4.7 Article

Distributed Generalized Nash Equilibrium Seeking for Energy Sharing Games in Prosumers

期刊

IEEE TRANSACTIONS ON POWER SYSTEMS
卷 36, 期 5, 页码 3973-3986

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2021.3058675

关键词

Games; Power systems; Optimization; Nash equilibrium; Linear programming; Electrical engineering; Convex functions; Energy sharing; prosumer; distributed algorithm; generalized Nash game; generalized Nash Equilibrium

资金

  1. Chenguang Program Research on operation, evolution, and regulation of local power markets based on Game Theory
  2. National Key R&D Program of China [2016YFB0901900]
  3. National Natural Science Foundation of China [51677100, U1966601, U1766206]

向作者/读者索取更多资源

This paper proposes a distributed approach to solving the Generalized Nash equilibrium (GNE) of the energy sharing game, by proving the strong monotonicity of the game and converting the GNG into an equivalent optimization problem. An algorithm based on Nesterov's methods is used to solve the equivalent problem and find the GNE in a distributed manner. The algorithm's convergence is rigorously proven based on the nonexpansive operator theory, and its performance is validated through experiments with three prosumers and scalability tested with simulations using 1888 prosumers.
With the proliferation of distributed generators and energy storage systems, traditional passive consumers in power systems have been gradually evolving into the so-called prosumers, i.e., proactive consumers, which can both produce and consume power. To encourage energy exchange among prosumers, energy sharing is increasingly adopted, which is usually formulated as a generalized Nash game (GNG). In this paper, a distributed approach is proposed to seek the Generalized Nash equilibrium (GNE) of the energy sharing game. To this end, we first prove the strong monotonicity of the game. Then, the GNG is converted into an equivalent optimization problem. An algorithm based on Nesterov's methods is thereby devised to solve the equivalent problem and consequently find the GNE in a distributed manner. The convergence of the proposed algorithm is proved rigorously based on the nonexpansive operator theory. The performance of the algorithm is validated by experiments with three prosumers, and the scalability is tested by simulations using 1888 prosumers.

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