Insulated Switchgear Research Articles

Comparative Study on Multiple Methods for Partial Discharge Detection of Gap Defect in Medium Voltage Switchgear

Abstract The medium voltage switchgear is a key equipment in the distribution network of the power system, which directly faces users. Once a fault occurs, it will cause huge economic losses and adverse social impacts. Partial discharge measurement is an important means to ensure the safe operation of switchgear. The physical quantities measured by different partial discharge detection methods are different, so the detection effects by different methods for the same defect are also different. This paper takes the common internal air gap defects of solid insulation in switchgear as the research object, and conducts partial discharge detection tests on real switchgear equipment. At the same time, radio frequency method, ultrasonic method, transient earth voltage (TEV) method, and pulse current method are used to detect and analyze the partial discharge generated by the defect. The results show that the radio frequency method, TEV method, and pulse current method have good detection sensitivity for air gap defects, but the ultrasonic method cannot detect this type of defect. Comparing the amplitudes of the three electrical signals, it can be found that the correlation between the TEV method and the pulse current method is relatively high, while the correlation between the radio frequency method and the two is relatively low. As the applied voltage increases, the amplitude of the radio frequency method changes linearly, which can more sensitively reflect the degree of defect change.

Gas-insulated switchgear partial discharge acoustic–electric joint localisation method based on the Salp Swarm Algorithm and least squares estimation

Partial discharge (PD) is an early warning of gas-insulated switchgear (GIS) insulation faults. Consequently, accurate localisation of PD is crucial for the safe operation of GIS. The time difference of arrival method based on acoustic emission technology is more favorable for the engineering application of PD source localisation owing to its noninvasive characteristics and the small amount of required data. However, because PD ultrasonic signal propagation in GIS will introduce a variety of errors, current localisation algorithms suffer from problems of low accuracy and poor stability. Therefore, this study simulate and analyse the ultrasonic propagation characteristics as well as the sources of errors in GIS, based on which a joint acoustic–electric localisation method based on the Salp Swarm Algorithm is proposed, and an error-correction method based on least squares estimation is introduced. The localisation results show that the proposed method can effectively reduce the localisation error caused by multiple sources of error, and the mean localisation error can be reduced to within 20 mm in different structural gas chambers of GIS, which is more accurate and more stable compared with other methods, and it has good value for engineering application.

Pressure Monitoring in Medium-Voltage Vacuum Interrupters

Innovation in the economy is closely tied to energy development, encompassing the exploration of new energy sources, increased energy production efficiency, and the integration of diverse energy sources for safe and effective supply to industries and households. Outdated energy infrastructure disrupts electricity continuity and hampers economic innovation. Power interruptions lead to higher SAIDI and SAIFI reliability indices. Quality and reliability requirements have sparked interest in enclosed energy devices. Vacuum technology has been pivotal in electrical switchgear insulation and arc-quenching for over four decades. However, the lack of real-time pressure monitoring systems for vacuum equipment, especially enclosed disconnectors, limits their use as isolation connectors. Potential insulation failure poses risks to power line maintenance teams and can lead to unplanned shutdowns, further compromising energy supply quality. This article explores an innovative pressure monitoring system for vacuum interrupters, utilizing fiber optic Bragg grids as a measuring sensor, enabling pressure measurement within the vacuum chamber ranging from 2 × 101 Pa to 5 × 105 Pa.

