TY - GEN A1 - Parlikar, Anupam A1 - Schott, Maximilian A1 - Kucevic, Daniel A1 - Hesse, Holger C. A1 - Jossen, Andreas T1 - Battery-Assistance vs. Grid Reinforcement for High-Power EV Charging: An Emissions Perspective T2 - Energy Sciences for Europe’s Green Deal N2 - An increasingly large number of battery electric vehicles (BEVs) and electric buses are hitting the roads globally each year. These numbers are expected to grow further in light of ever-more favourable costs, and improved battery technology that addresses concerns about range anxiety and charging times. This upward trend in electrification of the automobile sector essentially shifts the mobility energy demand from the oil & gas sector to the electricity sector. Power transmission bottlenecks in the grid, caused on the supply-side by periods of strong renewable generation, may get further aggravated by adding demand-side bottlenecks to the mix as well. The grid, at several locations, will need to be overhauled to be able to supply huge bursts of power intermittently to cover large power demands to support fast-charging simultaneously at multiple locations. This can entail huge monetary investments for the upgradation of grid infrastructure. Battery-assisted high power charging (BA-HPC) is thought of as a convenient solution to this problem. This solution enables demand-side peak- load shaving, and draws energy more uniformly over extended periods of time. While this solution may well be economically profitable in some cases, an investigation of the environmental impact of this solution can yield interesting insights, and aid decision-makers by identifying scenarios in which one solution is more favorable over the other. This is crucial, since the rationale for shifting to electromobility is the curbing of greenhouse gas emissions. In this work, we employ in-house python-based time-series analysis simulation tools to simulate the grid reinforcement and the battery energy storage systems, and present comparative lifetime emissions analyses for both solutions in a variety of configurations. Y1 - 2021 UR - https://opus4.kobv.de/opus4-hs-kempten/frontdoor/index/index/docId/1388 VL - 2021 SP - 18 EP - 18 PB - Technische Universität München, Munich School of Engineering CY - Garching ER -