The electrical system is currently undergoing a transition, where newhigh-power flexible loads, e.g., electric vehicles (EVs), are penetrating residential areas, and distributed power production from e.g., photovoltaic (PV) panels are also rapidly increasing in the low voltage (LV) grid. This transition requires new modeling methods to accurately predict the vulnerabilities and the needs to upgrade the current grid. A methodology to utilize spatiotemporal Markov based models of PV and EV charging to evaluate the impacts of these technologies on the high voltage (HV)/medium voltage (MV) substations is presented in this report. Furthermore, a case study on a large Swedish city was made. In this case study, penetrations of 100% for the EVs and PV were simulated. The results indicated that EV charging increases the peak load in the city by up to 18%–28%, and the peak load in the substations increased by up to 55%. During July, the PV yield was at most 45% of the winter consumption peak in the city and the summer-time net in-feed was at most 77% in any of the primary substations. Only 3 out of 10 substations experienced overloading events, and in all but one substation these events were shorter than 17 h/year. These overloading have negligible impact on the life-time of the main transformers as they predominantly occur when the ambient temperature is low. To avoid expensive upgrades to the MV transformers, the reserve transformers in the substations can be used to alleviate these overloading incidences. This solution however will not solve hosting capacity limitations in the underlying grid.