Surface modification of aramid fiber by cascade process with atmospheric plasma and TDI grafting

Aramid fiber (AF)/epoxy composites are often used as mechanical and insulating materials for ultra-high voltage gas-insulated switchgear (GIS) insulation pull rods. However, the product performance is believed to be restricted by the poor adhesion between AF and the resin matrix, affecting the operation reliability of GIS. In this work, a cascade process was applied to modify the AF surface to improve interfacial behavior. The AF was first treated with air dielectric barrier discharge at atmospheric pressure to obtain a rough surface and then reacted with toluene-2,4-diisocyanate (TDI) to introduce polar functional groups onto the surface. The plasma discharge power and treatment time were investigated as major parameters, and the aging effect was studied. The modified AF was characterized by scanning electron microscope, Fourier transform infrared spectrometer, x-ray photoelectron spectroscopy, atomic force microscope, and filament yarn tensile test. The interfacial behavior of the AF/epoxy composite was analyzed by interfacial shear strength (IFSS) test of micro-bond specimen and interlaminar shear strength (ILSS) test of Naval Ordnance Laboratory rings. Experimental results showed that polar functional groups were introduced onto the AF surface. The IFSS and ILSS of AF/epoxy composite were increased by 32.8% and 20.2% at most, respectively, and the tensile strength of the AF was mostly preserved. Moreover, with the increase in plasma discharge power, the interfacial strength of the modified AF/epoxy interface increased firstly and then decreased. The AF modified by TDI retained a relatively good modification effect after aging for some time. This study presents a cascade process for the AF surface modification with simplicity, effectiveness, and resource-saving, which is suitable for industrial applications.

A novel hybrid meta-learning for few-shot gas-insulated switchgear insulation defect diagnosis

Though deep learning-based diagnosis methods have been extensively researched in gas-insulated switchgear (GIS) insulation defects diagnosis. Training a high-precision and robust GIS insulation defect diagnosis model under complex and few-shot conditions remains difficult. To address these issues, a novel hybrid meta-learning for a few-shot GIS insulation defect diagnosis is proposed. The meta Siamese network (MSN) is designed by incorporating the model-agnostic meta-learning (MAML) into the Siamese network (SN). Firstly, a SN is designed to acquire knowledge of GIS insulation defect diagnosis. To capture the discriminative characteristics, the attention mechanism is introduced into SN to reduce the attention to irrelevant information. Then, the model parameters are optimized through MAML. To ensure the model’s optimal performance, the meta-stochastic gradient descent is introduced to realize optimizer learning in an end-to-end form. The experimental results show that when the support sets is 5, MSN can achieve 93.15% accuracy, which outperforms other methods. Furthermore, the issue of unbalanced samples is effectively avoided, providing a feasible solution for the few-shot GIS insulation defects.

Metal Particle Movement and Induced Insulator Flashover Under Impact Vibration Generated By Switching Operation in GIS

Gas insulated switchgear (GIS) insulation failures occur frequently in field operations, seriously affecting the reliability of power systems. Fault statistics show that nearly half of the insulation flashover faults in field operation are strongly related to the switching operation, and metal particles are considered to be a crucial cause of flashover. The impact vibration generated by the switching operation may activate the metal particles and make them lift and jump in the GIS, reducing the insulation performance. Therefore, in this study, an experimental platform was established to simulate the impact vibration generated by the switching operation. The flashover characteristics induced by metal particles under impact vibration were studied, and the movement behavior of metal particles was also analyzed. The results show that metal particles lying on the enclosure lift under the impact vibration and then keep jumping in the GIS. These particles can jump to cause insulator flashover with high probability after the impact vibration. The longer the metal particles, the higher the probability of insulator flashover, and the shorter the average jump duration of the metal particles before the flashover. Moreover, compared with the flake particles, linear particles are more likely to cause insulator flashover after the impact vibration. This study demonstrates the mechanism of insulator flashover caused by metal particles under impact vibration, which provides a significant support for understanding the insulation failures strongly related to the switching operation in practical applications.

