Scheduling of Flexible EV Charging under Grid Constraints and Uncertainty

Abstract

In this thesis, we study the problem of the real-time scheduling of flexible-rate Electric Vehicle charging under resource constraints and uncertainty. We present a novel Schedule Generation Scheme (SGS) which repeatedly mutates schedules to find potential improvements. This method is evaluated on various network layouts using a discrete-event simulation and compared to other well-known SGSs which have been adapted to this problem context. We show how our SGS can yield schedules with reduced customer delays, even when schedules are updated less frequently than other methods.