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Méthodes d'Optimisation et de Théorie des Jeux Appliquées aux Systèmes Électriques Décentralisés

Abstract : In the context of smart grid and in the transition to decentralized electric systems, we address the problem of the management of distributed electric consumption flexibilities. We develop different methods based on distributed optimization and game theory approaches.We start by adopting the point of view of a centralized operator in charge of the management of flexibilities for several agents. We provide a distributed and privacy-preserving algorithm to compute consumption profiles for agents that are optimal for the operator.In the proposed method, the individual constraints as well as the individual consumption profile of each agent are never revealed to the operator or the other agents.Then, in a second model, we adopt a more decentralized vision and consider a game theoretic framework for the management of consumption flexibilities.This approach enables, in particular, to take into account the strategic behavior of consumers.Individual objectives are determined by dynamic billing mechanisms, which is motivated by the modeling of congestion effects occurring on time periods receiving a high electricity load from consumers.A relevant class of games in this framework is given by atomic splittable congestion games.We obtain several theoretical results on Nash equilibria for this class of games, and we quantify the efficiency of those equilibria by providing bounds on the price of anarchy.We address the question of the decentralized computation of equilibria in this context by studying the conditions and rates of convergence of the best response and projected gradients algorithms.In practice an operator may deal with a very large number of players, and evaluating the equilibria in a congestion game in this case will be difficult.To address this issue, we give approximation results on the equilibria in congestion and aggregative games with a very large number of players, in the presence of coupling constraints.These results, obtained in the framework of variational inequalities and under some monotonicity conditions, can be used to compute an approximate equilibrium, solution of a small dimension problem.In line with the idea of modeling large populations, we consider nonatomic congestion games with coupling constraints, with an infinity of heterogeneous players: these games arise when the characteristics of a population are described by a parametric density function.Under monotonicity hypotheses, we prove that Wardrop equilibria of such games, given as solutions of an infinite dimensional variational inequality, can be approximated by symmetric Wardrop equilibria of auxiliary games, solutions of low dimension variational inequalities.Again, those results can be the basis of tractable methods to compute an approximate Wardrop equilibrium in a nonatomic infinite-type congestion game.Last, we consider a game model for the study of decentralized peer-to-peer energy exchanges between a community of consumers with renewable production sources.We study the generalized equilibria in this game, which characterize the possible energy trades and associated individual consumptions.We compare the equilibria with the centralized solution minimizing the social cost, and evaluate the efficiency of equilibria through the price of anarchy.
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Paulin Jacquot. Méthodes d'Optimisation et de Théorie des Jeux Appliquées aux Systèmes Électriques Décentralisés. Optimization and Control [math.OC]. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLX101⟩. ⟨tel-02445214⟩

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