Monitoring and prediction of thermal failure of high-voltage switchgear insulation materials by studying the thermodynamic properties of FR-4 epoxy resin and the characteristic gas of thermal decomposition

FR-4 epoxy resin is a common material used as internal parts in high voltage switchgear. In this paper, we adopted the accelerated thermal aging method to explore the thermal aging behavior of FR-4 epoxy resin, simulating the practical application of this material in high voltage switch. The effects of thermal aging on the thermodynamic properties and thermal decomposition characteristic gases of FR-4 epoxy resin were characterized by FT-IR, DSC, TG and GC-MS analyses. The experiment results showed that thermal aging could destroy the internal crystal structure of FR-4 epoxy resin, which could lead to this material easier to be decomposed after heating. We also detected that the thermal decomposition rate of FR-4 epoxy resin aging was greatly accelerated compared with the materials that had not been aged. In addition, unaged FR-4 epoxy resin could release 9 main volatile gases under 120°C, and irreversible defects or structural damages occurred in the materials along with the volatilization of small organic molecules. Furthermore, after continuous thermal aging at 120 °C for 672 h, the molecules of FR-4 epoxy resin were more cracked and volatilized, we observed a more obvious phenomenon of thermal decomposition in this materials. In total, we compared the types of thermal decomposition gases and the decomposion mechanism of aged and unaged FR-4 epoxy resin. In application, our results can provide reference for condition monitoring and fault prediction for this material in high voltage switchgear in the future.

Corona Onset Characteristics of Contact Box in Switchgear With Condensation Under High Humidity and Pollution Conditions

Corona discharge occasionally occurs to the contact box of switchgear due to condensation under high humidity and pollution conditions, which may result in a switchgear insulation fault. In this article, we develop an experimental platform for the condensation of contact boxes in switchgear. A metallographic microscope is used to measure the size and distribution characteristics of dewdrops on the surface of the contact box under various temperature, humidity, and pollution conditions. A simulation model for the distribution of dewdrops is established using fractal theory, and the simulation results match the measured results well. The corona onset voltage is predicted and verified by the UV imager’s measurements by substituting the electric field distribution around the contact box with different dewdrops into the streamer inception criterion. The research results indicate that higher humidity and temperature differences result in a larger dewdrop and a shorter condensation formation time, resulting in a lower corona onset voltage. The effect law is similar under high pollution conditions, but the dewdrop is larger, the condensation formation time is longer, and the corona onset voltage is significantly lower than under clean conditions. As a result, high humidity and pollution conditions must be avoided during the operation of switchgear.

A Novel Federated Transfer Learning Framework for Intelligent Diagnosis of Insulation Defects in Gas-Insulated Switchgear

Deep learning driven diagnostic methods have shown significant ability to diagnose certain types of insulation defects. However, for these methods to achieve excellent results, it is necessary for the clients to obtain a large amount of data, which is not realistic for a typical client. For this reason, there is an incentive for different clients to collaboratively develop effective diagnostic models, but due to conflicts of interest and privacy protection issues, data sharing has become a challenge. In addition, due to domain shift, it is difficult to apply the model developed by some clients to others. In response to this, we propose a novel federated transfer learning framework. Specifically, we developed a federated adversarial learning that achieves domain adaptation while protecting data privacy, and we introduced a federated minimax algorithm for global model aggregation, which not only solves the problem of gradient drift caused by sample imbalance but also improves the accuracy of the global model. We verified that our method can achieve high-precision and robust diagnosis of gas-insulated switchgear insulation defects with experiments composed of laboratory and field clients. The superior performance for unbalanced small samples on-site shows that the application of the proposed federated transfer learning is promising.

Partial Discharge yang Merusak Isolasi SF6 pada Gas Insulated Switchgear (GIS) Tiga Fasa Pengaruh Keberadaan Partikel Asing

This paper analyzes the effect of the presence of foreign particles on an equilateral arrangement of 3 phase gas insulated switchgear (GIS) insulation equipment. Gas Insulated Switchgear (GIS) that uses SF6 insulation, partial discharge will occur as the insulation ages and there are several other factors that affect the insulation. Partial Discharge needs to be detected to avoid failures that cause damage to equipment in theGIS. In this calculation, the electric field characteristics will be analyzed in 3-phase equilateral GIS by varying the location of the particles in the GIS tank. Particles are modeled to have a length of 5 mm and a thickness of 0.5 mm located in a 3 phase GIS equilateral arrangement with a tank diameter of 150 mm and a conductor diameter of 25 mm. The electric field calculations are reviewed at several points in the 3-phase equilateral GIS tank. The simulation and calculation of the electric field were calculated with FEM method software. The results of the calculations show that thereare differences in the characteristics of the electric field between normal GIS and GIS where foreign particles are present. The difference in these characteristics can be seen in the magnitude of the electric field, and the ratio of eccentricity from some point of view.

