he integration of future grid customers, e.g., electric vehicles, heat pumps, or photovoltaic modules, will challenge existing low-voltage power grids in the upcoming years. Hence, distribution system operators must quantify future grid reinforcement measures and resulting costs early. On this account, this work initially evaluates different methods to quantify future grid reinforcement needs, applied by the current state of research. Thereby, it indicates the significance of large-scale grid simulations, i.e., simulating several thousand low-voltage grids, to quantify grid reinforcements accurately. Otherwise, a selected area’s total grid reinforcement costs might be misjudged significantly. Due to its fast application, deterministic grid simulations based on coincidence factors are most commonly used in the current state of research to simulate several thousand grids. Hence, in the second step, recent studies’ approaches to applying grid customers’ coincidence factors are evaluated: While simplified approaches allow fast simulation of numerous grids, they underestimate potential grid congestion and grid reinforcement costs. Therefore, a fully automated large-scale grid simulation tool is developed in this work to allow the simulation of multiple grids applying grid customers’ coincidence factors appropriately. As a drawback, the applied deterministic framework only allows an estimation of future grid reinforcement costs. Detailed determination of each grid’s grid reinforcement costs requires time-resolved grid simulations.