Abstract: The digital twin aims to construct the mapping of physical entities from the real space to the virtual model. Through the real-time closed-loop drive of the two-way interactive data, the real-time status and dynamic characteristics of the physical entities are simulated. As an important component in the power system, the distribution automation equipment will cause major economic losses to the power system if it fails. Based on the digital twin technology, this paper realizes the functions of information interaction, fault prediction, and early maintenance between the distribution automation terminal equipment and the distribution master station. The status evaluation comment set, the evaluation weight and the fault set are constructed and corrected in real time in the digital twin system through statistical analysis of the historical data and fault handling information collected byat the distribution automation terminals in a certain area. At the same time, an intelligent state evaluation and failure prediction model is built to provide a reference for the real-time monitoring of the state of distribution automation terminal equipment and a guidance for the distribution network operation and maintenance.