Optimal Fully Electric Vehicle load balancing with an ADMM algorithm in Smartgrids

TL;DR

This paper introduces a two-level control system using an ADMM algorithm for optimal load balancing of fully electric vehicles in smart grids, enhancing economic efficiency and resource management.

Contribution

It presents a novel two-tier control architecture and a distributed ADMM-based algorithm for EV load balancing in smart grids, integrating market mechanisms.

Findings

Effective load balancing achieved

Economic benefits demonstrated for all actors

Distributed algorithm converges efficiently

Abstract

In this paper we present a system architecture and a suitable control methodology for the load balancing of Fully Electric Vehicles at Charging Station (CS). Within the proposed architecture, control methodologies allow to adapt Distributed Energy Resources (DER) generation profiles and active loads to ensure economic benefits to each actor. The key aspect is the organization in two levels of control: at local level a Load Area Controller (LAC) optimally calculates the FEVs charging sessions, while at higher level a Macro Load Area Aggregator (MLAA) provides DER with energy production profiles, and LACs with energy withdrawal profiles. Proposed control methodologies involve the solution of a Walrasian market equilibrium and the design of a distributed algorithm.