This paper introduces an HVDC SF6/N2 gas insulated transmission line (GIL) prototype that operates under 100 kV DC application. In the first part, the development history of GIL products over the past 50 years is reviewed. After that, the design concept of the 100 kV HVDC SF6/N2 GIL is introduced. A GIL prototype was prepared and the DC withstanding voltage test and DC superimposed lightning impulse voltage test were performed. The results show that this GIL prototype passed all the required tests, including hydrostatic test, gas tightness test, thermal cycling test, DC withstanding test, and DC superimposed impulse test, etc. The successful preparation of this product promoted a major step in researches of DC GIL and the prototype laid a solid foundation for the development of subsequent industrial products.

The strain clamps and leading wires are important components that connect conductors on overhead transmission lines and conduct current. During operation, poor contact between these components can cause abnormal overheating, leading to electric failures and threatening power system reliability. Recently, the use of unmanned aerial vehicles equipped with infrared thermal imagers for strain clamp and leading wire maintenance has become increasingly popular. Deep learning‐based image recognition shows promising prospects for intelligent fault diagnosis of overheating faults. A pre‐treatment method is proposed based on dynamic histogram equalisation to enhance the contrast of infrared images. The DeepLab v3+ network, loss function, and existing networks with different backbones are compared. The DeepLab v3+ network with ResNet101 and convolutional block attention module added, and the Focal Loss function achieved the highest performance with an average pixel accuracy of 0.614, an average intersection over union ( AIoU ) of 0.567, an F1 score of 0.644, and a frequency weighted intersection over union of 0.594 on the test set. The optimised Atrous rates has increased the AIoU by 12.91%. Moreover, an intelligent diagnosis scheme for evaluating the defect state of the strain clamps and leading wires is proposed and which achieves a diagnostic accuracy of 91.0%.

Trapped space charges in epoxy composite distort the electric field, which will induce the failure of the insulation system, and nano graphene oxide may inhibit the curing behavior of epoxy resin matrix. This paper analyzes how the two interfaces affect the electron traps of epoxy resin/graphene oxide systems with different nanofiller contents. The electron affinity energy of epoxy resin matrix and nano filler molecules in the epoxy resin/graphene oxide system is calculated based on quantum chemistry. It is found that nano graphene oxide has a strong electron affinity energy and is easier to capture electrons. Then the influence of the interface formed by the epoxy resin matrix and the nano graphene oxide on the electron transfer ability is calculated. The epoxy resin matrix contains the electron transfer ability of interfaces formed by nano graphene oxide and the molecular chain is different from that of unreacted molecules. The results can provide a reference for the modification of epoxy resin/graphene oxide nanocomposites.

Perfluoroisobutyronitrile (C₄F₇N) gas mixture is considered one of the most promising alternative gases for SF₆ due to its excellent environmental protection and insulation performance. At present, the Shanghai region of China has adopted 8.5% C₄F₇N-86% CO₂-5.5% O₂ proportion gas mixture as the insulation medium for 126 kV gas insulated switchgear and has put it into practical engineering application. This paper conducted decomposition experiments on the proportion gas mixture under spark discharge, suspension discharge, and corona discharge conditions, respectively. The composition analysis of the decomposition products was carried out using a gas chromatography mass spectrometry and a gas chromatography-pulsed discharge helium ionization detector, which got decomposition products of the C₄F₇N/CO₂/O₂ gas mixture under discharge faults mainly include CO, CF₄, C₃F₈, C₄F₈, C₃F₆, and CF₃CN. According to the decomposition path of the C₄F₇N gas mixture, this paper selected three primary decomposition products (CO, CF₄, C₃F₈) and one secondary decomposition product (C₄F₈) for the correlation characterization of discharge types, and proposed the ratios of c(CO)/c(CF₄) and c(C₄F₈)/c(C₃F₈) as the characteristic quantities to characterize the different discharge types. Finally, in order to accurately identify the C₄F₇N/CO₂/O₂ gas mixture discharge type, this paper chose the decision tree algorithm to build a identification tree. The final identification result indicates that the ratio of c (CO)/c (CF₄) and c (C₄F₈)/c (C₃F₈) can be used as the identification criterion for typical discharge fault types.

In this paper, the molecular structure of the insulating gas was optimized on the B3LYP/DGDZVP theoretical level based on density functional theory, the molecular descriptors of the sample gas was obtained, and a gas insulation strength data set containing 47 kinds of gas molecules was established. According to the gas discharge theory and the molecular descriptor screening method, four molecular descriptors that have a significant impact on the insulation strength were obtained. The Multiple Linear Regression (MLR) method was used to establish the structure-property relationship model 1 between the gas molecule descriptors and the insulation strength. And on this basis, model 2 was established for gas molecules containing triple or double bonds, and the reliability and predictive ability of the model were significantly improved. The results show that the insulation strength of gas molecules is significantly related to_van der Waals volume ( V_m ), electrostatic potential positive ellipsoidized surface area ( A ⁺ _so ), highest occupied orbital energy ( E _HOMO ) and lowest unoccupied orbital energy ( E _LUMO ). When the molecular chemical bond type is considered, van der Waals surface area ( A_s ) and positive and negative electrostatic potential balance parameters ( v ) become the main factors affecting the strength of gas insulation.

In recent years, Chinese power enterprises have adopted SF ₆ /N ₂ to replace SF ₆ gas in transmission electrical equipment. In this paper, an experimental platform was set up to simulate the local overheating fault of gas insulated electrical equipment. The relationship between the decomposition products of SF ₆ /N ₂ gas and temperature, experimental time, gas pressure and SF ₆ content was studied. The results showed that the main products of SF ₆ /N ₂ gas decomposition were SO ₂ , SO ₂ F ₂ , N ₂ O, C ₂ F ₆ , COS, CS ₂ and CF ₄ . The content of SO ₂ increased nonlinearly with the increase of temperature, experimental time, gas pressure and SF ₆ content. However, the contents of SO ₂ F ₂ , N ₂ O, C ₂ F ₆ , COS, CS ₂ and CF ₄ decreased first and remained unchanged with the increase of gas pressure, and increased with the increase of temperature, experimental time and SF ₆ content. And C element in metal also affected the type and quantity of gas products.