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Polymeric dielectrics exhibit remarkable dielectric characteristics and wide applicability, rendering them extensively employed within the domain of electrical insulation. Nevertheless, the electrical strength has always been a bottleneck, preventing its further utilization. Nanocomposite materials can effectively improve insulation strength, but uniform doping of nanofillers in engineering applications is a challenge. Consequently, a nanocomposite interfacial coating was meticulously designed to interpose between the electrode and the polymer, which can significantly improve DC breakdown performance. Subsequently, the effects of filler concentration and coating duration on DC breakdown performance, high field conductivity, and trap distribution characteristics were analyzed. The results indicate that the composite coating introduces deep traps between the electrode-polymer interface, which enhances the carrier confinement, resulting in reduced conductivity and enhanced DC breakdown strength. The incorporation of a composite coating at the interface between the electrode and polymer presents novel avenues for enhancing the dielectric insulation of polymers. [ABSTRACT FROM AUTHOR]

In high-voltage power equipment, insulation defects are probably generated during the production, assembly, and operation processes, which degrade the insulation materials and even cause failure under electrical stresses. As a result, various detection and diagnosis methods for insulation status have been developed to discover potential defects in equipment, but extra testing devices are usually required. Insulation materials with special stimulus–response performance, as an example, luminescence under the stimulation of intensified electric field or temperature induced by insulation defects, can be developed to realize self-detection and diagnosis of these defects. In this article, a self-diagnosis composite coating was prepared by filling electroluminescence zinc sulfide (ZnS) fillers into polydimethylsiloxane (PDMS). Two kinds of typical electrode configurations, namely, rod plane and needle plane, were processed to examine the luminescence characteristics of composite coating. The influence of the composite coating on flashover characteristics was also investigated. Experimental results indicated that ZnS composite coating exhibits obvious luminescence under relatively low voltage, and its luminance increases with electric field and ZnS content, which can effectively realize the self-detection and diagnosis function. Moreover, the composite coating can effectively improve the ac/dc surface flashover voltage. The approach presented herein provides a new insight for self-diagnosis of defects in power equipment. [ABSTRACT FROM AUTHOR]

In this work, a phase-field model is presented to characterize the breakdown properties of polymers under alternating voltage. The breakdown status is described with a spatially and time dependent continuous variable, and the evolution of damage phase is driven by the electrostatic and thermal energy in the system. The relationship between breakdown strength and material properties such as permittivity and dielectric loss can be represented with the phase-field model. For thermoplastic polyolefin with low permittivity and dielectric loss, the electric breakdown is probably the dominant mechanism at room temperature. For other polymers, the breakdown characteristics may be dominated by the electrothermal mechanism. The dielectric loss of polymers increases with temperature, which intensifies the thermal energy and further reduces the breakdown strength. Dielectric loss of polymers with high glass transition temperature increases slowly, and they can keep high breakdown strength at high temperatures. [ABSTRACT FROM AUTHOR]

Electrical treeing is a main cause of long term degradation of polymeric insulation and inorganic nanofillers have been added to improve the treeing resistance of polymers. In this work, a phase field model for the propagation of electrical tree in nanocomposites is presented, in which the damage status of insulation is described with a spatially and time dependent continuous variable. The evolution of damage phase is described with a modified Allen-Cahn equation, which is driven by the free energies originated from the phase separation, interface and electric field. The electric field distribution during growth of electrical tree is obtained by solving the iterative form of Poisson's equation with the spectral iterative perturbation method. Then the phase field model is applied to investigate the influence of nanofillers shape and distribution on propagation process of electrical tree. The results indicate that the phase field model can reproduce the dendritic shape of electrical tree, and the parallel nanosheet presents superior performance in hindering electrical tree than nanoparticle and random nanosheet. [ABSTRACT FROM AUTHOR]

