Efficient Online Scheduling of Electric Vehicle Charging Using a Service-Price Menu

Abstract

We present an online algorithm for scheduling the charging of Electric Vehicles (EVs) in a Charging Station, aiming to optimize the overall quality of service through sum of weighted completion time minimization. Upon arrival of each EV, the algorithm generates a menu of service-price options. By letting the EV users pick their most preferable option, the algorithm offers guaranteed quality of service, achieves near optimal performance, and prevents the users from acting strategically.

Fair and Scalable Electric Vehicle Charging Under Electrical Grid Constraints

“…Notice that problem ( 27) is defined as minimizing the simple Lagrangian (26), where the terms of f t , that are not depended on local variables, Y s are discarded. In the iterative method to 1 Depending on regulatory aspects, the role of the Coordinating Entity can be assumed by the DSO itself or by a third party, e.g.…”

“…However, such studies typically disregard the electrical grid's constraints, while some others consider only a static upper bound on the charging station's power. Examples of studies adopting such a static upper bound include [2], [26], where the authors have proposed online algorithms for allocating charging to EVs in the absence of future information, and [6] where a genetic algorithm was proposed. In contrast, power-network-aware coordination is a more efficient approach, and it is typically achieved by Lagrangian methods [27], [28]; namely, the Alternating Direction Method of Multipliers (ADMM).…”