Search

The impacts of single Shockley-type stacking faults (1SSFs) on the electrical characteristics of 4H-SiC PiN diodes were examined by fabricating the PiN diodes containing the 1SSF monolayer in the active area with a covering ratio of unity and evaluating the forward current–voltage (I–V) characteristics at various temperatures from 296 to 523 K. The measured I–V characteristics were compared with the previous results for Schottky barrier diodes (SBDs) containing the 1SSF monolayer. Based on the comparison, we clarified the similarity and differences between the impacts of the 1SSFs on the unipolar and bipolar conductions. The forward current conduction of the PiN diodes is limited by the 1SSF similar to that of the SBDs, while the forward current in the PiN diodes exceeds that in the SBDs at elevated temperatures. The difference was attributed to the contribution of hole and recombination currents, the insights into which were obtained by analyzing several experimental results, including dependences of the forward current on the temperature and thickness of the blocking-voltage layer. A simulation analysis was also conducted by adopting the model proposed in the previous study. [ABSTRACT FROM AUTHOR]

The correct generator circuit breaker (GCB) dimensioning is essential for the safe and reliable operation of a power plant or generation system. The dimensioning is usually based on standardized calculation methods according to standards (IEC standard 60909‐0, IEC/IEEE standard 62271‐37‐013, IEEE Std C37), often supplemented by selected transient calculations. A non‐systematic approach can often be observed here, which does not adequately take into account significant influencing variables or operating states of the generator. This article therefore systematically examines various parameters that influence the short‐circuit current components of the generator and are relevant for the dimensioning of the generator circuit‐breaker: short‐circuit angle, operating point, impedance ratios, phase clearing, switching arc, and fault arc. The results of the current parameters most relevant to the dimensioning of the GCB were then compared for different calculation methods. Special attention was paid to the effect of the switching and fault arc, which were modelled as a constant arc voltage, and its effect on the short‐circuit currents is systematically recorded. This work aims to summarize all relevant variables that influence the generator short‐circuit current and are relevant for the dimensioning of the GCB and to present the different results based on a short‐circuit calculation according to the standard and transient calculation to create a basis for a proper dimensioning of the generator circuit breaker. [ABSTRACT FROM AUTHOR]

Winding inductance always plays a key role in the electromagnetic performances of stator surface-mounted permanent magnet (SSPM) machines, including their flux-weakening capability, prospective fault current, power factor, current ripple, etc. Generally speaking, winding inductance mainly comprises three components: an air-gap component, a slot-leakage component, and an end-leakage component. In this paper, firstly, the winding pole pairs of SSPM machines are investigated based on the magneto-motive force-permeance model, through which the winding configurations can also be determined. Then, according to the winding configurations, three analytical expressions for each inductance component are derived to evaluate the winding inductance per phase. In addition, finite element analysis (FEA) is employed to verify the effectiveness of the derived analytical expressions. Meanwhile, three prototyped SSPM machines are manufactured, and their winding inductances are measured to further verify the analytical expressions. The measured results agree with both the analytical and FEA results very well. [ABSTRACT FROM AUTHOR]

In low voltage distribution systems, series arc fault current is small and hidden, and traditional circuit protection devices cannot effectively identify it. To address this problem, a series arc fault detection method based on multi-domain depth feature association is proposed in this paper. By building an experimental platform, the current signal data on normal and arc fault states under different loads are obtained. The time-domain features, frequency-domain features and wavelet packet energy features of the current signal are extracted. To enhance the quality of the data, the importance of each domain characteristic is ranked using four distinct tree techniques, and the most useful features are chosen. A one-dimensional stacked neural network (1D-SNN) fault detection model is constructed to further extract the depth features of each domain. To achieve series arc defect detection, the depth features are combined and fed into a fully connected neural network. The Radam algorithm is used to optimize the detection model. It is then compared with Adam, SGD, and RMSprop optimization algorithms, which verifies that Radam has a better effect on the optimization of the arc detection model. Experimental results show that the average detection accuracy is 99.63%. [ABSTRACT FROM AUTHOR]

Copyright of Scientia Iranica. Transaction D, Computer Science & Engineering & Electrical Engineering is the property of Scientia Iranica 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.)

At present, DC grid fault current analyses are usually based on numerical analyses and/or simulations. To make fault current analyses more practical and convenient, this study proposes a fast fault current level assessment methodology that is applicable when a symmetrical monopole DC (SMDC) system encounters a pole-to-ground (PTG) fault. To further clarify how PTG faults develop in SMDC systems, fault current analysis is implemented in the frequency domain rather than the time domain. Specifically, we find the key factors that impact the high-frequency domain, as these factors have a high correlation with fault currents in the initial milliseconds. Based on simplified SMDC fault circuits and a high-frequency characteristic analysis, a practical index to assess PTG faults is ultimately proposed. It is proved that the index can be used for various SMDC systems with different topologies. With the proposed method, the topology of a DC grid can be optimized to decrease the fault current level, which can help with the design and construction of practical DC grid projects. [ABSTRACT FROM AUTHOR]

This paper presents a fault signal reconstruction method for current sensors in an interleaved buck DC–DC converter, utilizing a sliding mode observer (SMO). A filter bank is used to design the observer within an extended-order system, effectively treating sensor faults as actuator faults, which enables precise estimation of the fault signal. Thus, the proposed approach allows for the identification of the faulty sensor and supports the implementation of fault-tolerant strategies. The paper provides an in-depth analysis of current sensor faults, verifies their impact on current balancing control, and demonstrates the challenge of achieving error-free current estimation in one phase using observers. A comprehensive set of simulation results is carried out, validating the method's effectiveness and showing a strong correlation with theoretical principles. [ABSTRACT FROM AUTHOR]

Real-time and accurate predictive maintenance of industrial equipment is fundamental for ensuring the safety and stability of advanced manufacturing processes. Current fault diagnosis methods based on data mining rely on a large number of labeled samples, and obtaining sufficient labeled data for diagnosing industrial equipment faults is challenging. Meta-learning can achieve the diagnosis of few-shot samples to a certain extent, but the effect is not ideal. Semi-supervision can effectively leverage a large number of unlabeled samples, which is of great practical significance for handling scenarios involving limited labeled samples. However, noise interference can occur when unlabeled samples appear that do not belong to known categories. Therefore, this study proposes adaptive semi-supervised meta-learning networks (ASMNs) for noisy few-shot gearbox fault diagnosis. Firstly, a residual network with a Morlet Wavelet layer is used to extract signal features. Next, sample-level attention is defined to select unlabeled samples that are more similar to labeled sample prototypes, thereby reducing the influence of noisy samples. The adaptive metric is used to obtain the relational distance functions of labeled samples and unlabeled samples. Adaptive semi-supervised ASMNs uses unlabeled data to refine prototypes for better fault diagnosis. The effectiveness and anti-noise performance of the proposed method are verified by using two gearbox datasets with various few-shot noise scenarios. [ABSTRACT FROM AUTHOR]

