This research presents a flexibility simulation tool developed under the EU-funded research project AHEAD that considers a growing challenge of managing electric vehicle charging in parking facilities with limited grid capacity. Based on field data collected at a industrial campus in Lisbon, Portugal, the research demonstrates practical solutions for minimizing peak loads in congested secondary substations through load shifting strategies.

The research focuses on developing a flexibility simulation tool to optimize charging schedules in parking lots experiencing substation congestion. The demonstration site has over 60 charging points of 11 kW and a 120-kW e-bus charger connected to a single 630 KVA secondary substation at the Labelec campus. The simulation tool processes real user charging requirements and parking duration to create optimized charging schedules that satisfy user needs while minimizing peak power demand.

Our approach employs Mixed Integer Linear Programming (MILP) techniques to implement load shifting strategies among different EVs. The optimization algorithm considers individual vehicle charging requirements, arrival and departure times, and grid constraints to determine optimal charging schedules. To evaluate future scenarios with varying EV adoption rates and usage patterns, we implemented a Monte Carlo Simulation method.

Three primary scenarios were tested: 1) the current standalone configuration, 2) integration with photovoltaic generation and 3) integration with three bidirectional 11kW chargers (one being wireless). These scenarios reflect both current operations and planned upgrades at the demonstration site. The testing environment represents realistic conditions with peak charging patterns following typical office hours with a daily consumption occasionally exceeding 300kWh.

Preliminary results demonstrate significant potential for peak load reduction through optimized charging schedules. The implementation of load shifting strategies achieves 20-30% reductions in peak power demand compared to uncontrolled charging while ensuring all vehicles receive their requested charge before departure. The bidirectional charging scenario shows a particular promise, mostly in energy arbitrage, if used by fleet vehicles to enable self-consumption during high demand periods. Monte Carlo simulations indicate these benefits remain robust across various future adoption scenarios.

The developed flexibility simulation activation tool shows that controlled charging management strategies can substantially improve infrastructure utilization efficiency in local congestion. This research contributes valuable insights to facility managers and grid operators to increase the effective capacity of existing infrastructure without costly grid investments.