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Showing papers in "IEEE Transactions on Dielectrics and Electrical Insulation in 2017"


Journal ArticleDOI
TL;DR: The proposed method significantly improves the accuracy of power transformer fault diagnosis by analyzing the relationship between the gases dissolved in transformer oil and fault types and the Non­code ratios of the gases are determined as the characterizing parameter of the DBN model.
Abstract: Dissolved gas analysis (DGA) of insulating oil can provide an important basis for transformer fault diagnosis. To improve diagnosis accuracy, this paper presents a new transformer fault diagnosis method based on deep belief networks (DBN). By analyzing the relationship between the gases dissolved in transformer oil and fault types, the Non­code ratios of the gases are determined as the characterizing parameter of the DBN model. DBN adopts multi-layer and multi-dimension mapping to extract more detailed differences of fault types. In this process, the diagnosis parameters are pre-trained. A back-propagation algorithm adjusts them with the labels of the samples and optimizes the parameters. To verify the effect of the proposed method, the diagnostic DBN model is constructed and tested using various oil chromatographic datasets collected from the State Grid Corporation of China and previous publications. The performances of the DBN diagnosis model are analyzed by different characterizing parameters, different training datasets and sample datasets. In addition, the influence of discharge and overheating multiple faults on the diagnosis model is studied. The performance of the proposed approach is compared with that derived from support vector machine (SVM), back-propagation neural network (BPNN) and ratio methods respectively. The results show that the proposed method significantly improves the accuracy of power transformer fault diagnosis.

171 citations


Journal ArticleDOI
TL;DR: In this article, the authors evaluated dissolved gas analysis (DGA) interpretation in detecting different faults and the techniques considered as conventional methods of DGA are investigated based on DGA data obtained from oil samples of real transformers.
Abstract: Transformers are the most important equipment in power systems, and their failure can cause serious problems. In order to avoid hazardous operating conditions and reduce outage rates, fault detection in the incipient stage is necessary. Incipient faults cause thermal or/and electrical stresses on the transformer with a major consequence on insulation decomposition. The insulation decomposition causes the evolution of gases which can be dissolved in oil. Dissolved gas analysis (DGA) interpretation is one of the main techniques used for fault diagnosis in oil-immersed transformers. In this paper, DGA interpretation is evaluated in detecting different faults and the techniques considered as conventional methods of DGA are investigated. The evaluation is based on DGA data obtained from oil samples of real transformers.

164 citations


Journal ArticleDOI
Tao Shao1, Feng Liu1, Bin Hai1, Yunfei Ma1, Ruixue Wang1, Chengyan Ren1 
TL;DR: In this article, an atmospheric-pressure dielectric barrier discharge is used to modify the surface of the epoxy material and enhance the dissipation of surface charge to reduce the accumulation of surface charges.
Abstract: In this paper, an atmospheric-pressure dielectric barrier discharge is used to modify the surface of the epoxy material and enhance the dissipation of surface charge to reduce the accumulation of surface charge. In the experiments, atmospheric-pressure air dielectric barrier discharge is driven by a microsecond pulse generator. Surface properties of epoxy before and after the plasma treatment are characterized by water contact angle, surface potential, and surface/volume conductivity measurements. Atomic force microscope and X-ray photoelectron spectroscopy are used to investigate the changes of the morphology and the chemical composition of the epoxy surface. Experimental results indicate that the surface of epoxy is etched by the plasma and the increase of the surface roughness enhances the surface insulation ability. The O radicals in plasma and the carbonyl groups formed on the surface make the surface charge trap shallower, change the epoxy surface composition then increase the surface conductivity and accelerate surface charge dissipation. When the epoxy is treated for an appropriate time, the epoxy surface insulation performance will be enhanced obviously and the surface charge dissipation will be accelerated.

151 citations


Journal ArticleDOI
TL;DR: In this article, the authors reviewed the history and development of polymeric HVDC cables and summarized the key technical problems in extruded HVDc cables and pointed out that two key issues should be solved.
Abstract: Extruded polymeric HVDC cables have drawn great attention in modern power systems. This paper reviews the history and development of the polymeric HVDC cables and summarizes the key technical problems in extruded HVDC cables. It is pointed out that two key issues should be solved. One is the electric field inversion within HVDC cable insulation which is caused by the temperature and electric field dependent DC volume resistivity of the polymeric insulation materials. The other is the space charge behavior under multi-fields coupling, including charge injection, transportation, accumulation and dissipation characteristics. The following aspects need to be particularly concerned in the future: the interaction between temperature, electric field, space charge and DC volume resistivity under multi-fields coupling; mechanisms of nanoparticles doping on enhancing the properties of polymeric insulation material; the long-term operation characteristics of nanodielectrics; collaborative optimal regulation methods and theories on the properties of polymeric insulation material; and recyclable insulation materials for future HVDC cables.

