SF₆, which is currently widely used in gas-insulated power transmission equipment, is a greenhouse gas with a very strong greenhouse effect. Therefore, developing environmentally friendly gas insulation equipment to gradually reduce the use of SF₆ has become a hot research topic. As the most potential alternative gas, C₄F₇N is of great significance to study the electrical characteristics of the medium-voltage switching field to promote the green development of the power industry. Based on multi-physical field coupling to construct the 40.5 kV circuit breaker mode, this paper uses C₄F₇N/CO₂ mixed gas to compare and study the dynamic characteristics of a C₄F₇N/CO₂ mixed gas circuit breaker when breaking the short-circuit current and the dielectric recovery strength with no-load breaking, as well as to evaluate the electrical performance of C₄F₇N mixed gas in a 40.5 kV breaker with the gas breakdown criterion. The results show that mixing O₂ in a high current can improve the breaking performance of an environmental protection circuit breaker and increasing the C₄F₇N mass fraction can enhance the dielectric recovery strength of the environmentally friendly circuit breaker. Considering the overall performance of the gas, the 5%C₄F₇N/90% CO₂/5%O₂ mixed gas has some alternative potential.

Aiming at the economic benefits, load fluctuations, and carbon emissions of the microgrid (MG) group control, a method for controlling the MG group of power distribution Internet of Things (IoT) based on deep learning is proposed. Firstly, based on the cloud edge collaborative power distribution IoT architecture, combined with distributed generation, electric vehicles (EV), and load characteristics, the MG system model in the power distribution IoT is established. Then, a deep learning algorithm is used to train the features of the data model on the edge side. Finally, the group control strategy is adopted in the power distribution cloud platform to reasonably regulate the coordinated output of multiple energy sources, adjust the load state, and realize the economic operation of the power grid. Based on the MATLAB platform, a group model of MG is built and simulated. The results show the effectiveness of the proposed control method. Compared with other methods, the proposed control method has higher income and minimum carbon emission and realizes the economic and environmental protection system operation.