Gas Insulated Research Articles

Experimental investigations and optimization of non-electrical parameters during microelectrode fabrication

ABSTRACT Microelectrodes have applications in EDM drilling and milling to fabricate microholes and microchannels. Moving Block Electrical Discharge Turning (MB-EDT) is a technique used to manufacture these microelectrodes. Gaseous dielectrics in EDM are critical due to their environmental friendly characteristics. Process optimization of microelectrode fabrication requires consideration of both electrical and non-electrical factors. This study investigated the impact of non-electrical factors on MRR and surface roughness of fabricated microelectrodes. A statistical model was established successfully for each response. Dielectric pressure significantly influences, contributing 57.78% to MRR and 42.77% to Ra. Using a multi-objective genetic algorithm, optimal parameters were identified for spindle rotation speed at 412 rpm, block linear feed rate at 7.36 mm/sec, and dielectric pressure at 6.4 bar for a maximum MRR of 0.0087 μm3/min and minimal Ra of 0.6138 μm. SEM micrographs illustrate improved surface uniformity at higher process factor levels, underscoring the optimization’s effectiveness in enhancing microelectrode quality.

Multi-source partial discharge pattern recognition in GIS based on Grabcut-MCNN

Partial discharge (PD) surveillance constitutes a pivotal methodology for diagnosing insulation failures in electrical equipment. Enhancing comprehensively the precision of identifying PD anomalies in Gas Insulated Switchgear (GIS) is of paramount significance for ensuring the steady functioning of power grids. This study introduces a novel framework that integrates Phase-Resolved PD Graph Segmentation (PRPD-Grabcut) with a tailored MobileNets-based Convolutional Neural Network (MCNN) to classify GIS-related PD issues. Leveraging image segmentation via PRPD-Grabcut, crucial features are extracted from PRPD diagrams, which then facilitate the construction of the MCNN model. This model employs depth-wise separable convolutions alongside inverted residual architectures to tackle the vanishing gradient dilemma inherent in Deep Convolutional Neural Networks (DCNNs) during GIS PD pattern discernment. Upon the model's subsequent training and validation, empirical evidence illustrates that the PRPD-Grabcut-MCNN hybrid significantly alleviates the computational load and storage requisites of the model, concurrently enhancing the recognition precision and expediting the training process of the neural network. Relative to diverse established lightweight neural network architectures, MCNN manifests superior performance in terms of recognition accuracy, reduced cross-entropy loss, and expedited training duration.

Initial Characteristics of Submillimeter Metal Particles in GIS under Impact Vibration

As a critical component within power systems, Gas Insulated Switchgear (GIS) is notably susceptible to insulation degradation due to submillimeter metal particles, compromising its operational safety and stability. Moreover, impact vibrations induced by circuit breaker operations can dislodge particles that typically adhere to the interior walls, causing them to become airborne and thereby intensifying their movement and discharge activities. To investigate this phenomenon, this study establishes a testing platform where alternating current (AC) voltage is superimposed with impact vibration. A camera system, interfaced with an upper computer, is used to capture the real-time motion behavior of the particles. This study focuses on characterizing the initial movement of submillimeter metal particles of varying sizes under the influence of impact vibration by analyzing critical voltages, such as the initial lift-off voltage, stable jumping voltage, and extinction voltage. Furthermore, the effects of introducing large, centimeter-scale spherical metal and rubber particles on these initial characteristics are examined. The findings provide crucial insights into the initial behavior of submillimeter metal particles in GIS, particularly in relation to circuit breaker operations.

SF6 Gas Humidity Prediction Model Based on Deep Learning

SF6 gas is widely used in Gas Insulated Switchgear(GIS) as an insulating and arc extinguishing medium in electric power industry. However, SF6 gas humidity has a significant impact on the performance and reliability of GIS equipment. The accurate prediction of humidity level is one of the keys to ensure the long-term stable operation of GIS equipment. Traditional humidity prediction methods are often limited by model complexity and data processing ability, which is difficult to meet the actual demand. In this paper, deep learning, as a powerful data-driven approach, shows great potential in gas humidity prediction. An efficient SF6 gas humidity prediction model for GIS equipment is constructed based on deep learning algorithm. The deep learning model can learn complex feature representations from a large number of historical data, and then accurately predict SF6 gas humidity.