Introduction. Recently, three-phase induction motor drives have been widely used in industrial applications; however, the feedback signal failures of current sensors can seriously degrade the operation performance of the entire drive system. Therefore, the motor drives require a proper solution to prevent current sensor faults and improve the reliability of the motor drive systems. The novelty of the proposed research includes integrating the current sensor fault-tolerant control (FTC) function according to enhanced technique into the field-oriented control loop for speed control of the motor drive system. Purpose. This research proposes a hybrid method involving a third difference operator and signal comparison algorithm to diagnose various types of current sensor faults as a positive solution to enhance the stability of the induction motor drive system. Methods. A hybrid method involving a third difference operator for the measured speed signals and a comparison algorithm between measured and estimated current signals are proposed to diagnose the current sensors’ health status in the fault-tolerant process. After determining the faulty sensor, the estimated current signals based on the Luenberger observer are used immediately to replace the defective sensor signal. Results. The current sensor is simulated with various failure types, from standard to rare failures, to evaluate the performance of the FTC method implemented in the MATLAB/Simulink environment. Simultaneously, a fault flag corresponding to a defective sensor should be presented as an indicator to execute the repair process for faulty sensors at the proper time. Practical value. Positive results have proven the feasibility and effectiveness of the proposed FTC integrated into the speed controller to improve reliability and ensure the stable operation of the induction motor drive system even under current sensor fault conditions. [ABSTRACT FROM AUTHOR]

Proton exchange membrane fuel cell (PEMFC) has become a hotspot due to its high efficiency, compact structure, and good dynamic operation efficiency. However, problems such as poor reliability and short lifespan create bottlenecks in its large‐scale applications. There has been a large amount of research on fault diagnosis and health management techniques dedicated to addressing the lifespan issues of PEMFC systems. This article provides an in‐depth analysis on the fault mechanism of PEMFC and systematically sorts out the types, causes, and impacts of faults. On this basis, the research progress of PEMFC fault diagnosis technology is summarized, and the measurement characterization methods for fuel cell status monitoring and fault detection are summarized. The literatures of model‐based and data‐driven fault identification methods are summarized and compared. The relevant mitigation measures for PEMFC faults are discussed. Finally, based on the challenges in the current research of fault diagnosis, people mainly conduct research on fault model, online diagnostic technology, and improving diagnostic mechanisms. Overall, this article can provide useful summary and guidance for future research. [ABSTRACT FROM AUTHOR]

This paper proposes a fault current limiting scheme (FCLS) for full-scale wind power generators based on logic bang-bang funnel control (LBFC). Different from the convention methods such as frequency droop control and sliding control, which design the control strategy according to the specific fault currents, LBFC is able to restrict various fault current within acceptable range in the shortest time, and it is robust to system nonlinearities and external disturbances. The control signal of the LBFC is bang-bang with the upper and lower limits of control variables. In the model of full-scale wind power generators connecting with the power grid, LBFC is designed to control the switches of inverter bridges when over-current is detected, and a vector controller is applied during the normal operation. Time-domain simulations were conducted with PSCAD, and the performance of LBFC was validated. [ABSTRACT FROM AUTHOR]

In small-current grounding systems, the fault current during a single-phase grounding fault is small, and the transient process is complex, leading to challenges in line selection accuracy and reliability. This paper proposes a single-phase grounding line selection method based on transfer learning using the ResNet-50 model. Zero-sequence voltage and current waveforms at the fault moment are preprocessed and combined to generate training data for the model. Simulation results using PSCAD demonstrate that the proposed method achieves 99.77% validation accuracy, even under noisy conditions. These results confirm the method's feasibility and reliability in identifying grounding faults in various conditions. [ABSTRACT FROM AUTHOR]

This paper proposes an approach for computing the network's equilibrium point related to the fault clearing time in transient stability studies. The computation of this point is not a trivial task, particularly when the algebraic network's equations are expressed in the power balance form. A natural attempt to solve this problem is using Newton's method. However, convergence issues are found because of the lack of a general strategy for initializing nodal voltages at the clearing time. This problem has not been widely discussed in the existing literature and, therefore, is comprehensively analyzed in this paper. Furthermore, the paper proposes the use of a network's model based on current injections and an extended admittance matrix to overcome the problem. This model is efficiently solved via the fixed-point iteration method, which involves factorization of the extended admittance matrix into the product of a lower triangular matrix [L] and an upper triangular matrix [U]. This solution executes a just once and only forward–backward substitution during the iterative solution process. Case studies clearly demonstrate the proposal's effectiveness in computing the equilibrium point in operating conditions where Newton's method fails to converge. [ABSTRACT FROM AUTHOR]

Cepstral decomposition is beneficial for highlighting certain geological features within the particular quefrency bands which may be deeply buried within the wide quefrency range of the seismic data. Converting seismic traces into the corresponding cepstrum components can better analyse some characteristics of underground strata than the traditional spectral decomposition methods. We propose the sliding windowed differential cepstrum–based coherence analysis approach to delineate the fault features. First, the data are decomposed using a sliding windowed differential cepstrum, which results in multi‐cepstrum data of corresponding quefrency of certain bandwidth. These different multi‐cepstrum data may highlight the different stratigraphic features in a certain quefrency band. We select the first‐order common quefrency volume as the featured attribute. Then, eigenstructure‐based coherence is applied on the first‐order common quefrency data volume to statistically obtain the fault detection result with a finer and sharper image. Synthetic data and field data examples show that the proposed method has the ability to better visualize all the possible subtle and minor faults present in the data more accurately and discernibly than the traditional coherence method. Compared with the ant‐tracking method, the proposed method is more effective in revealing the major faults. It is hoped that this work will complement current fault detection methods with the addition of the cepstral‐based method. [ABSTRACT FROM AUTHOR]

