This paper presents a mixed-integer game-theoretic equilibrium analysis of a system involving Electric Vehicles (EVs) and the Generation Unit Operator (GUO) as players, with the Charging Station Operator (CSO) as the coordinator. EVs aim to optimize their charging profiles during the charging period by minimizing battery degradation costs and deviations from their desired State of Charge (SoC). Meanwhile, GUO seeks to optimize the energy generation of the installed generator at the charging station, minimizing generation costs while satisfying capacity, supply, and demand constraints for the EVs. A semi-decentralized learning approach is proposed to maintain the privacy of both EVs and GUO.
Semi-decentralized game solution for charging schedule of electric vehicles
Ghavami, M.;Vasca, F.;Iannelli, L.;Liuzza, D.;Mostacciuolo, E.
2025-01-01
Abstract
This paper presents a mixed-integer game-theoretic equilibrium analysis of a system involving Electric Vehicles (EVs) and the Generation Unit Operator (GUO) as players, with the Charging Station Operator (CSO) as the coordinator. EVs aim to optimize their charging profiles during the charging period by minimizing battery degradation costs and deviations from their desired State of Charge (SoC). Meanwhile, GUO seeks to optimize the energy generation of the installed generator at the charging station, minimizing generation costs while satisfying capacity, supply, and demand constraints for the EVs. A semi-decentralized learning approach is proposed to maintain the privacy of both EVs and GUO.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
