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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Bibliographic Details
Published in:IEEE transactions on cybernetics Vol. 52; no. 8; pp. 8315 - 8325
Main Author: Deng, Zhenhua
Format: Journal Article
Language:English
Published: United States IEEE 01.08.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:2168-2267, 2168-2275, 2168-2275
Online Access:Get full text
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Summary: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.
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ISSN:2168-2267
2168-2275
2168-2275
DOI:10.1109/TCYB.2021.3049462