Ultra-high frequency (UHF) detection method is highly accurate and has fault localization function. At present, most gas-insulated switchgear (GIS) systems are equipped with online UHF monitoring devices to detect partial discharges. In order to ensure the accuracy of the detection results, UHF sensors need to be verified regularly. UHF sensors used for on-line monitoring are usually installed at the handholes of the GIS and cannot be removed. Measuring laboratory verification indexes (e.g. equivalent height, dynamic range, etc.) of the sensors directly is very difficult. However, it is easier to measure S₁₁ of the sensor to be verified and S₂₁ between it and the neighboring sensors by injecting power signals. Accordingly, this paper presents a simulation study of the GIS partial discharge UHF sensor verification method based on the joint cross-comparison of S₁₁ and S₂₁. Firstly, the equivalent S-parameter network and the change characteristics of S₁₁ and S₂₁ during the verification of GIS UHF sensors are analyzed. Secondly, UHF sensors and degraded sensors caused by typical factors are modelled. Finally, the above sensors are coupled in the handholes of different structural GIS according to the actual situation. The S₁₁ and S₂₁ curves of various types of sensors are simulated and the accuracy of the simulation models are verified by experiments. Analyzing the results of this simulation model, S₁₁ is mainly related to the sensor performance and the handhole; S₂₁ is mainly related to the sensor performance and the GIS structure. Therefore, S₁₁ and S₂₁ can be used as indicators for on-site verification of GIS UHF sensors. Then, the performance of the sensors can be effectively verified by cross-comparing S₁₁ and S₂₁ at corresponding positions across different phases of GIS.

Radiator cooling configurations need to account for both efficient heat dissipation and energy conservation requirements. Rapid and rational determination of cooling system configurations constitutes a critical aspect of transformer design, enhancing electrical power energy utilization efficiency. Computational fluid dynamics (CFD) is widely recognized as a well-established technique for simulating and optimizing heat dissipation systems. However, this approach is time-consuming because of pre-processing procedures, such as meshing. This paper proposes a fast iterative optimization model for calculating the outlet oil temperature and airflow distribution. Based on the analytical model results, this paper identifies the optimal energy-saving range for radiator cooling configurations, incorporating the cooperative effects of cooling efficiency, air pressure drop during heat transfer, and inlet–outlet temperature difference. The analytical model demonstrated errors in energy dissipation and temperature difference calculations within an acceptable range. The calculation time was reduced by more than 99%. Radiator configurations within the optimal range effectively minimize energy waste while meeting the target temperature difference and enhancing cooling efficiency. Finally, the PC2600-22/520 radiator was utilized to validate the accuracy of the analytical model and the rationality of the co-optimal intervals.