GIS Insulation Research Articles

Weighted Heterogeneous Domain Adaptation for GIS Insulation Fault Diagnosis Based on SF6 Decomposition Products

Weighted Heterogeneous Domain Adaptation for GIS Insulation Fault Diagnosis Based on SF₆ Decomposition Products

DBD Plasma Treatment of Aramid Fiber to Improve Dielectric Property of Fiber-Reinforced Composites for GIS Insulation Rod

DBD Plasma Treatment of Aramid Fiber to Improve Dielectric Property of Fiber-Reinforced Composites for GIS Insulation Rod

A Novel Bilateral Branching Network With Cost-Sensitive Res2Net for Diagnosis GIS Insulation Defects on Imbalanced Data

A Novel Bilateral Branching Network With Cost-Sensitive Res2Net for Diagnosis GIS Insulation Defects on Imbalanced Data

Electrical Tree Growth in Fiber Reinforced Epoxy Composites for GIS Insulation Rod

Electrical Tree Growth in Fiber Reinforced Epoxy Composites for GIS Insulation Rod

Partial Discharge Detection Technology for GIS Insulation Defects under Complex Electromagnetic Environment

Abstract This paper first introduces the main types of GIS insulation defects and explores the discharge mechanism of GIS insulation. Then, the space of discharge features of GIS insulation defects in a complex electromagnetic environment is constructed, and the feature dimensionality reduction is carried out by using principal component analysis. Then, the support vector machine algorithm is explored and optimized with the immune algorithm to identify and detect the local features of insulation defects. Finally, the local discharge characteristics of GIS insulation defects are investigated through simulation experiments, and the discharge results are analyzed. The results show that the average peak-to-peak value is around 31mV and the power distribution band is 133~168MHZ for the spiky insulation defects, the average peak-to-peak value is around 19.8mV and the power distribution band is around 202MHZ for the metallic particles insulation, and the peak value of the air gap is less than 8mV and more than 48mV for some, and the power distribution band is 98MHZ~146MHZ. The localized discharge characteristics of the defects of the GIS insulation parts are identified and detected by the immune optimization of the support vector machine algorithm. The overall recognition rate of immunodeficient partial discharges of insulating parts is around 0.90. This study is able to detect the type of partial discharges in GIS insulating parts well.

A Numerical Study on the Decomposition and Diffusion Characteristics of SF6 in Gas-Insulated Switchgear with Consideration of the Temperature Rising Effect

The optimized concentration of SF6 gas is the key to maintaining a good insulation performance by GIS equipment. The precise measurements of the SF6 concentration and decomposition byproducts could be used to indicate the remaining GIS insulation level during long-term operations. In this paper, a finite-element simulation model was created to investigate the SF6 gas decomposition and diffusion dynamics. A theoretical analysis and simulation of the overheating fault, i.e., the contact between the GIS disconnect switches, were carried out, followed by an estimation of the SF6 decomposition and diffusion characteristics caused by the local heating faults, based on the calculated flow velocity field and temperature field.

Deep Learning in High Voltage Engineering: A Literature Review

Condition monitoring of high voltage apparatus is of much importance for the maintenance of electric power systems. Whether it is detecting faults or partial discharges that take place in high voltage equipment, or detecting contamination and degradation of outdoor insulators, deep learning which is a branch of machine learning has been extensively investigated. Instead of using hand-crafted manual features as an input for the traditional machine learning algorithms, deep learning algorithms use raw data as the input where the feature extraction stage is integrated in the learning stage, resulting in a more automated process. This is the main advantage of using deep learning instead of traditional machine learning techniques. This paper presents a review of the recent literature on the application of deep learning techniques in monitoring high voltage apparatus such as GIS, transformers, cables, rotating machines, and outdoor insulators.