A novel adversarial transfer learning in deep convolutional neural network for intelligent diagnosis of gas‐insulated switchgear insulation defect

Recently, numerous data-driven fault diagnosis methods have been developed, and the tasks involving the same distribution of training and test data have been well solved. However, considering the particularity of gas-insulated switchgear (GIS), collecting massive data, especially with the same distribution, is difficult. Therefore, existing fault diagnosis methods hardly achieve satisfactory insulation defect diagnosis with small datasets. Aiming at solving this problem, a novel domain adversarial transfer convolutional neural network (DATCNN) is proposed, realising the diagnosis of GIS insulation defects on small samples. First, a residual CNN is built to learn feature representations from the source and target domains. Second, the domain adversarial training strategy is used for feature transfer, where a conditional adversarial mechanism is introduced, and the joint distribution of features and labels is improved to a random linear combination, which realises the simultaneous adaptation of features and labels. Finally, the Nesterov accelerated gradient descent optimisation algorithm is used to speed up the gradient convergence. DATCNN has 99.15% and ≥89.5% diagnosis accuracy for GIS insulation defects in the laboratory and on-site, respectively. Comprehensive experiment results show the effectiveness and superiority of the proposed method in diagnosing GIS insulation defects with small samples.

Defect Localization Inside Simulated MV Switchgear Based on Cumulative Energy Curve Using Transient Earth Voltage Sensors

The partial discharge (PD) leads to catastrophic failure of the medium voltage (MV) switchgear insulation. Determination of the PD source (defect) location in high voltage (HV) equipment is very important in the maintenance procedures and in isolating the root cause of PD generation. In this paper, the transient earth voltage (TEV) detection method was used to acquire defect-initiated PD signals in a simulated MV switchgear model. An array of four TEV sensors were placed on the surface walls outside an MV switchgear tank to acquire the PD signals generated from the known location(s)/coordinates of sharp needle type defect inside the tank. The time difference of arrival (TDOA) between signals that are captured by the TEV sensors array was critically analyzed. Estimating the TDOA between PD signals generated by PD source at a known location with high accuracy is of great importance for accurate defect localization. The cumulative energy method (CEM) is used to estimate the onset time point of each TEV signal. The estimated TDOA by the cumulative energy method is compared with actual and expected TDOA based on known coordinates of PD source and TEV sensors. Experimental data are used as a basis for determining the TEV method accuracy for PD source localization. Experimental results show the average error of time difference is about 1.34 ns, which is equivalent to the propagation distance of 0.4 m.

Design of Insulation Online Monitoring and Anti-Condensation Control System for Distribution Switchgear

The partial discharge and condensation in distribution switchgear seriously affect the insulation state, which can cause insulation failure and lead to the shutdown of electrical equipment. This paper designs and develops a set of insulation online monitoring and anti-condensation control system for distribution switchgear. By comprehensive use of transient earth voltage (TEV) technology and ultrasonic technology for partial discharge detection, temperature and humidity detection, control technology and wireless communication technology, the system realizes the online monitoring of insulation, temperature and humidity in switchgear. In addition, the system can automatically control the heater, fan or other environmental adjustment equipment and reduce the occurrence of condensation in switchgear.