133 citations


Journal ArticleDOI
TL;DR: In this article, the effect of different nanoparticles on tuning the electrical properties of polypropylene (PP) insulation material was investigated, where surface modified MgO, TiO 2, ZnO and Al 2 O 3 nanoparticles with various contents were melt blended with PP and the microstructural morphology, dielectric properties, DC volume resistivity, space charge behavior and DC breakdown strength of the nanocomposites were investigated.
Abstract: Polypropylene (PP) has shown great potential as recyclable HVDC cable insulation material. This paper aims to investigate the effect of different nanoparticles on tuning the electrical properties of PP. Surface modified MgO, TiO 2 , ZnO and Al 2 O 3 nanoparticles with various contents were melt blended with PP. The microstructural morphology, dielectric properties, DC volume resistivity, space charge behavior and DC breakdown strength of the nanocomposites were investigated. It was found that the dielectric permittivity all increases with the increase of nanoparticle content, only the dielectric loss of TiO 2 /PP nanocomposites increases. For MgO and TiO 2 nanocomposites, the DC volume resistivity increases with the increase of nanoparticle content and then decreases, while it continues to increase for Al 2 O 3 nanocomposite. TiO 2 /PP nanocomposite with 5 phr nano-TiO 2 shows lower volume resistivity than PP. Space charge suppression and DC electric breakdown strength show similar variation trend, both increase with the increase of nanoparticle content and then decrease. MgO and TiO 2 nanocomposites show the most obvious space charge suppression and TiO 2 nanocomposites exhibit the highest DC breakdown strength, which is 43% higher than that of pure PP. Considering the electrical properties investigated, the optimal content for MgO, TiO 2 , ZnO and Al 2 O 3 nanoparticles is about 3, 1, 1 and 1 phr, respectively. Among these four kinds of nanoparticles, MgO and TiO2 nanoparticles are more capable than ZnO and Al 2 O 3 nanoparticles to modify the electrical properties of PP and more potential to be used as recyclable HVDC cable insulation material.

121 citations


Journal ArticleDOI
TL;DR: In this paper, a model GIL spacer in 0.1 MPa air under DC voltage was obtained by an advanced measurement method, from which the dominant uniform charging pattern and random charge speckles were separated.
Abstract: Charge accumulation on a solid insulator surface is one of the critical factors for the development of dc gas-insulated equipment since it will lead to the overstress of polymeric insulation due to local field distortion and enhancement. Therefore, it is important to study the charge accumulation phenomenon on spacer surface under dc field. For decades, researchers have made tremendous progress on this subject by measurement and simulation. However, measurement results are quite different by different researchers due to various electrode configurations and experimental conditions. Further, most researchers use potential to represent charge density, which is not rigorous in that many charge density distribution details are hidden behind the potential. As for pure numerical simulation, reports are rather academic and sometimes cannot accord with the real fact. In this paper, attempts are made to characterize the charge accumulation patterns on spacer surface in HVDC gas-insulated system. Surface charge distributions on a model GIL spacer in 0.1 MPa air under DC voltage are obtained by an advanced measurement method, from which the dominant uniform charging pattern and random charge speckles are separated. Mechanism responsible for the dominant uniform charging pattern is discussed with the aid of a simulation model. Results indicate that, in a well-cleaned system, the electric current through the spacer bulk is the principal factor, but gas conduction is not negligible due to some inevitable ion sources. Highly localized pockets of charge are also observed, which are referred to as speckles. They may originate from micro discharges due to tiny metal particles on the spacer surface or microscopic protrusions on the electrodes.

112 citations


Journal ArticleDOI
TL;DR: In this article, the melting and crystallization behavior, crystal structure, supramolecular structure, mechanical properties, space charge distribution and DC breakdown strength of six different polymers were investigated.
Abstract: Thermoplastic materials are highly desirable for power cable insulation application because of their recyclability and ease of processing. They are particularly suitable for high voltage direct current (HVDC) cable insulation because of the absence of byproducts during cable production, which may result in the reduction of undesirable space charge accumulation and the degassing cost. Polypropylene based polymers may have the potential for recyclable thermoplastic cable insulation application because of their high melting temperatures and adjustable mechanical and electrical properties. This work aimed at evaluating the potential of isotactic polypropylenes, propylene-ethylene block copolymers and random copolymers for thermoplastic cable insulation application. We investigated the melting and crystallization behavior, crystal structure, supramolecular structure, mechanical properties, space charge distribution and DC breakdown strength of six different polymers (two isotactic polypropylenes, two block copolymers and two random copolymers). A comprehensive analysis of these parameters indicates that the propylene-ethylene binary random copolymers are more potentially suitable for thermoplastic cable insulation application.