Nonlinear Materials Applied in HVDC Gas Insulated Equipment: From Fundamentals to Applications

The electric field distortion along the gas-solid interface on insulators in GIS or GIL greatly threatens their long-term insulation performance. In recent years, with the developments of field grading materials, their application on GIS/GIL insulators has been considered as an effective approach to suppressing the field distortion and enhancing the insulation property. Many reviews about field grading materials had been published. However, these articles rarely focus on the nonlinear materials and their unique characteristics when used in gas insulated equipment. Compared with traditional applications, such as cable accessories, generator coils, and motor stator bars, nonlinear materials in GIS/GILs are mainly used for grading the surface electric field and avoiding unwanted charge accumulations. Hence, there are two characteristics of the material that need to be paid special attention to-the surface insulation performances and the charge release functions-which are not so critical in previous applications. In this paper, first, types and principles of several commonly used nonlinear grading materials are summarized briefly. Then, the existing application cases of nonlinear materials in gas insulation equipment are sequentially introduced from the optimization ideas, material selection, manufacturing process, and using effects. Finally, the problems encountered in the application of field grading materials in practice are discussed. Suggestions for the follow-up studies are given in order to guide the application of nonlinear materials in GIS/GIL insulators.

GIS vibration test method and characteristic signal recognition

Based on the characteristics of GIS insulation and mechanical fault types and practical measurement experience, two typical vibration measurement methods, direct measurement method and natural frequency measurement method, are proposed in this paper. Then, based on the real data of experiment and field measurement, the vibration signals of typical insulation fault and mechanical fault such as spike discharge and end cover looseness are compared, analyzed and summarized, and their respective data characteristics are extracted, which can provide the basis for the determination of GIS vibration fault types.

Research on Partial Discharge State Detection in GIS Based on Internet of Things Technology

With the continuous development of the Internet of Things technology, the Internet of Things technology can be used in many aspects of the smart grid. Apply advanced Internet of Things technologies in substation GIS, including sensing technology, network communication technology, intelligent decision-making technology, automatic control technology, and energy and power technology, etc., and combine them closely to form a coordinated organic system. At present, partial discharge is the main cause of equipment insulation deterioration in substations. Partial discharge detection and evaluation has become an important means of monitoring insulation conditions. The monitoring of GIS partial discharge conditions in substations can help find insulation defects in GIS in time, avoid insulation failures, and improve the safe operation of GIS. It is possible to achieve GIS insulation condition maintenance, reduce power outage time and save maintenance costs. The effective application of the Internet of Things technology in the GIS partial discharge state detection system of intelligent substations can effectively improve the construction of modern intelligent substations in China.

An Alternative Method for GIS Insulation Performance Evaluation

The continuous improvement of system capacity and voltage level is somewhat accompanied by insulation fault as one of the main faults of GIS device. In this paper, an alternative method for identifying the GIS insulation performance based on fuzzy evidence theory is proposed by way of judging the four main features of GIS insulation level. Firstly, the fuzzy statistic test was used to obtain the normalized values of the four feature quantities of GIS insulation level. Four methods were used to calculate their respective expectations and deviations. The membership degree value was determined by the membership function, and the difference between the membership degrees was also considered. The degree of fusion was used to determine the weight of each feature quantity, so that the membership degree of the same kind of feature information fusion was obtained. Finally, the merged membership degree was transformed into the basic trust distribution function. The evidence theory then took the job to realize the pairwise fusion of the trust distribution functions between different feature quantities. The experimental results showed that this alternative way was proven to make effective judgment on the GIS insulation performance.

Application of Improved BPNN Algorithm in GIS Insulation Defect Type Identification

In this paper, a new BP neural network has been built with GA algorithm, which possesses high effectivity, parallel processing ability and global search feature, in order to overcome the original shortcomings such as the low convergence rate and the confusion of local minimum points. Ten parameters of partial discharge characteristics are obtained as input of BPNN to identify four typical insulation defect physical models designed in this paper for the purpose of measuring the recognition accuracy of the improved BPNN. Experiments show that the improved BPNN has a better performance of convergence speed and recognition accuracy than that of adaptive momentum BP neural network.

