as well as the outcomes are promising. [ABSTRACT FROM AUTHOR]

Efforts to protect electric power systems from faults have commonly relied on the use of ultra-high frequency (UHF) antennas for detecting partial discharge (PD) as a common precursor to faults. However, the effectiveness of existing UHF antennas suffers from a number of challenges such as limited bandwidth, relatively large physical size, and low detection sensitivity. The present study addresses these issues by proposing a compact microstrip patch antenna with fixed dimensions of 100 mm × 100 mm × 1.6 mm. The results of computations yield an optimized antenna design consisting of 2nd-order Hilbert fractal units positioned within a four-layer serpentine arrangement with a fractal unit connection distance of 3.0 mm. Specifically, the optimized antenna design achieves a detection bandwidth for which the voltage standing wave ratio is less than 2 that is approximately 97.3% of the UHF frequency range (0.3-3 GHz). Finally, a prototype antenna is fabricated using standard printed circuit board technology, and the results of experiments demonstrate that the proposed antenna is capable of detecting PD signals at a distance of 8 m from the discharge source. [ABSTRACT FROM AUTHOR]

Almost half of all electrical pump capacity consume in three-phase induction motors and most of them use in gas pumps and compressor in processes of industries for heating, cooling, pumping, conveyors, etc. The most important role of fault detection and detection (FDD) for manufacturing equipment is an effective indicator that can identify the faulty state of a process and then take appropriate action against future failures or adverse events. The impact of proper maintenance is reflected on an especially costly type of industrial machine. To avoid reducing the efficiency of the gas station, automated fault detection and diagnostics is very important and need to study. This article aims to establish a criterion for selecting which faults can be tested under laboratory conditions or by simulation with a virtual model and to determine the features that identify those faults. This efficiency identify of faults leads to saving of energy, service and operating costs. Virtual sensors applied to gas pumps to reduce the cost associated with FDD implementation are described. Finally, several areas of improvement for the aspects reviewed have been identified: increase the use of performance indicators for FDD, new and updated studies about the health status of field heat pumps, testing methods that take into account the gradual and probabilistic nature of heat pump faults and further research in the use of virtual sensors in FDD systems. [ABSTRACT FROM AUTHOR]

Broom-shaped structures are widely seen in transtensional basins, including those discovered in many sags of the Bohai Bay Basin. Broom-shaped transtensional structural zones are generally petroliferous and thus important targets for hydrocarbon exploration. This study analyzed the evolution and genetic mechanisms of the broom-shaped transtensional structures in the Gaoqing area of the Dongying Sag using the 3D seismic flattening technique and a physical simulation experiment. Furthermore, the control effects of the broom-shaped transtensional structures on hydrocarbon accumulation and distribution were discussed. The research results are as follows. The Gaoqing area is of a broom-shaped transtensional structure in planar view, composed of several arc-shaped secondary faults intersecting with high-level main fault in the same direction. On the seismic section, it appears as a typical semiflower-like structure. In the early stage (that is, during the deposition of the Kongdian Formation to the lower submember of the 4th member of the Shahejie Formation, Es4(L)), single-fault pattern consisting of single or multiple faults in alignment was developed under extensional stress. While with the change of structural stress (that is, during the deposition of the Es4(U) to the Es2(L)), more secondary faults were formed, and came in a pattern of broom-shaped structure together with the major fault. In the late stage (that is, during the deposition of the Es1 to the Guantao Formation), the en echelon fault pattern was formed, as the major fault broke into multiple secondary faults. The divergent end of the broomshaped transtensional structure has many secondary faults developed, the fault planes are gentle, and small-scale fan deltas are the predominant type of deposits. The hydrocarbon tends to laterally migrate far away and accumulate mianly in structural and lithologic-structural traps. On the other hand, in the convergent end, the fault planes are relatively steep, resulting in small-scale subaqueous fans or largescale deltas deposited along the major fault, with hydrocarbon accumulating minaly in structurallithologic traps proximal to the provenances. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper deals with the problem of fault-tolerant control for a class of perturbed nonlinear systems with nonlinear nonaffine actuator faults. Fuzzy systems are integrated into the design of the control law to get rid of the system nonlinearities and the considered actuator faults. Two adaptive controllers are proposed in order to reach the control objective and ensure stability. The first term is an adaptive controller involved to mollify the system uncertainties and the considered actuator faults. Therefore, the second term is known as a robust controller introduced for the purpose of dealing with approximation errors and exogenous disturbances. In general, the designed controller allows to deal automatically with the exogenous disturbances and actuator faults with the help of an online adaption protocol. A Butterworth low-pass filter is utilized to avoid the algebraic loop issue and allows a reliable approximation of the ideal control law. A stability study is performed based on Lyapunov's theory. Two inverted pendulum example is carried out to prove the accuracy of the controller. [ABSTRACT FROM AUTHOR]