Improved Corona Resistance of Epoxy Resin for Gas‐Insulated Equipment in Nitrogen Gas by Direct Fluorination

Direct fluorination has demonstrated efficacy in modulating the surface electrical properties of epoxy insulators and preventing surface charge accumulation. Comparative corona treatments were conducted on both surface fluorinated (modified) epoxy samples and untreated (virgin/original) samples using a modified electrode setup in a nitrogen (N2) atmosphere. The purpose was to evaluate the resistance of the modified epoxy surface layer against corona discharge. The results of ATR‐IR analysis and SEM surface and cross‐sectional imaging indicate that corona treatment did not alter the chemical composition of the fluorinated sample or the thickness of the fluorinated layer. Based on assessments of potential decay and water contact angle measurements, the surface conductivity of the modified sample was decreased by corona treatment. The wettability of fluorinated sample remained unchanged after corona treatment, and no soluble degradation products were produced. Conversely, the surface conductivity of the virgin sample exhibited an increase following corona treatment, accompanied by the formation of soluble degradation products. These results confirm that direct fluorination improves the epoxy insulator's discharge resistance in N2 and provides technical support for enhancing the electrical performance of epoxy insulators in gas insulated equipment. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Development of exhaust gas insulation system for quarry diesel locomotives

This study focuses on developing an innovative device for isolating and managing exhaust gases from diesel locomotive engines, specifically aiming to reduce environmental impact and enhance operational safety. The study used experimental analysis, validated results using Cochrane and Fisher criteria, and conducted empirical data analysis. Study utilized an experimental stand with a 1.9-liter Volkswagen diesel engine, ZIL-130 compressor, custom exhaust gas storage system with tanks, thermometers, pressure gauges, and control valves. The study developed a mathematical model analysing input parameters and system outputs, achieving 95% accuracy, proving its reliability in representing exhaust gas dynamics of TEM2 diesel locomotives.

Impact of X-Ray Irradiation on Discharge Inception in Gas Insulated Switchgear: A Simulation Investigation

Impact of X-Ray Irradiation on Discharge Inception in Gas Insulated Switchgear: A Simulation Investigation

A boiling point prediction method based on machine learning for potential insulating gases

The boiling point is a crucial indicator for assessing the suitability of insulating gases. Its theoretical prediction has consistently garnered significant attention from the scientific community. In this study, a boiling point database composed of hexa-element (C, H, O, N, F, S) for potential insulating gases was constructed. The model of Gradient Boosting Regression with RDKit descriptors (RDKit-GBR) achieved superior predictive ability on the test set with a coefficient of determination of 0.97, a mean absolute error of 17.74 °C, and a root-mean-squared error of 27.83 °C. The SHapley Additive exPlanations analysis showed that the “Ipc” feature in RDKit, which represents the spatial relationship and interaction between pairs of atoms within molecules, plays a central role in predicting the boiling points for insulation gases. Furthermore, the applicability of RDKit-GBR method was further validated across several elemental combinations. Eventually, compared with the previously reported models, the hexa-element model achieves excellent accuracy.

Pure and Ce-Doped MnO2–ZnO Nanocomposites for Colossal Dielectric Energy Storage and Gas Sensing Applications

Pure and Ce-Doped MnO2–ZnO Nanocomposites for Colossal Dielectric Energy Storage and Gas Sensing Applications

Decomposition characteristics and influencing mechanisms of C4F7N/CO2 gas with different metal materials

C4F7N/CO2 gas mixture, as the main new environmentally friendly gas insulation medium, is now being widely used in the ring network switchgear and other gas electrical equipment. In this paper, a test platform was constructed to simulate partial discharge in a gas medium, the decomposition characteristics of the C4F7N/CO2 gas mixture during suspended potential discharge were studied under four different metal electrode materials: stainless steel, purple copper, tungsten copper, and aluminum alloy. The results show that the main decomposition products of the C4F7N/CO2 gas mixture during suspended discharge are CO, CF4, C4F8, C3F8, C3F6, CF3CN, and C2F4 gases, which are independent of the metal material. On the whole, when the metal electrode material is stainless steel, the highest amount of decomposition products are generated from the C4F7N/CO2 gas mixture; when the metal electrode material is aluminum alloy, the amount of decomposition products produced by C4F7N/CO2 gas mixture is the least, and the content difference of some decomposition products between these two metal materials is as high as 70%. The decomposition products of the C4F7N/CO2 gas mixture decreased gradually with the increase in the gas pressure. Finally, the influence mechanism of different metal materials on the decomposition process of the C4F7N/CO2 gas mixture was analyzed from the microscopic perspectives of charge transfer between gas molecules and molecular structural characteristics. In general, the research results can provide technical reference for the design, selection, and optimization of environmental protection gas insulation equipment.

