Ju Tang

The contamination of damp cellulose particles in flowing transformer oil degrades its insulation performance. Classic “bridge” breakdown theory is established under static transformer oil, and its applicability under dynamic oil flow exhibits limitation. In this paper, the bridging process of flowing transformer oil with cellulose particles containing different moisture contents under both AC and DC voltages were observed until the final breakdown, and the breakdown voltage was tested. The results indicated that the increasing cellulose moisture content deteriorated the insulation performance in transformer oil under both AC and DC voltages. At AC voltage, the concentration of cellulose particles with 1% moisture content in the whole oil gap first increased and then decreased with rising flow velocity, while the trend of breakdown voltage was opposite. The oil flow velocity corresponding to extreme point was 0.04 m/s. When the moisture content increased to 4-7%, the variation of particle concentration and breakdown voltage was similar to those at 1% moisture content, but the corresponding flow velocity at the extreme point increased to 0.06 m/s. At DC voltage, with the rising flow velocity, the cellulose bridge width at 1-4% moisture content increased, while the breakdown voltage decreased. When the moisture content increased to 7%, the flow velocity corresponding to the maximum of bridge width and the minimum of breakdown voltage shifted from 0 m/s to 0.02 m/s compared to lower moisture contents. This paper will provide experimental support for the establishment of “bridge” breakdown theory in flowing liquid dielectrics

High-voltage direct current gas-insulated equipment (HVDC GIE) is becoming a key component in DC transmission systems due to its compactness and reliability, particularly for cost-effective offshore wind power integration. However, its reliability is compromised by surface charge accumulation at the gas–solid interface—a problem intensified by metallic contaminants and the adoption of eco-friendly gas mixtures. Addressing this challenge requires not only material and design innovations but also the development of standardized testing protocols to validate insulation performance. This review systematically examines the critical, interconnected areas essential for advancing HVDC GIE, focusing on the dynamics of charged metallic particles and their role in charge accumulation, interface charge behavior under alternative gas environments, and experimental methodologies with evolving test standards. By synthesizing insights across these domains, this work aims to provide both theoretical insights and practical guidance for optimizing HVDC GIE insulation design formulating scientifically grounded operation and maintenance strategies.

High voltage direct current (HVDC) gas-insulated equipment (GIE) has become a critical component in long-distance power transmission projects, owing to its advantages such as compact structure and high reliability. However, the gas–solid interface insulation of DC GIE under long-term operation faces charge accumulation phenomenon, which will distort the electric field distribution and cause insulation flashover. Due to the lack of technical guidelines for the insulation design of DC gas-insulated equipment, the method of insulation design usually adopts increasing the insulation structure size to ensure sufficient creepage along the surface, which greatly increases the dimensions and manufacturing costs of the final equipment, and fails to fully leverage the unique advantages of GIE in compactness and lightness. Therefore, it is of importance to clarify the mechanism of charge accumulation on the surface of insulators under HVDC, and to propose an insulation design method that can effectively inhibit the charge accumulation and adjust the electric field distribution at the gas–solid interface, which holds practical significance for the safe application of large-scale DC GIE projects. In view of this, this paper firstly summarizes the characteristics of surface charge accumulation at gas–solid interface, and then reviews the existing research progress from two perspectives: surface charge suppression of insulation structure and gas–solid interface electric field regulation, providing theoretical and technical support for optimizing the design of GIE insulation structure, formulating scientific operation and maintenance measures.

Accurate localization of partial discharge (PD) in power transformers is critical for condition monitoring and fault prevention. However, localization algorithms are primarily validated through laboratory experiments or offline tests, making it difficult to assess their performance accurately in operational transformers. In this paper, a method is proposed to evaluate the positioning accuracy of PD localization algorithms by injecting pulse current into an ultra-high frequency (UHF) sensor to simulate PD source. The proposed method is first validated on an in-service 220 kV transformer equipped with six built-in UHF sensors. The results show that this method is safe, controllable, and capable of flexibly changing the location of PD. Furthermore, extensive experiments are conducted on another 220 kV transformer equipped with 18 built-in UHF sensors to systematically analyze the impact of sensor number and placement on the localization error of time difference of arrival (TDOA). It is found that increasing the number of sensors can reduce the likelihood of large positioning errors to some extent. But for highly accurate positioning, the best result is achieved when using five or six sensors. In terms of sensor placement, TDOA-based localization is less robust when sensors are placed on the same side or in adjacent areas. Uniform placement on all sides of the transformer can improve robustness, but it is difficult to achieve a high accuracy of the positioning error within 0.5m.

With the development of wide bandgap power semiconductor devices represented by silicon carbide (SiC) to higher voltage levels and faster switching speeds, the reliability of packaging insulation is facing severe challenges. In this paper, the strategy of modifying silicone gel by nano boron nitride (BN) doping is proposed, and the breakdown characteristics of composite insulation materials under high du/dt voltage are studied. The experimental results show that the breakdown voltage of composite insulating materials with different BN doping mass fractions decreases significantly with the increase of voltage rise rate. The doping of BN can effectively improve the high du/dt breakdown voltage of the composite insulating medium, and the modification effect is the most significant when the doping mass fraction of BN is 2%. Further combined with molecular simulation studies, it is found that the change in energy level structure of composite insulating materials under the action of electric field will lead to an increase in the number of carriers, which will accelerate the initiation of avalanche breakdown under high du/dt conditions. The doping of BN changes the charge transport mechanism of the composite material, and enhances the polarization of the molecular chain, thus exhibiting better insulation performance under high du/dt conditions. This study provides important data support and theoretical basis for the development of new high-performance insulation materials for new generation power device packaging.