In order to evaluate the petrophysical properties, characterize the structural framework and determine the hydrocarbon in place of potential reservoirs in the Baris Field, onshore Niger Delta Basin, Nigeria, 3D seismic and well log data from the field were collected and interpreted using Geographix and Petrel software. Two reservoir zones B2 and B5 were identified having porosity ranging from 21% to 22%, permeability from 235 to 523 mD and water saturation from 16% to 28%. Petrophysical parameters show that the two zones are good reservoirs and highly petroliferous. Seismic interpretation revealed the presence of six listric faults, two major faults (F1 and F2 trending in the northwestesoutheast direction) and four minor faults (F3, F4, F5 and F6). Faults 3, 4 and 5 trend in the same direction as the major faults, while fault 6 trends in the northeastesouthwest direction. Two major horizons were identified, and they correspond to the two reservoir tops (B2_top and B5_top). Roll-over anticlinal structures between the two major listric faults were identified. The depositional environment of the Reservoirs B2 and B5 have been deciphered to be of a barrier bar or crevasse play and the trapping mechanism in the Baris Field is a four-way structural closure. STOOIP and GIIP for the two zones have been estimated with the zone B5 more prolific with a STOOIP and GIIP of 7.98MMSTB and 12.77MMMSCF respectively. [ABSTRACT FROM AUTHOR]

Copyright of Journal Industrial Engineering / Revista de Ingeniería Industrial is the property of ECORFAN-Mexico S.C. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Unbalanced loads and faults cause power quality problems in power grids, which may lead to system elements failure, particularly to synchronous generators. Faults detection and identification of the disturbance severity level are essential in the grids. Important equipment are often protected with dual protection systems. A backup protection operates and trips appropriate circuit breaker(s) only if the main protection fails to detect the disturbance presence or miss opening the breakers. This paper proposes a backup protection scheme for detecting and evaluating the disruption severity of voltage and current signals for protecting the synchronous generators. This scheme is based on a numerical technique of correlation applied for the electrical signals to detect and assess the fault situation. Different fault types are experimentally conducted on a motor‐generator set to test the proposed algorithm effectiveness using Data Acquisition Card (DAC) and LABVIEW software. The scheme has proven to be successful for fault detection and assessment. The algorithm has shown high reliability at various faults and operating conditions. Moreover, the practical results reveal that the scheme is able to evaluate the severity degree of disturbances/unbalances, and it is effective and secure considering the acceptable overloading, harmonics and temporary faults in power grids. [ABSTRACT FROM AUTHOR]

In modern infrastructure, the demand for DC power-based appliances is rapidly increasing, and this phenomenon has created a positive impact on the acceptance of the DC microgrid. However, due to numerous issues such as the absence of zero crossing, bidirectional behavior of current, different magnitudes of fault current during grid connected and islanded modes of operation protection of the DC microgrid remains a difficult task. Apart from these challenges, intermittent conditions are also a major challenge throughout the year. Under such type scenarios, shadow conditions in the solar based DERs will reduce the desired output of the solar panels simultaneously wind based DERs will be also affected due to the low pressure of air. In this type of circumstances, threshold setting based overcurrent relays may fail to sense the operational dynamics of the system. Therefore, in this manuscript, an ensemble of decision tree-based protection scheme is proposed to provide immunity against the stochastic conditions under the varying nature of the fault resistances. A total of 7150 test cases have been considered for validation of the protection scheme and all modules have been tested. After successful testing of the modules, the accuracy of the mode detection module is 99.23% for grid connected mode and 98.16% for islanded mode. Similarly, for fault detection/classification modules, accuracies are 99.06% and 97.98% respectively for both of the modes. The outcomes after validation of the protection scheme reveal that the protection scheme is robust and efficiently working. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid system is proposed to predict and classifies the power system transmission line faults. The proposed technique is the consolidation of both the truncated singular value decomposition (TSVD) and Human urbanization algorithm (HUA) based Recurrent Perceptron Neural Network (RPNN), and hence it is named as TSVD-HUARPNN technique. TSVD is matrix decomposition, this technique qualify the outcome it as fast or not. In the proposed work, the qualification of the results from the TSVD is improved by a lemma theorem; it is a proven proposition which is used to obtain a larger and optimal result. For that reason, it is also known as a "helping theorem" or an "auxiliary theorem". Here, it has two modules for power system fault analysis: (i) fault detection, (ii) fault classification. The first process of the proposed system is the generation of the dataset of normal and abnormal conditions of transmission line parameters of power system using TSVD. The extracted dataset is assessed by HUA-based RPNN system to classify the fault analysis that occurs in transmission system. The TSVD-HUARPNN system is used to predict and classify the fault present in the transmission line. The proposed TSVD-HUARPNN system ensures the system with less complexity for the detection and classification of the fault, therefore the accuracy of the system is increased. By then, the proposed model is activated in MATLAB/Simulink, its performance is evaluated with the existing models. The performance with noise at 20 dB of the proposed technique is 99.77%. • Hybrid technique is proposed for predicts, classifies the power system transmission line faults. • The proposed technique is the consolidation of both TSVD and HUA based RPNN. • TSVD prepare dataset based on transmission line parameters normal and abnormal condition. • The extracted dataset is assessed by the HUA based RPNN technique. • The proposed technique guarantees the system with lessens complexity. [ABSTRACT FROM AUTHOR]