105 citations


Journal ArticleDOI
TL;DR: In this paper, a new strategy for fabrication of polymeric composites combined with low dielectric loss and desirable thermal conductivity was presented, where hyperbranched polyborosilazane (hb-PBSZ) was incorporated into bisphenol A cyanate ester (BADCy) matrix.
Abstract: In this paper, we presented a new strategy for fabrication of polymeric composites combined with low dielectric loss and desirable thermal conductivity. With the incorporation of hyperbranched polyborosilazane (hb-PBSZ) into bisphenol A cyanate ester (BADCy) matrix, the modified hb-PBSZ/BADCy resin with 4 wt% hb-PBSZ possessed a low dielectric constant (a) value of 2.37 and relatively low dielectric loss tangent value of 0.008 at 1MHz. Furthermore, by integrating micrometer boron nitride particles (mBN) into hb-PBSZ/BADCy matrix, the mBN/hb-PBSZ/BADCy composites presented relatively low a of 3.09, desirable thermally conductive coefficient (λ of 0.63 W/(m·K)) and thermal diffusivity (α of 0.42 mm2/s) values. It provides an important perspective for designing dielectric and thermally conductive polymeric composites for electrical packaging and energy storage fields.

93 citations


Journal ArticleDOI
TL;DR: In this article, a new calibration procedure for the UHF method is proposed and discussed in respect of the procedure for IEC 60270 compliant conventional electric method, which is based on the concept of transmitting electromagnetic waves through the transformer tank from one UHF sensor to another.
Abstract: The reliability of electrical energy networks depends on both, the quality and reliability of its electrical equipment, e.g. power transformers. Local failures inside their insulation may lead to breakdowns and hence to high outage and penalty costs. Power transformers can be tested on partial discharge (PD) activity before commissioning and monitored during service in order to prevent these events. In the first part, this contribution presents different types of ultra-high frequency (UHF) sensors for PD measurement. Various applications of UHF sensors and proper sensor installation are discussed. The second part of the contribution is about the necessity of UHF measurement comparability and reproducibility. Therefore, a new calibration procedure for the UHF method is proposed and discussed in respect of the procedure for the IEC 60270 compliant conventional electric method. The characterization of UHF sensors is a key precondition for the UHF calibration process in order to obtain calibration for the full measurement path. Sensor characteristics are described by the antenna factor (AF) which is determined under inside transformer conditions in an oil-filled Gigahertz Transversal Electromagnetic cell (GTEM cell). In addition to the calibration procedure, the performance of the installed sensor has to be determined. The evaluation is based on the concept of transmitting electromagnetic waves through the transformer tank from one UHF sensor to another. This performance check procedure is used in this contribution for the examination of the influence of the sensor's insertion depth into the tank. These results are compared to the reference GTEM cell measurement used for calibration.

86 citations


Journal ArticleDOI
TL;DR: In this article, the heat transfer surface charge accumulation model of operating DC-GIL was developed, including the nonlinear relationship between volume current in gas and electric field, and the space charge was also considered in the model.
Abstract: With this expected future advance of HVDC, the use of gas insulated transmission lines (GIL) for dc application are getting increasingly interesting. For now, the problem of surface charge accumulation on gas-insulator interface is one of the critical factors for the development of DC-GIL. In many previous works, the model of surface charge accumulation on insulator was investigated. However, the quantitative relationship between temperature and surface charge accumulation on insulator was not exactly obtained since the lack of complicated heat transfer progress in the model. In this paper, the heat transfer surface charge accumulation model of operating DC-GIL was developed, including the nonlinear relationship between volume current in gas and electric field. Moreover, the space charge was also considered in the model. Based on the developed model, temperature distributions in DC-GIL insulator under different current are obtained. Afterwards, the temperature impact on space charge density in the insulator, the saturation time of surface charge accumulation, the surface charge on the insulator surface, and the electric field distribution on the insulator were investigated. It was proven that the tangential component of the electric field reaches to 5.3 kV/mm on lower interface and 5.0 kV/mm on upper interface for Ti=378 K. This value increase 17.8% on lower interface and 17.6% on upper interface along with the conductor temperature from 298 K to 378 K. The data can be referred in the insulation design of DC-GIL.

78 citations


Journal ArticleDOI
TL;DR: In this paper, the density normalized effective ionization coefficients and critical breakdown electric field of the Heptafluoro-iso-butyronitrile (Fluoronitriles), and Fluoronitrile-CO2 mixture are investigated using the steady state Townsend (SST) experimental setup, over a range of the DNE from 200-1066 Td (E is the electric field and N the gas density).
Abstract: The density normalized effective ionization coefficients and critical breakdown electric field of the Heptafluoro-iso-butyronitrile (Fluoronitriles), and Fluoronitriles-CO2 mixture are investigated using the steady state Townsend (SST) experimental setup, over a range of the density normalized critical electric field (E/N) from 200–1066 Td (E is the electric field and N the gas density). Breakdown voltage measurements are also performed to plot the Paschen curves for small product values (N×d) (d being the electrode gap), to identify the Paschen minimum, and to validate the density normalized critical electric field (E/N)0 when α=η (α and η are the ionization and attachment coefficients, respectively). The influence of electrode surface roughness is also analyzed.