AC breakdown and decomposition products detection characteristics of eco-friendly insulating medium in gas insulated switchgear

Gas Insulated Switchgear (GIS) was a crucial electrical equipment that provides the safety and security of power systems, and finding the eco-friendly alternatives of sulphur hexafluoride (SF6) as insulating medium in GIS has been an urgent demand in past decades. However, few studies reported the specific dielectric strength under various electrodes and partial discharge (PD) decomposition products detection of applying the eco-friendly gas in GIS. In this paper, the insulation properties among C4F7N/CO2 mixtures, dry air and CO2 were explored under the reduced-scale gas-insulated experimental device. The relationship between AC breakdown voltage and gas pressure was gained under the different electrodes and gap distances, and 0.6 MPa 7% C4F7N/93% CO2, 0.9 MPa dry air, 0.9 MPa CO2 all possess the capacity to be the insulating medium in eco-friendly gas insulated switchgear. Furthermore, the partial discharge experimental was also carried out to realize the decomposition products detection of dry air, which designs three common defect types including metal protrusion defects, air gap defects, and metal contamination defects. The decomposition products detection result shows that the contains of CO2, CO, and NO2 linearly increase with the increasing applied voltages and times, and the partial discharge defects are distinguished according to the ratios of c(CO2 + CO)/c(NO2) and c(CO2)/c(CO). The results can provide the basis for the further development of eco-friendly gas insulated switchgear.

Locating Insulation Defects in HV Substations Using HFCT Sensors and AI Diagnostic Tools.

In general, a high voltage (HV) substation can be made up of multiple insulation subsystems: an air insulation subsystem (AIS), gas insulation subsystem (GIS), liquid insulation subsystem (power transformers), and solid insulation subsystem (power cables), all of them with their grounding structures interconnected and linked to the substation earth. Partial discharge (PD) pulses, which are generated in a HV apparatus belonging to a subsystem, travel through the grounding structures of the others. PD analyzers using high-frequency current transformer (HFCT) sensors, which are installed at the connections between the grounding structures, are sensitive to these traveling pulses. In a substation made up of an AIS, several non-critical PD sources can be detected, such as possible corona, air surface, or floating discharges. To perform the correct diagnosis, non-critical PD sources must be separated from critical PD sources related to insulation defects, such as a cavity in a solid dielectric material, mobile particles in SF6, or surface discharges in oil. Powerful diagnostic tools using PD clustering and phase-resolved PD (PRPD) pattern recognition have been developed to check the insulation condition of HV substations. However, a common issue is how to determine the subsystem in which a critical PD source is located when there are several PD sources, and a critical one is near the boundary between two HV subsystems, e.g., a cavity defect located between a cable end and a GIS. The traveling direction of the detected PD is valuable information to determine the subsystem in which the insulation defect is located. However, incorrect diagnostics are usually due to the constraints of PD measuring systems and inadequate PD diagnostic procedures. This paper presents a diagnostic procedure using an appropriate PD analyzer with multiple HFCT sensors to carry out efficient insulation condition diagnoses. This PD procedure has been developed on the basis of laboratory tests, transient signal modeling, and validation tests. The validation tests were carried out in a special test bench developed for the characterization of PD analyzers. To demonstrate the effectiveness of the procedure, a real case is also presented, where satisfactory results are shown.

