Pricing scheme for aggregate load scheduling of plug-in electric taxi fleet

This paper aims at scheduling the charging behavior of a large population of plug-in electric taxis (PET) by means of pricing, in order to respond to load requirement of future smart grid in critical situations. The main contributions consist of two parts. First, the charging behavior of a single PET is analyzed, and a threshold-based scheduling algorithm is proposed from the perspective of PET in order to minimize its cost. Second, based on the individual behavior the aggregate charging behavior of a fleet of PETs is analyzed, and a pricing scheme is proposed so that the aggregated load of PET fleet can track a given target load profile. Numerical simulations verify the proposed method.