Comprehensive Evaluation and Application of GIS Insulation Condition Part 1: Selection and Optimization of Insulation Condition Comprehensive Evaluation Index Based on Multi-Source Information Fusion

Comprehensive Evaluation and Application of GIS Insulation Condition Part 1: Selection and Optimization of Insulation Condition Comprehensive Evaluation Index Based on Multi-Source Information Fusion

Research on the detecting effectiveness of on-site lightning impulse test for GIS equipment with insulation defects

On-site lightning impulse (LI) test waveform, restricted by the large load capacitance and impulse generator's inherent inductance, has a long wavefront time Tf compared with standard LI, called non-standard LI. The non-standard LI test has been carried out in the field. But its insulation defect detecting effectiveness is not clear. In this paper, a generating system of impulses with different waveform parameters, including double-exponential impulses with different wavefront times in the range of 0.08 ∼ 23.5 μs and an oscillating LI with wavefront time around 10 μs, was established. The insulation characteristics of SF6 gas gap with highly inhomogeneous electric field under impulses with different waveform parameters were investigated. Experimental results show that the insulation defects detecting effectiveness of oscillating LI with long Tf around 10 μs is lower than that of standard LI. Tf plays an important role in the insulation defects detection. With Tf increases, the 50% breakdown voltages for rod-plane gaps have an increased trend. The V-t curve presents a U-shape. Prospective voltage is introduced to evaluate the insulation defects detecting effectiveness. The prospective voltage-time characteristics confirm the conclusion that with the increase of impulse voltage Tf, the detection effectiveness for GIS insulation is reduced. The gap distance has influence on the shape of V-t curve. With distance increase, the 50% breakdown voltage of the gap is more sensitive to the wavefront time Tf and voltage rise rate dU/dt. Corona stabilization effect is not just in relationship with the rise rate of impulse, but also with electrode structure and gas pressure. The critical dU/dt for corona stabilization is calculated for different rod-plane gaps.

Study on insulation characteristics of GIS under combined voltage of DC and lightning impulse

Operating experience shows that residual DC voltage remains in GIS bus bar for a long time after opening of disconnectors. This DC voltage will not only cause accumulation of charges and contaminants on the insulator surface, but will also easily lead to motion of free metallic particles in SF6 gas gap, weakening the insulation ability of GIS. At the time of disconnectors reclosing, impulse voltage could be generated in the bus bar and superimpose on the pre-existing DC voltage. As a result, GIS will be under combined voltage of DC and impulse. This paper experimentally studies the insulation characteristics of GIS under combined voltage of DC and lightning impulse. It is found that, for non-contaminated insulators, when DC and LI voltage are of the same polarity, flashover voltage under combined voltage is nearly the same as the flashover voltage under LI alone. However, when they are of the opposite polarity, flashover voltage decreases with increasing DC voltage. In cases there are metallic particle or powder around insulator, pre-stressed DC voltage will cause adhesion of contaminants on the insulator surface and lead to decrease of flashover voltage. Specially, for the particle-contaminated insulator, it is found that the surface charge accumulation caused by DC voltage will have big influence on the flashover voltage, and the most critical condition is when DC and LI voltage are of the opposite polarity. In addition, the breakdown characteristics of SF6 gas gap with free metallic particle are investigated. It is found that under pre-stressed DC voltage, particle will do standing motion or bouncing motion. And breakdown voltage becomes lowest when particle is doing standing motion. The results of the experiments show that residual DC voltage in GIS could deteriorate its insulation ability and the combined voltage of DC and impulse is found to be a critical condition for GIS insulation. Moreover, the combined voltage is shown to be more sensitive to detect some insulation defects in GIS than applying impulse voltage alone, especially for free metallic particles, which are commonly found in GIS but up to now no effective detection method is proposed. Therefore combined voltage of DC and impulse could be considered to serve as a supplement of field test for GIS.

에폭시 알루미나 멀티-콤포지트의 기계적 특성연구

In order to develop an electrical insulation material for gas GIS (insulation switch gear) spacer, 4 types of epoxy/micro-alumina (40, 50, 60, 70 wt%) composites and 9 types of epoxy/nano-alumina (1, 3, 5 g)/micro-alumina (40, 50, 60, 70 wt%) composites were prepared and tensile test was carried out. In here, nano-alumina was previously surface-treated with GDE (glycerol diglycidyl ether). As micro-alumina and GDE-treated nano-alumina contents increased, tensile strength increased and the highest value was shown in the system with 3 g GDE-treated nano-alumina.

