Integrating gamification into a MILP for flexible smart charging of EVs in public parking lots

This study proposes a mixed-integer linear programming (MILP) framework for the operation of bidirectional electric vehicle charging stations (EVCS) in public parking facilities, incorporating gamification mechanisms to enable flexible smart charging. Based on real EV charging session datasets, the model exploits user-provided extended connection time (idle time) as a source of operational flexibility in Level-2 charging infrastructures. By allowing vehicles to remain connected beyond the completion of charging, the optimisation model increases its scheduling capacity, enabling load shifting towards low-tariff periods and enhancing coordinated vehicle-to-vehicle (V2V) energy exchanges. The flexibility programme is incorporated into the optimisation framework through dedicated cost components that represent user participation and extended connection time. In this way, user-provided idle time directly influences the scheduling decisions of the model. A Monte Carlo analysis was conducted to evaluate the robustness of the proposed approach, confirming stable performance across different occupancy scenarios. Results demonstrate that sustained user flexibility significantly improves operator revenues, as providing additional connection time allows the model to allocate a greater amount of flexible time and enables a higher number of coordinated V2V operations.