Rapid technological development in grid integration of renewable energy (RE) plants has increased the RE penetration level in power utility network. This dramatic change in power scenario challenges the protection and stability of grid. Therefore, this work proposed a protection scheme algorithm (PSA) for the RE integrated hybrid power system. This PSA is implemented in the following steps: (1) calculate Wigner distribution function powered fault index (WFI), (2) calculate Stockwell transform powered combined FI (SCFI), (3) calculate hybrid FI (HFI) using WFI and SCFI, (4) classify the faults using number of faulty phases and fault ground index. Proposed hybrid fault index is used for the identification of faults. It also considers the change in magnitude and waveform distortions of current signals. The proposed PSA effectively identifies and classifies the faulty events such as single phase to ground, two phase, two phase to ground and all phases to ground. PSA is successfully tested for the recognition of faults under various operating scenarios like noisy scenario, different magnitudes of fault impedance, fault location node and fault incidence angle, lines comprising of overhead section and underground cable with availability of transformer. This PSA is effective to discriminate the operational switching events compared to faulty events. It is concluded that performance of the introduced PSA is better and fault detection time is less compared to wavelet energy spectrum entropy based PSA, discrete wavelet transform (DWT) based PSA and Stockwell transform supported PSA. [ABSTRACT FROM AUTHOR]

A testbench is built to verify a functionality of a shift register IC (Integrated Circuit) from stuck-at-faults, stuck-at-1 as well as stuck-at-0. The testbench is supported by components, i.e., generator, interface, driver, monitor, scoreboard, environment, test, and testbench top. The IC consists of sequential logic circuits of D-type flip-flops. The faults may occur at interconnects between the circuits inside the IC. In order to examine the functionality from the faults, both the testbench and the IC are designed using SystemVerilog and simulated using Questasim simulator. Simulation results show the faults may be detected by the testbench. Moreover, the detected faults may be indicated by error statements in transcript results of the simulator. [ABSTRACT FROM AUTHOR]

The paper presents the fault recognition and reconfiguration technique for three-phase five-level cascaded H-bridge multilevel inverter operation. The multilevel inverter operation is carried out by using space vector modulation technique. Open switch fault is very frequent in multilevel inverter, which is located using fuzzy logic whereas the fault reconfiguration is done by adding one auxiliary inverter module with the main multilevel inverter which operates in a faulty condition and regulates the output voltage. The operation of auxiliary inverter module is according to the switching state provided which is based on a fault that occurs in a particular switch. In this method continuous operation of the main multilevel inverter is possible even in the fault condition with only one or two voltage level missed at the output. The continuous operation of multilevel inverter with reduced THD is achieved without using filter which is affirmed by MATLAB® simulation. [ABSTRACT FROM AUTHOR]

In this paper a novel technique is presented for fault location in distribution networks in the presence of distributed generators (DGs). The proposed approach uses recorded voltage and current at the beginning of feeder and DG terminals. This method is based on transient state data, and due to presence of high frequencies in this state, to achieve high accuracy it utilizes the distributed time‐domain (DTD) line model. The fault location problem is formulated as an optimization problem and is solved using Genetic Algorithm (GA). Through modal transformation, in addition to locate the symmetrical three‐phase to ground (3LG) faults, the location of asymmetrical faults including single line to ground (SLG) and double line (LL) faults can also be determined. The effects of fault distance, fault resistance and fault inception angle on the accuracy of the proposed algorithm have also been investigated. A solution is also proposed to overcome the multi‐response problem. The simulations are conducted and the results are obtained via PSCAD and MATLAB softwares, respectively. The effectiveness of the proposed approach has been verified using the modified IEEE 34‐node test feeder under different fault conditions. The simulation results demonstrate the high efficiency and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

The renewable energy sources (RESs) projects are solutions with environmental benefits that are changing the traditional power system operation and concept. Transient stability analysis has opened new research trends to guarantee a secure operation high penetration. Problems such as frequency fluctuations, decoupling between generator angular speed, network frequency fluctuation and kinetic energy storing absence are the main non-conventional RESs penetration in power systems. This paper analyzes short-circuit influence on frequency response, focusing on weak distribution networks and isolated, to demonstrate relevance in frequency stability. A study case considered a generation outage and a load input to analyze frequency response. The paper compares frequency response during a generation outage with a short-circuit occurrence. In addition, modular value and angle generator terminal voltage affectation by electric arc and network ratio R⁄X, failure type influence in power delivered behavior, considering fault location, arc resistance and load. The arc resistance is defined as an added resistance that appears during failure and influences voltage modulus and angle value results showing that intermittent nonconventional RES participation can lead to frequency fluctuations. Results showed that arc resistance, type of failure, location and loadability determine the influence of frequency response factors in weak power systems. [ABSTRACT FROM AUTHOR]

Copyright of Electric Drive is the property of Electric Drive Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The noise and vibration level in modular‐type permanent magnet synchronous machines with fractional slot concentrated windings (FSCW) is considered to be an important design consideration, particularly for applications requiring fault tolerance. In this work, an interior permanent magnet synchronous machine (IPMSM) with FSCW is designed in a modular manner by dividing its stator windings into different arrangements having independent three‐phase sub‐modules with separate neutral points. First, the modular concentrated winding arrangement is studied to investigate the radial forces, vibration, and the associated noise level in the prototype machine having three‐phase sub‐modules under open‐circuit fault conditions. Then, another type of distributed three‐phase sub‐module winding arrangement is analysed to further investigate the vibration and noise level in the same prototype machine under the same operating conditions. A detailed two‐dimensional (2D) fast Fourier transform analysis is performed to investigate and compare the machine radial forces, induced harmonics, and sub‐harmonics for the two analysed winding arrangements. Considering the advantages and disadvantages of both the winding arrangements, the third type of mixed concentrated and distributed three‐phase sub‐modules winding arrangement is introduced in this work, combining the first two winding design approaches. A comprehensive harmonic (3D) structure, along with the vibration and noise analysis, is performed using a multi‐physics model analysis for all the winding arrangements under different three‐phase sub‐modules open‐circuit fault conditions. Lastly, the vibration levels of all the machine prototype models under different winding arrangements are experimentally validated. Moreover, the different modular types of winding arrangements are deeply investigated in this work to suggest the best winding arrangement approach that enables the machine to work in a wide range of applications requiring lower power levels or under critical, faulty, and hostile conditions. The proposed winding arrangement has reduced stator deformation with a reduced vibration and noise level under three‐phase sub‐modules open‐circuit fault‐tolerant conditions that can be used according to process requirements. [ABSTRACT FROM AUTHOR]

