Mitigating Transformer Loss of Life and Reducing the Hazard of Failure by the Smart EV Charging

The impact of uncoordinated charging of electrical vehicles (EVs) under high penetration on distribution transformers is studied. It was shown that EV charging may cause prolonged transformer overload condition, that may in turn result in transformer loss of life and increased hazard of failure. To mitigate the impact, a fuzzy logic-based system for determining EV charging schedule is devised. It uses four main inputs: 1) EV battery state of charge; 2) required state of charge for the next trip; 3) estimated time of EV departure; and 4) customer comfort level. The resulting output is a performance index that the distribution system operators can utilize in a decision-making tool to determine whether to delay the charging of given EV and pay the incentive to the EV owner. The data for the city of College Station, Texas, USA including temperature, price of electricity and load profile are collected from various sources to simulate different use cases. The example illustrates how the proposed EV management approach could mitigate the impact of EV charging on the transformer loss of life and hazard of failure. The main advantage of the proposed approach is the low cost due to simple design implementation. The information that needs to be sent from the consumer to the distribution system operator is minimized, which helps in maintaining costumers' privacy.