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The increasing prevalence of electric vehicles (EVs) in the transportationsector will introduce a large number of highly flexible electric loads that EVaggregators can pool and control to provide energy and ancillary services tothe wholesale electricity market. To integrate large populations of EVs intoelectricity market operations, aggregators must express the aggregateflexibility of the EVs under their control in the form of a small number ofenergy storage (battery) resources that accurately capture the supply/demandcapabilities of the individual EVs as a collective. To this end, we propose anovel multi-battery flexibility model defined as a linear combination of asmall number of base sets (termed batteries) that reflect the differinggeometric shapes of the individual EV flexibility sets, and suggest aclustering approach to identify these base sets. We study the problem ofcomputing a multi-battery flexibility set that has minimum Hausdorff distanceto the aggregate flexibility set, subject to the constraint that themulti-battery flexibility set be a subset of the aggregate flexibility set. Weshow how to conservatively approximate this problem with a tractable convexprogram, and illustrate the performance achievable by our method with severalnumerical experiments.

A Multi-Battery Model for the Aggregate Flexibility of Heterogeneous Electric Vehicles