Ground Fault Research Articles

Assessment of the spectral energy of zero-sequence currents in protected feeders with the presence of single-phase to ground fault in the isolated network

Subject of research: methods of relative measurement of higher harmonics for detecting a faulty feeder with a single-phase ground fault. Purpose of research: evaluation of sensitivity of the methodology of faulty feeder search using wavelet transform. Object of research: distribution networks of 6(10) kV. Main results of research: the level of higher harmonics does not affect the performance of the technique, regardless of the point of the fault and the harmonic composition of the load, the damaged connection is the highest value of the spectrum energy.

A Hybrid Data-Driven Method for Main Circuit Gound Faults Diagnosis in Electrical Traction Drive Systems

A main circuit ground fault (MCGF) is a typical system fault in an electrical traction drive system (ETDS). When two or more MCGFs occur, it will cause serious accidents. Therefore, it is particularly important to detect and handle MCGFs in a timely manner. To improve the efficiency of train operation and ensure driving safety, this paper proposes a hybrid data-driven MCGF diagnosis method. First, the voltage signals related to the fault are selected according to the mechanism analysis of the MCGF, and then the initial feature variables are constructed according to these voltage signals. Secondly, the initial feature variables of different types of MCGF are analyzed in the time and frequency domains by wavelet transform, and four feature indicators are calculated. Finally, the fault feature indicators are trained by random forest to obtain a model for subsequent fault diagnosis. After comparative experiments using various machine learning methods, it was found that the RF used in the proposed method has a better diagnostic effect, and the correct isolation rate exceeds 99%.

Seismic input method coupling ground motion and fault dislocation for near-fault engineering sites

Seismic input method coupling ground motion and fault dislocation for near-fault engineering sites

AC Ground Fault Location Method Through Voltage Frequency Components Analysis for Variable Speed Drives

AC Ground Fault Location Method Through Voltage Frequency Components Analysis for Variable Speed Drives

Evaluative assessment of a five-phase and three-phase permanent magnet synchronous machine at varied loads and fault conditions

Multiphase machines are very essential for industrial applications that require high reliability of operation. In this paper, a comparative study of three-phase and five-phase inverter fed permanent magnet synchronous motors (PMSMs) was evaluated with respect to their performance characteristics under a healthy state and during transient disturbances such as varied load and double line to ground faults. To avert inherent high oscillations in speed and torque ripples during fault condition, the machine load was significantly reduced to 1/4th of the full load and a post fault current limiting series dynamic braking resistance (SDBR) with a bypassed switch was introduced to enhance the machine fault tolerant level and improve its operational performance. Spectral analyses were carried out to determine the magnitude of harmonic distortion during these conditions. The simulation results show that the five-phase PMSM achieved a reduced oscillatory transient and a faster settling time of speed and torque under a varied load. It also exhibited good harmonic profiles as indicated in the respective % THD values when compared to the three phase PMSM which is prone to high harmonic overheat. However, when subjected to a double line to ground fault, their various %THD values in speed and torque increased with five-phase PMSM still having a reduced %THD values over the three-phase PMSM. Therefore, for a higher fault tolerant capability, greater efficiency with proven reliability, a five-phase PMSM with a fault current limiting series dynamic braking resistance is a better substitute when compared with the three-phase PMSM in industrial applications where safety and loss minimization is a top priority. All simulation processes in this paper were achieved in MATLAB 2015.

The New Method for Ground Insulation Monitoring of the Secondary Circuit in Substations

When two-or-more-point grounding faults occur in the secondary circuit of a substation, they will lead to large data measurement errors in the protection, measurement, and control devices, which can easily cause protection malfunction. At present, there is a lack of an online panoramic monitoring system for the secondary circuits of substations, and it is difficult to accurately identify the faults in these secondary circuits. In order to solve this problem, this paper proposes a cloud–edge collaboration framework for the power Internet of Things (IoT), which can accurately identify faults by monitoring the secondary circuit of power grid substations with panoramic online status, reducing maintenance costs and improving overall operational efficiency. Firstly, the collection requirements of current transformer (CT) and potential transformer (PT) fault characteristics in the secondary circuit of the substation are analyzed. The platform architecture of the secondary loop panoramic monitoring system of the cloud-side cooperative substation is proposed, along with the algorithm and data wireless acquisition scheme of the edge computing, cloud computing, and cloud-side system. Furthermore, the edge computing platform and the current and voltage wireless sensors are developed. The maximum error in the accuracy test of the voltage sensor is 1.9180%, while the maximum error in the accuracy test of the current sensor is 1.3406%.

