Computation and implementation of an optimal mean field control for smart charging

TL;DR

This paper develops a mean field control framework for optimizing the charging of large populations of electric vehicles, demonstrating convergence of algorithms and practical implementation through numerical examples.

Contribution

It introduces a novel mean field control approach for PEV charging, including discretization, convex analysis, and algorithm convergence proofs.

Findings

Convex analysis ensures the existence of an optimal control solution.

Chambolle-Pock algorithm converges to the optimal solution.

Numerical examples validate the proposed control method.

Abstract

This paper addresses an optimal control problem for a large population of identical plug-in electric vehicles (PEVs). The number of PEVs being large, the mean field assumption is formulated to describe the evolution of the PEVs population and its interaction with the central planner. The resulting problem of optimal control of partial differential equations (PDEs) is discretized. Using convex analysis tools, we show the existence of an optimal solution and the convergence of the Chambolle-Pock algorithm to a solution. The implementation of this optimal control to the finite population of PEVs is detailed and we illustrate our approach with two numerical examples.