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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Abstract: Ultra-high-frequency (UHF) sensing technique has been introduced to detect and localize partial discharge (PD) sources in air-insulated substation (AIS). This paper presents a probability-based algorithm to localize multiple PD sources which may occur simultaneously in different power equipment. Assuming that the time difference of arrival (TDOA) between all pairs of antennas in a array are normally distributed, the probability density function (PDF) of PD source coordinates can be obtained by substituting the linearized form of time difference equations into PDFs of TDOAs. When large number of PD signals are recorded, the joint PDF (JPDF) can be calculated from the product of PDF of each TDOA. Then the PD coordinates to be solved are regarded as with highest probability, and can be solved by taking the derivative of JPDF. In the case of multiple PD sources, mixed UHF signals are separated by clustering the TDOA vectors with K Means clustering method. PD experiments are performed to test the presented algorithm, and the localization accuracy of proposed algorithm is compared with other typical methods such as Newton-Raphson, Particle Swarm Optimization and plane intersection method. The results indicate that the probability-based localization algorithm reasonably integrates the TDOAs of continuous signal sequence, which can effectively reduce the influence of TDOA estimation errors and improve the localization accuracy.

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.

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.

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.

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.

Abstract: High temperature vulcanized (HTV) silicone rubber (SiR) is widely used as HVDC cable accessory insulation considering its outstanding electrical properties along with elasticity and thermal resistance. However surface charge caused by corona would accumulate on SiR surface and distort the local field which in consequence led to accessory premature discharge and insulation failure. This paper focused on the behavior of surface charge of SiR composites and managed to modify it by incorporating silicon carbide (SiC) particles into SiR matrix. The content of SiC varied from 0 to 100 % and its effects on the field-dependent conductivity and surface charge behaviors were discussed. The outcomes of experiments showed that the SiR/SiC composites performed a nonlinear conductivity as a function of electric field when the content of SiC exceeded 30 %. It was also noticed that this field-dependent conductivity became more obvious when the content of SiC increased. Meanwhile, the decay rate of surface charge was observed to rise with the increase of SiC content and voltage. It was confirmed that the SiR/SiC composites could accelerate the decay of surface charge and increase the dc conductivity under high voltage, resulting from the modification of the trap level distribution.

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.

Abstract: An important and essential diagnostic tool for insulation systems in condition monitoring is partial discharge (PD) measurement. Through PD measurement, the results may be used for insulation condition assessment. However, the modelling of PD is important because it is helpful in attaining a better understanding of PD phenomenon. The physical mechanisms and critical parameters influencing PD events under various conditions of defects and stresses can be identified. The relationship between the insulation design parameters, test conditions and defect characteristics with PD activities can also be developed. There have been many researches that reported on simulation of PD events in a void in insulation material. PD models can be categorized in three models, they are the induced charge concept model, three-capacitance model and the finite element method models. Each model has its own strengths and limitations in certain aspects. Therefore, in this paper, comparative studies and simulations for various PD models that have been developed to date are reported and discussed. The disadvantages and advantages of every model are presented in details. The results from the simulation using those models were compared with the measurement data to observe their performance in terms of physical parameters values. From comparative studies between each model, the most suitable PD model can be chosen to simulate PD events depending on the requirement selected by the users.

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.

Abstract: A series of nanoparticles was prepared by functionalizing a commercial nanosilica with alkylsilanes of varying alkyl tail length, from propyl to octadecyl. By using a constant molar concentration of silane, the density of alkyl groups attached to each system should be comparable. The effect of chain length on the structure of the resulting nanosilica/polyethylene nanocomposites was examined and comparison with an unfilled reference system revealed that, other than through a weak nucleating effect, the inclusion of the nanosilica does not affect the matrix structure. Since water interacts strongly with applied electric fields, water was used as a dielectric probe in conjunction with dielectric spectroscopy to examine the effect of the nanofiller and its surface chemistry on the system. Sets of samples were prepared through equilibrating under ambient conditions, vacuum drying and water immersion. While the water content of the unfilled polymer was not greatly affected, the water content of the nanocomposites varied over a wide range as a result of water accumulation, in a range of states, at nanoparticle interfaces. The effect of water content on breakdown behavior was also explored and, in the unfilled polymer, the breakdown strength was found to depend little on exposure to water (∼13% reduction). In all the nanocomposites, the increased propensity for these systems to absorb water meant that the breakdown strength was dramatically affected (>66% reduction).

Abstract: Space charges are likely to accumulate at the interface between insulation materials with different properties, which may lead to accelerated degradation of insulation systems. Cable accessories made of ethylene-propylene-diene terpolymer (EPDM) are considered to be the weakest part of HVDC cable system due to the existence of the interface between cable insulation and itself. Direct-fluorination can be applied to adjust the electrical properties of polymer insulation. Therefore, this paper intends to investigate the effects of direct-fluorination on the interface charge distribution between LDPE and EPDM composite insulation. The EPDM samples were fluorinated for 0, 15, 30 and 60 min, and LDPE for 0 and 30 min, respectively. The interface charge distribution were measured under 20 kV/mm. Obtained results show that the polarity of interface charge is the same with the voltage applied on EPDM sample, which can be verified by the Maxwell-Wagner-Sillars (MWS) theory. The fluorination for 30 min effectively suppresses the interface charge accumulation between LDPE and EPDM. However, excessive fluorination leads to significant accumulation of interface charge. Though fluorination of both dielectrics has the same effect with the single fluorinated EPDM on interface charge behaviors, more hetero-charges injection in the vicinity of cathode. The interface charge accumulation and dissipation process depends on not only the time constant but the surface state controlled by the fluorination time. As a consequence, the approximate direct fluorination can effectively suppress the interface charge accumulation of cable accessories and will make a potential application for the dc cable accessories.

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.