Plug-in electric vehicles (PEV) have been identified as an option that can reduce criteria pollutant and greenhouse gas emissions associated with the transportation sector. The electricity demand of one of these vehicles is comparable to that of a typical U.S. household and thus clustering of PEVs in a neighborhood might have adverse effects on the transformer and disruption of service. In this paper, the electricity demand of a neighborhood is modeled based on measured vehicle and household data. The electricity demand profile of the PEVs is modeled based on the vehicle type, arrival and departure times and the daily miles traveled, all taken from the National Household Travel Survey (NHTS). A thermal model is developed to calculate the hot spot temperature and loss of life of the transformer. Results show that Level 1 charging has a small impact on the transformer aging and that only in one case, with Level 2 charging, the transformer might fail due to excessive temperatures. Overall addition of a significant number of PEVs is manageable for the transformer. The negative effects on the life time can be mitigated by properly designing the transformers and using smart charging scenarios.