Journal ArticleDOI
TL;DR: In this article, a transformer physical model is established by taking these complex factors into consideration, and the velocity and propagation factors are set for each node according to its acoustic wave propagation characteristics.
Abstract: Methods to infer the location of partial discharge (PD) in high-power transformers using acoustic emission (AE) data have been extensively studied. The inner complex structure of the transformers is one of the most critical points in localization with AE method. Windings and cores affect acoustic wave propagation by changing the arrival time because of inhomogeneous propagation. A transformer physical model has been established herein by taking these complex factors into consideration. Each node in the model is a potential PD position, and an acoustic wave route comprise a series of nodes. The velocity and propagation factors are set for each node according to its acoustic wave propagation characteristics. A propagation-time estimation algorithm is proposed to calculate the propagation-time. Based on the transformer physical model, a particle-swarm-optimization route-searching (PSORS) algorithm is employed for searching the position of the PD source. By comparing time differences of measured AE signals and the ones estimated by the PSORS algorithm, the velocities and positions of particles are continually adjusted, which can ensure their convergence to the PD source position. Localization experiments were performed in 35 and 110 kV transformers, respectively, to verify the applicability of the proposed algorithm. A protrusion defect is used to trigger PD pulses, and four AE sensors with two different arrangements are employed. The results confirm that the accuracy of proposed localization method is insensitive to the presence of metal structures blocking acoustic wave routes.

Journal ArticleDOI
TL;DR: In this paper, SiC particles were dispersed into EPDM with 0, 10, 30 and 50 wt% respectively to suppress the interface charge accumulation under different stresses, which is attributed to the nonlinear conductivity and more shallow traps of EPDm/SiC composite.
Abstract: Interface charges are easy to accumulate between two different dielectrics with various characteristics, which may cause accelerated degradation of insulation systems. Ethylene-propylene-diene terpolymer (EPDM) is used mainly for HVDC cable joint, which is the most vulnerable part of the cable system because of the interface. Particles with nonlinear conductivity can be doped into the polymer matrix to modify the interface charge behaviors through altering the conductivity under combined stresses. In this paper, silicon carbide (SiC) particles were dispersed into EPDM with 0, 10, 30 and 50 wt% respectively. The space charge behaviors at the interface between LDPE and EPDM filled with SiC particles was measured under 15 and 30 kV/mm. Besides, dielectric constant, dc conduction and trap distribution were introduced to elaborate the suppression mechanism with SiC doping. The SEM results show that the particles are well distributed in the EPDM. The permittivity increases with the fillgrade and the dc conductivity shows an obvious nonlinear trend under various electrical fields. SiC doping can effectively suppress the interface charge accumulation under different stresses. The suppression mechanism is attributed to the nonlinear conductivity and more shallow traps of EPDM/SiC composite. As a consequence, the approximate SiC doped EPDM can availably suppress the interface charge accumulation and offers a possible method for the improvement of cable accessory performance.

Journal ArticleDOI
TL;DR: In this paper, an approach for the estimation of partial discharge (PD) is presented based on the source-filter model of acoustic theory, which extracts an estimation of the excitation source (PD pulse) by isolating it from the acoustic response of the tank-oil system.
Abstract: Partial discharge (PD) localization employing acoustic emission technique is commonly done by estimating the time difference of arrival (TDOA) between signals captured at multiple acoustic sensors placed on the walls of the transformer tank. The localization accuracy of PD sources depends on the accuracy with which the TDOA is estimated. Hence it is important to accurately estimate the TDOA as far as possible. This paper presents a novel approach for the estimation of TDOA which is based on the source-filter model of acoustic theory. The TDOA is estimated by extraction of the excitation source signal from the acoustic signals in the form of an estimation of the PD pulse. The PD pulse serves as the excitation source signal for the acoustic detection system, whereas the acoustic path through the transformer tank and oil constitutes the physical system, which when excited by the PD pulse, gives rise to the acoustic pressure waves. The source-filter model extracts an estimation of the excitation source (PD pulse) by isolating it from the acoustic response of the tank-oil system. The extracted PD pulse information gives a sharp estimate of the instant of appearance of the PD pulse at each sensor. Hence, the TDOA between any two sensors determined from the cross-correlation function between the PD pulse estimates at the respective sensors gives a high estimation accuracy.

