Search Results (93)

Single-phase ground faults (SPGFs) in isolated neutral medium-voltage networks are difficult to detect, especially under high transient resistance. This paper proposes a centralized ground fault protection unit (CGFPU) that combines zero-sequence current (ZSC) magnitude and phase-angle analysis to enhance selectivity. Simulation results show that as transient resistance increases from 1 Ohm to 10 kOhm, fault currents decrease significantly, yet the CGFPU reliably identifies the faulty feeder by exploiting the characteristic 180° phase shift of ZSC phasors. The method remains selective with angular deviations up to ±20° and distinguishes between feeder and busbar faults. Compared with conventional amplitude- or model-based techniques, the proposed approach achieves faster detection, lower computational complexity, and robustness against unbalanced and charging currents. Furthermore, the CGFPU operates adaptively in alarm or trip mode depending on fault severity, thus preserving continuity for high-resistance faults and ensuring rapid isolation of bolted faults. These contributions establish a practical, scalable, and future-ready solution for SPGF protection in medium-voltage isolated neutral networks. Full article

The neutral point of a 10 kV distribution network often adopts an arc suppression coil or high resistance grounding mode to ensure the reliability of the power supply. The single-phase grounding fault current is below 10 A, and the distribution network can continue to operate with the fault for up to 2 h. However, long-time arc faults may ignite cables and cause electrical fires, causing further damage to adjacent cables and seriously affecting the safety of the power grid. To study the combustion characteristics of a single-phase grounding fault of a distribution network cable under the action of a long-term small current arc, the cable fault ignition test was carried out by using the arc ignition method of welding tin wire fuses. Then, the temperature distribution of the cable channel in an electrical fire was simulated, based on an FDS simulation, and the damage of adjacent cables under typical layout was further analyzed. The results show that the 10 kV cable was quickly ignited by the high temperature arc within 0.04 s after the breakdown and damage of the cable. Flammable XLPE insulation melted or even dripped off at a high temperature in fire. Thus, the fire spread to both ends when burning. Under the condition of 4–10 A, the maximum flame temperatures above the arc fault point reached 725 °C, 792 °C, 812 °C and 907 °C, respectively. According to the network structure, some protection, such as fireproof tape, needs to be applied directly above the faulty cable when the fault current exceeds 6 A. Full article

This paper proposes a novel method for locating single-phase grounding faults in generator stator windings with high resistance, which are typically challenging to locate due to weak fault characteristics. The method utilizes an active voltage injection technique combined with traveling wave reflection analysis, singular value decomposition (SVD) denoising, and discrete wavelet transform (DWT). A DC voltage signal is then injected into the stator winding, and the voltage and current signals at both terminals are collected. These signals undergo denoising using SVD, followed by DWT, to identify the arrival time of the traveling waves. Fault location is determined based on the reflection and refraction of these waves within the winding. Simulation results demonstrate that this method achieves high accuracy in fault location, even with fault resistances up to 5000 Ω. The method offers a reliable and effective solution for locating high-resistance faults in generator stator windings without requiring winding parameters, demonstrating strong potential for practical applications. Full article

In this paper, a method to improve the protection of a four-core power cable of a salt-producing floating platform equipped with an automatic breaker with an independent tripping mechanism is suggested. The use of this automatic breaker in combination with a suggested protection device ensures reliable protection of not only the power cables of the platform against all faults but also the personnel of the platform and animals on the reservoir banks against electric shock in the event of a single-phase ground fault in reservoir water. This would be possible due to a voltage sensor made in the form of a metal ring on the power cable and a relay; one terminal of the relay winding is connected to the voltage sensor by a single-core control cable, and the other to the neutral of a power source on the platform. The typically open contacts of this relay are connected to an electric circuit which includes a power source and a coil for an independent tripping mechanism of the automatic breaker. This design ensures reliable operation of the suggested protection device in the event of a single-phase ground fault in the power cable of the platform when underwater cable insulation is damaged. Full article

