Traditionally, electricity grids were built to distribute electricity from large producers to consumers with an inflexible load. As more sectors are electrified, such as passenger cars, and electricity production becomes increasingly decentralized in terms of solar and wind power, greater stress is exerted on the local electricity grid and on its ability to connect production and demand in both space and time. An expected challenge to distribution grids is large-scale home charging of electric vehicles (EVs). Electricity costs can be split into the cost of electricity production, typically captured in an electricity price, and the cost of distribution, typically captured in a network tariff. Previous work has focused on the impact of electricity price on EV charging, however, little work has been done on the impact of network tariffs. Yet, these network tariff systems may need to be adjusted to promote desired behaviors and reduce the need for grid reinforcements. Therefore, this study examines how different network tariff designs impact the charging of EVs and the peak power on the local electricity grid.

A dataset of logged EV data is used in a cost-minimizing linear optimization model together with electricity spot prices and different network tariff designs to study EV charging behavior applying three different network tariff designs. The tariff designs consider annual peak power per household, monthly peak power per household, and/or annual peak power in the local grid. Preliminary results show that the two tariffs that only consider the peak power of individual households have a limited impact on cost-optimal EV charging and therefore the total peak power in the local electricity grid. However, the tariff design that considers the whole load on the local grid tends to move charging in time to a larger extent than when only considering individual households. It lowers the coincidence of EV charging and thereby the peak power on the local grid. It can be concluded that the design of the network tariff can alter the EV charging behavior and, through that, lower the burden on the local electricity grid. Future studies will describe and compare additional tariff designs, as well as look into how they impact the need for grid reinforcement.