Hélène Le Cadre

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This article proposes an original approach to predict the electric vehicles (EVs)' energy demand in a charge station using a regret minimization learning approach. The problem is modelled as a two players game involving: on the one hand the EV drivers, whose demand is unknown and, on the other hand, the service provider who owns the charge station and wants(More)
In this article, we consider houses belonging to an eco-neighborhood in which inhabitants have the capacity to optimize dynamically the energy demand and the energy storage level so as to maximize their utility. The inhabitants' preferences are characterized by their sensitivity toward comfort versus price, the optimal expected temperature in the house,(More)
N independent sources choose their provider depending on the perceived costs associated with each provider. The perceived cost is the sum of the price and quality of service proposed by the provider coefficiented by the source sensitivity to the quality of service. The source chooses the smallest cost provider or refuses to subscribe if all the perceived(More)
In this article, the smart grid is modeled as a decentralized and hierarchical network, made of three categories of agents: producers, providers and microgrids. To optimize their decisions concerning the energy prices and the traded quantities of energy, the agents need to forecast the energy productions and the demand of the microgrids. The biases(More)