The influence of electric vehicle charging strategies on the sizing of electrical energy storage systems in charging hub microgrids

Economic, ecologic, and social benefits support the rapid diffusion of grid -connected microgrids (MG). Economic feasibility still stands out as the primary goal of commercial MGs. A stationary electrical energy storage system (ESS) is often a central component of MGs, facilitating islanding and cost-effective management of main grid use. Therefore, previous research has focused on the sizing of stationary ESS. The advent of large-scale electric vehicle (EV) charging hub MGs (CHMGs) such as the one along the freeway A8 near Augsburg, Germany, profoundly changes the economically optimal capacity of stationary ESS. While it is well conceived that EVs can be aggregated and then compensated for stationary ESS, research still lacks quantifiable evidence and metho- dological guidance on how the charging strategy (immediate, controlled, bidirectional) influences the eco- nomically optimal capacity of the stationary ESS. To address this gap, this paper proposes a method that includes a mixed -integer linear programming model for scheduling decisions under various conceivable ESS capacities and provides scenario analyses on the EV charging strategies as well as on ESS cost. Thereby, the method thus identifies the economically optimal capacity of the ESS. The results show that in the considered CHMG near Augsburg, the stationary ESS sizing decision is relevant in all but extreme scenarios. In particular, the eco- nomically optimal stationary ESS capacity soars if more than 65% of the EVs begin to charge immediately and the storage costs falls below 150 EUR/kWh. In contrast, smaller portions of controlled charging EVs can already drastically reduce stationary ESS. Remarkably, this paper also gives quantitative evidence that investments in bidirectional charging do not to pay off in the CHMG near Augsburg.