Journal ArticleDOI
TL;DR: In this paper, a high noise tolerance principal component analysis (PCA)-based feature extraction was proposed and compared against conventional input features such as statistical and fractal features, which were used to train the classifiers to classify each defect type in the cable joint samples.
Abstract: Cable joints are the weakest point in cross-linked polyethylene (XLPE) cables and are susceptible to insulation failures. Partial discharge (PD) analysis is a vital tool for assessing the insulation quality in cable joints. Although many works have been done on PD pattern classification, it is usually performed in a noise-free environment. Also, works on PD pattern classification are mostly done on lab fabricated insulators, where works on actual cable joint defects are less likely to be found in literature. Therefore, in this work, classifications of cable joint defect types from partial discharge measurement under noisy environment were performed. Five XLPE cable joints with artificially created defects were prepared based on the defects commonly encountered on-site. A high noise tolerance principal component analysis (PCA)-based feature extraction was proposed and compared against conventional input features such as statistical and fractal features. These input features were used to train the classifiers to classify each defect type in the cable joint samples. Classifications were performed using Artificial Neural Networks (ANN) and Support Vector Machine (SVM). It was found that the proposed PCA features displayed the highest noise tolerance with the least performance degradation compared to other input features under noisy environment.

Journal ArticleDOI
TL;DR: In this paper, the electric insulation and current interruption performance of C5F10O perfluoroketone (C5 PFK) was investigated for high voltage applications.
Abstract: C5F10O perfluoroketone (C5 PFK) is a practically non-toxic, synthetic fluid with high dielectric strength and global warming potential below the one of CO2 that is being considered as an alternative to SF6 in certain types of electrical equipment. For high voltage applications, the low vapor pressure of C5 PFK makes it more suitable for use in indoor applications. The electric insulation and current interruption performance were investigated: Under certain conditions, mixtures of C5 PFK, oxygen and carbon dioxide can achieve electric insulation performance similar to that of SF6, while the current interruption performance measured in a model circuit breaker is somewhat below that of SF6.

Journal ArticleDOI
TL;DR: The Support Vector Machine (SVM) and the K-Nearest Neighbor (KNN) algorithms combined to the Duval method may complement theDuval Pentagon 1 diagnosis method.
Abstract: The carried out investigations deal with the application of machine learning algorithms to Duval Pentagon 1 graphical method for the diagnosis of transformer oil. In fact, combined to graphical methods, pattern recognition aims to may complement. For this purpose, we have used the Support Vector Machine (SVM) and the K-Nearest Neighbor (KNN) algorithms combined to the Duval method. The SVM parameters have been optimized with the Particle Swarm Optimization (PSO). Inspired from IEC and IEEE, five classes namely PD, D1, D2, T1&T2, and T3 have been adopted. The combined algorithms were verified using 155 samples from IEC TC 10 and related databases. We found that KNN, SVM may complement the Duval Pentagon 1 diagnosis method.

Journal ArticleDOI
TL;DR: In this article, the effects of nano-filler addition on polypropylene (PP) insulating properties were investigated in five kinds of experiments, namely TEM, DSC, breakdown strengths (BDs), space charge and dielectric measurement.
Abstract: Polypropylene (PP) has special advantages in replacing conventional crosslinked polyethylene (XLPE) to be insulation material of power cable. In order to reveal the effects of nano-filler addition on PP, five kinds of experiments, namely TEM, DSC, breakdown strengths (BDs), space charge and dielectric measurement were investigated to evaluate the insulating properties of PP and its nanocomposites with surface-treated nano-MgO of different concentration. It is revealed that, with the addition of nano-MgO, favorable dispersibility of nano-filler and significant increase of crystallinity of polymer are observed. BDs under dc voltage increase apparently with loading of nano MgO, but when the nano concentration reaches higher than 1 wt%, the BDs have a slight decline compared with 1 wt%. It is clarified that space charge and electric field distortion are well restricted with the addition of nano-MgO, while this effect is not obvious with the nano concentration reaches 6 wt%. Permittivity has trends of increase with the rise of temperature at first and then decrease when the temperature reaches about 333 K, and the addition of nano-filler MgO could also decrease permittivity. When the nano-filler concentration reaches high, dielectric loss increases to a high level. Low nano-filler concentration in MgO/PP shows better electrical insulation properties compared with PP and high nano-filler concentration composites.