The increasing use of inverter‐based distributed generation requires a comprehensive study of its effects on fault analysis and the effectiveness of protection systems in distribution networks. This study examines the impact of different inverter control modes on multiple types of protective relay schemes. These include different overcurrent relay (OCR) schemes, both standard and nonstandard tripping characteristics, optimal coordination approaches, and different grid operation scenarios. The investigation is conducted through the utilization of grid‐connected and islanding operation modes, with fault resistance values of 0 and 5 Ω. The study is carried out on a 14‐bus CIGRE network which includes two photovoltaic (PV) farms with a capacity of 10 MVA each. The research provides several significant contributions, including the analysis of fault current contributions, examination of issues in OCR protection, investigation of the influence of fault impedance levels on OCR performance, evaluation of ideal coordination methods, and carrying out a comparative analysis utilizing optimization technique by using the water cycle optimization algorithm (WCA) and the particle swarm optimization algorithm (PSO). In addition, to guarantee the robustness of the suggested protection strategy, this work adopts a hardware‐in‐the‐loop approach. The OMICRON‐256 system is utilized to carry out real‐time testing on a SIPROTEC 7SJ62 multifunction protection relay, which validates the effectiveness of the proposed method in protecting microgrids under different PV control strategies. The total operating time for the nonstandard tripping scheme was 12.077–12.3003 s for PSO and WCA, respectively, while for the standard tripping scheme, it was 12.1226 and 12.1564 s. Moreover, these findings offer practical insights that can assist operators in effectively designing the power networks with grid‐connected PV systems by showing OCR miscoordination and no tripping events in power systems with PVs under inverters controllers. [ABSTRACT FROM AUTHOR]

The use of multi-terminal high voltage direct current (HVDC) power transmission systems is being adopted in many new links between different generation and consumption areas due to their high efficiency. In these systems, cable energization must be performed at the rated voltage. Healthy energizations at the rated voltage result in large inrush currents, especially in long cables, primarily due to ground capacitance. State-of-the-art protection functions struggle to distinguish between transients caused by switching and those associated with ground faults, leading to potential unwanted tripping of the protection systems. To prevent this, tripping is usually blocked during the energization transient, which delays fault detection and clearing. This paper presents a novel method for prompt discrimination between healthy and faulty energizations. The proposed method outperforms conventional protection functions as this discrimination allows for earlier and more reliable tripping, thus avoiding extensive damage to the cable and the converter due to trip blocking. The method is based on the transient analysis of the current in the cable shields, therefore, another technical advantage is that high voltage-insulated measuring devices are not required. Two distinct tripping criteria are proposed: one attending to the change in current polarity, and the other to the change in current derivative sign. Extensive computer simulations and laboratory tests confirmed the correct operation in both cases. [ABSTRACT FROM AUTHOR]

In the proposed protection coordination scheme, the depreciation of the operation time of the entire relay in the primary and backup protection modes for all possible fault locations is considered as the objective function. The limitations of this problem include the equations for calculating the operation time of the relays in both forward and reverse directions, the limitation of the coordination time interval, the limitation of the setting parameters of the proposed relays, the restriction of the size of the reactance that limits the fault current, and the limitation of the standing time of distributed generation per small signal fault. The operation time of the relays depends on the short circuit current passing through them, so it is necessary to calculate the network variables before the fault occurs. For this purpose, optimal daily power distribution should be used in the micro-grid, because micro-grids consist of storage and renewable resources. The proposed plan includes the uncertainties of consumption and generation capacity of renewable resources. Then, to achieve a reliable answer with a low standard deviation, the refrigeration optimization algorithm is used to solve the proposed problem. Finally, the proposed design is implemented on the standard test system in the MATLAB software, and then the capabilities of the proposed design are examined. [ABSTRACT FROM AUTHOR]

As the capacity of medium or large hydroelectric generators increases, conventional grounding methods face challenges in effectively limiting single‐phase to earth fault current and neutral displacement voltage within acceptable range. Excessive fault current and neutral displacement voltage pose threats to the stability and safety of power generation and transmission systems. Inherent design deficiencies in conventional grounding methods lead to failures in meeting fault current and voltage requirements. To address this, this paper proposes a novel grounding method utilizing high impedance to restrict excessive fault current and neutral displacement voltage. The method minimizes both fault current and neutral displacement voltage by optimally selecting device parameters through minimal iterative trials. Additionally, a novel indicator is introduced to evaluate the effectiveness of grounding method by monitoring changes in neutral displacement voltage. The method is tested through theoretical calculation and field experiments, successfully implemented in large‐size hydroelectric generator. [ABSTRACT FROM AUTHOR]

The rapid fault isolation is the necessity for the proficient operation of the microgrid because it can increase resiliency of the system by restoration of the power distribution system after isolation of the faulty area. In modern power system, many renewable and nonrenewable sources are integrated through different types of converters; therefore, it is too much tedious to develop a protection scheme which can easily detect and isolate faults under such unpredictable faulty conditions. Further, variation in weather conditions and the fault current level during such conditions is not predictable for traditional protection schemes and needs modification. In addition to above difficulties in the microgrid, distinct category of the AC faults makes protection task more difficult when fault resistance is varying due to change in grounding conditions. Motivated by the above challenges in the proposed microgrid, an ensemble of kNN-based protection scheme has been devised in this work to provide robustness to the microgrid. The tasks of the mode detection, fault detection/classification and faulty section identification under varying weather conditions have been considered in grid-connected and islanded modes as a class of the problem. Discrete wavelet transform has been used to pre-process the measured voltage and current signals retrieved from the appropriate bus. To validate the protection scheme, numerous cases of dissimilar operating scenarios have been considered under both of the operating modes. The results in Sect. 6 indicate that protection scheme is efficient and reliable to increase the robustness of the microgrid. [ABSTRACT FROM AUTHOR]

Fractional slot concentric winding (FSCW) machine features with short end winding, high torque density and good fault tolerance. However, this type of machine suffers from abundant MMF harmonics which causes high iron loss and partial saturation, etc. Hence, majority of the FSCW adopts surface-mounted PM (SPM) rotor which have large effective airgap to minimize the influence of the MMF harmonics while the interior PM (IPM) rotor is rarely used. The SPM rotor tends to induce high PM flux linkage and cause large fault current when experiencing a short-circuit failure. As a result, this paper presents a triple 3-phase FSCW-IPM for fault-tolerant applications. The triple 3-phase windings facilitate the uninterrupted fault tolerant operation, the more even distributed windings also induce a more sinusoidal MMF which enables the application of IPM rotor. The IPM rotor reduces the PM usage while reluctance torque can be explored to compensate the PM torque reduction which improves the machine fault tolerance. As a result, the proposed machine owns good performance and excellent fault tolerance. The machine is investigated by electromagnetic and thermal finite element analysis and prototyping tests. Both findings confirm that the proposed triple 3-phase FSCW-IPM is a competitive solution for high reliability application. [ABSTRACT FROM AUTHOR]