Due to the “low damping” characteristics of the DC distribution system, the traditional passive scheme is not suitable for DC fault detection and positioning. Therefore, this paper proposes an active injection fault identification method suitable for DC feeder line under single-pole grounding faults. Based on the high controllability of converters, this method uses the oscillation circuit characteristics of the DC side single-pole grounding fault to superimpose the harmonics of fixed frequency into the converter modulated wave, and derives the selection principles of harmonic amplitude and frequency. After the fault, the positive and negative current signals are extracted from the feeder lines, and the zero-mode current components are extracted by the Karrenbauer transformation and band-pass filter, the current phases are compared to achieve the fault feeder line selection. According to simulation verification, the power quality of the actively injected harmonics is within the standard range under the condition of global injection, and the single-pole grounding faults in each feeder line can be identified. Full article

Single-phase ground (SPG) faults pose significant challenges in three-phase four-wire distribution systems due to their complex transient characteristics and the presence of multiple influencing factors. To solve the aforementioned issues, a comprehensive fault identification framework is proposed, which uses the TabNet deep learning architecture with hyperparameters optimized by Optuna. Firstly, a 10 kV simulation model is developed in Simulink to generate a diverse fault dataset. For each simulated fault, voltage and current signals from eight channels (L1–L4 voltage and current) are collected. Secondly, multi-domain features are extracted from each channel across time, frequency, waveform, and wavelet perspectives. Then, an attention-based fusion mechanism is employed to capture cross-channel dependencies, followed by L2-norm-based feature selection to enhance generalization. Finally, the optimized TabNet model effectively classifies 24 fault categories, achieving an accuracy of 97.33%, and outperforms baseline methods including Temporal Convolutional Network (TCN), Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), Capsule Network with Sparse Filtering (CNSF), and Dual-Branch CNN in terms of accuracy, macro-F1 score, and kappa coefficient. It also exhibits strong stability and fast convergence during training. These results demonstrate the robustness and interpretability of the proposed method for SPG fault detection. Full article

High impedance grounding faults (HIGFs) are a common yet difficult-to-detect issue in distribution networks. Characterized by low fault currents and prolonged durations, they pose a significant risk of triggering secondary hazards such as wildfires. Existing HIGF prevention and control technologies face challenges in effectively addressing arc ignition, fault current limitation, and wildfire mitigation. To tackle these limitations, this paper proposes a novel asymmetric operational structure incorporating a single-phase isolation transformer and supplementary edge-phase capacitance. Through theoretical modeling and simulation analysis, the interrelations among fault current, phase voltage, zero-sequence voltage, and HIGF characteristics are systematically explored. A coordinated control strategy is developed to optimize three-phase voltage distribution within the distribution network. Simulation results demonstrate that the proposed configuration significantly reduces edge-phase voltages, suppresses fault current levels, prevents arc initiation, extends arc ignition delay times, and consequently mitigates wildfire risk. This study presents a new technical pathway for HIGF prevention and control, offering both practical engineering value and theoretical insight. Full article

The 2 × 25 kV flexible traction power supply system (FTPSS), using a three-phase-single-phase converter as its power source, effectively addresses the challenges of neutral section transitions and power quality issues inherent in traditional power supply systems (TPSSs). However, the bidirectional fault current and low short-circuit current characteristics degrade the effectiveness of traditional TPSS protection schemes. This paper analyzes the fault characteristics of FTPSS and proposes a fault identification method based on empirical wavelet transform (EWT) and 1-sequence faulty energy. First, a composite sequence network model is developed to reveal the characteristics of three typical fault types, including ground faults and inter-line short circuits. The 1-sequence differential faulty energy is then calculated. Since the 1-sequence component is unaffected by the leakage impedance of autotransformers (ATs), the proposed method uses this feature to distinguish the TPSS faults from disturbances caused by electric multiple units (EMUs). Second, EWT is used to decompose the 1-sequence faulty energy, and relevant components are selected by permutation entropy. The fault variance derived from these components enables reliable identification of TPSS faults, effectively avoiding misjudgment caused by AT excitation inrush or harmonic disturbances from EMUs. Finally, real-time digital simulator experimental results verify the effectiveness of the proposed method. The fault identification method possesses high tolerance to transition impedance performance and does not require synchronized current measurements from both sides of the TPSS. Full article