This study proposes a novel method to improve the fault identification performance of transformers. First, to couple multiple factors, a high‐dimensional feature map composed of the feature gas concentrations and some associated variables is constructed. Second, the deep residual shrinkage network is revised using the updated alternating direction multiplier, and the newly constructed variable soft thresholding is proposed to eliminate constant deviations. In addition, the fast iterative shrinkage‐thresholding algorithm is adopted, as it can speed up the determination of the threshold. For the output end, the uniform manifold approximation and projection algorithm are adopted to ensure the integrity of the local optimal solution and the global solution. Compared with traditional dissolved gas analysis methods, the novel refined deep residual shrinkage network exhibits superior precision, which is justified through experiments. The results show that the recognition accuracy of the new model is more than 1.3% higher than that of the existing methods. The new method has good scalability in power applications and fault prevention. [ABSTRACT FROM AUTHOR]

Inter‐turn faults are most commonly the initial stator winding fault in power trains with Voltage Source Inverters. Without counteractions, these faults can propagate and cause catastrophic failures in safety critical applications like all‐electric aircraft. The propagation of an inter‐turn fault can be reduced, by limiting the local temperature at the fault. In this article, a fault tolerant control scheme is designed and validated, which reduces the heat of an inter‐turn fault by a controlled adaption of the operating point. The control strategy utilizes the hyperbolas of constant torque and the controller design is based on a linear time‐invariant system description. A machine learning regression is used for the online heat estimation and a 3D lumped‐parameter model to evaluate the thermal effectiveness. To test the control scheme, an inter‐turn fault is actively switched, which generates the local heat equal to 13% of the overall stator copper losses. The control scheme adopts the operating point within 30 electric periods, which reduces the generated heat of the inter‐turn fault by 70%. This causes a temperature reduction at the fault locally from 367°C to 175°C, which extends the approximated insulation life from 30 s to 5000 h. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of fault diagnosis in discrete event systems through a decentralized structure. Within the proposed decentralized diagnosis structure, local most permissive bbservers (MPOs) are employed as diagnosis tools, and an effective protocol is proposed to coordinate local MPOs to infer diagnosis information. It is shown that the proposed technique can diagnose fault occurrences subjected to proper sensing decisions. A sufficient condition on sensing decision policies is derived for diagnosis of faults in a decentralized setting. Further, it is proven that the proposed decentralized structure has less complexity than a centralized structure. The details of the proposed technique are illustrated by applying the developed method to a manufacturing system. [ABSTRACT FROM AUTHOR]

In principle, every vehicle is equipped by a suspension system, which usually consists of springs and shock absorbers. The main purpose of the suspension system is to eliminate vibration of sprung and unsprung masses. Therefore, the proper operation conditions of the shock absorbers affect in a fundamental way total running properties of vehicles. However, during operation, shock absorbers are being worn out or they can even be damaged. Then, such a situation is unwanted and it has to be detected as soon as possible. The content of this article is focused on analysis of vehicles' shock absorbers defects. Methods for detection of possible shock absorbers faults are presented. Further, a proposal of the method for detection of a state of a hydraulic shock absorber during its operation is presented. The method uses identification of the temperature change of a hydraulic shock absorber during operation. [ABSTRACT FROM AUTHOR]

Power outage is the problem that hinders social and economic development especially for developing countries like Tanzania. Frequent power outages damage electric equipment, and negatively affect the industrial production process. Power outages cannot be completely eradicated due to uncontrolled cause like natural calamities but technical challenges can be managed and hence reducing power outages. The existing manual methods used to locate power outage like customer calls is inefficient and time consuming. On the other hand, modern method like the Advanced Metering Infrastructure (AMI) still faces a challenge in effectively classifying power line outage due to the nature of imbalanced datasets. Therefore, there is a need to develop a Machine Learning (ML) model to accurately classify power line outage. In this study, machine learning models are constructed from ensemble algorithms and tested using outage AMI data from 2012 to 2019 with 2 hours interval records. We propose the following ensemblebased machine learning approach to enhance classification; data sampling, algorithm weighting and finally ensembling. Results show that the Hybrid Stacking Ensemble Classifier (HSEC) model outperforms the others by accuracy of 0.981 G-mean, followed by Extra tree with accuracy of 0.964 G-mean. This model can be used in power line outage classification in any Secondary Electrical Distribution Network (SEDN). This study can be extended to locate power outage to household. [ABSTRACT FROM AUTHOR]

