Behaviour-driven electric vehicle charging decisions and its implications on demand response flexibility for the integration of renewable energies in Germany

The expected increase in battery electric vehicles poses both, opportunities and risks for the decarbonisation of future power systems. While electric mobility may technically serve as a source of flexibility, it increases the overall power demand and may as well increase peak load demand. Electric mobility in national and continental scale energy system optimization is often treated in an aggregated fleet, however user behaviour and charging decisions play a crucial role in the availability of vehicles' batteries for balancing electric load and renewable energy (RE) feed-in. Michaelis, Gnann & Klingler (2018) find that reduction of peak load and RE surplus electricity stemming from battery electric vehicles (BEVs) in Germany may be as high as 2.2 GW and 1.8 TWh respectively for 2030. However, they assume constant charging stations’ power of 3.7 kW that seem conservative. Also, the authors don’t explicitly describe to what effect user behaviour limits vehicle charging. By linking the modular energy system optimization model REMix with the vehicle stock model VECTOR21 and the charging decision simulation tool CURRENT, we aim to determine a more realistic demand response potential for future electric vehicles compared to previous studies. All three models are developed at the German Aerospace Center (DLR) and have been applied and validated in different project contexts. We for the first time integrate hourly profiles determined by individual charging decisions as input for an energy system optimization model. Thereby, we determine the reduction potential of peak load, RE curtailment as well as RE capacity expansion for the different cases of controlled charging versus uncontrolled charging for Germany for 2030. Thus, we provide both methodological and quantitative insights into the effects of coupling power and transport sector that are of value to the scientific discussion