Analysis of Charging Patterns of Electric Vehicles, Case Study in Uppsala, Sweden.

Abstract: Electric vehicles (EVs) are used instead of fossil fuel-burning vehicles to reduce greenhouse gases. The increased rate of utilizing EVs has an impact on the electric power system. This is due to the fact that EVs are loads that increase the peak demand. From these perspectives, this thesis studies the load of the electric chargers in a parking house in Uppsala and studies the effect of adding battery storage systems. The cost of used electricity is also calculated at different battery storage system (BSS) capacities, and the electricity bill is evaluated at these different conditions.  The data used in this work was collected from a parking house allocated in Uppsala city in 2021. It is equipped with 30 charging stations and 60 charging points in total. In addition, the parking house is connected to a PV system with two racks of batteries with a capacity of 137kWh. The surplus power generated by the PV system is sold to the grid. The data from the PV production and EVs demand is analyzed using MATLAB. The electricity price used in this study is from a standard contract from Vattenfall, with different prices at day and night (0.144 SEK/kWh at night and 0.48 SEK/kWh during day time). The battery is charged during the night, at a lower price, and discharges during the day. The excess power from the PV is also stored in the battery as self-consumption is more profitable than selling it to the grid.  The results show that the installed BSS units reduce the overall cost of the load as compared to those without BSS units. By studying the system under different battery capacities, the electricity bill is reduced to a certain limit. However, the increase in storage capacity beyond 137 kWh has no effect on the overall electricity cost. This maximum limit of the BSS unit's capacity would be greatly affected by the size of the installed PV system and the number of EVs to be charged. Controlling the charging and discharging periods has a significant impact on reducing the system cost.