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We consider the problem of optimally scheduling the flexible electricity demand of a fleet of plug-in electric vehicles (PEVs). More specifically, we analyze the solutions of the following charging optimization problems: a) the welfare-optimal problem, where the overall system cost is minimized; b) the fleet-optimal problem, where the charging cost of the fleet as a whole is minimized by a central...
Due to high power in-feed from photovoltaics, it is expected that more battery systems will be installed in the distribution grid in near future. In this paper, we present a method to optimally control multiple battery sets in real-time to collectively provide services to power systems. The method is based on a Model Predictive Control (MPC) framework that tries to track an aggregated signal, while...
We introduce a novel contract design framework that enables demand side resources to participate in ancillary services markets in a cost efficient manner. Resources enter contracts with aggregators (which may be utilities) to provide capacity, which is directly controlled by the aggregator via a control signal. The contracting process allows consumers to make choices based upon their own cost/benefit...
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