High Voltage最新文献

As a novel chemical marker, methanol has been widely applied to evaluate the ageing state of insulating paper in recent years. Methanol gas sensor (MGS) could be applied to detect the methanol content in transformer oil for its high portability and stability. However, it has the defects of a high limit of detection (LOD) and poor anti-interference performance. Therefore, a novel method of detecting methanol in transformer oil based on MGS with the solid-phase extraction (SPE) technology was investigated in this paper. A detection platform for methanol in transformer oil based on SPE was established, and the SPE experimental process and the crucial parameters were optimised. The results show that the SPE decreased the LOD of MGS from 0.4 to 0.2 ppm and effectively eliminated the interfering substances in oil. Although a part of methanol would be lost during the SPE process, the regression correction coefficient was proposed to correct the evaluation errors. The results indicate that the average relative errors decreased from 17.09% to 4.38%, and the proposed method has good applicability.

Porcelain insulator is an important component of power transmission systems, and its condition detection is essential to ensure safe operation of the power grid. Nevertheless, it is difficult for existing detection models to effectively solve the contradiction between detection accuracy and resource consumption. To address this issue, a high-precision lightweight insulator defect detection model (BCM-YOLO) based on an improved YOLOv8 is proposed. Firstly, bidirectional feature pyramid network (BiFPN), with a simplified bidirectional information flow mechanism, is employed to replace the path aggregation network with feature pyramid network in YOLOv8 to alter the feature fusion mode, thereby reducing the model size. Secondly, a cross-stage partial Bottleneck with 2 convolutions partially replaced by a context-guided block (C2f_CG) structure with parameter sharing is designed using the improved context-guided block to optimise the cross-stage partial Bottleneck with 2 convolutions (C2f) modules, thus further decreasing the number of model parameters. Finally, multiscale dilated attention is introduced into the BiFPN network to enhance the perception ability of different scales of features to improve the detection performance. Experimental results indicate that compared to YOLOv8s, the BCM-YOLO model reduces the number of parameters by 50.5%, lowers floating-point operations by 31.3% and increases mean average precision at intersection over union = 0.5 (mAP0.5) by 2.8%. The proposed model not only improves detection accuracy but also decreases parameter counts, making it more suitable for deployment on edge devices.

Polypropylene (PP) has become the focus of research and development of recyclable polymer dielectric materials because of its excellent electrical and thermal properties. The residual catalyst after PP polymerisation is the main part of ash. It was found that ash particles are uniformly dispersed in the PP matrix. The increase in ash content leads to a gradual decrease in their spacing, and leads to a significant decrease in electrical properties, with a difference of more than one order of magnitude for volume resistivity. The decrease in the ion migration potential barrier caused by the increase of ash content is the key factor in deteriorating the electrical properties of PP. The effect of ash on the electrical properties of PP mainly lies in enhancing the migration of ion carriers. The PP volume resistivity corresponds to an ash threshold of 292 ppm, above which the concentration leads to an increase in ion carriers. The accumulation of carriers leads to internal electric field distortion enhancing the transition ability of carriers and leading to a rapid decrease in the electrical properties of PP. This study provides a feasible reference for the development of high-performance PP insulation materials for power cables and other applications.

Silicon carbide (SiC) high-voltage, high-power semiconductor devices are essential for next-generation power systems, yet conventional silicone elastomer encapsulation materials suffer from insulation degradation under extreme thermal and electrical stresses, highlighting the critical need for novel dielectric materials. This article brings phenyl groups into the side group of conventional silicone elastomers through ring-opening polymerisation and hydrosilylation, developing phenyl-modified silicone elastomers. The material's superior thermal resistance is substantiated through thermal ageing and thermogravimetric analysis. Moreover, this study delineates the insulating robustness of the material by gauging its dielectric breakdown voltage. By subjecting the material to pulse electric fields, we investigate the insulating properties of the encapsulation material under operational conditions reflective of actual service environments. Dielectric testing and molecular electrostatic potential simulations are further employed to analyse the enhancement of the material's insulating properties due to the introduction of phenyl groups. Research studies indicate that phenyl silicone elastomers exhibit outstanding temperature and electrical resistance, performing well under pulsed electric field. This is associated with the phenyl group's rigid structure, conjugated system, and its electron-withdrawing characteristics. Study provides a theoretical foundation for improving the insulating properties of encapsulation materials and the operational reliability of power electronic devices.

The space charge accumulation in the heterogeneous insulation composed of cross-linked polyethylene (XLPE) cable and silicone rubber (SiR) accessory poses a serious threat to the safe operation of the high voltage direct current (HVDC) cable. When the cable is in heavy load, the charge transport behaviour in XLPE/SiR becomes more complicated due to the high temperature. In order to investigate the charge transport characteristics of XLPE/SiR under heavy load condition, the simultaneous measurement of space charge and relaxation current is performed on XLPE/SiR at both 70°C and 30°C with different polarities. The results show that the polarity of the interface charges in XLPE/SiR is always consistent with that of the SiR side electrode, and the influence of high temperature (70°C) caused by heavy load on the interface charge accumulation of XLPE/SiR is reversed at different polarities. The interface trap depth of XLPE/SiR is consistently greater than the bulk trap depths in both XLPE and SiR. When at high temperature of 70°C, the depth and density of interface traps increase, and the bulk traps in XLPE and SiR also exhibit increased depth. The component of polarisation relaxation current associated with space charge activity increases and exhibits longer decay time at 70°C, indicating more active and complex charge trapping-detrapping activities under heavy load condition. In this paper, an advanced simultaneous measurement is used to correlate the internal charge distribution with the external current for analysis, and the charge transport characteristics of XLPE/SiR under heavy load condition is revealed. The results can provide reference for the operation and maintenance of HVDC cable, and can also provide a basis for the space charge regulation of heterogeneous insulation at HVDC cable accessories.

