A Game-Theoretic Decentralized Real-Time Control of Electric Vehicle Charging Stations - Part II: Numerical Simulations

TL;DR

This paper demonstrates a game-theoretic decentralized control method for EV charging stations, integrating SG-ADMM into a hierarchical EMS to optimize charging in large-scale scenarios efficiently.

Contribution

It introduces a novel hierarchical EMS framework using SG-ADMM for incentive-based EV charging control, validated through large-scale simulations.

Findings

The method is cost-effective and fair in large-scale EVCS.

It outperforms decentralized, centralized, and uncontrolled approaches.

The approach is computationally efficient for real-time control.

Abstract

In the first part of this two-part paper a game-theoretic decentralized real-time control is proposed in the context of Electric Vehicle (EV) Charging Station (CS). This method, relying on a Stackelberg Game-based Alternating Direction of Multipliers (SG-ADMM), intends to steer the EVs' individual objectives towards the CS optimum by means of an incentive design mechanism, while controlling the EV power dispatch in a distributed manner. We integrate SG-ADMM in a hierachical multi-layered Energy Management System (EMS) as the real-time control algorithm, formulating the two-layer approach so that the SG leader (i.e., the CS), holding commitment power, trades off the available power with the incentives to the EVs, and the SG followers (i.e., the EVs) optimizes their charging curve in response to the leader decision. In this second part, we demonstrate the applicability of SG-ADMM as a incentive design mechanism inside an EVCS EMS, testing it in a large-scale EVCS. We benchmark this method with a decentralized (ADMM-based), a centralized and a uncontrolled approach, showing that our method exploits EV-level flexibility in a cost-effective, fair and computationally efficient manner.