The urban and rural energy systems are undergoing modernization. This modernization is motivated by the need to increase sustainability in both systems. Some characteristics of this modernization include electrification of industries, transports, and heating and cooling loads. Additionally, there has been an increase in building-applied photovoltaic (PV) systems, and in the flexibility of customer loads. This thesis aims to progress the knowledge regarding the electric power production and consumption in the future urban and rural energy systems. In total, three models were developed and applied to case studies: a spatial electric vehicle (EV) charging model, a residential load forecasting model, and a clear-sky index (CSI) generative model. The results of the EV spatial model showed that there is an aggregation effect for the charging of the EVs. If all EVs charge opportunistically upon arrival using 3.7 kW, at most 19% of the EVs in a large area will charge simultaneously. Delaying the charging to after 22:00 will result in a significant increase in the simultaneity factor — to 59%. Two forecasting models were compared for the residential load. Both models achieved a root mean square error (RMSE) smaller than 4%. One model had a slightly sharper forecast than the other model — by 2.6% — and a variable prediction interval (PI) which decreased at night. As regards the spatiotemporal matching between PV power production and EV charging in rural and urban areas, the results showed that there were no correlations between the building type in each part of the city and the temporal matching. Both residential and workplace areas had similar temporal matching. This is because of the orientations of the roofs in the cities and the sizes of the parking lots. Considering the impacts of EV charging on the distribution grid of a Swedish municipality (Herrljunga), it is shown that 3.7 kW chargers will result in at most a 1% decrease in the voltage of the grid. No under-voltages were witnessed. In conclusion, the urban and rural energy systems can withstand the penetration of PV and EVs in the nearby coming years. Extreme scenarios might, however, require increasing the flexibility or performing upgrades to the systems.