Journal ArticleDOI
TL;DR: In this article, sheet-shaped and truncated cone epoxy samples were prepared and were fluorinated in a laboratory stainless vessel using a F2/N2 mixture with 12.5% F2 by volume at 0.1 MPa and 85 °C for 30 min.
Abstract: In order to prove the effectiveness of direct fluorination in improving dc flashover performance of epoxy insulators in SF6 gas and also to provide evidence for the importance of surface conductivity of solid insulators, sheet-shaped and truncated cone epoxy samples were prepared and were fluorinated in a laboratory stainless vessel using a F2/N2 mixture with 12.5% F2 by volume at 0.1 MPa and 85 °C for 30 min. Physicochemical characteristics of the fluorinated surface layer were evaluated by ATR-FTIR and SEM techniques, and the results showed substantial chemical modification of the surface layer, which has a thickness of 0.89 μm and a roughened surface. Further, as expected on the basis of previous studies, measurements of surface electrical properties of the surface fluorinated sample, compared to the unfluorinated one, revealed a four orders of magnitude higher surface conductivity and a much more rapid decay of surface potential after corona charging. Dc flashover tests were performed on the truncated cone samples in SF6 gas at 0.1 MPa with a stepwise increasing voltage before and after the fluorination. The flashover test results showed a definite improvement in dc flashover voltage. For example, the flashover voltage at 63.2% probability or the mean flashover voltage for 2 min duration of the voltage step increased by 13.8% or 13.6% after the fluorination. The performance improvement is mainly attributed to easy leakage and dispersion of the charge deposited on the surface fluorinated sample from the gas phase, due to high conductivity of the fluorinated layer. The flashover test results also showed the influences of the duration of the voltage step on the flashover voltage and on the increase rate of flashover voltage. This means that even the time constant of the fast gas phase charging should be larger than 2 min, and that there should be different influences of the inhomogeneous surface conduction between the virgin sample and the fluorinated sample.

Journal ArticleDOI
TL;DR: In this article, an attempt has been made to separate this current component from de-polarization current through considering charge de-trapping mechanism, which has been applied on several practical transformers.
Abstract: Accumulation of interfacial space charge in oil-paper interface is a critical issue in insulation diagnostics of transformers. This interfacial charge mainly accumulates due to the conductivity difference of oil and paper. Accumulation of interfacial charge leads to localized field enhancement, which further leads to partial discharges and acceleration in the aging of insulation. Therefore, from the point of view of transformer insulation diagnostics, assessment of interfacial charge is very important. However, it is not easy to estimate interfacial space charge behavior from the transformer diagnostics methods currently in use. In case of Polarization-Depolarization Current (PDC) measurement, a well known method for transformer condition monitoring, the effect of interfacial charge is reflected in the non-linearity of current response during polarization and de-polarization. During de-polarization process, a part of the interfacial charge accumulated during polarization period is absorbed by the electrodes producing a current, which is difficult to separate using conventional linear dielectric theory. In this paper, an attempt has been made to separate this current component from de-polarization current through considering charge de-trapping mechanism. Terming this current component as de-trapping current, its relationship with other parameters of transformer insulation is discussed. The developed methodology has been applied on several practical transformers. It was observed that the time constant of de-trapping current is related to the paper conductivity, oil conductivity, dissipation factor and age of the insulation.

Journal ArticleDOI
TL;DR: In this paper, a detailed review on the properties and applications of super-hydrophobic coatings in outdoor high voltage insulation is presented, which can be beneficial to scientists and engineers in evaluating the performance and durability of superhydrophilic coatings.
Abstract: The deposition of ice, snow, pollution or their mixtures on the surface of outdoor insulators may severely affect their performance, resulting in electrical and or mechanical failures. Various preventative methods are used to minimize the problems of ice and pollution build up on the surface of outdoor insulators. In the last few decades, advanced coatings have been developed for better performance of outdoor insulators in contaminated and freezing environments. These advanced coatings offer the advantage of low wettability, high thermal and ultraviolet resistance, self-cleaning, self-healing, low ice adhesion strength and delayed freezing time. It is believed that these benefits will not only increase the reliability of transmission systems but may also reduce the capital cost of transmission infrastructure. This paper presents a detailed review on the properties and applications of superhydrophobic coatings in outdoor high voltage insulation. This review can be beneficial to scientists and engineers in evaluating the performance and durability of superhydrophobic coatings in polluted and freezing conditions. It also highlights the need for standardized tests and procedures for better understanding the behavior of superhydrophobic coatings in different environments and their long-term durability.

Journal ArticleDOI
TL;DR: In this paper, the authors summarized the measurement techniques and the phenomena of space charge behaviors at the interfaces between different insulating materials and indicated that surface states should be included in the numerical simulation of the charge and field distributions.
Abstract: Multi-layer insulations are commonly used in HVDC applications, giving rise to physical and chemical interfaces in the insulation systems. Space charges at the interface between insulators play crucial roles on the electric field distribution of such insulation systems. The issue arises in the design of high voltage direct current (HVDC) insulations. How to understand the behaviors, mechanisms and effects of interface charges on the electric field distribution? In the past two decades, this specific topic has attracted much interest. Much experimental evidence has shown that interface charges may not follow the classic Maxwell-Wagner-Sillar (MWS) theory. In this paper, the measurement techniques and the phenomena of space charge behaviors at the interfaces between different insulating materials are summarized. It is indicated that surface states should be included in the numerical simulation of the charge and field distributions.

