Charging plug-in electric vehicles as a mixed-integer aggregative game
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Abstract (arXiv)
We consider the charge scheduling coordination of a fleet of plug-in electric vehicles, developing a hybrid decision-making framework for efficient and profitable usage of the distribution grid. Each charging dynamics, affected by the aggregate behavior of the whole fleet, is modelled as an inter-dependent, mixed-logical-dynamical system. The coordination problem is formalized as a generalized mixed-integer aggregative potential game, and solved via semi-decentralized implementation of a sequential best-response algorithm that leads to an approximated equilibrium of the game.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Oct 2019.
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Citing papers per year: 2021: 1; 2022: 3.
4 papers.
- 2021Learning equilibria with personalized incentives in a class of nonmonotone gamescited by 2
- 2022Personalized incentives as feedback design in generalized Nash equilibrium problemscited by 1
- 2022Optimal service station design for traffic mitigation via genetic algorithm and neural networkcited by 0
- 2022An active learning method for solving competitive multi-agent decision-making and control problemscited by 0
- 2022An active learning method for solving competitive multi-agent decision-making and control problems23 Dec 2022
- 2022Optimal service station design for traffic mitigation via genetic algorithm and neural network18 Nov 2022
- 2022Personalized incentives as feedback design in generalized Nash equilibrium problems24 Mar 2022
- 2021Learning equilibria with personalized incentives in a class of nonmonotone games6 Nov 2021