In this study, a simulation model of surface charge accumulation has been established. The model considers three accumulation ways, i.e. electrical conduction within the gas, through insulator volume and along the insulator surface. The generation, diffusion, drift and recombination of charge carriers are also taken into account. Based on it, the influence of polarity reversal, reversal time on surface charge and electric field distribution on a basin‐type insulator are studied. The polarity of the surface charges and the direction of the electric field change after the voltage polarity reversal. When the preload voltage is equal to reversal voltage, the surface charge and the electric field distributions at steady state before and after voltage polarity reversal are all the same with opposite sign, and not affected by the reversal time. However, the time to reach the steady state varies with different reversal time. The steady‐state surface charge and electric field increased with the rise of reversal voltage. The transient normal and tangential electric field would not exceed the value of the steady state, which means voltage polarity reversal has no additional influence on insulation performance. This research can provide guidance to the design and manufacture of DC GIS/GIL.

The use of SF6 gas decomposition components for the fault diagnosis of gas insulated equipment (GIE) has received widespread attention and been extensively adopted by the power industry. However, the present focus is mainly the use of a component type or absolute content for generating qualitative judgments on the existence of a fault, and the practical diagnosis method for field diagnosis is extremely lacking. In this paper, ten-year fault data were collected and analyzed. Decomposition components were extracted and combined based on the decomposition characteristics of SF6, and enhancement factors were given to three component characteristic quantities using fuzzy C-means clustering algorithm (FCM). The component characteristic quantities that characterized the high-energy discharge fault, partial discharge, and partial over-thermal fault of the device were extracted: % $\rm (SOF_{2}+SO_2)$ , % $\rm (9SO_{2}F_2)$ , and % $\rm (5CO_2)$ . With adoption of these characteristic quantities as the coordinate axes of the triangle coordinate system, a triangle fault diagnosis method for field diagnosis of SF6 GIE was constructed. The diagnosis method was validated by a large number of experimental data and field failure data, and 128 of the 150 experimental samples were correctly recognized. Moreover, the test conditions did not considerably affect the diagnostic results of the method. This technique can provide a simple and effective field diagnostics technology for the power industry.

This study mainly aims to obtain the decomposition characteristics of SF6 under various degrees of negative partial discharge (PD) and establish a method for evaluating internal PD fault for gas-insulated equipment (GIE). Thus, metal protrusion, a frequent insulation defect in DC GIE, was used in the study of PD characteristics from the initial discharge to the near breakdown process. Then, seven parameters for characterizing the development stage of PD were extracted, and the fuzzy C-means clustering algorithm was used for the categorization of PD into three degrees, namely, slight, medium, and severe. We performed SF6 decomposition experiments on the PD degrees to obtain the decomposition characteristics. Results show that the SF6 decomposition characteristics (formation and content variation of five characteristic components, namely, CF4, CO2, SO2F2, SOF2, and SO2) are closely related to PD status. Fuzzy comprehensive evaluation theory was used for the establishment of a PD fault status assessment model, which was based on SF6 decomposition characteristics. Then evaluate the collected samples and the accuracy of the evaluation method is up to 87.5%. This paper lays the foundation for the future comprehensive assessment and fault diagnosis of insulation status of DC GIE on the basis of SF6 decomposition characteristics.

Based on the physical phenomena of optical effects produced by the partial discharge (PD) and on the characteristics of fluorescent fiber sensing of weak fluorescent signals, a PD measurement system using a fluorescent fiber sensor was designed. The main parameters of the sensing system were calculated, an experimental testing platform for PD simulation in the lab was established, and PD signals were then detected through ultra-high frequency (UHF) and optical methods under a needle-plate discharge model. PD optical pulses in transformer oil contained signal-peak and multi-peak pulse waveforms. Compared with UHF detection results, the number of PD pulses and the elapsed PD pulse phase time revealed a good corresponding relationship. However, PD signal amplitudes presented the opposite, thus indicating that PD UHF signals reflected pulse amplitude value, whereas PD optical signals reflected pulse energy magnitude. The n-u-φ three-dimensional distributions indicated that most of the PD signals concentrated in the nearby industrial frequency voltage peak value. Overall, the proposed fluorescent fiber sensing system design can be used successfully in transformer PD signal detection.

Bubble is a typical insulation defect in transformer oil, which can easily initiate partial discharge (PD) during the operation of transformer. Moreover, it migrates along with the oil flow and may be deformed due to the forced oil circulation and temperature difference within transformer bulk, leading to the complexity of PD characteristics and PD mechanism. However, the understanding of to this phenomenon is not clear. In order to identify it, finite element method was employed to simulate the movement process and deformation of bubbles, as well as electric field distribution under the conditions with different oil flow rates. In addition, numerous experiments were performed, mainly including the change of PD ϕ-q and ϕ-n patterns with oil flow rates. By comparing the simulation and experimental results, it is found that PDs are mainly concentrated in the negative half-cycle. Electric force causes bubbles to stretch along the electric field direction. At the stationary condition, bubbles eventually exhibit horizontal stretching and cause maximum electric field distortion. However, bubbles eventually exhibit vertical stretching in flowing oil. Flowing oil can significantly reduce PD intensity. The PD intensity declines rapidly with the increase of the flow velocity, and then increases slowly.

At present, reports on the arc interruption and decomposition behavior of a C ₄ F ₇ N/air gas mixture especially the biosafety of its by‐products are limited. Herein, a 57% C ₄ F ₇ N/43% air gas mixture was employed as an arc‐quenching medium to conduct 200 breaking tests on a load switch (630 A/24 kV). The arc interruption and decomposition behavior of the gas mixture were evaluated, and the biosafety of the decomposition products was assessed based on an acute inhalation toxicity test. It was found that the average arcing time of the 200 breakings was about 10.1 ms and that breakings were basically completed at the zero‐crossing of the second or third current half‐cycle. The gas mixture after breaking decomposed dramatically (the C ₄ F ₇ N content decreased by 75.6%), generating a large number of gaseous by‐products (CO, CF ₄ , C ₂ F ₆ , C ₃ F ₈ , CF ₃ CN, C ₄ F ₈ , CO ₂ , C ₄ F ₁₀ N ₂ , C ₃ F ₆ , C ₂ N ₂ , etc.) as well as solid by‐products (carbon particles). The lethal concentration of 50% (LC50, 4 h) of C ₄ F ₇ N/air after 200 breakings was 31 ppm (male mice) and 34 ppm (female mice), respectively, and the toxicity was classified as Grade 1. In general, C ₄ F ₇ N has an arc interruption capability, albeit weaker than that of SF ₆ under the same conditions. After breaking, the C ₄ F ₇ N gas mixture has a relatively high acute inhalation toxicity, and relevant safety protection measures for research or operation personnel are strictly needed.