In order to improve the localization accuracy and model interpretability of single-phase ground fault sections in distribution networks, a knowledge-integrated and data-driven fault localization model is proposed. The model transforms the transient zero-sequence currents into Markov Transition Field (MTF) images based on transfer entropy, and improves the two-channel feature expression with both causal and temporal structures. On this basis, a knowledge guidance mechanism based on a physical mechanism is introduced to focus on the waveform backpropagation characteristics of upstream and downstream nodes of the fault through the feature attention module, and a similarity weighting strategy is constructed by integrating the Hausdorff distance in the all-connectivity layer in order to enhance the model’s capability of discriminating between the key segments. The dataset is constructed in an improved IEEE 14-node simulation system, and the effectiveness of the proposed method is verified by t-SNE feature visualization, comparison experiments with different parameters, misclassification correction analysis, and anti-noise performance evaluation. For misclassified sample datasets, this method achieves an accuracy rate of 99.53%, indicating that it outperforms traditional convolutional neural network models in terms of fault section localization accuracy, generalization capability, and noise robustness. Research shows that the deep integration of knowledge and data can significantly enhance the model’s discriminative ability and engineering practicality, providing new insights for the construction of intelligent power systems with explainability. Full article

In distribution networks, single-phase ground faults often lead to abnormal changes in voltage and current signals. Traditional single-modal fault diagnosis methods usually struggle to accurately identify the fault line under such conditions. To address this issue, this paper proposes a fault line identification method based on a multimodal feature fusion model. The approach combines time-frequency images—generated using a Short-Time Fourier Transform (STFT) and Wigner–Ville Distribution (WVD) fusion algorithm with one-dimensional time-series signals for classification. The time-frequency images visualize both temporal and spectral features of the signal and are processed using the RepLKNet model for deep feature extraction. Meanwhile, the raw one-dimensional time-series signals preserve the original temporal dependencies and are analyzed using a BiGRU network enhanced with a global attention mechanism to improve feature representation. Finally, features from both modalities are extracted in parallel and fused to achieve accurate fault line identification. Experimental results demonstrate that the proposed method effectively leverages the complementary nature of multimodal data and shows strong robustness in the presence of noise interference. Full article

The traditional arc suppression device suffers from high costs and low utilization. These problems can be effectively avoided by using a hybrid multi-function arc suppression device (HMF-ASD). However, an HMF-ASD will consume active power during arc suppression. Based on this, a P-Q arc suppression method based on DC-link voltage stability is proposed. The energy flow during a single line-to-ground (SLG) fault is analyzed to optimize operation of the HMF-ASD. The topology and principle of the HMF-ASD are introduced. Secondly, the influence mechanism of the traditional arc suppression method on the output active power and energy flow direction of the HMF-ASD is analyzed. The internal reason for the change in the DC-link voltage is clarified. Additionally, non-fault phases of the HMF-ASD are regulated to produce no active output, delivering only the reactive current required for arc suppression. This method effectively mitigates SLG faults while maintaining DC-link voltage stability. Non-fault phases exclusively supply reactive power, with the active power needed for arc suppression drawn directly from the grid. The validity of the proposed method is confirmed through both simulation and experiment. Full article

Flying cars are an important vehicle for future urban air mobility. Mainstream flying cars predominantly adopt the e-VTOL-like configuration. Unlike traditional aircraft, these flying cars must be operated by a single pilot. The corresponding hybrid ground-flight control scheme remains immature, with only a few reliability analyses focused on flight safety. Based on the single-pilot operation (SPO) concept, this paper designs a hybrid control scheme for e-VTOL-like flying cars and proposes a restricted driving mode for the the take-off and landing stages and an autonomous driving mode for the cruising stage, respectively. Taking the landing phase as an example, a fault mode analysis and fault tree analysis are conducted for the restricted driving mode, focusing on factors that are sensitive to flight safety. A fault probability analysis is performed of the landing control unit in the restricted driving mode. The calculated probability of the top event occurring is 1.98 × 10⁻⁸ per flight, which proves the feasibility of the design meets the safety requirements. This study provides a foundation for a safety assessment of driving modes in future designs of flying cars. Full article

