Although electric vehicles were first used as early as the 19th century, they have only recently gained popularity. By charging them with renewable sources, electric vehicles present a route to zero or low emission mobility. This is a significant reason for their recent popularity given the climate crisis. However, the integration of electric vehicles comes with a unique set of problems, such as over-loading of grid elements and under-voltages of nodes. The integration of photovoltaic generation is also another source of complexity. The focus of this thesis is to investigate the influence of electric vehicles and solar generation in low voltage power grids.
Different charging algorithms are analysed and compared to the uncontrolled charging scenario. The price based charging algorithm is a centralised control strategy. The other three algorithms - average rate charging, nodal voltage charging, and smart charging - are decentralised strategies. Each of these algorithms manipulate the charging power at different chargers in the grid according to their specific conditions.
The aforementioned algorithms are tested by performing simulations in three types of German distribution grids: rural, urban, and sub-urban. These simulations are carried out for High PV, Low PV, and No PV scenarios. In all three grids, there is neither over-loading of equipment nor under-voltage of nodes in the No PV case. The under-voltages are improved due to photo-voltaic generation. In the High PV case, excessive generation causes over-loading and over-voltages in the sub-urban grid. The possibility of using electric vehicles as dynamic storage elements has been explored. Based on the insights obtained from the grid simulations, the performance of different charging algorithms is analysed and compared in this thesis.