Charging plug-in electric vehicles as a mixed-integer aggregative game

Carlo Cenedese; Filippo Fabiani; Michele Cucuzzella; Jacquelien M.A. Scherpen; Ming Cao; Sergio Grammatico

doi:10.1109/CDC40024.2019.9030152

Charging plug-in electric vehicles as a mixed-integer aggregative game

Carlo Cenedese, Filippo Fabiani, Michele Cucuzzella, Jacquelien M.A. Scherpen, Ming Cao, Sergio Grammatico

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

15 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Proceedings of the IEEE 58th Conference on Decision and Control, CDC 2019
Publisher	IEEE
Pages	4904-4909
ISBN (Electronic)	978-1-7281-1398-2
DOIs	https://doi.org/10.1109/CDC40024.2019.9030152
Publication status	Published - 2019
Event	58th IEEE Conference on Decision and Control, CDC 2019 - Nice, France Duration: 11 Dec 2019 → 13 Dec 2019

Conference

Conference	58th IEEE Conference on Decision and Control, CDC 2019
Country/Territory	France
City	Nice
Period	11/12/19 → 13/12/19

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10.1109/CDC40024.2019.9030152

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title = "Charging plug-in electric vehicles as a mixed-integer aggregative game",

abstract = "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.",

author = "Carlo Cenedese and Filippo Fabiani and Michele Cucuzzella and Scherpen, {Jacquelien M.A.} and Ming Cao and Sergio Grammatico",

year = "2019",

doi = "10.1109/CDC40024.2019.9030152",

language = "English",

pages = "4904--4909",

booktitle = "Proceedings of the IEEE 58th Conference on Decision and Control, CDC 2019",

publisher = "IEEE",

address = "United States",

note = "58th IEEE Conference on Decision and Control, CDC 2019 ; Conference date: 11-12-2019 Through 13-12-2019",

}

Cenedese, C, Fabiani, F, Cucuzzella, M, Scherpen, JMA, Cao, M & Grammatico, S 2019, Charging plug-in electric vehicles as a mixed-integer aggregative game. in Proceedings of the IEEE 58th Conference on Decision and Control, CDC 2019. IEEE, pp. 4904-4909, 58th IEEE Conference on Decision and Control, CDC 2019, Nice, France, 11/12/19. https://doi.org/10.1109/CDC40024.2019.9030152

TY - GEN

T1 - Charging plug-in electric vehicles as a mixed-integer aggregative game

AU - Cenedese, Carlo

AU - Fabiani, Filippo

AU - Cucuzzella, Michele

AU - Scherpen, Jacquelien M.A.

AU - Cao, Ming

AU - Grammatico, Sergio

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

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U2 - 10.1109/CDC40024.2019.9030152

DO - 10.1109/CDC40024.2019.9030152

M3 - Conference contribution

AN - SCOPUS:85082448338

SP - 4904

EP - 4909

BT - Proceedings of the IEEE 58th Conference on Decision and Control, CDC 2019

PB - IEEE

T2 - 58th IEEE Conference on Decision and Control, CDC 2019

Y2 - 11 December 2019 through 13 December 2019

ER -

Charging plug-in electric vehicles as a mixed-integer aggregative game

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