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

TL;DR

This paper models the coordination of electric vehicle charging as a mixed-integer aggregative game, proposing a hybrid decision framework and a semi-decentralized algorithm to achieve efficient grid usage.

Contribution

It introduces a novel hybrid decision-making framework and models EV charging as a mixed-integer aggregative potential game for improved coordination.

Findings

The proposed algorithm converges to an approximate equilibrium.

The framework enhances grid efficiency and profitability.

Model captures complex interdependent charging dynamics.

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.