Petal-shaped distribution networks are receiving increasing attention due to their enhanced reliability. However, the integration of distributed generators (DGs) significantly alters the fault characteristics during single-phase to ground faults. Traditional short-circuit calculation methods become inadequate due to the unmodeled effects of negative sequence current control in DGs. To address this challenge, this study establishes, for the first time, a mathematical model for single-phase to ground faults in a petal-shaped network with DG integration under both positive and negative sequence control. It explicitly derives the DGs’ output current under three control goals: maintaining constant active power, maintaining constant reactive power, and injecting a symmetric three-phase current. Utilizing the symmetrical component method, a composite sequence network incorporating the DGs’ negative sequence current output is developed. Based on the node–voltage relationships, an analytical short-circuit current calculation method suitable for multiple control goals is proposed. Validation via MATLAB R2022a simulations demonstrates high-fidelity accuracy: in Case 1 with different fault locations, the maximum relative error is 0.31%, while in Case 2, it is 2.04%. These results quantify the critical impact of the negative sequence current—reaching up to 14.78% of the DG output during severe voltage sags—providing theoretical support for the protection design of a petal-shaped distribution network with high DG integration. Full article

In view of the complex operating environments of wind farms and the characteristics of multi-branch mixed collector lines, in order to improve the accuracy of single-phase grounding fault location, the convolutional neural network (CNN), bidirectional long short-term memory network (BiLSTM), and attention mechanism (attention) were combined to construct a single-phase grounding fault location strategy for the CNN–BiLSTM–attention hybrid model. Using a zero-sequence current as the fault information identification method, through the deep fusion of the CNN–BiLSTM–attention hybrid model, the single-phase grounding faults in the collector lines of the wind farm can be located. The simulation modeling was carried out using the MATLAB R2022b software, and the effectiveness of the hybrid model in the single-phase grounding fault location of multi-branch mixed collector lines was studied and verified. The research results show that, compared with the random forest algorithm, decision tree algorithm, CNN, and LSTM neural network, the proposed method significantly improved the location accuracy and is more suitable for the fault distance measurement requirements of collector lines in the complex environments of wind farms. The research conclusions provide technical support and a reference for the actual operation and maintenance of wind farms. Full article

Balance control in pirouettes has previously been characterized by constraint of the topple angle. However, there is a paucity of research using the margin of stability (MoS) as a dynamic measure of balance related to pirouettes. Therefore, this study aimed primarily to examine the MoS as a metric of balance during a single-turn en dehors pirouette in healthy female amateur ballet dancers. Four participants performed pirouettes until five successful pirouettes were achieved without hopping or loss of balance. Three-dimensional motion capture was used to record the motion trajectories of anatomical markers based on the Plug-in-Gait and Oxford Foot models. Motion synchronized with ground reaction forces was used to calculate the center of pressure (CoP), base of support (BoS), center of the pivot foot, center of mass (CoM), and extrapolated center of mass (XCoM) throughout the turn phase, using laboratory (LCS) and virtual left foot (LFT) coordinate systems. In the LCS and LFT coordinate system, the excursions and patterns of motion of both the CoM and XCoM relative to the CoP were similar, suggesting a neurological relationship. Two different measures of the margin of stability (MoS) in the LFT coordinate system were tabulated: the distance between the (1) XCoM and CoP and (2) XCoM and BoS center. The magnitude of both versions of the MoS was greatest at turn initiation and toe-touch, which was associated with two foot contacts. The MoS values were at a minimum approximately 50% of the stance during the turn phase: close to zero along the anteroposterior (A/P) axis and approximately 50 mm along the mediolateral (M/L) axis. On average, MoS magnitudes were reduced (mean across participants: approximately 20 mm) along the A/P axis, and larger MoS magnitudes (mean across participants: approximately 50 mm) along the M/L axis throughout the turn phase. Although all turns analyzed were completed successfully, the larger MoS values along the M/L axis suggest a fall potential. The variability between trials within a dancer and across participants and trials was documented and showed moderate inter-trial (16% to 51%) and across-participant CV% (range: 10% to 28%), with generally larger variations along the A/P axis. Although our results are preliminary, they suggest that the MoS may be useful for detecting faults in the control of dynamic balance in dehors pirouette performance, as a part of training and rehabilitation following injury. Full article