High-voltage cables will continue to operate for a period of time in the event of a small current arc fault, which poses a risk of fire. Two simulated ignition methods, moving electrode and melting fuses, are proposed to analyze the ignition characteristics of low-current arcs. The ignition test was carried out, and the combustion effect was compared. The results indicate that the moving electrode ignition method can achieve long-distance arc ignition test when the current is small and is suitable for simulating the arc ignition situation of cable outer protective layer damage. By controlling the movement speed, it can be ensured that the arc will not be interrupted during the electrode movement process. However, the arc is difficult to sustain using the fuse melting method when the current is small and the distance is long. The fuse melting method is suitable for simulating insulation breakdown situations. The results show that the critical arc duration for cable ignition under five different current conditions of 2–10 A is 28 s, 21 s, 14 s, 9 s, and 4 s, respectively. The maximum height of the cable flame under 2–10 A arc current is 9–52 cm and 16–63 cm, respectively, when the arc duration is 50 s and 100 s. The self-ignition time of the cable after the arc extinguishing is 8–95 s and 14–261 s, respectively. The maximum temperature of the cable flame is positively correlated with arc current, and the maximum flame temperature of the cable under 2–10 A arc current is 540–980 °C. Based on the actual current monitoring data in cable tunnels, the research results can provide reference for the risk assessment and protection of cable tunnel fires. [ABSTRACT FROM AUTHOR]

The diode-rectifier unit (DRU)-based high-voltage direct current (HVDC) transmission system offers an economical solution for offshore wind power transmission. However, this approach requires offshore wind farms to establish a strong grid voltage. To meet this requirement while fulfilling the dynamic characteristics of the DRU, this paper proposes an advanced grid-forming (GFM) control strategy for offshore wind turbines connected to DRU-HVDC. The strategy incorporates a P-U controller and a Q- ω controller based on reactive power synchronization. Furthermore, a novel virtual power-based pre-synchronization method and an adaptive virtual impedance technique are integrated into the proposed GFM control to improve system performance during wind turbine (WT) integration and low-voltage ride-through (LVRT) scenarios. The virtual power-based pre-synchronization method reduces voltage spikes during the integration of new wind turbines, while the adaptive virtual impedance technique effectively suppresses fault currents during low-voltage faults, enabling faster recovery. Simulation results validate the effectiveness of the proposed GFM control strategy, demonstrating improved start-up and LVRT performance through the pre-synchronization and adaptive virtual impedance methods. [ABSTRACT FROM AUTHOR]

It is difficult to identify an arc fault accurately when the loads on the user side are more complicated, which hinders the development of low‐voltage monitoring and pre‐warning inspection. This study acquired a series of arc‐fault signals according to IEC 62606. The main time‐frequency features were strengthened with high efficiency by applying the generalized S‐transform to them with a bi‐Gaussian window. Further, the power spectrum density determination allowed for the detection of imperceptible high‐frequency harmonic energy reflections, thus increasing the rate of arc‐fault diagnosis and making it suitable for arc‐fault monitoring of non‐linear loads. The final samples were trained and classified using a 2D convolutional neural network and the overall accuracy of identification was observed to be 98.13%, which involved various domestic loads, thus providing a reference for follow‐up arc‐fault monitoring and inspection research. [ABSTRACT FROM AUTHOR]

To address the issues of low efficiency and poor noise immunity in traditional active distribution network (ADN) fault location methods based on swarm intelligent optimization algorithms, this paper proposes a two-stage fault location method utilizing the COA-SVM model and cosine similarity. First, this paper constructs the fault signature database for the target distribution network by randomly simulating single- and multi-point faults using the fault current state equation. Next, this paper introduces the COA-SVM classification model, establishing the high-dimensional mapping relationship between the fault current direction matrix and the fault zones through model training. The well-trained COA-SVM classification model is used to identify the fault zones, which include the fault line segments. Finally, for each identified fault zone, this paper calculates the cosine similarity of the fault current direction information of adjacent line segments, accurately pinpointing the fault line segments by identifying mutation points of the cosine similarity. Using the modified IEEE 33 node test distribution network as an example, simulation results demonstrate that the proposed two-stage fault location method offers higher accuracy and resistance to signal interference compared to fault location methods based on swarm intelligence optimization algorithms. The COA-SVM classification model surpasses conventional models, achieving high accuracy and excellent noise resilience. It accurately identifies fault segments within the test distribution network with a remarkable 100% precision. Moreover, the accuracy of fault localization remains above 83% when the FTU encounters fewer than three abnormal signals. [ABSTRACT FROM AUTHOR]

Stator faults are one of the common issues in pumped storage generators, significantly impacting their performance and safety. To ensure the safe and stable operation of pumped storage generators, a stator fault diagnosis method based on an improved short-time Fourier transform (STFT)-support vector data description (SVDD) hybrid algorithm is proposed. This method establishes a fault model for inter-turn short circuits in the stator windings of pumped storage generators and analyzes the electrical and magnetic states associated with such faults. Based on the three-phase current signals observed during an inter-turn short circuit fault in the stator windings, the three-phase currents are first converted into two-phase currents using the principle of equal magnetic potential. Then, the STFT is applied to transform the time-domain signals of the stator's two-phase currents into frequency-domain signals, and the resulting fault current spectrum is input into the improved SVDD network for processing. This ultimately outputs the diagnosis result for inter-turn short circuit faults in the stator windings of the pumped storage generator. Experimental results demonstrate that this method can effectively distinguish between normal and faulty states in pumped storage generators, enabling the diagnosis of inter-turn short circuit faults in stator windings with low cross-entropy loss. Through analysis, under small data sample conditions, the accuracy of the proposed method in this paper can be improved by up to 7.2%. In the presence of strong noise interference, the fault diagnosis accuracy of the proposed method remains above 90%, and compared to conventional methods, the fault diagnosis accuracy can be improved by up to 6.9%. This demonstrates that the proposed method possesses excellent noise robustness and small sample learning ability, making it effective in complex, dynamic, and noisy environments. [ABSTRACT FROM AUTHOR]