Efficient Fault Detection and Analysis of Power System Distribution Networks by Integrating BP Data Mining

As the basic guarantee for people’s production and life, the safe operation of the power system has an important impact on the development and operation of society. To ensure the safe and stable operation of the power grid, predicting potential faults and taking reasonable preventive measures can effectively avoid the occurrence of power accidents. However, due to the difficulty in ensuring the prediction accuracy of traditional methods, there are issues of protection misoperation and rejection. Therefore, in order to achieve accurate prediction of power grid faults and avoid protection misoperation and rejection issues, a distribution network fault classification prediction model using a combination of three-layer data mining model (TLDM) and adaptive moment estimation (Adam) algorithm/random gradient descent algorithm improved backpropagation neural network (BPNN) is proposed. The implementation results showed that the classification accuracy of artificial fish school [Formula: see text] priori, [Formula: see text]-means clustering convolutional neural network model and TLDM for single-phase grounding faults was 93.2%, 91.5% and 96.6%, respectively. The classification accuracy for two-phase faults was 92.8%, 92.4% and 95.7%, respectively. The classification accuracy for two-phase grounding faults was 93.7%, 91.2% and 96.9%, respectively. The classification accuracy for three-phase faults was 93.3%, 92.1% and 97.1%, respectively. The TLDM had the highest classification accuracy. The average accuracy, average accuracy and average recall of the BPNN improved by the combination of the ADAM algorithm and random gradient descent algorithm were 94.1%, 90.9% and 88%, respectively, which were higher than the BPNN improved by the combination of ADAM algorithm and random gradient descent algorithm. The above results indicate that the proposed distribution network fault classification and prediction model has good performance and can achieve accurate prediction of distribution network faults.

An Enhanced Fault Localization Technique for Distribution Networks Utilizing Cost-Sensitive Graph Neural Networks

Accurate and timely fault diagnosis is of great significance for the stable operation of a distribution network. Traditional artificial intelligence-based localization methods rely heavily on large-scale labeled datasets, making them prone to being affected by distributed generators. To address this issue, this study proposes a fault location method for distribution systems using a cost-sensitive graph attention network model. In this approach, the physical structure of the distribution network is considered a crucial constraint for model training, thereby enhancing its information perception capabilities. Specifically, the electrical nodes and lines of the distribution network are mapped to the vertices and edges within the graph attention network, with the attention weights determined by the correlation of adjacent node fault characteristics, thus improving the sensitivity to grounding faults. Additionally, a cost-sensitive matrix is used to balance class distribution, enhancing the robustness and generalization ability of the model. Fault localization experiments were conducted on the IEEE-33 bus distribution system to validate the effectiveness of the proposed fault localization method. Factors such as data disturbance, varying fault grounding resistances, and distributed power supply access were employed to assess the model’s anti-interference performance. The experimental results demonstrate that the fault location method exhibits high positioning accuracy and excellent robustness.

Detection of Faulty Energizations in High Voltage Direct Current Power Cables by Analyzing Leakage Currents

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.

A Method for Single-Phase Ground Fault Section Location in Distribution Networks Based on Improved Empirical Wavelet Transform and Graph Isomorphic Networks

When single-phase ground faults occur in distribution systems, the fault characteristics of zero-sequence current signals are not prominent. They are quickly submerged in noise, leading to difficulties in fault section location. This paper proposes a method for fault section location in distribution networks based on improved empirical wavelet transform (IEWT) and GINs to address this issue. Firstly, based on kurtosis, EWT is optimized using the N-point search method to decompose the zero-sequence current signal into modal components. Noise is filtered out through weighted permutation entropy (WPE), and signal reconstruction is performed to obtain the denoised zero-sequence current signal. Subsequently, GINs are employed for graph classification tasks. According to the topology of the distribution network, the corresponding graph is constructed as the input to the GIN. The denoised zero-sequence current signal is the node input for the GIN. The GIN autonomously explores the features of each graph structure to achieve fault section location. The experimental results demonstrate that this method has strong noise resistance, with a fault section location accuracy of up to 99.95%, effectively completing fault section location in distribution networks.

Research on single-phase grounding detection method in small-current grounding systems based on image recognition

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.

