High Voltage最新文献

High-strength copper contact wire is of great significance to the electrified railway power supply system, which constantly provides electric power to the trains during operation. However, contact wire is subject to pressure, vibration, and natural forces such as wind, rain, ice, etc. which inevitably result in mechanical fatigue over time. This mechanical fatigue can lead to a decrease in the mechanical strength of the contact wire, and ultimately lead to problems such as wire detachment, fracture, or breakage, posing a serious safety hazard to the electrified railway system. Herein, the authors propose a strategy using nanosecond pulsed laser induced breakdown spectroscopy (LIBS) combined with machine learning technique to realise a fast evaluation on the fatigue level of copper contact line. Three different fatigue levels of copper samples have been made related with the requirement of operational conditions, and a total of 898 LIBS spectra were collected. Twenty-four combinations of spectral pre-processing, feature extraction, and optimisation algorithms were used to compare the recognition results with the accuracy, recall rate, and time cost taken into accounted. Results have shown that the standard normal variable transform–principal component analysis–genetic algorithm improve support vector machine (SNV-PCA-GASVM) model have presented a most satisfactory performance than the others. The cross-validation accuracy of the SNV-PCA-GASVM model was 92.97% while the dimensionality of input variables was reduced by 99.62%. This work is useful for the safety operation of power supply system in high speed railway, and technique development concerning the fast evaluation on materials fatigue in other industrial fields.

Multi-terminal flexible high-voltage direct current (HVDC) transmission and DC grid technology are developing rapidly. The hybrid DC circuit breaker (HCB) has broad application prospects in the field of HVDC transmission and DC power grid. Nevertheless, existing HCBs have one or more following blemishes: arc suppression scheme of mechanical switch, high cost and unreliable adaptive reclosure. In this paper, a modified thyristor-based hybrid DC circuit breaker with short arcing capacity (SA-HCB) is introduced, which consists of the main branch, the fault handling branch and the pre-charging branch. Besides, the modified SA-HCB has the inherent capability of adaptive reclosing. The advantages of thyristors are fully used in the SA-HCB, such as low cost, low conduction voltage drop, and natural shutdown. The detailed structure diagram and mathematical model of the SA-HCB are introduced, and the operation processes of the fault current transfer are also analysed. Later, a design method for parameters of the proposed SA-HCB is provided. Then, a single-ended equivalent system is built in PSCAD/EMTDC to verify the accuracy of the theoretical analysis and parameter design. Subsequently, based on four-terminal simulation, the economy of the SA-HCB is verified by comparing with the topology proposed by ABB. Finally, the small-scale experiment of the proposed SA-HCB is introduced.

Optical image method has been the earliest and most used direct method for observing gas discharge. Currently, research on gas discharge monitoring based on visible light mainly relies on high-speed cameras, but the large size, significant data storage requirements, and susceptibility to interference from complex backgrounds and lighting conditions limit their further application. Dynamic vision sensing (DVS) technology is a neuromorphic sensing technology that asynchronously measures the luminance changes at each pixel. It offers advantages such as a large dynamic range (>120 dB), high temporal resolution (up to 1 µs), and small data volume (MB level). In this study, dynamic vision sensing technology was employed to monitor both 30 mm short-gaps and 1080 mm long-gaps discharge processes simultaneously. This study developed the CountImage encoding method for event data and conducted image reconstruction, time-domain analysis, and frequency-domain characteristic analysis based on the event data. The results show that the event-reconstructed images are highly consistent with the high-speed camera images, and the arc development process and its path can also be clearly observed. Additionally, this study discovered a correlation between the electrical characteristics and event information during the discharge process. In the time domain, the duration of the maximum DVS event count closely matches the duration during which the voltage drops to zero during flashover. In the frequency domain, the Pearson correlation coefficient between the event stream spectrum and the voltage signal spectrum is greater than 0.95. Both the maximum number of brightening events (ON_max) and the maximum number of darkening events (OFF_max) are positively correlated with the voltage applied between the electrodes. This study demonstrates that, compared to the GB/s data rate of high-speed cameras, this approach can record the discharge process and accurately reconstruct the discharge process, arc morphology, and discharge path at MB/s data rates, while also adapting to changes in brightness without the need for exposure adjustment. Additionally, there is a positive correlation between the frequency-domain characteristics of the event data and the voltage characteristics. These results indicate that dynamic vision sensing holds promise as a replacement for high-speed cameras in laboratory discharge observations and could be even effectively applied to discharge monitoring in electrical equipment in real grid.

In the summer of 2018–2019, rocket-triggered lightning experiments were conducted in Guangzhou, China. There were two types of lightning targets: ground and overhead line. By comparing the current and the electric field data in the two cases, it was found that when the continuous current level (I_CC) and current amplitude (I_M) of M-components (current pulses generated during the continuous current stage) are large, the time difference between the electric field peak and the current peak (T_D) will always be small. The rise time (R_T) and half peak width (T_HPW) of M-components with high I_CC and I_M are low in both the cases. The threshold upper limit of T_D in the case of lightning striking the ground is higher, approximately 2.6 times than that in the case of lightning striking the overhead line. We use an optimised guided wave model to simulate the electric field waveforms of M-components. It was found that the shorter R_T and T_HPW of the M-component, the smaller T_D. The changes in wave speed and I_M cannot affect the size of T_D, and the impact of distance changes is very weak. The difference in the threshold upper limit of T_D may be related to the significant difference in ground impedance in two cases.

