While the expected rise of electric vehicles (EVs) in The Netherlands could attenuate climate change, new challenges arise.; one challenge is that large-scale penetration of EVs could increase system costs. Specifically addressed is the integration of the EV in the Dutch local grid system: (1) the charging infrastructure and (2) the distribution grid. This thesis introduces the highly efficient Solar Electric Vehicle (SEV), the Dutch Lightyear One, as an alternative for the conventional Battery Electric Vehicle (BEV). A SEV is less dependent on the system by its low energy consumption and its integrated solar roof. This thesis aimed at uncovering the differences between the SEV and the BEV to explore to what extent SEVs could reduce the system costs of BEVs in the future energy system. The system integration costs were derived from an approximated load curve of an existing Agent-Based Model that modelled the local electricity demand system in urban, suburban, and rural neighbourhoods. A scenario in 2050 is exploited comparing a 100% BEV fleet with a 100% SEV fleet. The results showed that in a winter week, the SEV reduces the maximum required charging infrastructure up to ~3 times; a belonging cost difference of ~€8 billion was estimated until 2050. The difference is caused by the prognosed Dutch charging behaviour that is influenced by the smart charging strategy; and the low electricity consumption and electricity solar yields of the SEV accounting for respectively ~66% and ~34% of the cost reduction. In contrast to the charging infrastructure, the difference between the SEV and the BEV in grid impact was slightly visible in the peak loads. However, the difference is not significant enough to require extra grid reinforcements for the BEV compared to the SEV; no difference in costs for the grid was presented. In conclusion, an estimated total system cost saving of ~€8 billion caused by the reduced charging infrastructure requirement, was presented in this thesis. In this research, many assumptions were made to approximate the future load curve and the system costs of electric mobility. Due to sensitive parameters, the system costs measured are solely applicable to the scenario that is presented in this thesis.