Entire process of surface discharge of GIS disc‐spacers under constant AC voltage

Surface contamination on the disc-spacers is one of the main threats to the safe operation of gas insulated switchgear (GIS) insulation. The authors’ research has confirmed the phenomena of intermittent discharge of such defects under AC constant voltage and concluded that long-intermittent discharge may be the cause of sudden flashover failure of GIS. To explore the characteristics of the process from the partial discharge (PD) inception to the breakdown of surface discharge under constant AC voltage, a 126 kV GIS test platform was built and long-term uninterrupted detection was carried out in this study. By processing the discharge data of the entire process, distribution characteristics of phase-resolved PD and N–V spectra and the trend of discharge repetition rate, discharge amplitude (maximum, mean, standard deviation) and discharge time interval (maximum, mean, standard deviation) were obtained. The results indicate that: there are two typical stages in the entire process of surface discharge under constant voltage and both discharge characteristics and risk of breakdown of those two stages are different obviously. Furthermore, based on the electro-chemical aging theory and space charge effects, the long-intermittent characteristics of solid insulation discharge are explained.

Partial Discharge Pattern Recognition of Gas-Insulated Switchgear via a Light-Scale Convolutional Neural Network

Partial discharge (PD) is one of the major form expressions of gas-insulated switchgear (GIS) insulation defects. Because PD will accelerate equipment aging, online monitoring and fault diagnosis plays a significant role in ensuring safe and reliable operation of the power system. Owing to feature engineering or vanishing gradients, however, existing pattern recognition methods for GIS PD are complex and inefficient. To improve recognition accuracy, a novel GIS PD pattern recognition method based on a light-scale convolutional neural network (LCNN) without artificial feature engineering is proposed. Firstly, GIS PD data are obtained through experiments and finite-difference time-domain simulations. Secondly, data enhancement is reinforced by a conditional variation auto-encoder. Thirdly, the LCNN structure is applied for GIS PD pattern recognition while the deconvolution neural network is used for model visualization. The recognition accuracy of the LCNN was 98.13%. Compared with traditional machine learning and other deep convolutional neural networks, the proposed method can effectively improve recognition accuracy and shorten calculation time, thus making it much more suitable for the ubiquitous-power Internet of Things and big data.

Through-Process Finite Element Modeling for Warm Flanging Process of Large-Diameter Aluminum Alloy Shell of Gas Insulated (Metal-Enclosed) Switchgear.

The large diameter metal shell component (LDMSC) is an important part of gas insulated (metal-enclosed) switchgear (GIS). The LDMSC with multi branches is filled with gas under certain pressure. The plastic forming process is an efficient approach to manufacturing the high reliability LDMSC. The warm flanging process has been widely used to form LDMSC using aluminum alloy. The forming process is characterized by local heating, and the distribution of temperature is strongly inhomogeneous. Although the wall thickness of the shell is 10 mm to 20 mm, the ratio of outer diameter to thickness is more than 40. These present some difficulties in the flanging process and result in some forming defects. Detailed forming characteristics are hard to obtain by analytical and experimental methods. Thus, the through-process finite element (FE) modeling considering heating, forming, unloading, and cooling is one of the key problems to research the manufacturing process of LDMSC. In this study, the through-process FE modeling of the warm flanging process of LDMSC using aluminum alloy was carried out based on the FORGE. The thermo-mechanical coupled finite element method was adopted in the modeling, and the deformation of the workpiece and the die stress were considered together in the modeling. A full three-dimensional (3D) geometry was modeled due to inhomogeneous distribution in all directions for the temperature field. The simulation data of local flame heating could be transferred seamlessly to the simulations of the deforming process, the unloading process, and the cooling process in the through-process FE model. The model was validated by comparison with geometric shapes and forming defects obtained from the experiment. The developed FE model could describe the inhomogeneous temperature field along circumferential, radial, and axial directions for the formed branch as well as the deformation characteristic and the unloading behavior during the warm flanging process. By using the FE model, the forming defects during the flanging process and their controlling characteristics were explored, the evolution of the temperature field through the whole process was studied, and deformation and springback characteristics were analyzed. The results of this study provide a basis for investigating deformation mechanisms, optimizing processes, and determining parameters in the warm flanging process of a large-diameter aluminum alloy shell component.

