Distributed Algorithm Design for Aggregative Games of Euler-Lagrange Systems and Its Application to Smart Grids

The aggregative games are addressed in this article, in which there are coupling constraints among decisions and the players have Euler-Lagrange (EL) dynamics. On the strength of gradient descent, state feedback, and dynamic average consensus, two distributed algorithms are developed to seek the var...

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Vydané v:	IEEE transactions on cybernetics Ročník 52; číslo 8; s. 8315 - 8325
Hlavný autor:	Deng, Zhenhua
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.08.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Aggregative games Algorithms Communication networks Convergence Couplings cyber-physical systems (CPSs) Distributed algorithms Electricity Electricity supply industry Euler–Lagrange systems Game theory Games generalized Nash equilibrium (GNE) Heuristic algorithms multiagent systems Perturbation methods Singular perturbation Smart grid Smart grids State feedback Turbines
ISSN:	2168-2267, 2168-2275, 2168-2275
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Abstract	The aggregative games are addressed in this article, in which there are coupling constraints among decisions and the players have Euler-Lagrange (EL) dynamics. On the strength of gradient descent, state feedback, and dynamic average consensus, two distributed algorithms are developed to seek the variational generalized Nash equilibrium (GNE) of the game. This article analyzes the convergence of two algorithms by utilizing singular perturbation analysis and variational analysis. The two algorithms exponentially and asymptotically converge to the variational GNE of the game, respectively. Moreover, the results are applied to the electricity market games of smart grids. By the algorithms, turbine-generator systems can seek the variational GNE of electricity markets autonomously. Finally, simulation examples verify the methods.
AbstractList	The aggregative games are addressed in this article, in which there are coupling constraints among decisions and the players have Euler-Lagrange (EL) dynamics. On the strength of gradient descent, state feedback, and dynamic average consensus, two distributed algorithms are developed to seek the variational generalized Nash equilibrium (GNE) of the game. This article analyzes the convergence of two algorithms by utilizing singular perturbation analysis and variational analysis. The two algorithms exponentially and asymptotically converge to the variational GNE of the game, respectively. Moreover, the results are applied to the electricity market games of smart grids. By the algorithms, turbine-generator systems can seek the variational GNE of electricity markets autonomously. Finally, simulation examples verify the methods.The aggregative games are addressed in this article, in which there are coupling constraints among decisions and the players have Euler-Lagrange (EL) dynamics. On the strength of gradient descent, state feedback, and dynamic average consensus, two distributed algorithms are developed to seek the variational generalized Nash equilibrium (GNE) of the game. This article analyzes the convergence of two algorithms by utilizing singular perturbation analysis and variational analysis. The two algorithms exponentially and asymptotically converge to the variational GNE of the game, respectively. Moreover, the results are applied to the electricity market games of smart grids. By the algorithms, turbine-generator systems can seek the variational GNE of electricity markets autonomously. Finally, simulation examples verify the methods. The aggregative games are addressed in this article, in which there are coupling constraints among decisions and the players have Euler-Lagrange (EL) dynamics. On the strength of gradient descent, state feedback, and dynamic average consensus, two distributed algorithms are developed to seek the variational generalized Nash equilibrium (GNE) of the game. This article analyzes the convergence of two algorithms by utilizing singular perturbation analysis and variational analysis. The two algorithms exponentially and asymptotically converge to the variational GNE of the game, respectively. Moreover, the results are applied to the electricity market games of smart grids. By the algorithms, turbine-generator systems can seek the variational GNE of electricity markets autonomously. Finally, simulation examples verify the methods.
Author	Deng, Zhenhua
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SubjectTerms	Aggregative games Algorithms Communication networks Convergence Couplings cyber-physical systems (CPSs) Distributed algorithms Electricity Electricity supply industry Euler–Lagrange systems Game theory Games generalized Nash equilibrium (GNE) Heuristic algorithms multiagent systems Perturbation methods Singular perturbation Smart grid Smart grids State feedback Turbines
Title	Distributed Algorithm Design for Aggregative Games of Euler-Lagrange Systems and Its Application to Smart Grids
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