Under the background of increasing system service data, it is difficult to trace the faults of power dispatching system. The current fault tracing method has some problems, such as low precision, low efficiency and difficult troubleshooting. To solve this problem, a fault tracing method based on data partition hybrid sampling method and multiple incremental regression tree algorithm is proposed. In this paper, it first uses the hybrid sampling method of data partition and dynamic selection technology to detect the business anomaly, and then applies the clustering algorithm and the information difference graph model to realize the fault tracing of system components. The experimental results showed that the F-metric value and geometric mean value of the study design method were 0.964 and 0.685, respectively. In addition, normalized discounted cumulative gains were observed in the top 10, and the mean average precision of the top 10 was 0.752 and 0.186, respectively. The proposed method can effectively improve the fault tracing efficiency of power grid operation and maintenance personnel, and provide strong data support for the safety maintenance of power grid dispatching system. [ABSTRACT FROM AUTHOR]

ABSTRACT With the rapid development of industrial technology, industrial processes become increasingly complex, presenting characteristics of large‐scale and multi‐unit collaboration. However, most current fault detection methods focus on nonlinearity, dynamics, and other characteristics, while neglecting spatiotemporal information. To address this issue, an adaptive spatiotemporal decouple graph convolutional network based quality‐related fault detection method is proposed in this article. First, the temporal graph convolutional network and spatial graph convolutional network are combined organically in the form of joint training. Second, considering that fixed graph structures cannot reflect the dynamic relationships among nodes, we proposed an adaptive weighted mask mechanism to construct dynamic correlation graph embedded with priori knowledge. Multi‐attention mechanism is used to integrate spatiotemporal information, besides, we designed a decoupling layer to avoid information redundancy. Finally, the proposed spatiotemporal graph convolutional network is used to establish a regression model, the quality‐related latent variables are extracted by the decoupling layer, and the statistic is constructed based on Kullback–Leibler divergence. The effectiveness and feasibility of the proposed method are illustrated with the hot strip mill process and the Tennessee Eastman process. [ABSTRACT FROM AUTHOR]

Hybrid DC circuit breakers combine mechanical switches with a redirecting current path, typically controlled by power electronic devices, to prevent arcing during switch contact separation. The authors' past work includes a bipolar hybrid DC circuit breaker that effectively redirects the fault current and returns it to the source. This reduces arcing between the mechanical breaker's contacts and prevents large voltage overshoots across them. However, the breaker's performance declines as the upstream line inductance increases, causing overvoltage. This work introduces a modification to the originally proposed hybrid DC breaker to make it suitable to use anywhere along DC grid lines. By using a switch-controlled surge arrester in parallel with the DC breaker, part of the arc energy is dissipated in the surge arrester, preventing an overvoltage across the mechanical switches. Based on the experimental results, the proposed method can effectively interrupt the fault current with minimal arcing and reduce the voltage stress across the mechanical switches. To address practical fault currents, tests at high fault currents (900 A) and voltage levels (500 V) are conducted and compared with simulation models and analytical studies. Furthermore, the application of the breaker for the protection of DC distribution grids is illustrated through simulations, and the procedure for designing the breaker components is explained. [ABSTRACT FROM AUTHOR]

To maintain the security of transformer differential protection, it is essential to restrain its response to oversetting differential current caused by the inrush current or other switching conditions. This paper presents a new proposed method to discriminate the transformer's internal fault from the inrush current; the discrimination process is based on a convolutional neural network (CNN) with a combination of the higher order spectral estimations that perform a deep learning classification with high accuracy. This research succeeded in proposing two robust and efficient CNN models; the first one is the 1D CNN, which takes the sole signal without any transformation, while the second model is the 2D CNN, which takes the short‐time Fourier transform of the signal. Both developed models are light and have the minimum number of layers that can achieve a very high performance. The performance of the proposed models is tested using a dataset prepared according to laboratory‐measured transformer parameters. The results are compared with other well‐known methods, and the achievement of high numerical performance evaluation validates the consistency of the proposed methods. [ABSTRACT FROM AUTHOR]

Vector-controlled drives require stator current information for use in current feedback and/or state variable estimators. That is why the detection and compensation of possible current sensor (CS) damage is so important. This article focuses on CS fault-tolerant control (FTC) in induction motor (IM) drive systems. In contrast to solutions known from the literature, two modified Luenberger observers (MLO) were applied, allowing for high-quality estimation of currents used in the detector and fault compensator. In a simple implementation of a detection algorithm based on residuals, an adaptive threshold coefficient was employed, enabling effective detection of various types of faults, regardless of whether the second CS was faulty or intact. The presented solution was evaluated during both motor and regenerative operation, with faults occurring in transient states, unlike solutions known in the literature. [ABSTRACT FROM AUTHOR]

The transformer grounding is typically inserted across a transformer or generator's ground. In a transformer and generator, this ground is often used to reduce the current of a disturbance from phase to earth. During a ground fault in a transformer, a very high current can flow, posing a danger to equipment and personnel. By connecting a resistor between the neutral point of the transformer and ground, the NGR limits this fault current. In the following paper, the protection mechanism of two high-voltage to medium-voltage transformers which connected in parallel during routine operation as well as in emergency situations will be explored. Protecting two parallel transformers with two different neutral grounding resistors involves ensuring proper coordination of protective devices to detect and isolate faults while minimizing damage to equipment and ensuring system stability. Another scenario under discussion involves a generator linked to the medium-voltage (MV) system, which distinct had a distinct ground value. A short circuit occurring in different neutral grounding resistor (NGR) systems refers to a fault scenario where more than one transformer or generator linked in parallelly, each with its own NGR of varying resistance values. This situation poses challenges for protection coordination and fault current distribution. To address this issue, a protective scheme is suggested, which modifies its configurations according to the operational status of the system. [ABSTRACT FROM AUTHOR]

The electrical protection of active distribution networks is crucial for ensuring reliable, safe, and flexible operations. However, protecting these networks presents several challenges due to the emergence of bi-directional power flows, network reconfiguration capabilities, and changes in fault current levels resulting from the integration of inverter-based resources. This paper introduces an innovative protection strategy for active distribution networks, leveraging the principles of distributed coordination and multi-agent systems. The proposed strategy consists of two stages. The first stage involves a fault detection algorithm that relies solely on local measurements, while the second stage uses agent classification to compute the optimal operating time based on a dynamic matrix representation of the fault path, combined with a simplified distributed optimization problem. The coordination process is formulated as a set of linear optimization problems, simplifying the solution. The proposed protection strategy is validated in a real-time simulation environment using a modified CIGRE MV European grid as a case study, considering low-impedance symmetric fault scenarios and topological changes. The results demonstrate that the protection scheme exhibits robust performance, enhancing the adaptability of the protection equipment while ensuring suitable sensitivity and operational speed. [ABSTRACT FROM AUTHOR]

