Methodology to assess distribution transformer thermal capacity for uptake of low carbon technologies

Low-voltage network is concerned on the penetration of low carbon technologies. Distribution transformer thermal capacity is one of the most concerned, due to the aged and capital-intensive nature of the transformer fleet. Extensive studies have been done on this topic, and most of them have applied exiting thermal models such as IEC 60076 thermal model to estimate the hot-spot temperature (HST). However, it is lack of consideration on how accurate the thermal model is or how to refine the thermal model for more accurate estimation of HST. In this study, a methodology is introduced to improve the accuracy of IEC thermal model by refining its thermal parameters based on measured temperature data during the heat run test. Verification of the methodology under one 1 MVA 6.6/0.415 kV distribution transformer shows that the accuracy of predicting the HST is improved by reducing the maximum error from 25.8 to 3.6 K under constant loads and 8.15 to 4.16 K under cyclic loads. Also, a worst-case scenario study under the penetration of electric vehicles (EVs) shows the maximum penetration level of EVs is improved by 9% by applying refined thermal parameters to estimate the HST of the distribution transformer.