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We propose an algorithm for distributed charging control of electric vehicles (EVs) using online learning and online convex optimization. Many distributed charging control algorithms in the literature implicitly assume fast two-way communication between the distribution company and EV customers. This assumption is impractical at present and also raises security and privacy concerns. Our algorithm...
We design an optimal contract between a demand response aggregator (DRA) and a customer for incentive-based demand response. We consider a setting in which the customer is asked to reduce her consumption by the DRA and she is compensated for this reduction. However, since the DRA must supply the customer with as much power as she desires, a strategic customer can temporarily increase her base load...
We consider the problem of optimally scheduling the charging of electric vehicles to obtain a favorable total load profile. A large collection of our main contribution is to account for the capacity constraints induced by the power grid distribution lines and other components such as transformers in scheduling. We propose three distributed algorithms to minimize the total load variance while satisfying...
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