A grid-forming (GFM) inverter can effectively support active power and reactive power, and the stability problem induced by the low inertia can be thereby alleviated in a power electronics-dominated power system. Yet, the voltage source characteristic presented by the grid-forming inverter induces an overcurrent problem during a short-circuit fault. Furthermore, the time delay induces an inrush current in traditional digital control, triggered by a predefined timing sequence. To address the overcurrent problem of the GFM inverter controlled by the digital controller, the operation characteristics of GFM inverters under grid-voltage drops are investigated, and a mathematical model of the instantaneous fault current is established, which depicts the relationship between the instantaneous fault current's magnitude, grid-voltage drop severity, equivalent output impedance, and current inner-loop response speed. Then, a Set–Reset (SR) latch-based dynamic current limitation with event-triggered control is proposed for the low-voltage ride-through of the GFM inverter. In the proposed method, the current limitation is enabled during grid fault, and the active and reactive powers can be recovered rapidly after fault clearance. Meanwhile, the active and reactive power references are designed to enhance synchronization stability during the grid fault. The proposed method addresses the issue of the repeated switching of virtual impedance during grid fault and achieves rapid power recovery after fault clearance. In addition, the proposed method uses the logic of event triggers to respond to the overcurrent event in real time and realize overcurrent protection. The simulation and experimental results demonstrate the effectiveness of the proposed method in current limitation and active-power recovery after fault clearance. [ABSTRACT FROM AUTHOR]

Abstract The correct generator circuit breaker (GCB) dimensioning is essential for the safe and reliable operation of a power plant or generation system. The dimensioning is usually based on standardized calculation methods according to standards (IEC standard 60909‐0, IEC/IEEE standard 62271‐37‐013, IEEE Std C37), often supplemented by selected transient calculations. A non‐systematic approach can often be observed here, which does not adequately take into account significant influencing variables or operating states of the generator. This article therefore systematically examines various parameters that influence the short‐circuit current components of the generator and are relevant for the dimensioning of the generator circuit‐breaker: short‐circuit angle, operating point, impedance ratios, phase clearing, switching arc, and fault arc. The results of the current parameters most relevant to the dimensioning of the GCB were then compared for different calculation methods. Special attention was paid to the effect of the switching and fault arc, which were modelled as a constant arc voltage, and its effect on the short‐circuit currents is systematically recorded. This work aims to summarize all relevant variables that influence the generator short‐circuit current and are relevant for the dimensioning of the GCB and to present the different results based on a short‐circuit calculation according to the standard and transient calculation to create a basis for a proper dimensioning of the generator circuit breaker.

In the present work, it is proposed to use stator current spectrum analysis by Gabor transform (GT) to identify electrical defects in induction motors. Current-based fault detection plays an important role in the proposed work as it overcomes the major pitfalls associated with other conventional sensor-based monitoring. A Poly Phase Induction Motor (IM) of 2 HP, 415 ± 10 % V, 50 Hz is taken for online testing of proposed fault detection at variable speed regime. At varying load situations, the motor's input current is gathered for various fault conditions. After performing frequency spectral subtraction, advanced GT offers signal processing on the collected stator current. The GT coefficients are used for further analysis to estimate and localize the fault. Fault indexing parameter (FIP) is proposed for fault severity estimation. The data acquisition is carried out in LabVIEW environment and processed by MATLAB programming. [ABSTRACT FROM AUTHOR]

Abstract This work deals with designing an advanced integral sliding mode controller (AISMC) for residual current compensation (RCC) inverters connected with arc suppression coils to compensate for power distribution networks where the main idea is to alleviate hazardous circumstances caused by electric faults on powerlines. The key advancement in the proposed AISMC over traditional sliding mode controllers is the utilization of an improved exponential reaching law which ensures the faster convergence of the desired control objective that is the fault current compensation in this particular application. An improved exponential reaching law (IERL) used in this work is a combination of the exponential and constant‐proportional reaching laws (while existing approaches use constant reaching laws) which assists to minimize the current injection error through the RCC inverter in the steady‐state. The integral action in conjunction with the exponential function in the sliding surface, based on which the proposed controller is designed, helps to eliminate the chattering effects in a quickest way that can be evidenced from the settling time and percentage overshoot. The feasibility of the proposed AISMC is theoretically assessed by analyzing the stability using the Lyapunov stability theory. Simulation and processor‐in‐loop results further justify the theoretical foundation by confirming the desired current injection and compensating voltage and current due to the fault. Finally, results are compared with a TIMSC for demonstrating the superiority of the AISMC.

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power 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.)

As the demand for power supply stability and reliability in the active distribution network (ADN) increases, the primary and secondary integrated intelligent switch (PSIIS) has become the primary choice for smart grid transformation in many weak infrastructure areas. However, the number of PSIISs that can be configured is often limited. It is necessary to comprehensively utilize the measurement data and sectional capabilities of PSIISs through the optimal configuration method to find the optimal configuration scheme. Therefore, fault observability-related indexes (FORIs) are proposed based on the functional characteristics of PSIISs. These indexes include fault type observability, fault location observability, fault current distribution characteristics observability, transition resistance observability, and weak infrastructure area observability. An optimization configuration model of PSIISs considering the comprehensive fault observability (CFO) is constructed. The adaptive genetic algorithm (AGA) is selected as the model-solving method. Subsequently, an optimal configuration method of PSIISs considering CFO is proposed. Finally, an example analysis is conducted in MATLAB to verify the effectiveness and feasibility of the proposed method. This optimal configuration method aims to maximize the use of a limited number of PSIISs by considering CFO, and the AGA proves to be an effective tool in solving the optimal configuration scheme. [ABSTRACT FROM AUTHOR]

