Visual Evaluation of Digital Transformer DP Based on Virtual and Real Sensing

The development of digital twin transformers is of great significance for supporting the intelligent and digital operation and maintenance of transformers. However, due to the lack of corresponding digital twin capabilities, many deficiencies still exist in current transformers. To address this, this study investigates a virtual-physical fusion method for simulating internal parameters of transformers. First, the distributions of temperature fields and moisture content were calculated. Subsequently, a dynamic evolution model of the degree of polymerization distribution was established. Finally, the visualized results of the degree of polymerization distribution at any given time were obtained. The results indicate that the maximum moisture content distribution reaches approximately 3.2% in the 48th year, and the degree of polymerization distribution is 252.15 in the same year. This research achieves an evaluation of the internal aging parameter distribution of transformers, providing a data foundation for the subsequent development of digital twin transformers.