Dry-Type Transformers in Intelligent Monitoring and Health Assessment Based on Digital Twin Technology

Establishing an intelligent operation and maintenance system for distribution network dry-type transformers from two aspects: online measurement of winding operating temperature through interference methods and health status assessment based on holographic temperature data twin technology. Fiber Bragg grating temperature sensors are quasi-distributed and embedded within the high and low voltage winding units of the transformer. The grating temperature measurement and control unit acquires the winding temperature data during operation, enabling the construction of a digital twin temperature model for dry-type transformer windings. By analyzing the variation patterns of the holographic temperature data from the model, a fault early warning method and a dynamic capacity regulation method for dry-type transformers are proposed. Test results on the interference-based transformer temperature measurement demonstrate that fiber Bragg grating technology achieves highly accurate temperature measurements up to 180° C, with a maximum temperature error of only 1.4%.