The submodule in multilevel modular converters experiences a very fast transient overvoltage (VFTO) during switch operation of gas-insulated switchgear, which also results in overvoltage on power devices, such as thyristors and insulated gate bipolar transistors (IGBTs). This work presents an embedded circuit that utilises a gap in conjunction with a metal oxide varistor (MOV) to control the voltage of the surge arrester and prevent false triggers during the transient phase when the IGBT is turned off. The mechanism of VFTO is analysed. Moreover, the design idea is suggested and the gap-MOV circuit is constructed. Ultimately, experiments are conducted to validate the effectiveness of the suggested gap-MOV in suppressing overvoltage.

Syntactic foam materials, due to their advantages of low densities, low water absorption, and high dielectric strengths, have significant application potential in the cores of post insulators. However, because of a large number of microbubble structures within the syntactic foam, it might decrease the partial discharge inception voltage. It is necessary to investigate the partial discharge characteristics of the foam to assess the feasibility of its internal insulation application. In this study, the syntactic foam samples with four different microsphere contents (0%–2%) were prepared, and the physical structures of the materials were characterised by using Fourier transform infrared spectroscopy, scanning electron microscopy, and three-dimensional computed tomography. Subsequently, finite element simulations of the electric field were performed to analyse the influence of the microsphere content and distribution on the internal electric field of the syntactic foam. The results suggested that both the microsphere content and distribution affected the partial discharge activity. When the microsphere content was low, the doping of microspheres essentially meant that more air gap defects were present, leading to a decrease in the partial discharge performance. However, when the microsphere content was high, the microspheres were distributed in a dense and orderly manner, improving the field concentration phenomenon and hence inhibiting the partial discharge to a certain extent. In conclusion, the findings of this study provide a data reference and theoretical support for the application of syntactic foam in the cores of composite post insulators.

Power systems grapple with the challenges of high load rates and intermittent new energy sources integration. Transformers, as vital equipment, employ oil/pressboard (oil/PB) insulation. Uneven moisture distribution in this insulation can jeopardise safety thresholds, necessitating precise moisture assessment for grid stability. A novel mathematical model, adsorption–desorption and porous media moisture transfer (ADP-MoT), is presented. This model incorporates adsorption and desorption processes within the porous pressboard, enabling a description of the dynamic moisture transfer between the oil and pressboard. Using this mathematical model, simulations for moisture dynamics were performed on a 750-kV transformer across four typical days. The results indicate that temperature fluctuations are the primary driving factor for moisture migration at the oil/PB interface. Convection and diffusion contribute to moisture movement towards cooler regions. Fluid properties and structural characteristics induce a distinctive streamline-shaped moisture flow within horizontal oil channels, with localised moisture accumulation in specific areas. Moreover, the analysis of 96 transient results uncovers potential free-state moisture formation during severe conditions, underscoring the importance of monitoring the pressboard at winding bases during high load fluctuations. In conclusion, this study significantly contributes to scientifically identifying and addressing risks tied to new energy sources integration in power systems.

Due to the complex structure and large size of large-capacity oil-immersed power transformers, it is difficult to predict the winding temperature distribution directly by numerical analysis. A 180 MVA, 220 kV oil-immersed self-cooling power transformer is used as the research object. The authors decouple the internal fluid domain of the power transformer into four regions: high voltage windings, medium voltage windings, low voltage windings, and radiators through fluid networks and establish the 3D fluid-temperature field numerical analysis model of the four regions, respectively. The results of the fluid network model are used as the inlet boundary conditions for the 3D fluid-temperature numerical analysis model. In turn, the fluid resistance of the fluid network model is corrected according to the results of the 3D fluid-temperature field numerical analysis model. The prediction of the temperature distribution of windings is realised by the coupling calculation between the fluid network model and the 3D fluid-temperature field numerical analysis model. Based on this, the effect of the loading method of the heat source is also investigated using the proposed method. The hotspot temperatures of the high-voltage, medium-voltage, and low-voltage windings are 89.43, 86.33, and 80.96°C, respectively. Finally, an experimental platform is built to verify the results. The maximum relative error between calculated and measured values is 4.42%, which meets the engineering accuracy requirement.

Partial discharge (PD) detection of cable terminals is crucial for the safe operation of the traction power system in trains. However, similar PD signals in complex train-operating environments cause difficulty to recognise the insulation defects. Therefore, a PD signal image transformation recognition method is proposed for PD detection of cable terminal defects to identify defects in cable terminals with similar PD characteristics accurately. In the proposed method, the raw PD signals are firstly transformed to images via the Gramian angular field (GAF) representation. This can reveal the discriminative characteristics embedded in the original PD signals and subsequently facilitate differentiating the PD sources, which exhibit similar characteristic in the time domain. The obtained GAF representation of PD signals (named as PD GAF images) is extracted from local and global features to train an efficient MobileVIT model, which is then utilised to identify similar types of PD sources in cable terminals. The results show that the proposed method achieves 97.5% recognition accuracy in the field experiment, which is superior to other methods.

The insulating properties of silicone gel used for silicon carbide-insulated gate bipolar transistors encapsulation may deteriorate seriously under ultra-fast pulsed electric fields. The essence of insulation degradation lies in the deterioration of materials caused by dynamic phenomena at microscopic scale, such as charge trapping and detrapping. Different from the steady-state operating condition, insulating materials exhibit a sharp decrease in their insulating properties when subjected to a rapidly changing electric field. To investigate the insulation failure of silicone gel materials under an ultra-fast pulsed electric field, Marcus hopping mechanism for charge response is proposed. By calculating the relaxation time with different defects, we characterise the degradation of the materials. According to the force analysis of space charge, the authors establish a relationship between insulation failures and charge relaxation time. Combined with the experimental results on electrical treeing in silicone gel, the feasibility of the theory is verified. The experimental phenomenon can be well explained, that is, the initial voltage of the electrical trees decreased sharply with shortening the edge time of the pulsed electric field, especially on the nanosecond time scale.