Density-functional theory study of SnSe/GeSe heterostructure for gaseous sulfur hexafluoride decomposition products sensing

Partial discharge, local overheating and other factors will lead to the decomposition of superior dielectric gas sulfur hexafluoride (SF6) used in gas insulated substations (GIS). Detecting gaseous sulfur hexafluoride (SF6) decomposition products by gas sensors to diagnose early latent insulation failures is a potential approach to guarantee safety and reliability of gas insulated substations (GIS). However, the main difficulties in the detection of SF6 decomposition products lie in sensitivity, operating temperature and sulfur poisoning of the sensor. Metal oxide selenides (MOSs)-based gas sensors suffer from high working temperature, long recovery time, and sulfur poisoning. Two dimensional selenides-based chemiresistor-type gas sensors have been reported to detect certain gases at room temperature. Compared with pristine materials, heterostructures usually have narrower band gaps and higher carrier mobility which promise low power and sensitivity. In this work, a SnSe/GeSe van der Waals heterostructure model is constructed and optimized to investigate the gas sensing properties by density functional theory (DFT) calculations. Compared with the pristine SnSe and the pristine GeSe, the SnSe/GeSe heterostructure exhibits huge adsorption energy and comparatively large charge transfer to the SF6 decomposition gases. The band structure analysis, charge analysis, electron localization function (ELF), and density of states (DOS) analysis suggest that the excellent sensing properties are contributed to the synergistic effect between the SnSe and the GeSe layers: both the layers transfer charge and orbitally interact with gas molecules. Besides, physical adsorption of the SF6 decomposition gases on SnSe/GeSe heterostructure avoids sulfur poisoning of the material, promising the recoverability and repeatability of detection. This study provides theoretical bases for the repeatable detection of SF6 decomposition products by SnSe/GeSe heterostructures and its potential in the design of electronic nose.

Application of sulfur hexafluoride in electrical engineering. Historical past, current state and prospects in future

A pressing issue today is the analysis of the possibilities of using SF6 gas and its possible limitations of use from the point of view of harmful effects on the environment. The article, based on free sources of information, systematizes the historical facts of the development of SF6 gas, the main stages of the formation of the SF6 gas environment as insulation for electrical equipment. Comparative characteristics of electrical strength for various insulating substances are presented. Research has been carried out on modern examples of the use of SF6 gas in medium and high voltage circuit breakers. Examples of the use of SF6 gas and its mixtures as gas insulation for high-voltage power lines are analyzed. It is shown that a promising direction for the development of SF6 gas is its use in gas-insulated power lines. Design features and examples of practical application of high-voltage gas-insulated power lines are presented. The features of using SF6 insulation in electrical equipment of different voltage classes are determined. Current environmental problems associated with the use of SF6 gas are analyzed and possible directions for overcoming them are established. The elements of SF6 gas decomposition products that are toxic and pose the greatest danger are considered. The characteristics of SF6 gas as a greenhouse gas are given and promising ways to reduce its use are shown. It has been established that by using not pure SF6 gas, but gas mixtures based on it, it is possible to significantly reduce the percentage of SF6 gas use. Promising directions for further development of gas insulating medium for electrical equipment without the use of SF6 gas have been established.

Analysis on Discharge Fault of Busbar in 220kV Gas Insulated Switchgear

Abstract In this paper, the disintegration of the 220kV gas insulated switchgear (GIS) basin-type insulator which discharge is occurred during the restoring power supply process of a 220kV transformer substation is introduced. The relay protection action is analyzed and the results of predelivery test are traced. Meanwhile, the electric field of the basin-type insulator is simulated and analyzed. Finally, the cause of discharge fault of basin-type insulator is determined.

A Collaborative Diagnosis Method for Abnormal Discharge of SF6/N2 Mixed Gas Insulation Based on Multi-parameter Sensing

A Collaborative Diagnosis Method for Abnormal Discharge of SF6/N2 Mixed Gas Insulation Based on Multi-parameter Sensing

Theoretical study of the compatibility between environmentally friendly insulation gas CF3SO2F and silver, zinc, and zinc oxide materials in gas-insulated equipment