In this work, the thermal pyrolysis process and produced chemical defects of crystalline polyethylene, taking the effects of oxygen into account, are explored by molecular dynamics simulation based on ReaxFF force field. The trap energies and sites of various types of chemical defects are calculated by density function theory (DFT), in which hybrid functional XC HSE06 is adopted. The results indicate that double bond C=C, conjugate double bond C=C-C=C, C=C=C and carbonyl C=O are the main products during thermal aging, and these defects are easier to formed at the breaking points of carbon backbone, which is different from the geometries generally used in the previous DFT computations. For electrons, chemical defects C=O and C-C=C-C at breaking points (BP) produce relative deep traps 1.810 and 1.054 eV, and C=C at BP shows shallower traps with energy of 0.445 eV. For holes, C=C-C=C at BP and C=C in the backbone generate deep traps 1.614 and 1.119 eV, and C=C at BP presents shallower traps with energy of 0.689 eV. [ABSTRACT FROM AUTHOR]

Partial discharge (PD)‐based diagnosis is extensively employed in condition assessment of electrical equipment. In the case of multiple PD sources, discrimination of mixed signals is significant for reliable PD interpretation. To improve the separation performance of three or more PD sources, a multi‐step discrimination method is proposed. The cumulative energy functions are exploited to characterise wave shapes of PD signals, and width and sharpness features are extracted and classified to separate mixed patterns. With the objective of maximising a novel evaluation parameter of separation capability, the oblique line and length of structure element are optimised in the feature extraction stage. For the multi‐step discrimination method, the feature extraction and clustering procedures are repeatedly applied to the whole dataset, sub‐classes, sub‐sub‐classes etc., until no more clusters are generated. To evaluate the separation performance of the proposed algorithm, a mathematical model for PD pulse is proposed, which is the multiplication of Heidler enveloping function and an oscillating function whose frequency spectrum confirms Gaussian distribution. In the end, the multi‐step discrimination method is tested with PD current pulses and ultra‐high‐frequency signals of three artificial defects in transformer and gas‐insulated system, and the results prove the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this study, a novel ultra‐high frequency (UHF) sensor using an inner grading electrode inside an insulting spacer is employed to detect gas‐insulated switchgear (GIS) partial discharge (PD[AQ ID=Q1]). The simulation of the waveguide modes of the 252 kV GIS and the frequency response characteristics of this UHF sensor are performed by using the finite difference time domain (FDTD) method. Three kinds of typical defects are employed to investigate the PD detection characteristics of this UHF sensor. It is shown that the resonance frequencies of this sensor are extremely abundant below 3 GHz, and the major resonance frequencies around 0.5–1.2 and 2.2–3 GHz. The phase‐resolved PD (PRPD) images accumulated by using this UHF sensor present the typical PRPD images of defects. The main frequency spectrum of the metal protrusion on a high‐voltage conductor and floating potential defects are distributed below 1.5 GHz, which is consistent with waveguide mode simulation. A resonance frequency of a grading electrode UHF sensor appears at about 115 MHz, which is close to the simulation value of a resonance frequency at 140 MHz. The PD detection sensitivity of this sensor is much higher than that of an external sensor; however, it is a little lower than that of an internal sensor. [ABSTRACT FROM AUTHOR]

