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Article Dans Une Revue European Journal of Operational Research Année : 2020

Peer-to-Peer Electricity Market Analysis: From Variational to Generalized Nash Equilibrium

Résumé

We consider a network of prosumers involved in peer-to-peer energy exchanges, with differentiation price preferences on the trades with their neighbors, and we analyze two market designs: (i) a centralized market, used as a benchmark, where a global market operator optimizes the flows (trades) between the nodes, local demand and exibility activation to maximize the system overall social welfare; (ii) a distributed peer-to-peer market design where prosumers in local energy communities optimize selfishly their trades, demand, and exibility activation. We first characterize the solution of the peer-to-peer market as a Variational Equilibrium and prove that the set of Variational Equilibria coincides with the set of social welfare optimal solutions of market design (i). We give several results that help understanding the structure of the trades at an equilibrium or at the optimum. We characterize the impact of preferences on the network line congestion and renewable energy surplus under both designs. We provide a reduced example for which we give the set of all possible generalized equilibria, which enables to give an approximation of the price of anarchy. We provide a more realistic example which relies on the IEEE 14-bus network, for which we can simulate the trades under di erent preference prices. Our analysis shows in particular that the preferences have a large impact on the structure of the trades, but that one equilibrium (variational) is optimal. Finally, the learning mechanism needed to reach an equilibrium state in the peer-to-peer market design is discussed together with privacy issues.
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Dates et versions

hal-01944644 , version 1 (04-12-2018)
hal-01944644 , version 2 (30-06-2019)
hal-01944644 , version 3 (18-09-2019)

Identifiants

Citer

Hélène Le Cadre, Paulin Jacquot, Cheng Wan, Clémence Alasseur. Peer-to-Peer Electricity Market Analysis: From Variational to Generalized Nash Equilibrium. European Journal of Operational Research, 2020, 282 (2), pp.753-771. ⟨10.1016/j.ejor.2019.09.035⟩. ⟨hal-01944644v3⟩
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