Quantification en présence de divergence d'intérêts : application aux réseaux d'électricité intelligents

Abstract : Motivated by an application to smart grid, this paper generalizes the problem of scalar quantization in the case in which an agent, the consumer, determines the quantization cells and the other agent, the electrical network operator called aggregator, determines the representatives. We know that the standard quantization consists of two fictitious agents, which can be identified as a single one, minimizing the distorsion on the cells and on the representatives. In this paper, we consider a variation of that framework where the payoff functions maximized by the two agents are distincts. Their difference is called bias and implies a new strategic approach to the problem. Using tools from game theory, this work will highlight some key differences between the "strategic quantization" and the standard quantization, namely all communication ressources are not necessarily used, the bias between the payoffs has an influence on the quantity of exchanged information and the speed of convergence of methods analogous to the Llyod-Max algorithm in the strategic case
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Olivier Beaude, Florian Danard, Benjamin Larrousse, Samson Lasaulce. Quantification en présence de divergence d'intérêts : application aux réseaux d'électricité intelligents. 25eme Colloque GRETSI 2015, Sep 2015, Lyon, France. ⟨hal-01201724⟩

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