Ultra-high-frequency (UHF) antenna array system is applied to detect and locate partial discharge (PD) sources in air-insulated substation (AIS). Time-difference localization algorithm is generally adopted in such system in which the antenna array is of large scale. In this paper, the phased array theory from radar field is introduced to estimate the direction-of-arrival (DOA) of PD source to reduce the array size. The DOA estimation results are calculated by two-sided correlation transformation (TCT) focusing algorithm and multiple signal classification (MUSIC) algorithm. Based on that, the optimum arrangement of antenna array is investigated considering both high directional accuracy and small array size. The DOA estimation performances of three array geometries namely uniform linear array (ULA), uniform circular array (UCA) and uniform Y-shaped array are compared through Cramer-Rao lower bound (CRLB), numerical simulation and experimental testing. Moreover, the number of elements and element spacing are optimized. The results indicate that 4-elements UCA with 0.2m element spacing is the optimum array arrangement for PD location in AIS. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) is the symptom of insulation breakdown in power equipment. The high rising steepness of PD current radiates electromagnetic waves which can be coupled with antenna. In this study, an antenna array is applied to PD detection and localisation in air‐insulated substations, in which the locations of PD sources are found with time difference of arrival localisation algorithm. The influences of antenna deployment including the size, aspect ratio and shape of antenna array on localisation accuracy are systematically investigated. Three approaches including Cramér–Rao lower bound, numerical simulation of root of mean square error and experiments are adopted to evaluate the localisation accuracy. Three kinds of antenna arrays with diamond, rectangle and Y shapes are designed for locating the coordinates of PD sources. Their localisation performances are compared by these evaluation approaches, and the optimum antenna configurations for coordinate estimation are derived. The results indicate that the optimum array is dependent on aspect ratio of array size. If the aspect ratio is higher than 0.5, the rectangle array gives minimum localisation error and wide bearing ranges with low error. For array with aspect ratio smaller than 0.25, the diamond array is optimum among the three shapes. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) measurement is an effective tool for insulation condition assessment of high-voltage power equipment. The occurrence of multiple PD sources causes great difficulty on pattern recognition and failure risk assessment. This paper presents a self-adaptive PD separation algorithm based on optimized feature extraction of cumulative energy (CE) function. The CE functions in time domain (TCE) and frequency domain (FCE) are calculated from PD waveforms and their FFT spectrums, respectively. By using an oblique line to cross the CE curves, width features are extracted from the intersection points between them. Through the mathematical morphology gradient (MMG) operation, sharpness features are extracted to characterize the rise steepness of CE. It is found that the separation capability of width and sharpness are dependent on the pre-selected oblique line and the structure element length (SEL) in MMG, respectively. In order to obtain satisfactory PD separation results for various experimental conditions, a density-function based parameter is proposed to evaluate the separation capability, and the oblique line and SEL are optimized with the goal of maximizing the evaluation parameter. A clustering algorithm is adopted to discover different clusters in feature space and separate PD signals. The separation algorithm is examined with mixed PD current pulses and ultra-high-frequency (UHF) signals acquired from experiments in laboratory and on-site equipment. The results indicate that the self-adaptive separation method is immune to the change of experimental conditions, and is effective for separating mixed PD signals. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

Ultra‐high‐frequency (UHF) method is regarded as an effective approach for partial discharge (PD) detection in gas insulated substation (GIS). The feature parameters representing UHF signal characteristics can be extracted from its waveform, and applied to PD source classification and mixed signals separation. In this study, an UHF signal feature extraction algorithm based on cumulative energy (CE) technique is proposed. The CE functions in time domain (TCE) and frequency domain (FCE) are calculated from UHF waveforms and their fast Fourier transform spectrums, respectively. The mathematical morphology gradient (MMG) operation is applied to TCE and FCE to characterise their rising behavior. The feature parameters including width, area and sharpness are extracted from CEs and MMGs in both time and frequency domain. Moreover, the extracted features are applied to UHF signals classification and mixed signals separation. First, experiments on four kinds of typical defects in a 252 kV GIS are performed, and the classification performance of the extracted features is examined with the acquired signals. Second, by clustering the extracted features with fuzzy maximum‐likelihood algorithm, mixed UHF signals originated from multiple PD sources are successfully separated. The results indicate that the proposed features are effective for representing UHF signal characteristics. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) measurement and interpretation have become a powerful tool for condition monitoring and failure risk assessment of high voltage power equipment insulation. The occurrence of multiple discharge sources affects interpretation accuracy. This paper presents a PD signal separation algorithm using cumulative energy (CE) function parameters clustering technique. The waveform of PD signals are acquired by digital detection instruments with high sampling rate. Cumulative energy functions in time domain (TCE) and frequency domain (FCE) are calculated from PD waveforms and their FFT spectrums, respectively. Mathematical morphology gradient (MMG) operation is applied to the TCE and FCE to describe their variation characteristics. The feature parameters including width, sharpness and gravity are extracted from CEs and MMGs in both time and frequency domain, and compose a six-dimension feature space. The improved density-based spatial clustering of applications with noise (IDBSCAN) clustering algorithm is adopted to discover clusters in the feature space. The proposed separation algorithm is examined with mixed current impulse signals acquired from PD experiments on artificial multi-defect models and an on-site transformer. The separation results indicate that the proposed algorithm is effective for separating mixed PD signals initiated from multiple sources. [ABSTRACT FROM PUBLISHER]

