High Voltage最新文献

Metallised film capacitors, for the most important merits is the excellent self-healing property, have significant electrical insulation advantage. The essential factors affecting the self-healing properties of metallised polypropylene film capacitors (MPPFCs) are first analysed, and a self-healing performance characterisation test platform for metallised polypropylene capacitor films was built. Both the voltage/current waveforms and discharge patterns of the self-healing process under multiple stresses including temperature, voltage and inter-layer pressure were recorded and discussed. The correlation between self-healing performance characterisation and the carbon that appeared on the surface of the dielectric layer during the arc extinction time is clarified. Finally, by virtue of an equivalent dynamic circuit model, the influence of square resistance and the equivalent capacitance of the power grid on self-healing has been theoretically studied.

It has been shown that noise emissions from HV overhead line conductors can be reduced under rain conditions by making their surfaces superhydrophobic. The working environment makes ensuring the longevity of any treatment a major challenge. The degradation of various superhydrophobic surfaces generated by applying a superhydrophobic coating and patterning microscale channels is assessed under an AC electric field (18 kV/cm) with continuous water spray. By examining the droplet distribution on the surfaces during the degradation and the surface roughness before and after degradation, the authors demonstrate that no water droplets were found on the microscale patterned surface, but droplets were formed on the coated surface after degradation. The surface roughness reduction of the coated surface and microscale patterned surface was 29.8% and 11.3%, respectively, indicating that the microscale patterned surface has better durability than the superhydrophobic coating under the AC electric stress.

End turn grading with resistive–capacitive coupling experiences severe electrothermal stress when subjected to pulse width modulation (PWM) voltage. In this paper, several experiments and simulations were carried conducted for four types of end turn grading. First of all, the temperature rise in the end turn grading increased with a decrease in rise time. When the rise time was less than 500 ns, the temperature rise at the terminal was higher owing to the increased capacitive current coupled from the main wall insulation. Further, the current in the linear region exhibited minimal variation at different fundamental frequencies resulting in synchronized the temperature rise at the terminal and overlap. Furthermore, the jump voltage was the key factor influencing temperature rise in end turn grading, confirmed by comparing different voltage magnitudes. Finally, the transient behaviour of the maximum field in the stress grading material was determined at rise time. The experimental and simulation results indicate that balancing and interdependently addressing the electrical and thermal stress protection in end turn grading is crucial. The study aims to provide an experimental and theoretical foundation for an insulation system of inverter-fed rotating machinery operating under PWM voltage.

The authors introduce the intactness-aware Mosaic data augmentation strategy, designed to tackle challenges such as low accuracy in detecting defects in insulation pull rods, limited timeliness in intelligent analysis, and the absence of a comprehensive database for information on insulation pull rod defects. The proposed strategy incorporates the YOLOv5s algorithm for detecting defects in insulation pull rods. Initially, the YOLOv5s network was constructed, and a dataset containing photos of insulation pull rods with white spots, fractures, impurities, and bubble flaws was compiled to capture images of defects. The research presented a data enhancement approach to improve the images and establish a dataset for insulation pull rod defects. The YOLOv5s algorithm was applied for both training and testing purposes. A comparative analysis was conducted to assess the detection performance of YOLOv5s against a conventional target detector for identifying defects in insulation pull rods. Furthermore, the utility of Mosaic's data augmentation technique, which incorporates intactness awareness, was evaluated to enhance the accuracy of identifying insulation pull rod defects. The research findings indicate that the YOLOv5s algorithm is employed for intelligent detection and precise localisation of flaws. The intactness-aware Mosaic data augmentation strategy significantly improves the accuracy of detecting faults in insulation pull rods. The YOLOv5s model used achieves a performance index [email protected]:0.95 of 0.563 on the test set, distinct from the training set data. With a threshold of 0.5, the [email protected] score is 0.904, indicating a substantial improvement in both detection efficiency and accuracy compared to conventional target detection methods. Innovative approaches for identifying defects in insulation pull rods are introduced.

The exploration of eco-friendly insulating gas to substitute the most potent greenhouse gas sulphur hexafluoride (SF₆) has consistently garnered significant attention. Herein, the authors evaluated the feasibility of utilising perfluoromethyl vinyl ether (PMVE, C₃F₆O) as a new branch of eco-friendly insulating gas for the first time. The primary dielectric and stability characteristics of PMVE regarding AC breakdown, partial discharge, dielectric recovery, and decomposition properties were revealed under various gas pressure and electrical field conditions. It was found that PMVE demonstrated superior dielectric strength, with the AC breakdown and PD inception voltage (PDIV) 1.10 and 1.14 times that of pure SF₆. Furthermore, the dielectric strength of PMVE exhibits stability even after undergoing 100 cycles of AC breakdowns, and there is no observable formation of solid precipitation on the electrode surface. The discharge decomposition of PMVE mainly generates fluorocarbon (CF₄, C₂F₆, C₃F₆, C₃F₈, etc.) and CO. Overall, the exceptional insulation stability and no absence of solid precipitation features endow PMVE to be utilised as a new eco-friendly gas for SF₆-free gas-insulated equipment.

