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It is a long‐term goal in external insulation studies to determine the discharge voltages of complicated engineering gaps by simulation methods. Based on the one‐to‐one correspondence between air gap structure and the static electric field (EF) distribution, this paper characterizes the transmission tower gap configuration by spatial EF features, which were used for machine learning to achieve switching impulse discharge voltage prediction. An interelectrode path and a conical zone between the energized sub‐conductor and the crossarm or the tower window were considered as EF regions strongly associated with gap breakdown, where 73 parameters were extracted to construct a feature set. Taking 15 extra‐high voltage (EHV) transmission tower gaps as training samples, with different gap distances and tower configurations, their EF features were input to a support vector machine (SVM) for model training to establish the relationships with discharge voltages. The trained SVM model was used to predict the impulse discharge voltages of 20 EHV and ultra‐high voltage (UHV) transmission tower gaps. The prediction results with different feature dimensions and various sizes of conical zones were compared to the experimental values, which demonstrate similar variation trends and acceptable errors. This study contributes to realize insulation strength calculation of engineering gaps.

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A high voltage current transformer of the inverted type is a commonly used measurement equipment in power grids. The thermal behaviour of the current transformer has a significant impact on its operating conditions and is directly related to its service life. The study presents a three-dimensional simulation model of a 220 kV inverted-type oilimmersed current transformer, and the fluid and temperature field are analysed by the finite volume method. The simulation results show that the hot-spot temperature under the rated load of the calculation model introduced in the study is 61.5°C, and located at the upper part of the core and the secondary winding. An experiment setup was designed to measure the temperature distribution inside a LVB-220W3-type current transformer. The temperature data measured under the rated load indicate that the simulation results agree well with the experimental results.