Renewable energy integration is increasing – alongside it, the main limiting factors of such sources of energy have to be considered. Each source of energy comes with its unique sets of challenges, namely the way that the generation curves behave. These patterns should be considered, if photovoltaics can contribute at a larger rate to the grid. The current non-renewable sources provide a high response rate and great control over voltage/frequency – key parameters of the grid. Proper utilization of renewable energies is key to sustainable systems of the future.The work considers the possibility of regulating the energy flow through the usage of electric vehicles (EV). The thesis proposes a model within which particle swarm optimization is used to derive EV charging rates, which contribute to the overall performance of a controlled household system. Three control strategies are considered – individual, bottom-up and top-down control. The methodologies are introduced and compared in the study.Top-down control proves to be the most stable and most efficient at reducing energy mismatch when compared to other control strategies. It should however be underlined that any control strategy proposed in the study leads to a greater utilization of renewable energy and can greatly benefit any system with EVs and PV energy present.