The high pulsating demand of fast charging stations (FCS) may cause monthly demand charges to account for a significant fraction of a station's electric bill. To reduce these costs, demand charge management can be applied to suppress peak power demands at FCSs, also using battery energy storage systems (BESS). This paper proposes a multi-objective approach for the optimal BESS and grid-tie sizing in FCS designs using genetic algorithms. With demand data from a FCS in the Netherlands, numerical studies are conducted in the Mosaik and Pymoo environments to assess the effectiveness of the proposed formulation.@en