Electric mobility imposes an increase in power demand on electrical power systems, which may vary by space and time. Additionally, the intrinsic variability of renewable generation sources, especially photovoltaic generation, significantly increases the uncertainties linked to the operation of electrical systems. Therefore, this research aims to study the impacts of the diffusion of photovoltaic generation systems (PVs) and electric vehicles (EVs). In this context, this study proposes a stochastic mathematical model of electric vehicle charging demand to obtain probabilistic performance indicators. The proposed methodology consists of three main steps: (a) definition of PV and EV penetration scenarios; (b) modeling of probability distribution functions for solar photovoltaic generation, EV charging cycles, and demand behavior; and (c) application of Monte Carlo Simulation technique to evaluate the integration categorization. In the scenarios evaluated based on data from a real electrical energy distribution network, the probabilities of occurrence of overvoltages, overloads, and power factor violations will be presented. These findings underscore the critical role of synergizing smart grid technologies with PV operations to develop advanced functionalities capable of dynamically managing EV charging cycles and PV output in response to evolving grid conditions and user preferences.