Data Model Transformation Method for Distribution Network Management System Based on CIM

With the development of the energy industry and the increasing maturity of intelligent technology, the requirements for power supply in distribution networks are also increasing. The traditional distribution network management mode mostly uses modular methods for data processing, which is difficult to meet the needs of complex power grid topology and massive data processing. The data collection module of the distribution network management system based on CIM (Common Information Model) is responsible for collecting various types of data from the distribution system, such as power grid topology, equipment status, load, etc. According to the mapping rules of CIM, the original data can be transformed into a structure and semantics consistent with CIM. The transformed data can be integrated into CIM to generate a comprehensive data model, and on this basis, compatibility and stability with existing systems can be achieved. In order to improve the performance and efficiency of the system and sustainably optimize and adapt the conversion methods, this study found that when the dataset size is 100 KB, the conversion time is 5 seconds, CPU (Central Processing Unit) utilization is 20%, and memory consumption is 50 MB. When the dataset size is 500 KB, the conversion time is 10 seconds, CPU usage is $\mathbf{3 0 \%}$, and memory consumption is 100 MB. The research results of this article can have important theoretical significance and application value in promoting the sustainable development of China’s energy industry.