Transient stability enhancement of Beles to Bahir Dar transmission line using adaptive neuro-fuzzy-based unified power flow controller

A power system is a complex, nonlinear, and dynamic system, with operating parameters that change over time. Because of the complexity of big load lines and faults, high-voltage transmission power systems are usually vulnerable to transient instability concerns, resulting in power losses and increased voltage variation. This issue has the potential to cause catastrophic events such as cascade failure or widespread blackouts. This problem affects Ethiopia's high-voltage transmission power grid in the northwest area. Because of the increased demand for electrical energy, transmission lines' maximum carrying capacity should be enhanced to maintain a secure and uninterrupted power supply to consumers. To address the problem, ANFIS-based UPFC is used for high-voltage transmission lines. This device was chosen as the ideal alternative due to its capacity to rapidly correct reactive power on high-voltage transmission networks. The PSO algorithm was used to determine the best location for the UPFC. The ANFIS controller receives voltage error and rate of change of voltage error as inputs. Seventy percentage of the retrieved data are used for ANFIS training and 30% for ANFIS testing. To show the performance of the proposed controller, three-phase ground faults are used from a severity perspective. When a three-phase ground fault occurs at the midpoint of the Beles to Bahir Dar transmission line, for instance, the settling time of rotor angle deviation, rotor speed, rotor speed deviation, and output active power of synchronous generators using ANFIS-based UPFC is reduced by 70.58%, 37.75%, 37.75%, and 43.75%, respectively, compared to a system without UPFC. At peak load, PI-based UPFC and ANFIS-based UPFC reduce active power loss by 51.25% and 71.50%, respectively, compared to a system without UPFC on the Beles to Bahir Dar transmission line. In terms of percentage overshoot and settling time, ANFIS-based UPFC outperforms PI-based UPFC for transient stability enhancement.

Faulty section location method for high impedance grounding fault in resonant grounding system based on discrete Fréchet distance

When a High Impedance Fault (HIF) occurs in a resonant grounding system, the differentiation of the current flowing upstream and downstream of the fault point is inconspicuous due to the weak electrical signal. This paper proposes a faulty section location approach based on Discrete Fréchet Distance (DFD) to address this issue. Initially, taking the zero-sequence current as the characteristic quantity, the instantaneous value of the zero-sequence current at each sampling point and its previous sampling moments are accumulated to amplify the fault signal, and furthermore to obtain the cumulative waveform of the zero-sequence current at each monitoring point. The DFD values between the cumulative waveforms of zero-sequence currents flowing through each section are also calculated. For a branchless section, if the Coefficient of Variation (CV) of the DFD in each section does not exceed the threshold value, it is identified as an end-of-line fault, otherwise, the section with the maximum DFD is identified as a faulty section. For a section with branches, the branching coefficient is calculated to determine whether it is a faulty section or not. Finally, MATLAB/Simulink simulation results and field-recorded data demonstrate the validity and robustness of the approach under various fault conditions, despite the connection of Distributed Generators (DGs).

Ground fault protection algorithm of active distribution network based on energy extremum direction

AbstractAfter large‐scale distributed power sources are connected to the distribution network, the fault current undergoes noticeable changes, affecting the accuracy of traditional single‐phase grounding fault algorithms. Therefore, the objective of this paper is to address the impact of distributed power integration on the grounding algorithms of distribution networks. The main contribution is: by establishing an electrical system structure and model for distribution network grounding faults that include distributed generation (DG), theoretically deriving and calculating the transient zero‐sequence current frequency changes at the moment of fault, analysing the directional characteristics of zero‐sequence currents under DG connection conditions, designing a local grounding fault judgment algorithm based on energy extremum direction, and providing a fault judgment and isolation process for grounding fault monitoring devices. The results show: through simulation and experimentation, the algorithm was tested, and the method can reliably judge grounding faults under various transition resistances, different numbers and capacities of connected distributed power sources, and different grounding switch‐on angles. The applicability of the algorithm covers both methods of neutral grounding through an arc suppression coil and ungrounded neutrals, adapting to scenarios with or without DG connections.