The temperature gradient significantly affects the surface charge accumulation on disc-type insulators in HVDC GIS/GIL. In this paper, the surface charge accumulation characteristics under various temperature gradients are tested, and a simulation model about electro-thermal coupling is established to provide the theoretical analysis. Experimental results show that the average homo-charge density decreases from 3.79 μC/m² to 1.57 μC/m² as temperature gradient increases, which is attributed that the dominant pathway of homo-charge accumulation transfers from surface to bulk conduction. In contrast, the average hetero-charge density increases from 0.98 μC/m² to 4.82 μC/m². This is because large temperature gradients cause the electric field near grounded electrode significantly increasing from 1.05 kV/mm to 2.78 kV/mm, thereby massive hetero-charges from the grounded electrode migrate to the nearby insulator surface. This work can provide valuable references for the insulation design of disc-type insulators in DC GIS/GIL.

SF ₆ is a greenhouse gas with strong greenhouse effect. How to rationally deal with waste SF ₆ has become an extensive research topic for scholars at home and abroad. Studies have shown that ZIF-8 has certain superiority as a catalyst, while metal doping in ZIF-8 may promote its catalytic ability. In this paper, the undoped ZIF-8 model and the Cu-doped ZIF-8 model (Zn: Cu=1:5; Zn: Cu=3:3) were constructed, and the most stable adsorption structures of SF ₆ at three typical sites were obtained based on density-functional theory (DFT), with the 6MR window as the optimal adsorption site. The stable adsorption energy was the largest in the Zn: Cu=5:1 doped model (-98.352 kcal/mol), and during the adsorption process, the SF ₆ molecular bond lengths changed most drastically, and even the bond breaking phenomenon appeared. The catalytic ability of the Zn: Cu=3:3 doping model was in between that of the ZIF-8 and Zn: Cu=1:5 doping models. The results of the Mulliken charge transfer and the HOMO-LUMO energy level showed that in the Zn: Cu=5:1 doping model, the Cu atom can both transfer a large number of electrons (-0.606 e) to SF ₆ and enhance the ability of Zn atoms to lose electrons, effectively weakening the S-F bond strength of SF ₆ gas molecules and thus promoting SF ₆ gas molecule catalysis. The HOMO wave function in the system is mainly distributed around the doped Cu atoms, the energy gap is significantly reduced, and the catalyst reactivity is enhanced.

The decomposition of SF ₆ is closely related to the internal insulation status of equipment. Using SF ₆ decomposition component information can effectively diagnose the internal insulation fault of gas insulated equipment. This method has been widely concerned by the power industry. However, due to the limited amount of SF ₆ fault decomposition component data accumulated now and the vast majority of them are laboratory simulation data, the application of this method in engineering is limited. According to the characteristics of SF ₆ decomposition component data, this paper proposes a fault diagnosis strategy based on Gaussian process classification and decision fusion. On the basis of a large amount of experimental data and on-site fault data accumulated in the early stage, the existing data are expanded by piecewise cubic spline interpolation. In order to improve the generalization ability of fault diagnosis, the expanded SF ₆ decomposition component data is applied to the ensemble learning model. The basic learner of ensemble learning will introduce the Gaussian process classification model based on Markov chain Monte Carlo sampling. At the same time, an improved scheme of Bagging integrated learning is proposed, in which the voting rule is improved to the combination rule of evidence theory. The proposed scheme of ‘data driven + model driven’ improves the diagnostic accuracy to 97%. It provides a set of efficient diagnosis strategies for the power industry.

Harvesting energy from natural water via an evaporation-driven hydrovoltaic device (EHD) has attracted tremendous interest, and it also offers exceptional potential for application in self-powered sensing owing to its independent operation and stability. Here, we fabricated an analytical strip by vacuum filtering single-walled carbon nanotubes (SWCNTs) into cellulose paper for highly sensitive salinity detection in water solution. The role of electrode structure, water solution ions, and temperature on the EHD response was systematically investigated. Specifically, this type of analytical strip has a specific continuous load capacity and produces a consistent voltage output of ~0.55V. Further, a self-powered equivalent salt deposit density (ESDD) sensor based on EHD was adopted for insulator contamination detection in electrical equipment, demonstrating superior sensitivity, stability and anti-interference ability. This work broadens the EHD-based self-powered sensor and provides a quick monitoring strategy for the operational state of insulators in the electrical equipment.

The chip junction temperature of high-power IGBT devices leads to the thermal aging of silicone gel inside the module, which directly affects the service life of IGBT. The microstructure and dielectric properties of silicone gel at different aging stages are the key to revealing the insulation degradation mechanism of IGBT packaging. In this paper, the crosslinking density, chemical structure, and dielectric properties of silicone gel under different aging stages were tested. Combined with molecular dynamics theory calculation, the variation characteristics of dielectric properties were studied from the microstructure of silicone gel. The results show that with the increasing aging, the side chain groups with non-polarity of silicone gel will be gradually consumed, and the Si-O-Si with higher bond energy will gradually increase and be exposed to the electric field, thus the polarization will become more significant. The crosslinking density and free volume ratio of the silicone gel increase with aging, which has effects on charge transport and group polarization. The research results provide a data basis for the packaging design of IGBT under long-term service conditions, and also provide theoretical support for further optimizing the thermal aging resistance of packaging materials.