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the influence of AC component in HVDC cable system on electrical tree growth and discharge characteristics, and the results showed that the AC component greatly accelerated the developing process of the electrical trees.
Abstract: The growth characteristics of electrical trees under DC and AC voltages are quite different. In order to investigate the influences of AC component in HVDC cable system on the electrical tree properties, the growth and discharge characteristics of electrical trees under AC-DC composite voltages were studied in this paper. The results showed that the AC component greatly accelerated the developing process of the electrical trees. The influences of the positive and negative DC bias voltages on the electrical tree growth properties were quite different. The growth rate under negative DC bias voltage was similar to that under pure AC voltage and pine-branch type electrical trees were more likely to form. In contrast, the growth rate of the electrical tree increased with the increase of the positive DC bias voltage and it was much faster than the negative DC biased one. More branch-like electrical trees would form under positive DC bias voltage. When the AC component decreased, the developing process of the electrical tree was fairly tough and it was easy to form bush-like electrical trees, which were the typical conducive electrical trees with fairly small discharges. Under the positive DC bias voltage, there was a fast re-growth process of electrical tree after the bush tree formed, and the positive DC bias voltage could promote the coming of the re-growth process. However, the detected partial discharge during this process was quite small. The test results indicated that it may pose a great threat to the safety of the cable insulation if there is a large AC component in the HVDC cable system.

Journal ArticleDOI
TL;DR: The paper presents a method using deep learning framework based on convolution neural network, for identification and localization of faults of transformer winding under impulse test, and shows that the proposed method outperforms the existing methods significantly.
Abstract: The paper presents a method using deep learning framework based on convolution neural network (CNN), for identification and localization of faults of transformer winding under impulse test. The results show that the proposed method outperforms the existing methods significantly. The present scheme eliminates the requirement of separate feature extraction and classification algorithms for the analysis of fault current patterns. A part of the proposed network performs feature learning and the other part classifies the features in a supervised manner. The method is computation intensive but capable of achieving very high degree of accuracy; on an average a margin of more than 7% compared to other published literature till date.

Journal ArticleDOI
TL;DR: In this article, the influence of the structure of the nanoparticle coating on the electrical conductivity of LDPE/Al 2 O 3 nanocomposites was analyzed. And the results showed that an appropriate surface coating on nanoparticles allowed uniform particle dispersion up to a filler loading of 10 wt.%, with a maximum reduction in electrical conductivities by a factor of 35.
Abstract: LDPE/metal oxide nanocomposites are promising materials for future high-voltage DC cable insulation. This paper presents data on the influence of the structure of the nanoparticle coating on the electrical conductivity of LDPE/Al 2 O 3 nanocomposites. Al 2 O 3 nanoparticles, 50 nm in size, were coated with a series of silanes with terminal alkyl groups of different lengths (methyl, w-octyl and n-octadecyl groups). The density of the coatings in vacuum was between 200 and 515 kg m−3, indicating substantial porosity in the coating. The dispersion of the nanoparticles in the LDPE matrix was assessed based on statistics for the nearest-neighbor particle distance. The electrical conductivity of the nanocomposites was determined at both 40 and 60 °C. The results show that an appropriate surface coating on the nanoparticles allowed uniform particle dispersion up to a filler loading of 10 wt.%, with a maximum reduction in the electrical conductivity by a factor of 35. The composites based on the most porous octyl-coated nanoparticles showed the greatest reduction in electrical conductivity and the lowest temperature coefficient of electrical conductivity of the composites studied.

Journal ArticleDOI
TL;DR: In this paper, it is shown that partial discharge patterns change through the early stages of tree growth, and consideration of these changes gives insight into the processes of the tree growth and its evolution.
Abstract: Electrical tree growth is a precursor to dielectric breakdown in high voltage polymeric insulation. Partial discharge (PD) has a close relationship with electrical tree propagation and can be both used to understand the aging process, and as a diagnostic tool for asset management. In this paper it is shown that PD patterns change through the early stages of tree growth, and consideration of these changes gives insight into the processes of tree growth. Here, trees have been grown in epoxy resin in needle-plane geometries with 2 mm gaps, at 15 kV peak AC. The PD phase-resolved pattern can be regarded as a combination of the well-known turtle-like and wing-like PD patterns. As a tree extends its length, a wing-like pattern is seen and the maximum discharge magnitude has an almost linear relationship with the maximum length of the growing branch. Comparison of the energy released by discharges and the vaporization energy needed for tree growth supports the proposal that the wing-like pattern corresponds to PDs responsible for growth in length of the trees. Implications for mechanisms for tree growth are considered. Results suggest that asset managers may be able to use partial discharge analysis to distinguish different stages of tree growth, providing a valuable prognostic tool for optimising high voltage plant management and replacement.