Operation of Vernier machines is based on flux modulation. They have some advantages including maintaining the rated torque in motor applications and the rated output power in generator applications at low speeds, high torque density and relatively low torque ripple due to their magnetic gear property and fault‐tolerance. In recent years, the motor with various topologies has been developed for different applications. Therefore, analysing and monitoring different faults is essential in the design and implementation stages. This study has two main purposes. First, to introduce an accurate frequency index independent of load variations for detecting the turn‐to‐turn short circuit (TTSC) faults in the stator windings of a permanent magnet Vernier machine. Second, modelling the machine in a healthy condition and in the presence of TTSC faults to investigate its effect on machine performance and output characteristics. An analytical model is presented using the modified winding function theory under the TTSC fault by taking into account the effect of stator slots which enhances the accuracy of the air‐gap permeance function estimation. In the process of calculating the fault index, frequency components of the output characteristics of the machine are obtained from the mathematical equations of the magnetic field. It is shown that the proposed indicators are robust against load variations. [ABSTRACT FROM AUTHOR]

Large-scale long-distance grid connection of wind farms has problems such as high line losses and small transmission capacity. The use of modular multilevel flexible direct current transmission (MMC-HVDC) for power transmission is an effective solution. And the recovery of system safety and stability under fault conditions is a hot spot for research. For the problem of DC bus voltage rise caused by symmetrical faults on the grid side, the AC voltage step-down method of the wind farm side converter station (WFMMC) is used for coordinated control with the self-regulating energy-consuming circuit. The capacity required for the self-regulating dissipation resistor is reduced while ensuring that the wind farm networked MMC-HVDC system can traverse the fault stably and smoothly; And the controller for suppressing negative sequence current is designed to effectively mitigate the three-phase current imbalance caused by asymmetric faults occurring on the grid side. The active power is transferred to the grid side while protecting the switching devices from damage. Finally, the correctness and effectiveness of the proposed scheme are verified in the PSCAD/EMTDC simulation software. [ABSTRACT FROM AUTHOR]

This paper proposes a novel Reduced Gaussian Process Regression (RGPR)‐based Random Forest (RF) technique (RGPR‐RF) for fault detection and diagnosis (FDD) of wind energy conversion (WEC) systems. First, two RGPR models are proposed to deal with WEC features extraction and selection. The proposed RGPR models extract the most relevant information from the WEC system data while reducing the computation burden compared to the classical GPR model. The complexity reduction is ensured by the selection of the most effective samples through the dimensionality reduction (DR) metrics including Hierarchical K‐means (HKmeans) clustering and Euclidean distance (ED). Next, in order to classify the WEC faults and improve the diagnosis abilities, RF classifier is developed. The proposed RGPRHKmeans‐RF and RGPRED‐RF techniques boost the classification speed and accuracy using a reduced number of features where only the most relevant and sensitive characteristics are kept in case of redundancy. The open‐circuit, wear‐out, and short‐circuit are the three transistor faults considered in order to illustrate the effectiveness and robustness of the developed techniques. The obtained results show that the proposed RGPR‐RF technique is characterized by a low computation time and high diagnosis accuracy (an average accuracy of 99.9%) compared to the conventional RF classifiers. [ABSTRACT FROM AUTHOR]

An improved natural frequency based method is proposed to accurately locate faults in transmission lines. The method only requires three phase instantaneous current measurements at the local terminal of the line and is compatible with protective relays using high‐speed tripping techniques. First, the theoretical peak frequencies along the entire frequency spectrum of the measured currents are derived, for different fault types, locations and resistances. Next, the fault location is determined by finding the minimum average distance between the theoretical and the measured peak frequencies. Compared to the existing natural frequency based fault location methods, the proposed method solves the mode mixing problem during single phase to ground faults and systematically considers the effect of fault resistances. In addition, the proposed method fully utilizes the frequency spectrum information instead of only the dominant frequency, and therefore overcomes the difficulty to extract the dominant frequency. Numerical experiments have shown that, compared to the existing method, the proposed method presents much higher fault location accuracy during single phase to ground faults, and slightly higher (comparable) fault location accuracy for other types of faults, regardless of fault locations and fault resistances. [ABSTRACT FROM AUTHOR]

The electric power transformer is an essential part of an electrical power system since it is used to step up or down voltage levels to maintain the system performance as well as possible. Frequency response analysis (FRA) is one of the most widely used techniques for detecting various types of mechanical damage in transformers. The equivalent circuit of the transformer will be represented by a complex network of R, L, and C elements in the FRA technique. For transformer faults diagnosis, various calculation techniques and diagnostic techniques may be used, such as acoustic emission analysis, thermal images of electromagnetic radiation, transformer temperature, and humidity analysis. SFRA test is one of these techniques that could be used to determine the fault type based on its response over a wide frequency range. The main challenge of the SFRA test is that the functional interpretation requirement for this test is not universally accepted Also statistical features are defined for this SFRA response to be used in fault detection and classification. In this paper, the effect of the transformer rating on the fault diagnosis techniques using SFRA is tested. Also, the effect of the transformer VA rating on the statistical parameters and the classification rules of fault diagnosis is discussed. Finally, the features used in fault diagnosis are ranked according to its independence of the transformer rating resulting in a more accurate matching fault diagnosis technique. [ABSTRACT FROM AUTHOR]