The degradation of oil-impregnated paper induced by partial discharge (PD) seriously affects the life of power equipment. In order to investigate the relationship between partial discharge and the degradation of oil-impregnated paper, PD characteristics and trap parameters of the impregnated paper are measured. In this work, a cavity discharge model is adopted and samples with different degrees of polymerization (DP) are fabricated using thermally accelerated aging to simulate transformers with different lifetimes. For each sample, phase resolved partial discharge (PRPD) spectrograms are recorded for various partial discharge times. The characteristics of partial discharge are analyzed, and the trap parameters of specimens are obtained by the thermally stimulated depolarization current (TSDC) method. Following this, the microstructures of the samples are observed using a scanning electron microscope (SEM). It is found that the damaging breakdown process of oil-immersed paper can be divided into three stages: initial stage, developing stage and pre-breakdown stage. There also exist two levels of trap on the surface of oil-impregnated paper: shallow (0.10-0.59 eV) and relatively deep (0.60-0.90 eV) energy. Importantly, the thermal aging makes the trap energy deeper while electrical aging makes the trap energy shallower. [ABSTRACT FROM AUTHOR]

Oil-polypropylene (PP) composite insulation has been widely used in power capacitors, and also being extended to other equipment such as specific transformers, etc. As discharge can readily creep along PP surface, the interface between oil and PP is a weak point in the insulation structure. The oil-PP insulation degrades under the impact of thermal and electrical stress during normal operation. In this study, the influence of thermal degradation on surface discharge characteristics for oil-PP insulation is investigated. Degraded samples are obtained by thermally accelerated aging of virgin oil-PP samples. The microscopic morphology of PP samples are observed with SEM, and the physical and electrical properties of degraded oil are measured. In addition, the isothermal surface potential decay (ISPD) measurement is employed to investigate the charge keeping capability of PP samples. After that, surface discharge detection experiments under AC voltage are performed for the virgin and degraded samples. The ISPD results indicate that charge decay rate of degraded PP sample is faster than virgin sample, which imply that space charge memory effect of virgin PP samples is more remarkable. For this reason, the PD inception phase of virgin sample is smaller than those of degraded samples. It is found that thermal degradation of oil-PP insulation enhances the surface discharge activity. It is considered that rough surface profile and higher bubble conservation capability of degraded PP sample, and impurities in degraded oil are responsible for the enhancement effect of thermal degradation on surface discharge. [ABSTRACT FROM AUTHOR]

Streamer and breakdown behavior of transformer oil under impulse voltage are investigated with experimental observations and simulation. The optical observation by using Intensified Charge-coupled Device (ICCD) fast snapshot technique indicates that streamer channel branching is of a stochastic nature. The 2-D axially symmetric modeling based on hydrodynamic drift-diffusion model is employed to depict the streamer dynamics of transformer oil. The experimental and simulation results reveal that bushy negative streamer requires higher excitation than filamentary positive streamer. Positive streamer travels faster than negative streamer from experimental estimation. [ABSTRACT FROM PUBLISHER]

Two new triterpenoid saponins, named ilexsaponins B4 (1) and C (2), have been isolated from the roots of Ilex pubescens. Their structures have been established as ilexgenin B 3-O-α-l-arabinopyranosyl-(2 → 1)-β-d-glucopyranosyl-(2 → 1)-β-d-xylopyranoside (1) and 3-O-β-d-xylopyranosyl spathodic acid 28-β-d-glucopyranosyl ester (2) by means of spectral and chemical methods. [ABSTRACT FROM AUTHOR]