Mitigation of transformers’ loss of life in power distribution networks with high penetration of electric vehicles

This paper presents a fuzzy-logic-based framework for aging mitigation of distribution transformers. At the first stage, a model for loading estimation of a transformer installed in the head of a power distribution network was developed in the MATLAB-Simulink environment. The model considers several factors that negatively affect the transformer's operation and lead to overheating of its windings, including high ambient temperatures, harmonic voltage distortions generated by nonlinear loads, reverse power flows, overloads due to high penetration of plug-in electric vehicles. At the second stage, a tuning algorithm was developed and measures aimed at optimizing the transformer's load level and power factor were elaborated. The developed model analyzes the parameters and factors that affect the normal operation of the transformer, and warns of the presence of dangerous factors that pose a threat to reliability and can lead to malfunction. Moreover, the effectiveness of photovoltaic generation units, shunt capacitor banks and battery energy storage systems, installed at the secondary voltage side, for distribution transformers' lifetime preserving were analyzed and discussed. The proposed measures allowed to reduce the transformer's loss of life more than 7 times, compared to the initial scenario. •A fuzzy-logic-based model is proposed as a framework to estimate the transformer's aging.•The effect of hourly variations of the ambient temperature is incorporated in the model.•The synergistic impact of EVs’ charging, power quality, and ambient temperature on the transformer’s lifetime is probabilistically assessed.•The efficiency of PV systems, BESSs, and shunt capacitor banks for transformers’ aging mitigation are studied.•A fuzzy-logic-based controller is implemented to prevent overloading of the transformer, while maintaining the desired PF.