The accumulation and partitioning of crustal strain in central Tibet remain debated. July 23, 2020, Mw 6.4 earthquake in the Nima region (≈86.864°E/33.144°N) thus provides an opportunity to gain insight into local, ongoing deformation. Here, we use Sentinel‐1 SAR data to assess co‐seismic deformation during that earthquake, and nonlinear/linear inversions to determine the location and geometry of the source and the finite fault slip distribution. The results show that the maximum surface subsidence was ≈25 cm, the causative fault had a ≈N28°E strike and ≈48° dip eastwards, and that the largest normal slip, with a peak of ≈1.5 m, occurred between 5 and 10 km depths. Details of the earthquake surface rupture were derived from a UAV‐based field survey. At three distinct sites, the high‐resolution UAV images revealed discontinuous, ≈N35°E‐trending arrays of fresh en‐echelon cracks and ≤20 cm‐high, free‐faced normal scarps, along a ≈10 km‐long, ≈20 m‐wide zone following the ≈ vertically projected western limit of maximum interferometric synthetic aperture radar slip at depth. These results, consistent with an earthquake intensity distribution based on building damage inspection, show that 2020 earthquake only broke a short segment of the west Yibu Chaka normal fault, along the middle stretch of the 300 km‐long Riganpei Co‐Yibu Chaka‐Jiangai Zangbo fault zone. Regional Coulomb stress changes suggest that larger, Mw 7+ earthquakes should be expected on the geomorphologically more prominent, ≈50 km‐long normal faults bounding the east side of the Yibu Chaka lake pull‐apart, and on the 120 km‐long, sinistral Riganpei‐Co fault to the southwest. Plain Language Summary: 2020, Mw 6.4, Nima/Rongma earthquake provides new insights on crustal deformation across central Tibet. By combining Sentinel‐1 SAR data inversions with a detailed, UAV‐based survey of surface deformation in the field, we determine the geometry of the fault source, the finite fault slip distribution, and the length of the co‐seismic surface rupture. These results, which are consistent with the earthquake intensity distribution based on building damage, indicate that this earthquake ruptured a deep, ≈15 km‐long patch of the northeast‐striking West‐Yibu Chaka normal fault. Primary normal slip (up to 1.5 m), mostly between 10 and 5 km depth, triggered extensional craking and smaller (≤20 cm) dip‐slip along a small, sub‐parallel fault splay and a ≈60 m‐high ridge at the surface. The combined, regional Coulomb stress changes due both to the 2020 event and 2008 (Mw 6.4 and 5.9) earthquakes farther south imply that the broad, central Tibetan region north of Nima remains at risk of larger (Mw ≈ 7) events along the geomorphologically more prominent East Yibu Chaka and Riganpei Co faults to the northeast and southwest, respectively. Key Points: Interferometric synthetic aperture radar inversion and field mapping of the Mw 6.4, 2020 Nima/Rongma earthquake rupture along central Tibet's Yibu Chaka normal faultMarked differences between active faulting north and south of the Bangong suturePotential for larger (M 7 + ?) earthquakes along northeast and southwest Yibu Chaka fault zone [ABSTRACT FROM AUTHOR]

A differentiation in three‐phase voltages or currents is termed as unbalance. Unbalance can be caused by unbalanced loads and power system faults. This disturbance results in serious problems in system elements, particularly to synchronous generators, due to the deviation of magnitude, frequency or phase shift. The ability to detect unbalance as well as to identify the severity level of unbalance is very important in power grids. This paper describes a protection scheme for voltage and current unbalance in synchronous generators. The scheme is based on dual numerical techniques application utilizing correlation and deviations percentages for voltage and current signals to detect and assess the unbalance situations. Different types of disturbances are simulated to verify the effectiveness of the proposed scheme using ATP and MATLAB programs. The simulation results prove that the scheme is successful for unbalance detection and assessment of synchronous generators. The different faults and operating conditions have no effect on the proposed scheme reliability. Also, the results show that the proposed scheme is able to classify the unbalance into different severity levels. Besides the obtained results reveal this scheme is effective and secure to the acceptable overloading and temporary faults in power systems. [ABSTRACT FROM AUTHOR]

Locating faults after detecting is one of the important steps in software debugging. For fault localization, many approaches are there. Mutant based approaches are also available for fault localization and they have performed better compared to statement based approaches. In the present paper, a new mutant based fault localization approach named "DAM-FL" is proposed which is based on diversity aware mutation adequacy criterion. It uses diversified or distinguished mutants and their respective test suites for locating faults. Experiments on projects of defects4j repository show that for single line faults, proposed approach with a reduced number of mutants performs better or gives similar results compared to the traditional mutant based fault localization approach. For multi-line faults, it can be said that the proposed approach is equivalent to the traditional approaches. [ABSTRACT FROM AUTHOR]

The work proposed in this paper concerns the study of short circuit faults in a single-phase inverter dedicated to a photovoltaic application by applying the frequency response analysis (FRA) technique on this IGBT-based inverter controlled by a 18F2550 microcontroller, a prototype inverter was designed in the laboratory to be able to apply off-line short-circuit faults using an LRC meter. The FRA technique is based on the comparison of amplitude-frequency and phase-frequency signatures of healthy cases and fault situations. The experimental results also led to the conclusion that frequency response analysis can be used as an effective tool to detect faults in power electronic devices. This method allows for efficient detection and classification of faults with ease of implementation. For fault location, the fault branch is determined according to its position relative to its healthy state. [ABSTRACT FROM AUTHOR]