Exploring the gas-solid compatibility between insulating gas and solids materials used in electrical equipment is of great significance for determining the long-term behavior of insulating gas trifluoromethanesulonyl fluoride (CF3SO2F). The gas-solid compatibility of CF3SO2F and its decomposition products with Ag, Zn, and ZnO common surfaces has been assessed based on first-principles calculations, with SF6 as the control group. CF3SO2F has excellent gas-solid compatibility with the solid surfaces by analyzing the adsorption configurations, adsorption energies, charge transfer, adsorption height, density of states, and ab initio molecular dynamics (AIMD) results. The external electric fields do not affect the excellent compatibility between CF3SO2F and the solid surfaces. Besides, the Ag(111) surface exhibits fine gas-solid compatibility with all decomposition products benefitting from its low surface energy. Originating in the existence of the three-center-four-electron (3c4e) π bond and F atoms with strong electronegativity in SO2F2, SO2F2 has poor compatibility with the Ag(110), (100), and Zn(001) surface. SO2, COF2, and HF gases may accelerate equipment failure due to the strong adsorption strength and poor compatibility with ZnO(100) and (110) surfaces. The results provide the theoretical guidance for the engineering application and long-term performance evaluation of CF3SO2F.

Pressure-Compensated Fiber-Optic Photoacoustic Sensors for Trace SO2 Analysis in Gas Insulation Equipment.

A high-sensitivity fiber-optic photoacoustic sensor with pressure compensation is proposed to analyze the decomposition component SO2 in high-pressure gas insulation equipment. The multiple influence mechanism of pressure on photoacoustic excitation and cantilever detection has been theoretically analyzed and verified. In the high-pressure environment, the excited photoacoustic signal is enhanced, which compensates for the loss of sensitivity of the cantilever. A fiber-optic F-P cantilever is utilized to simultaneously measure static pressure and dynamic photoacoustic wave, and a spectral demodulation method based on white light interference is applied to calculate the optical path difference of the F-P interferometer (FPI). The real-time pressure is judged through the linear relationship between the average optical path difference of FPI and the pressure, which gives the proposed fiber-optic photoacoustic sensor the inherent advantages of being uncharged and resistant to electromagnetic interference. The average optical path difference of FPI is positively related to pressure, with a responsivity of 0.6 μm/atm, which is based on changes in the refractive index of gas. In the range of 1-4 atm, the SO2 sensor has a higher detection sensitivity at high-pressure, which benefits from the pressure compensation effect. With the pressure environment of gas insulation equipment at 4 atm as the application background, the SO2 gas is tested. The detection limit is 20 ppb with an averaging time of 400 s.

Pt3 cluster doped SnS2 monolayer as a gas-sensing material to C4F7N decomposition: A DFT study

Perfluoroisobutyronitrile (C4F7N) is a new type of eco-friendly insulating gas widely used in various gas insulation systems. An effective method for diagnosing the operational status of insulation equipment is to design gas sensor materials to detect C4F7N breakdown products. Using density functional theory, we investigated the sensing ability of the Pt3 cluster doped SnS2 monolayer for common C4F7N decomposition gases (CF4, COF2, C2N2, and CF3CN). We explored the adsorption energy, charge transfer, adsorption distance, and density of states of the Pt3-SnS2 monolayer as a C4F7N breakdown gas sensor. The results indicate that the doping of Pt3 clusters has a relatively small improvement in the adsorption capacity of CF4 and COF2 gases, indicating physical adsorption, but a significant improvement in the adsorption capacity of C2N2 and CF3CN gases, indicating chemical adsorption. This work provides additional potential applications for Pt3 cluster doped SnS2 monolayer gas sensing materials.

Interference characteristics of leaking SF6 on photoacoustic detection of dissolved C2H4 in transformer oil

AbstractSF6 leaked from gas insulation equipment will interfere with the detection of dissolved characteristic gases in transformer oil. In order to determine the impact of SF6 on the detection of dissolved C2H4 gas in oil, a photoacoustic (PA) C2H4 detection system based on the combination of mid‐infrared thermal radiation source and near‐infrared laser was constructed. The excitation light from two bands was incident on a non‐resonant PA cell. The thermal radiation light source and the laser light source were switched to evaluate the interference level of SF6 on the detection of C2H4. The experimental results show that SF6 has significant interference to C2H4 when using a mid‐infrared thermal radiation light source. The interference coefficient is 2014%. The near‐infrared laser based on PA detection method can effectively suppress the interference of SF6 on C2H4. The minimum detection limit of C2H4 reaches 0.6 ppm when the average time is 60 s.