Predicting the Temperature Rise in Oil-Immersed Transformers Based on the Identification of Thermal Circuit Model Parameters

The temperature rise test for transformers is time-consuming, energy-intensive, and has low detection efficiency. To improve the efficiency of the temperature rise test and reduce energy consumption, this paper proposes a temperature rise prediction method for oil-immersed transformer windings. This method is based on identifying the parameters of a thermal circuit model. Firstly, a fifth-order thermal circuit model of oil-immersed transformers is put forward. Then, based on a two-hour temperature rise curve, the thermal capacity and resistance model is identified through genetic algorithms. The obtained parameters are used to compute the temperature rise curve, steady-state average temperature rise, and top oil temperature rise. The results show that the heat capacities of the low-voltage (LV) winding, high-voltage (HV) winding, oil tank, and oil of a 400 kVA transformer are approximately 50 kJ/K, 75 kJ/K, 320 kJ/K, and 90 kJ/K, respectively. Additionally, the thermal resistances from the LV winding to oil, HV winding to oil, oil tank, and air are about 8 mK/W, 5 mK/W, 1 mK/W, and 11 mK/W, respectively. When the transformer capacity increases, the heating power of the windings escalates, and the oil resistance of HV windings decreases from 8 mK/W for a 400 kVA capacity to 5 mK/W for an 800 kVA capacity. The absolute prediction error for transformers of 400 kVA, 630 kVA, and 800 kVA is 2.9 °C. These findings can facilitate the swift detection and assessment of the winding temperature rise in oil-immersed transformers.