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Renewable energy plays a key role in reducing carbon emissions. The electric power system is widely considered a platform to accommodate renewable energy because of the high efficiency in transmitting energy through electricity tie lines. However, most renewable energy generation is weather-dependent, bringing difficulties in balancing generations and electricity demands. There are two major solutions to address the imbalance problem. The first is to balance the fluctuation of renewable energy in time scales by deploying energy storage, but with huge costs and security risks. The other is to balance the fluctuation in spatial scales by enhancing the interconnection among electric power systems, which however results in a sharp increase in the fault current in many countries. The high level of fault current threatens the security of power system. In other words, the overrating fault current of electric power systems is one of the key bottlenecks for carbon neutrality. To mitigate the high-level fault current because of the interconnection, we propose a novel mechanism, namely fault current release. It achieves new functionalities with proven equipment at low cost and will create no impact on the electric power systems in normal operation. The simulation selected six representative electric power systems, including those in the USA, the UK, China, Brazil, Nigeria and IEEE reliable test system. Results show that the fault current release method enables an increase of renewable energy accommodation from 19.2% ∼ 47.2% to over 90%, much higher than the existing methods can do. Correspondingly, the emissions of CO 2 , NO X and SO X in these systems decrease by 67.84% ∼ 88.07%, 61.17% ∼ 88.24% and 58.25% ∼ 88.33%, respectively. The proposed method is also economical in that it can accommodate renewable energy at about one-tenth the cost of energy storage. Our findings hence suggest a promising way to build a carbon-free energy system. • Interconnection enables renewable energy penetration over 90%, but also increases the fault current level. • The proposed fault current release method effectively reduces the fault current with proven equipment at low cost. • Tight interconnection plus with fault current release achieves lower emission with lower cost compared to energy storages. [ABSTRACT FROM AUTHOR]

Voltage source converter‐based high voltage direct current (VSC‐HVDC) transmission system has become the mainstream of power construction and plays an increasingly important role in the power system. However, the DC line fault results in shutting down of the converters, which can greatly endanger the security of the power grid. So it is essential to find a fast fault identification strategy for DC line protection technology. In addition, the existing backup protection scheme has the problems of long delay and strict communication synchronisation requirements. Therefore, this study proposes a novel protection scheme for VSC‐HVDC transmission lines based on the fault current integral autocorrelation coefficient. The fault current and fault current frequency characteristics of VSC‐HVDC transmission lines are analysed first. Second, this study proposes a method to filter out distributed capacitance current by current integration and eliminate the oscillation of fault current. Finally, the difference of the current integral during different faults (internal or external fault) is analysed, and the autocorrelation coefficient is introduced to express the difference. Hence, this study proposes a new principle for identifying faults using the autocorrelation coefficient of the fault current integral. Simulation results show that the protection principle is not affected by the distributed capacitive current and does not require strict communication synchronisation. It has an excellent performance in intolerance to fault resistance and noise interference and can be used as backup protection for VSC‐HVDC transmission system. [ABSTRACT FROM AUTHOR]

An accurate inter‐circuit fault location algorithm for double‐circuit transmission lines compensated by a generalized unified power flow controller based on phasor analysis is presented. The proposed algorithm utilizes synchronous currents and voltages of the buses on both sides of the line to accurately calculate the fault location. Using the equations of sequence component circuits, the algorithm calculates voltage and current of the fault point on both circuits. Then, using boundary conditions equations for 98 types of inter‐circuit fault on the double‐circuit transmission lines, the accurate location of the fault is obtained. The number of boundary conditions equations varies depending on the type of faulty phases of the two circuits and the number of unknowns in the current and voltage equations of the fault point. The calculation of these boundary equations are also described. The results presented in the simulation section verify the validity and accurate performance of the proposed algorithm under different fault conditions. [ABSTRACT FROM AUTHOR]

High voltage direct current (HVDC) transmission is an economical option for transmitting a large amount of power over long distances. Initially, HVDC was developed using thyristor-based current source converters (CSC). With the development of semiconductor devices, a voltage source converter (VSC)-based HVDC system was introduced, and has been widely applied to integrate large-scale renewables and network interconnection. However, the VSC-based HVDC system is vulnerable to DC faults and its protection becomes ever more important with the fast growth in number of installations. In this paper, detailed characteristics of DC faults in the VSC-HVDC system are presented. The DC fault current has a large peak and steady values within a few milliseconds and thus high-speed fault detection and isolation methods are required in an HVDC grid. Therefore, development of the protection scheme for a multi-terminal VSC-based HVDC system is challenging. Various methods have been developed and this paper presents a comprehensive review of the different techniques for DC fault detection, location and isolation in both CSC and VSC-based HVDC transmission systems in two-terminal and multi-terminal network configurations. [ABSTRACT FROM AUTHOR]

Solar photovoltaic (PV) is a prominent technology for the generation of electricity and its utility is on the rise. The PV-based generation facilities are susceptible to faults which if mismanaged, can result in an interruption in the supply of load demand and damage to the system. Faults in PV systems are caused by a broad range of reasons and hence, it is crucial to situate a fault-tolerant system for reliable operation. This study proposes a fault-tolerant control strategy for power electronics inverters for the integration of PV systems into power systems. This is a supervisory mechanism designed to aid PV systems to continue their operation during faults. A computer simulation verifies the performance of the proposed control strategy under a series of common fault conditions assuming a wide range of configurations for the PV system and load variations. [ABSTRACT FROM AUTHOR]

