This research presents a flexibility simulation tool developed under the EU-funded project AHEAD to address the challenge of managing EV charging in parking facilities with limited grid capacity. Using field data from an industrial campus in Lisbon, Portugal, the study demonstrates practical solutions for minimizing peak loads in congested secondary substations through load shifting strategies. The tool optimizes charging schedules for over 60 charging points connected to a single 630 kVA substation. It employs Linear Programming (LP) techniques to implement load shifting strategies, considering individual vehicle requirements, arrival and departure times, and grid constraints. Monte Carlo Simulation is used to evaluate future scenarios with varying EV adoption rates and usage patterns. Three primary scenarios were tested: standalone configuration, integration with photovoltaic generation, and integration with bidirectional chargers. Preliminary results show significant potential for peak load reduction, achieving 20-30% reductions compared to uncontrolled charging. The bidirectional charging scenario shows a reduced impact for large homogenous EV fleet clusters. The tool demonstrates that controlled charging management can substantially improve infrastructure utilization efficiency, offering valuable insights for facility managers and grid operators to enhance existing infrastructure capacity without costly investments.