A Ground Fault Location Technique for Wound Field Poles of Synchronous Machines Through Frequency Response Analysis

A Ground Fault Location Technique for Wound Field Poles of Synchronous Machines Through Frequency Response Analysis

Fault Line Selection of Small Current Grounding System Research Based on Zero Sequence Circuit Current Phase

Abstract This paper investigates fault line selection in small current grounding systems, focusing on the zero sequence current phase characteristics. Small current grounding systems, prevalent in medium voltage distribution networks, face challenges in fault detection due to minimal fault currents during single status phase grounding faults. Traditional methods relying on manual line switching and zero sequence voltage monitoring are inefficient and can induce overvoltage. This study categorizes fault line selection techniques into three approaches: steady-state fault information, transient information, and modern signal processing technology. The analysis of zero sequence currents in non-grounded systems reveals that fault line zero sequence currents equal the sum of system capacitive currents, flowing opposite to those in non-fault lines. Additionally, transient signal analysis shows that these signals provide more robust information for fault detection. MATLAB simulations validate the theoretical models, demonstrating that zero sequence current direction and amplitude effectively identify fault lines. The results confirm the efficacy of combining steady-state and transient signal analyses for accurate fault line selection, contributing to enhanced safety and reliability in power distribution networks. This research offers practical insights and tools for engineers, improving fault management and reducing potential economic losses in small current grounding systems.

계통연계형 PV(Photovoltaic) 설계 및 과도상태 특성 연구

This study investigated the design of a grid-connected photovoltaic (PV) system based on solar power generation and its characteristics during ground-fault incidents. Various approaches to enhance the stability and efficiency of the PV system were explored. Experimental results confirmed that the integration of solar arrays, DC/DC converters, and inverters optimized the output characteristics of the system. In particular, the analysis focused on current changes and control mechanisms during ground fault incidents and compared the effectiveness of DC circuit breakers and superconducting fault current limiters. Simulations were performed to propose solutions to address the problem of sudden increases in fault current. The results demonstrated the effectiveness of DC circuit breakers in limiting fault currents. Additionally, the application of fault current limiters improved both fault current limitation and response times for disconnection. The results of this study enhance the safety and economic operation of solar power systems and facilitate the adoption of eco-friendly energy. The results can be used as a reference for the design and operation of solar power systems in the future and can support the implementation of renewable energy policies.

Adaptable Ground Fault Relay Protection for Neutral Grounding Resistor in Transformers and Generator: A Study in Indonesian Context

Adaptable Ground Fault Relay Protection for Neutral Grounding Resistor in Transformers and Generator: A Study in Indonesian Context

End-to-end deep learning on classification of neutral-to-ground voltage in secondary distribution systems

Neutral-to-ground voltage (NTGV) abnormalities in secondary distribution systems (SDS) pose significant power quality (PQ) challenges, including safety hazards, power losses, and equipment damage. Despite their importance, these abnormalities remain relatively understudied. Accurate classification of NTGV events is crucial for effective mitigation strategies. Existing research primarily relies on machine learning (ML) models trained on manually extracted features from simulated or real-world signals. This paper introduces a novel end-to-end deep learning approach that leverages Gate Recurrent Units (GRU) to bypass manual feature extraction, directly utilizing real-world signals from three NTGV event categories: ground fault, lightning strike, and normal conditions. This is first time that GRU has been used for NTGV classification using raw data. The model's generalizability is assessed through 5-fold cross-validation. A comparative analysis with baseline models and traditional ML techniques demonstrates the proposed model's superior performance and computational efficiency due to its ability to directly process raw data.

Testing the operation of protection devices against parallel arc breakdown and spark gaps in the event of a ground fault

Testing the operation of protection devices against parallel arc breakdown and spark gaps in the event of a ground faultTHE PURPOSE. Develop a laboratory rig for testing parallel arc fault and spark gap protection devices for tripping in the event of a ground fault. Conduct laboratory rig tests with subsequent development of requirements for the use of parallel arc fault and spark gap protection devices for tripping in the event of a ground fault.METHODS. Mathematical and statistical methods of analysis were used to achieve the stated objective. Laboratory tests of parallel arc fault and spark gap protection devices for different network parameters for correct tripping in the event of a ground fault.RESULTS. Laboratory tests of parallel arc fault and spark gap protection devices for correct tripping in the event of a ground fault were conducted with different network parameters. The oscilloscope recorded the shape of the voltage and current curve in the event of a ground fault and the tripping time of the devices. The tested devices demonstrated the ability to recognize and disconnect a ground fault. The tripping time of the devices varies, however, does not exceed the established requirements.CONCLUSION. A laboratory stand has been developed for testing parallel arc breakdown and spark gap protection devices for operation during a ground fault. This stand makes it possible to test devices for adequate operation during a ground fault with subsequent certification. The tests conducted demonstrate the need to develop mandatory requirements for the device to standardize their operating algorithm. Therefore, the use of this protection device can contribute to safer operation of low-voltage electrical networks by preventing emergency situations and reducing the risk of fires. This is an important technical aspect for improving the reliability and safety of power supply.