In some cases, LC filters are installed between the inverters and motors to suppress the adverse effects of pulse width modulation. However, some techniques should be modified, because the mathematical model of the drive system is changed by the LC filter and the sensors on the inverter output cannot measure some necessary variables. In this study, a multi-purpose proportional-integral (PI) observer is proposed at first. The type of observer depends on whether the position sensor is equipped. A sliding mode controller for the LC filter based on the observer is presented, therefore improving the dynamic performance. Furthermore, if the position sensor of the rotor is equipped, an open-switch fault diagnostic method is realised by means of the PI observer; if the position sensor is not equipped, the sensorless estimation is realized. The proposed strategies were realised without any additional current/voltage sensors. Experimental results verified the effectiveness of the proposed strategies. [ABSTRACT FROM AUTHOR]

Considering the problem to diagnose incipient faults in nonlinear analog circuits, a novel approach of fault feature-extracting based on HMFT (high order moment fractional transform) of the component parameter change is proposed. Firstly, the equivalence circuit model is established according to the topological structure and the voltage sensitivity of the circuit under test (CUT). Then the HMFT of component parameter changes are derived, which are used as fault features. Finally, using the extracted features, incipient fault diagnosis is accomplished. The simulations illustrate the proposed method and show its effectiveness in the incipient fault recognition capability. [ABSTRACT FROM AUTHOR]

This study aims to display fuzzy logic (FL) technique for diagnosis of fault induction machine. This allows monitoring of fuzzy information from different signals to give more accurate judgment on the health of the engine, through using a multi-winding model of induction machine for the simulation of broken bars. This model allows study the influence of defects and appear the behavior of the machine in the different modes of running conditions (healthy and fault). In this work, we focus the application of a fuzzy logic technique based on the fast Fourier transformation (FFT) by analyzing the stator current for fault detection. The results of the simulation obtained allowed us to show the importance of the fuzzy logic approach based on classification of signals for detecting the faulty. [ABSTRACT FROM AUTHOR]

The polyphase machine provides increased reliability by enabling operation with one or more phases in fault, and the most common faults are stator fault, it's for that a new analysis model of stator open phase faults in a five-phase induction motor has been presented in this paper. A new modeling of five phase induction machine in natural frame is elaborated, and the performance of five phase induction machine was analyzed under stator open phase using the principal component analysis (PCA) method. The PCA is a tool to reduce multidimensional data to lower dimensions while retaining most of the information, where the effect of the fault conditions caused by open phase on electromagnetic torque, mechanical speed, stator current and efficiency of this motor has been investigated. The findings of this research may be useful and help researchers who are interested on the fault tolerant control to minimize or eliminate this effect. [ABSTRACT FROM AUTHOR]

This study offers the opportunity to extend the functioning of the most advanced protection systems. The faults which can arise on the power transmission lines are numerous and varied: Short-circuit; Overvoltage; Overloads, etc. In the context of short circuits, the conventional sensor as the Mho distance relay also known as the admittance relay is generally used. This relay will be discussed later in this study. By taking into account the preventive risks of the Mho relay and discover the new techniques of artificial intelligence, namely the neural network which can contribute to the precise and rapid detection of all types of short-circuit faults. The results of the simulation tests demonstrate the effectiveness of the methods proposed for the automatic diagnosis of faults. [ABSTRACT FROM AUTHOR]

We present a smooth surface interpolation method enabling to take discontinuities (e.g. faults) into account that can be applied to any dataset defined on a regular mesh. We use a second-derivative multi-scale minimization based on a conjugate gradient method. Our multi-scale approach allows the algorithm to process millions of points in a few seconds on a single-unit workstation. The interpolated surface is continuous, as well as its first derivative, except on some lines that have been specified as discontinuities. Application in geosciences are numerous, for instance when a structural model is to be built from points picked on seismic data. The resulting dip of interpolation extends the dip of the input data. The algorithm also works if faults are given by broken lines. We present results from a synthetic and real examples taking into account fault network. [ABSTRACT FROM AUTHOR]

Despite advancements in technology, power system faults leading to electric power interruption remain a significant issue. Efficient restoration of the power system relies on the swift classification and clearance of faults. Among the various types of faults in transmission lines, open circuit and short circuit faults are commonly encountered. This study specifically focuses on the analysis of five types of short circuit faults: line-to-line, line-to-ground, double line-to-ground, triple line, and triple line-to-ground faults. Faults can cause both power failure and power loss in transmission lines. Once a fault occurs, it is crucial to restore electricity supply promptly to prevent further losses. Therefore, the development of a system capable of accurately and swiftly detecting and removing faults is essential. Traditionally, categorizing transmission line faults required sophisticated mathematical modeling, intricate signal processing techniques, and expert knowledge to interpret the output signals. In this paper, an alternative approach is proposed, utilizing deep learning techniques for transmission line fault classification. Specifically, the paper employs techniques such as artificial neural network (ANN), long short-term memory (LSTM), with and without window regression (WR). By implementing these deep learning techniques, automatic feature extraction and signal processing are achieved, streamlining the fault classification process. The experimental results obtained from this study demonstrate an accuracy of 42.98% for ANN, 99.98% for LSTM, and 99.99% for LSTM-WR. These outcomes underscore the effectiveness of the deep learning techniques employed in accurately classifying transmission line faults, with LSTM and LSTM-WR outperforming ANN in terms of accuracy. [ABSTRACT FROM AUTHOR]