The Swedish transport sector will need to undergo a major restructuring to achieve the established climate and environmental goals. The biggest change is that fossil fuels will be phased out and a larger part of the vehicle fleet will be electrified. This study deals with the electrification of heavy-duty trucks and how high-power charging stations affect the local electricity grid. Charging of heavy-duty trucks depends largely on the logistics of the transport system, which reduces the demand flexibility of power. High-power charging entails a risk of increased power peaks, which can affect the bus-voltage profiles, losses and loads on grid components. This thesis has been conducted as general study based on the case with the high-power charging station at Vädermotet in the area Hisingen of Gothenburg. The purpose was to build a generic model of the electricity grid at Hisingen and then investigate the consequences of high-power charging for the grid for two charging scenarios: the first scenario with four ABB Terra 360 chargers, and the second scenario with six ABB Terra 360 chargers and one MCS. The electricity network model and simulations were performed in PSS®SINCAL. The two charging scenarios, as well as the scenario before chargers were installed, were then simulated for three different system-load cases: maximum, average, and low load. The results showed that high-power charging of trucks had the biggest impacts for the voltage profiles during the case of low load. For the medium load and maximum load cases, the effect of the high-power charge decreased. Furthermore, electricity network losses increased for the low load case, but decreased slightly for the average and maximum load case. The reason was a more even load balance between the bus that connected the charging station to the grid and the rest of the network for the average and maximum load cases. In summary, the study indicated that grid implementation of a high-power charging station will have consequences for the local power system. However, the magnitude of the effects is not validated and can therefore only be regarded as indications. The outcome can be partly explained by the assumptions and simplifications of the model compared to the real system.