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Due to the ongoing electrification of transport in combination with limitedpower grid capacities, efficient ways to schedule electric vehicles (EVs) areneeded for intraday operation of, for example, large parking lots. Commonapproaches like model predictive control repeatedly solve a correspondingoffline problem. In this work, we present and analyze the Flow-based OfflineCharging Scheduler (FOCS), an offline algorithm to derive an optimal EVcharging schedule for a fleet of EVs that minimizes an increasing, convex anddifferentiable function of the corresponding aggregated power profile. To thisend, we relate EV charging to mathematical speed scaling models withjob-specific speed limits. We prove our algorithm to be optimal. Furthermore,we derive necessary and sufficient conditions for any EV charging profile to beoptimal.

Relating Electric Vehicle Charging to Speed Scaling with Job-Specific Speed Limits