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TL;DR: In this paper, the authors examined the importance of polarity and defect size on electrical tree propagation in epoxy resin under constant DC voltages of + 60 kV and −60 kV, but with small initial trees (< 100 μm) incepted under lower AC voltages before the DC tests.
Abstract: Electrical tree propagation is a precursor to dielectric failure in high voltage polymeric insulation. Tree growth has been widely studied under AC conditions, but its behavior under DC is not well understood. The aim of this work was to examine the importance of polarity and initiating defect size on DC tree propagation. Electrical tree propagation in epoxy resin under constant DC voltages of +60 kV and −60 kV was measured in samples with classical needle-plane electrodes, but with small initial trees (< 100 μm) incepted under lower AC voltages before the DC tests. Experimental results showed strong polarity dependence. In either polarity, the length of the initial AC tree had a major influence on the inception of the subsequent DC tree. The effect was attributed to the defect being influential if it is larger than the space charge injection region. As a consequence, there is a critical defect size that will accelerate failure of DC insulation dependent on space charge injection behavior of the polymer/electrode system in question — a critical finding for high voltage asset management.

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TL;DR: In this article, the effect of voltage duty cycle on partial discharge characteristics and endurance of inverter-fed motor insulation was investigated through a large number of tests performed on single-contact crossed enameled wires under bipolar repetitive impulse wave voltages.
Abstract: Dealing with electrical rotating machines fed by voltage converters, understanding the effect of impulsive voltage parameters on partial discharge features is of great importance to select appropriate impulsive voltage to perform partial discharge inception voltage measurements. Similarly, the dependence of insulation endurance on voltage parameters might help to develop qualification tests providing more accurate evaluation of insulation performance. The effect of voltage duty cycle on partial discharge characteristics and endurance of inverter-fed motor insulation were investigated through a large number of tests performed on single-contact crossed enameled wires under bipolar repetitive impulse wave voltages. The partial discharge pattern, magnitude, repetition rate show that short impulsive voltage duration (i.e. small duty cycles), can induce asymmetric PD patterns and reduce the probability of PD inception at the falling flanks of impulsive voltages. Moreover, the endurance tests indicate that the duty cycle of the repetitive square wave voltage can affect the insulation endurance significantly. Repetitive square wave voltages with small duty cycles tend to overestimate endurance. Accordingly, when performing partial discharge inception voltage and endurance tests on insulation of inverter-fed motors, the influence of duty cycle should be carefully considered.

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TL;DR: The back-propagation gradient descent method is used to train the model, to form an intelligent detection model for deteriorated insulator, which has the advantages of high accuracy and robustness, and represents a new method for intelligent detection of deteriorated insulators.
Abstract: Based on the analysis of the principle and structure of a convolutional neural network (CNN) model used for in-depth learning, an intelligent discriminant diagnosis method for porcelain fuselage insulators in transmission lines is proposed. Firstly, the infrared image of a porcelain insulator is extracted, and then Lenet is used to optimize the network structure. Finally, the model of fixed parameters is formed by training. The model has high classification and judgment robustness and offers accuracy under different conditions such as: temperature, humidity, position of deterioration on the insulator, and thermal load, which allows weight-sharing in the CNN model under different environmental conditions. Based on the experimental data from an infrared heating experiment using a porcelain deteriorated insulator, this work uses the back-propagation gradient descent method to train the model, to form an intelligent detection model for deteriorated insulators. This method has the advantages of high accuracy and robustness, and represents a new method for intelligent detection of deteriorated insulators.

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TL;DR: In this paper, the authors presented a method to improve the mechanical properties and breakdown strength of aramid insulation paper by combining molecular dynamics simulation and experimental analysis, the mechanisms for these improvements were studied.
Abstract: This paper presents a method to improve the mechanical properties and breakdown strength of aramid insulation paper. By combining molecular dynamics simulation and experimental analysis, the mechanisms for these improvements were studied. By investigating the relationships between the micro parameters of the models and the nanoparticle content, the optimum nanoparticle content was established to be 1 wt.%. Subsequently, an insulation paper with the same content of nanoparticles as the simulation experiment was prepared in the laboratory and its tensile strength, breaking elongation, power frequency breakdown strength, and other characteristic parameters were tested. The results showed that the properties of the insulation paper modified by nano-SiO2 had greatly improved. Finally, the interface interaction and microscopic mechanism by which the nano-SiO2 improved the properties of the insulation paper were analyzed. On the one hand, a strong interfacial interaction formed between the nanoparticles and the aramid fiber, which allowed them to combine well; on the other hand, the addition of nanoparticles effectively reduced the free volume of the aramid fiber. Therefore, the mechanical properties, thermal stability, and electrical properties of the aramid insulation paper were improved.