Partial Discharge Localization in Insulated Switchgears by Eigenfunction Expansion Method

A partial discharge (PD) is a well-known phenomenon particularly important in medium-voltage (MV) and high-voltage (HV) electric devices, eventually leading to failure events. Hence, PD detection and localization are fundamental in order to monitor their evolution and eventually perform some maintenance. In this paper, a totally new PD localization approach is proposed, which includes a priori information coming directly from the physics of the phenomenon. By processing the a priori information, it is possible to locate the PD sources in small (order of meters) and not homogeneous closed volumes and, at the same time, reduce the complexity of the measurement system and improve its accuracy. Here, the focus is restricted on electrical devices, such as metal-enclosed insulated switchgears (ISs). The proposed approach is based on the measurements of the electromagnetic (EM) radiation due to PDs, picked-up by few probes inside the IS volume. The a priori information concerning the EM wave propagation physics is introduced and dealt with adopting a proper eigenfunction basis defined inside the IS volume.

Influence of moisture on the insulation characteristics of nitrogen

AbstractUsing N2 or dry air to replace SF6 as high-voltage switchgear insulation media is a hot topic in the development of environmental friendly switching equipment. In order to make switchgear equipment with N2 has a much compact structure in space, engineers should fully understand the insulation characteristics of N2. In this paper, the breakdown characteristics of N2 at power frequency and with lightning pulse in the sphere-plate electrodes has been investigated and the effect of humidity on breakdown voltage analyzed. From the test results, it was revealed that the AC and impulse breakdown voltages of N2 were not seriously affected by different moisture content ranging from 0 to 1000 μL/L in N2. And the breakdown voltage was decreased 8~15% with increasing moisture contents from 1500 to 2000 μL/L.

Study on AC withstand characteristic of air gaps in switchgear at low air pressure condition

The bare conductor in switchgear constitutes complicated air gaps, and their AC withstand characteristic will obviously affect switchgear insulation performance. In this paper, AC withstand tests of various types of air gap were carried out. The air gap samples were rod-plane air gap and 4 typical types of air gap from the bus chamber of 40.5 kV metal-enclosed switchgear. The samples were tested in climate chamber where high altitude environment was simulated. And correction of withstand voltage for switchgear air gaps at low air pressure were conducted. Test results indicate that, the withstand characteristic of 4 typical types of air gap in switchgear are different from that of rod-plane air gap. The relationship between withstand voltage Uw and air gap distance d is nonlinear. The influencing characteristic exponent n of air pressure on Uw is related with air gap type. Linearity value m and air pressure index n are independent to some degree. An equation was proposed to express the relationship of Uw with air gap distance d and altitude H, and this equation can be used to calculate the safety distance of air gaps in switchgear under low air pressure situations. The results are significant for the design and selection of switch devices.

Status Review on Gas Insulated Switchgear Partial Discharge Diagnostic Technique for Preventive Maintenance

<p>Gas insulated switchgear (GIS) plays a vital role in high voltage transmission of electrical energy due to its advantages of high reliability and performance, compact in dimensions and outstanding compatibility with the environment. It uses sulphur hexafluoride gas as its insulant and coolant because of its high dielectric strength and excellent arc quenching ability. Gas insulated switchgear in operation suffers the challenge of its insulation decomposition and eventually failure due to the activities of partial discharge that arouses from defects. This failure is catastrophic and it will lead to entire power out stage that will affect all categories of human activities, so there is a need for Gas insulated switchgear condition monitoring and diagnoses in order to carry out preventive maintenance. This paper reviews diagnostic techniques and methods for Gas insulated switchgear insulation degradation caused by partial discharge for the purpose of carrying out preventive maintenance to avert its failure.</p>