Recently, ZnO-based composites have been widely applied in the field of electric power. To meet the diverse application requirements, it is necessary to figure out the I–V characteristics of ZnO composites whose high-voltage and ground-voltage electrodes are arranged on the opposite sides with a certain horizontal distance. 30 vol%, 40 vol% and 50 vol% ZnO-based silicone rubber composites were prepared. The horizontal distance between their electrodes was set as 50, 100, 500 μm, 1 and 2 mm, respectively. Results showed that with the increase of ZnO fillers volume fraction under a fixed horizontal distance of 100 μm, from 30 vol% to 50 vol%, the I–V curves shifted left, the leakage current increased and the switching voltage decreased. When the horizontal distance between electrodes increased from 50 μm to 1 mm under a fixed doping concentration of 40%, the I–V curves shifted to the right, the leakage current dropped and the switching voltage rose. The mathematical and physical models were established to explain the results. This work provides a referential significance for the practical application of ZnO composites, such as 5G folding mobile phones and power electronic modules.

To improve our knowledge of the spatio-temporal correspondence between radar reflectivity and VLF/LF total lightning data, this paper proposes indexes to quantify the horizontal distribution and temporal evolution characteristics between radar composite reflectivity images and total lightning density map, lightning clusters and radar cells with different radar reflectivity thresholds (30, 35, 40, 45 and 50 dBZ), respectively. It is found that the number of radar grid cells with radar reflectivity over 30 dBZ is ten times the number of lightning grid cells. At the identification stage, the lightning activity regions in a radar cell account for less than 30% using thresholds of 30, 35 and 40 dBZ, respectively, and the radar cell has more than one lightning cluster, which means that the mesoscale convective systems typically have more than one draft, and drafts are only small part of the convection. The majority of the centroid deviations is less than 10 km, indicating that there are some shifts between electrically active regions and convective regions. Results suggest that VLF/LF total lightning data are consistent with radar data and total lightning data can be used individually on a smaller spatio-temporal scale than radar data.

The safe operation of oil-immersed transformers is critical to the safety and stability of the power grid. As the operating time increases, the failure rate of oil-immersed transformers shows an increasing trend, posing serious challenges to safe operation. It is necessary to investigate the internal state of the oil-immersed transformer to improve the digital degree and achieve digitalisation and intelligent operation and maintenance. A physics-informed neural network (PINN) for oil-immersed transformers was introduced to reconstruct the temperature distribution inside the transformer. According to the approach, the loss function of the network would be optimised by incorporating physical constraint loss terms including heat transfer equations, initial conditions and boundary conditions. The results show that the method proposed can be used to reconstruct and predict the temperature field of transformers in a few seconds with satisfactory accuracy. In conclusion, the PINN proposed outperforms deep neural networks in terms of accuracy, reliability and interpretability, especially in data-poor cases.

Heptafluoroisobutyronitrile (C₄F₇N) is being considered as a promising alternative to the greenhouse gas SF₆ in the electrical industry. However, its biotoxicity necessitates the development of gas sensing technology to detect leaked C₄F₇N. A combination of density functional theory and experiments was employed to evaluate the adsorption and sensing performance of different metal-phthalocyanines as potential sensing materials for C₄F₇N detection. The study included exploring adsorption configurations with adsorption energies, electron transfer, and adsorption distance, as well as comparisons of electronic properties, electron distribution, and density of states (DOS) among the MPcs. Furthermore, gas sensing experiments were conducted using different MPcs to detect 25–100 ppm C₄F₇N. The results revealed that Mn-Pc, Fe-Pc, Co-Pc, and Zn-Pc exhibited considerable chemical interactions, while Ni-Pc and Cu-Pc showed weaker adsorption strength. These findings were further elucidated based on the electron density and DOS of atomic orbitals. Moreover, gas sensing experiments indicated that Co-Pc demonstrated a higher response compared to Fe-Pc at the same concentration of C₄F₇N. Overall, the theoretical and experimental insights offer valuable guidance for C₄F₇N detection and provide a systematic approach to screen and explore organometallic polymer-based gas sensors applicable in various fields.