Test and Analysis on Extended Temperature Rise of 110 kV Transformer Based on Distributed Temperature Sensing

Abstract

Transformer plays a vital role in grids and its internal hot-spot temperature is a crucial monitoring parameter. In this paper, three groups of temperature rise tests with the load rate of 70%, 100%, and 125% were carried out on a 110 kV transformer with built-in distributed sensing fiber. Based on the distributed temperature sensing technology, the temperature distribution of winding was acquired. Accuracy of IEC, Susa, and Swift thermal models was compared. To eliminate the non-negligible error in cooling process, a modified-Susa model based on driving factor and steady-state temperature rise was proposed. Using this, the top oil temperature prediction error during operation and cooling is reduced. In addition, the real-time tracking of hot spots and analysis of overall temperature gradient of windings was implemented. The accuracy of different hot spot calculation models was also compared. Results show that the prediction accuracy of each model is satisfactory during the operation, but the error during the cooling process cannot be ignored. The refined temperature distribution of the winding was also obtained by the high-resolution Brillouin optical time-domain analysis sensing method. Periodic temperature fluctuations and local hot spots inside windings are perceived, which is confirmed to be closely related to winding geometry.