Dynamic Temperature Correction Model and Experimental Study of Transformers Based on Distributed Optical Fiber Sensing
Year: 2026
Type: article
Abstract: The winding hot-spot temperature of power transformers is a key parameter for evaluating insulation aging and exploiting dynamic loading capability. To address the limited accuracy of conventional lumped-parameter models under dynamic loading conditions, this paper proposes a Dynamic Temperature Correction (DTC) model considering the temperature-dependent viscosity of insulating oil. By introducing real-time nonlinear correction factors, the proposed model dynamically corrects the oil time constant and winding time constant. Meanwhile, a 110 kV distributed optical fiber transformer was developed, and multi-condition temperature-rise tests were carried out. Short-circuit temperature-rise data under three different load rates and axial winding temperature distribution data under an 11-stage continuously varying load condition were obtained, revealing the winding hot-spot distribution and temperature evolution characteristics under different dynamic loading conditions. Based on the measured hot-spot temperature data from the distributed optical fiber transformer and the measured top-oil temperature data from an in-service 110 kV transformer, the calculation accuracy of the DTC model for hot-spot temperature and top-oil temperature was evaluated. The results show that the root mean square errors of the DTC model for hot-spot temperature and top-oil temperature are 1.71°C and 1.31°C, respectively, which are reduced by 22% and 46% compared with the IEC model. The experimental results indicate that the proposed DTC model can improve the calculation accuracy of transformer top-oil temperature and hot-spot temperature and has good potential for engineering application.
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,645
OpenAlex ID: W7172322234