A high proportion of distributed generators (DGs) connected to the distribution network causes a significant change in the normal and fault currents of the system as well as in the linearization of the characteristics. It is difficult to adapt to conventional protection. This paper theoretically analyzes the possible impact of fault current characteristics on traditional protection based on single-ended informativeness after connecting to DGs. From the perspective of protection action, the evaluation index system of DG protection is established by considering the maximum short-circuit current output from DG. Combined with the relay protection requirements, the calculation method of evaluation indexes is given concerning the protection characteristics and expert experience. An analytic hierarchy process (AHP) and a CRITIC combination assignment method based on the principle of minimum information identification are proposed. The scores of different types of protection before and after DG access are calculated using the proposed methodology employing a typical distribution network example. The proposed method can quantitatively obtain the distribution network protection adaptability boundary. In the actual calculation example selected in this paper, a DG can reasonably improve the adaptability of the three-stage current protection when it increases the current amplitude at a penetration rate of 50%; the DG needs to adjust the three-stage current protection rectification value when it decreases the current amplitude at a penetration rate of 20%; and adaptive overcurrent protection and inverse time limit current protection need to be adjusted when the penetration rate of DG is 50%. Compared with the traditional protection evaluation method, the method adopted in this paper can intuitively derive the weak link between protection handling faults after DG access as well as the appropriate capacity of DG to improve protection performance. It can provide a powerful reference for the optimization of protection schemes after the high percentage of DG access. [ABSTRACT FROM AUTHOR]

We propose a new approach for performing drained and undrained loading of elastoplastic geomaterials over large deformations using smoothed particle hydrodynamics (SPH), a meshfree continuum particle method, combined with the modified Cam Clay (MCC) model of critical state soil mechanics. The numerical approach draws upon a novel one‐particle two‐phase penalty‐method based formulation for handling undrained loading in saturated soils, which allows tracking of the buildup of pore‐water pressures under combined shearing and compression. Large‐scale parallelized simulations are employed to accommodate a significant number of degrees of freedom in a three‐dimensional setting. After verification and benchmark testing, the SPH based formulation is used to analyze the propagation of reverse faults through fluid‐saturated clay deposits and the rupture of strike‐slip faults across earthen embankments. The computational methodology tests the robustness of the meshfree approach in situations where the soil tends to dilate on the 'dry' side of the critical state line and to compact on the 'wet' side, but cannot, because of the incompressibility constraint imposed by undrained loading. Our results extend the current understanding of fault rupture modeling and further demonstrate the potential of our framework together with the SPH method for large deformation analyses of complex problems in geotechnics. [ABSTRACT FROM AUTHOR]

Protection blinding is a challenging issue in renewables‐penetrated distribution grids and refers to a situation where a circuit breaker may not trip due to fault current contribution from distributed generation. This research addresses how the distributed generation location and capacity impact the operation of the circuit breaker in terms of the response time of the circuit breakers. The relative electrical distances of the faults and distributed generation to the circuit breakers are considered. The impact of distributed generation capacity considering the fault location is characterized using a new index called the heterogeneity index. The electrical distance between distributed generations and circuit breakers and the electrical distance between fault and circuit breaker is considered by a second new index called the electrical distance ratio. Data analysis on simulation results shows that these indices capture the phenomena of protection blinding caused by distributed generation. Results show that a higher distributed generation penetration and faults that are electrically further away from a circuit breaker show severe cases of protection blinding captured by the indices. Furthermore, it is demonstrated how these indices can identify the worst impacted locations in the distribution grid. A key result is that protection blinding does not necessarily occur solely due to the presence of distributed generation between a circuit breaker and a fault, but is dependent on factors such as distributed generation location in the distribution grid, fault level, fault level distribution across the generation units and fault location. [ABSTRACT FROM AUTHOR]

To address the limitations of current DC residual current protection methods, which primarily rely on the amplitude of DC residual current for fault detection and fail to safeguard against electric shocks at two points on the same side in DC Isolated Terra (IT) System systems, this paper introduces a novel protection method based on DC electric shock features. This paper first analyzes the sliding curvature accumulation and peak rise time features of DC basic residual current, load mutation current, and animal body electric shock current under multi-factor conditions. The analysis shows that sliding curvature accumulation in the range of 0.1 ≤ K ≤ 1 and a peak rise time of Δt ≥ 20 ms can effectively distinguish animal body electric shock. Then, based on this electric shock's distinctive characteristics, an approach for identifying types of electric shock is developed. Finally, a DC residual current protective device (DC-RCD) is designed. The prototype test results demonstrate that the DC-RCD has an action time of ts < 70 ms. The proposed method accurately provides protection against electric shocks and effectively addresses the issue of inadequate protection when two fault points occur on the same side within an IT system. This approach holds significant reference value for the development of next-generation DC-RCDs. [ABSTRACT FROM AUTHOR]

Diagnosing bearing defects (BFs) in squirrel cage induction machines (SCIMs) is essential to ensure their proper functioning and avoid costly breakdowns. This paper presents an innovative approach that combines intelligent direct torque control (DTC) with the use of Hilbert transform (HT) to detect and classify these BFs. The intelligent DTC allows precise control of the electromagnetic torque of the asynchronous machine, thus providing a quick response to BFs. Using HT, stator current is analyzed to extract important features related to BFs. The HT provides the analytical signal of the current, thus facilitating the detection of anomalies associated with BFs. The approach presented incorporates an intelligent DTC that adapts to stator current variations and characteristics extracted via the HT. This intelligent control uses advanced algorithms such as neural networks (ANN-DTCs) and fuzzy logic (FL-DTCs). In this paper, a comparison between these two algorithms was performed in the MATLAB/Simulink environment for a three-phase asynchronous machine to evaluate their effectiveness under the proposed approach. The results obtained demonstrated a high ability to detect and classify BFs, confirming the effectiveness of each algorithm. In addition, this comparison highlighted the specific advantages and disadvantages of each approach. This information is valuable in choosing the most suitable algorithm according to the constraints and specific needs of the application. [ABSTRACT FROM AUTHOR]

Short-circuit impedance is an important economic and technical index to test the cost, efficiency and operation safety of transformers. Increasing the short-circuit impedance of the transformer can reduce the influence of the transformer fault current on the system. The short-circuit impedance of a general power transformer is 4~7%. When the short-circuit impedance is too small, the short-circuit current is too large, which will cause harm to electrical equipment. This paper proposes a method to adjust the short-circuit impedance by adding magnetic shunts of different thicknesses between the high and low voltage windings of the transformer. Compared with other methods, this method does not change the structure of the transformer core and winding, and is simple and efficient. In this paper, a three-dimensional simulation model of a single-phase multi-winding transformer is established by Altair Flux to study the influence of the thickness of magnetic shunts on the short-circuit impedance of a transformer. The feasibility of the proposed method is verified by comparing the simulation with the measured values. The magnetic shunt is also introduced into the three-phase transformer. The result shows that adding magnetic shunts of different thicknesses between the high and low voltage windings of the transformer will change the distribution and size of the leakage of the magnetic field. The short-circuit impedance increases significantly with the increase in the thickness of the magnetic shunt, but a certain number of magnetic shunts have minimal effects on the efficiency of the transformer. [ABSTRACT FROM AUTHOR]

