The 2050 carbon‐neutral vision spawns a novel energy structure revolution, and the construction of the future energy structure is based on equipment innovation. Insulating material, as the core of electrical power equipment and electrified transportation asset, faces unprecedented challenges and opportunities. The goal of carbon neutral and the urgent need for innovation in electric power equipment and electrification assets are first discussed. The engineering challenges constrained by the insulation system in future electric power equipment/devices and electrified transportation assets are investigated. Insulating materials, including intelligent insulating material, high thermal conductivity insulating material, high energy storage density insulating material, extreme environment resistant insulating material, and environmental‐friendly insulating material, are categorised with their scientific issues, opportunities and challenges under the goal of carbon neutrality being discussed. In the context of carbon neutrality, not only improves the understanding of the insulation problems from a macro level, that is, electrical power equipment and electrified transportation asset, but also offers opportunities, remaining issues and challenges from the insulating material level. It is hoped that this paper envisions the challenges regarding design and reliability of insulations in electrical equipment and electric vehicles in the context of policies towards carbon neutrality rules. The authors also hope that this paper can be helpful in future development and research of novel insulating materials, which promote the realisation of the carbon‐neutral vision.

The transformers work in a complex environment, which makes them prone to failure. Dissolved gas analysis (DGA) is one of the most important methods for oil-immersed transformers’ internal insulation fault diagnosis. In view of the high correlation of the same fault data of transformers, this paper proposes a new method for transformers’ fault diagnosis based on correlation coefficient density clustering, which uses density clustering to extrapolate the correlation coefficient of DGA data. Firstly, we calculated the correlation coefficient of dissolved gas content in the fault transformers oil and enlarged the correlation of the same fault category by introducing the amplification coefficient, and finally we used the density clustering method to cluster diagnosis. The experimental results show that the accuracy of clustering is improved by 32.7% compared with the direct clustering judgment without using correlation coefficient, which can effectively cluster different types of transformers fault modes. This method provides a new idea for transformers fault identification, and has practical application value.

Disruptions in ground communications during disasters significantly impede unmanned aerial vehicle (UAV)-based power line inspections, slowing down fault localization and threatening system secure operation. This paper proposes a spatiotemporal precise routing strategy for the integrated satellite-terrestrial network, focusing on achieving stable communication and balanced energy consumption among the UAV swarm under signal fluctuations. Here, satellite internet and flying ad-hoc network (FANET) are fully utilized concurrently, which is tailored to practical demand of post-disaster power line inspections and overcomes communication collapse. The proposed strategy features superior flexibility and resilience in various complex and hostile environments. The simulation results demonstrate that the proposed strategy outperforms traditional routing algorithms, supporting stable signal transmission for multi-UAV-based power line inspections, extending cluster operational time, and enhancing the speed of post-disaster power system recovery.

The presence of deteriorated insulators in power grids poses a significant threat to the safety of power transmission. The Electric Field Detection Method (EFDM) is considered an effective approach for detecting low or zero value insulators on high-voltage transmission lines. In this paper, we analyzed the effects of the detection device, measurement angle, and insulator deterioration on the axial electric field value of insulator strings using both test values and simulation values. Our results indicated that the detection device had minimal impact on the normalized values of the axial electric field, whereas the measurement angle affected the values. However, the errors between the test values and the simulation values at the ends of the insulator strings were larger, indicating that the measurement device is better suited for measuring at non-ends of the insulator strings. Based on our findings, we used the detection device to measure the electric field of insulator strings on a 220 kV transmission line. The results of the measurement showed that the electric field detector could accurately measure the axial electric field of the insulator string and detect deteriorated insulators, thereby providing a more effective measurement method. Our research thus confirms the feasibility of the electric field detection method in actual power transmission lines.