State Evaluation of Power Transformer Based on Digital Twin

Abstract

Transformer is the key substation equipment in power system. The data accumulated during system operation can provide information for further state evaluation and fault diagnosis to ensure safe and stable operation of power system. However, these data are uncertain and the evaluation is based on experience, which makes the state evaluation of transformer still a challenge. At present, digital twin, which could represent the features of any objects or subjects, has received widely attentions from various regions, while its application in power system is still limited. Therefore, this paper proposes a transformer state evaluation approach based on the digital twin. This approach establishes a digital twin model of power transformer, and acquires the sample data and labels from the simulation process and state evaluation under various condition. These sample data and labels will guide the decision making of state evaluation in the real situation. This paper compares the sample data and labels from the digital twin model with those from the physical system, so that the performance of digital twin model and real system would be promoted during this mutual amendment progress.