As Europe integrates more renewable energy resources, notably offshore wind power, into its super meshed grid, the demand for reliable long-distance High Voltage Direct Current (HVDC) transmission systems has surged. This paper addresses the intricacies of HVDC systems built upon Modular Multi-Level Converters (MMCs), especially concerning the rapid rise of DC fault currents. We propose a novel fault identification and classification for DC transmission lines only by employing Long Short-Term Memory (LSTM) networks integrated with Discrete Wavelet Transform (DWT) for feature extraction. Our LSTM-based algorithm operates effectively under challenging environmental conditions, ensuring high fault resistance detection. A unique three-level relay system with multiple time windows (1 ms, 1.5 ms, and 2 ms) ensures accurate fault detection over large distances. Bayesian Optimization is employed for hyperparameter tuning, streamlining the model's training process. The study shows that our proposed framework exhibits 100% resilience against external faults and disturbances, achieving an average recognition accuracy rate of 99.04% in diverse testing scenarios. Unlike traditional schemes that rely on multiple manual thresholds, our approach utilizes a single intelligently tuned model to detect faults up to 480 ohms, enhancing the efficiency and robustness of DC grid protection. [ABSTRACT FROM AUTHOR]

Summary: The non‐permanent dc short‐circuit fault is a crucial issue in overhead high voltage dc transmission (HVDC) lines. In this paper, a cross connected (CC) cell also known as hexagonal switch cell (HSC) based modular multilevel converter (MMC) with dc short‐circuit fault ride through feature is addressed for an HVDC system. During normal operation, the CC cell‐MMC is capable of producing an identical number of levels while using fewer power devices than full‐bridge (FB) and clamp double sub‐module (CDSM)‐based MMCs. Similarly to the FB‐MMC and CDSM‐MMC, the provided CC cell‐MMC not only blocks the dc fault current but can also function as a static synchronous compensator (STATCOM) during a DC‐Bus fault. The Proposed control technique uses MMC as a STATCOM to inject reactive power during a pole‐to‐pole DC‐Bus fault to keep the grid stable. The control approach comprises injecting zero‐sequence voltage into each phase to balance the mean voltage of capacitors and arm currents. The fundamental zero‐sequence voltage is obtained by a simple stationary reference frame‐based controller. The control strategy's efficacy is evaluated in MATLAB and confirmed in the Opal‐RT environment. [ABSTRACT FROM AUTHOR]

The fault location of an active distribution network is a vital analysis to prevent major outages in the power system. Considering the influence of renewable distributed generations on fault characteristics, this paper proposes a novel location method based on a dynamic quantum genetic algorithm to solve for fault locations in active distribution networks. In the method, the fault current code is measured based on feeder terminal units. A universal switching function is presented to convert the feeder switch status into an uploaded fault current code. The fault location model is defined as an optimization problem that presents the evaluation objective function with an anti-false-positive factor. The dynamic quantum genetic algorithm is developed to locate the fault feeder according to the uploaded fault current code of the feeder terminal unit. The algorithm adopts dynamic rotating gate strategy and adaptive quantum crossover strategy to satisfy the requirements of quickness and accuracy for fault location. Moreover, the method avoids easily falling into a local optimum by integrating the discrete quantum mutation. The proposed fault location technique is tested and compared to other existing techniques on a 33-bus active distribution network. The simulation results show that the proposed fault location method can locate fault feeders accurately with fast computational times under conditions of single or multiple faults and with an information distortion of the feeder terminal unit. [ABSTRACT FROM AUTHOR]

Fault detection and diagnosis of nonstationary processes are crucial for ensuring the safety of industrial production systems. However, the nonstationarity of process data poses multifaceted challenges to them. First, conventional stationary fault detection methods encounter difficulties in discerning evolving trends within nonstationary data. Secondly, the majority of current nonstationary fault detection methods directly extract features from all variables, rendering them susceptible to redundant interference. Moreover, nonstationary trends possess the capacity to conceal and modify the correlations among variables. Coupled with the smearing effect of faults, it is challenging to achieve accurate fault diagnosis. To address these challenges, this paper proposes sparse Wasserstein stationary subspace analysis (SWSSA). Specifically, a ℓ 2 , p -norm constraint is introduced to endow the stationary subspace model with excellent sparse representation capability. Furthermore, recognizing that fault variables within the sparse stationary subspace influence only a limited subset of stationary sources, this paper proposes a novel contribution analysis method based on local dynamic preserving projection (LDPP), termed LDPPBC, which can effectively mitigate the smearing effect on nonstationary fault diagnosis. LDPPBC establishes a LDPP matrix by extracting the latent positional information of fault variables within the stationary subspace. This allows LDPPBC to selectively analyze the contributions of variables within the latent fault subspace to achieve precise fault diagnosis while avoiding the interference of variable contributions from the fault-free subspace. Finally, the superiority of the proposed method is thoroughly validated through a numerical simulation, a continuous stirred tank reactor, and a real industrial roaster. • This method can realize fault diagnosis under the influence of nonstationarity. • The smearing effect of faults is effectively mitigated. • Through mathematical deduction, the convergence of the algorithm is proven. [ABSTRACT FROM AUTHOR]

The Java Madura Bali system is the largest interconnection system in Indonesia, covering about 70% of the national electrical energy market. Electricity sales increased from 125.49 TWh in the first half of 2021 to 133.87 TWh in the first half of 2022. To maintain power balance and support energy consumption growth, additional power plants are integrated according to the RUPTL. This research aims to anticipate the increase in short circuit levels for both single-phase to ground and three-phase faults at the Extra High Voltage Substation due to new power plants, ensuring the short circuit level remains below 40 kA, in line with equipment standards. This prevents the costly replacement of 500 kV transmission system equipment. Using the Digsilent application, the study models the existing system, maps the N-1 contingency, and calculates the short circuit levels after the integration of power plants from 2023 to 2028. The results identify the type and optimal location of fault current limiters. Installing these limiters is expected to reduce the short circuit level by 5%, avoiding the need to replace transmission and substation equipment rated at 40 kA. Consequently, the 500 kV system of Java Madura Bali can operate reliably with the new power plant integrations. [ABSTRACT FROM AUTHOR]