Partial discharge occurrence induced by crack defect on GIS insulator operated at 1100 kV

It was observed that partial discharges were not detected from GIS insulators with the crack defects operated at 1100 kV in the UHV substation in China. The question is that whether crack defects can induce partial discharge at the operated voltage. In order to obtain the relationships between PD occurrence and crack configuration on GIS insulator operated at 1100 kV, the electric field strengths in the crack, changed with crack length, crack depth, crack direction, crack position, were simulated on a 1100 kV GIS insulator at operation voltage. The simulated results indicated that the field strength in the cracks, which located on the surface of the insulator or paralleled to the electric field direction, were close to that in the insulator around the crack, and the crack cannot induce partial discharge. However, the field strength in the cracks, which located in the deep position of insulator and in perpendicular to the electric field direction, was much higher than that in the insulator around the crack. For example, in the case of the crack located close to high voltage conductor, field strength in deep crack perpendicular to electric field direction could be 5.6 times of the field strength in the insulator around the crack, and it close to the field criteria of gas discharge, leading partial discharge occurred at operation voltage. The simulated results were verified by the experiment conducted on the insulators with cracks. The experimental results indicated that the crack could produce partial discharge, only when it is located in deep insulator material and in perpendicular to the electric field direction, and close to high voltage conductor.

Development of GIS PD Location System Based on LabVIEW

On-line detecting partial discharge inside GIS and locating the source of partial discharge spatially can discover the premonition of GIS insulation defects. This article introduces a system for partial discharge on-line detection and source locating, which is based on the hardware consisting essentially of ultrasonic sensors, prepositive signal amplifiers, a TDS3034C oscilloscope and a laptop. The system is a virtual instrument based on LabVIEW platform, and it can sample the ultrasonic signals generated by partial discharge in real time, and provide a friendly human-computer interaction interface. This article deeply discussed the partial discharge signal acquisition, signal de-noising, multi-way signal delay calculation and algorithm based on the time lag. The result implies that the system can validly detect and locate partial discharge, and spatially demonstrate the coordinate of the source of partial discharge through human-computer interaction interface.

A Dimension Reduction Method and its Application in GIS Partial Discharge Pattern Recognition Research

GIS partial discharge pattern recognition is an important part of its state evaluation, authors have set up 252kV GIS partial discharge detection simulation experiment platform based on UHF detection method, and designed four kinds of typical partial discharge models in laboratory, then established corresponding UHF signal mapping database through the experimental method, and also extracted the original feature parameters; because the original characteristic dimension is high, which is bad for pattern recognition, based on this, the article uses a species mean kernel principal component analysis method, it mapped the partial discharge original data samples to high-dimensional feature space, at first, it calculate all kinds of class mean vector data, and then do principal component analysis based on class mean vector space, build the class average kernel matrix, at last, the class kernel mean principal component analysis algorithm is established. Results show that characteristic of this method contained all the information of the original data, and dimension is less than GIS insulation defect category numbers, and it can realize data dimension reduction without information loss, which improve the pattern recognition rate.

Pulsed X-ray induced partial discharge diagnostics for routine testing of solid GIS insulators

Detection of small (<; 2mm) voids in solid dielectric high voltage insulators using partial discharge (PD) measurement demands not only a sufficiently high electric field but also the availability of a start electron for the PD to initiate. The latter problem leads to long waiting times for void PD to initiate, far exceeding typical IEC test intervals (typically 60 seconds), thus making 100 % pre-screening economically infeasible. However, by using radiation to ionize the gas within the void and create start electrons, the test interval can be reduced to 60 seconds without risking small voids being missed. Using this method, known as Pulsed Xray Induced Partial Discharge (PXIPD), a test stand for routine testing of insulators up to 420 kV has been developed and put into commercial operation, with more than 20,000 GIS insulators being tested to date. Trials using insulators with known defects prove the effectiveness and reliability of the system to find voids- with the result that failures in factory tests due to voids were reduced by over 60 % compared to before. The short test cycle time plus knowing which insulators actually contain voids has led to more efficient GIS testing and immediate feedback for the insulator production process.