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Large scale EV charge scheduling under contractual power constraints: a priority rule-based semi-online algorithm

Pierre Blanchart 1 Marine Depecker-Quéchon 1 Cédric Auliac 1
1 LADIS - Laboratoire d'analyse des données et d'intelligence des systèmes
DM2I - Département Métrologie Instrumentation & Information : DRT/LIST/DM2I
Abstract : The scope of this research work is to study the implementation of Electric Vehicles (EVs) based Virtual Power Plants (VPPs) through optimized charging process of a fleet of vehicles spread over multiple charging stations. In this context, this paper focuses on smart charge scheduling for an ensemble of EVs operated by a fleet manager. We consider a semi-online setting where precise information about EVs' arrival times, parking durations and energy needs isn't available before the EVs' connection to the charge spots ; only global statistics (computed at the fleet level) for these quantities are made available beforehand. In this context we propose, as a first step, to learn a priority function to be used in a second step to perform online scheduling for forthcoming EVs' requiring a charging service, according to a "highest priority, processing first" scheme. As we ignore most about the shape of the priority function, we propose to learn this function in an offline way as a function of charging information collected from the EV fleet and consolidated in a historical database.
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Pierre Blanchart, Marine Depecker-Quéchon, Cédric Auliac. Large scale EV charge scheduling under contractual power constraints: a priority rule-based semi-online algorithm. Transport Research Arena 2014, Apr 2014, Paris, France. ⟨cea-01833120⟩

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