Power transformers are vital components in electric grids; however, methods to optimise their loading to extend lifespan while accounting for insulation degradation remain underdeveloped. This research paper introduces a novel integrated data-driven framework that combines particle filtering and model predictive health (PF-MPH) model for the predictive health management of power transformers. Initially, the particle filter probabilistically estimates power transformers' remaining life (R_L) using direct winding hotspot temperature $��\left({\chi }_H\right)�$ measurements. The obtained R_L will then be used to calculate the degree of polymerisation (DP) level and assess the current insulation condition. After that, a comparative analysis between direct and model-based $��{\chi }_H�$ measurement methods is performed to highlight the superior accuracy of direct measurements for predictive health management. Then, the MPH optimisation algorithm, which uses the R_L and DP forecasts from the PF method, derives an optimal trajectory over the transformer's R_L that balances the costs of increased loading against the benefits gained from prolonged insulation longevity. The findings show that the proposed PF-MPH model has successfully reduced the $��{\chi }_H�$ by 2.46% over the predicted 19 years. This approach is expected to enable grid operators to optimise transformer loading schedules to extend the R_L of these critical assets in a cost-effective manner.

The performance of polypropylene film determines the reliability of capacitors. This paper studies the change of insulation characteristics of the insulation dielectric polypropylene of high-voltage capacitors during the long-term operation process. Moreover, the correction of the insulation failure model of polypropylene media is implemented. Some conclusions are drawn from a series of experiments. The breakdown strength of the insulation dielectrics decreases as the withstand time rises, with a maximum decrease of 37.91% compared to the polypropylene sample without withstand voltage. As the electric field increases from −20 to −100 kV/mm, the total amount of space charge, the trap energy level and the trap density inside the polypropylene increase by 524.15%, 18.99% and 773.36%, respectively. In the capacitor simulation model, the electric field in the capacitor increases by 19.62% after presetting space charge relative to the nonspace charge. The experimental data are substituted into the inverse power model, and the trap parameters are used to modify the model. The results show that the ageing state of the polypropylene has a negative exponential relationship with the trap parameters. This paper provides an important reference for the study of the failure mechanism of polypropylene in high-voltage capacitors and the assessment of polypropylene ageing state.

This paper presents an approach to accurately forecast the yearly occurrence of flashovers caused by lightning-induced voltage in overhead power lines in the presence of layered ground. The aim is to improve the accuracy of flashover rate estimation by using the insulator volt-time model. In particular, two-layer horizontal ground structures are considered. A 3D finite element method is used to calculate induced voltages and a Monte Carlo simulation is applied to determine the annual flashover rate. Volt-time insulator characteristics are used to identify the flashover condition. The results are compared with those obtained by using the standard 1.5 times the critical flashover (CFO) threshold criterion. The results indicate that the conventional 1.5 times the CFO criterion may underestimate the rate of flashovers, particularly in regions with horizontally stratified soil, as the volt-time method offers a more accurate presentation of the flashover process. Furthermore, the effect of upper soil depth, upper soil conductivity, pole spacing, and different flashover distance calculation techniques on flashover rates are analysed. This paper presents a new mathematical formula for estimating yearly flashovers based on the results obtained by the volt-time method in the presence of stratified ground. The derived analytical formula provides an insightful tool for power system engineers to evaluate the lightning performance of overhead lines and implement efficient mitigation strategies.

The high voltage Padova test facility (HVPTF) is an experiment set in Padova, Italy, operating in the framework of the Neutral Beam Test Facility project of the International Thermonuclear Experimental Reactor (ITER). One of the purposes of HVPTF is to study the phenomenology of discharge events occurring between electrodes at high voltage differences over long vacuum gaps, which is crucial in the development of the neutral beam injector foreseen for ITER. The facility hosts a cylindrical vacuum vessel with stable pressure control, where two electrodes of different possible geometries can be mounted. Two independent power supplies allow for total voltage differences up to 800 kV_DC with adjustable gap widths up to 250 mm. Among the diagnostics, a gas electron multiplier (GEM) detector is installed for acquisition of x-ray emission on a radial line of sight of the vessel. This paper presents a study of the experimental sessions featuring stainless-steel needle-plane electrodes. The analysis is based on the GEM data, in relation to the information on current and voltage of the two power supplies. The events are characterised in terms of both temporal and spatial evolution, providing sequential emission profiles with spatial resolution of tens of millimetres on timescales of the order of hundreds of nanoseconds.

Silicone rubber of composite insulators is extensively utilised because of its superior hydrophobicity and hydrophobicity transfer characteristics, especially in heavily polluted environments. This work investigates the hydrophobicity transfer process of silicone rubber materials with different insoluble substances and explores the impact of microscopic parameters on hydrophobicity transfer. Experiments employed diatomaceous earth and kaolin of various particle sizes and origins as inert substances to analyse their effects on hydrophobicity transfer characteristics. Results indicate that diatomaceous earth, with its porous structure, facilitates faster transfer compared to the dense structure of kaolin. Pore size and specific surface area are critical parameters influencing transfer rates. Larger outer pores accelerate the initial ‘fast process’ while smaller inner pores govern the subsequent ‘slow process’ Fractal characteristics of pores also affect transfer efficiency with higher fractal dimensions leading to more extensive transfer. The hydrophobicity transfer process in silicone rubber involves dynamic diffusion influenced by the complexity of internal channels and surface structures. Enhanced understanding of these mechanisms can improve the performance and reliability of composite insulators in polluted environments.