Distributed Vehicle Grid Integration Over Communication and Physical Networks

TL;DR

This paper introduces a distributed vehicle grid integration framework that models EV behavior and market operations, addressing communication challenges and computational complexity in power distribution networks.

Contribution

It presents a novel distributed solution for the day-ahead distribution market that accounts for physical network details and EV charging needs, reducing reliance on centralized data.

Findings

Effective VGI framework demonstrated on multiple distribution feeders.

Distributed solution reduces computational effort compared to centralized methods.

Framework accommodates unbalanced three-phase networks with various configurations.

Abstract

This paper proposes a distributed framework for vehicle grid integration (VGI) taking into account the communication and physical networks. To this end, we model the electric vehicle (EV) behaviour that includes time of departure, time of arrival, state of charge, required energy, and its objectives, e.g., avoid battery degradation. Next, we formulate the centralised day ahead distribution market (DADM) which explicitly represents the physical system, supports unbalanced three phase networks with delta and wye connections, and incorporates the charging needs of EVs. The solution of the centralised market requires knowledge of EV information in terms of desired energy, departure and arrival times that EV owners are reluctant in providing. Moreover, the computational effort required to solve the DADM in cases of numerous EVs is very intensive. As such, we propose a distributed solution of the DADM clearing mechanism over a time-varying communication network. We illustrate the proposed VGI framework through the 13-bus, 33- bus, and 141-bus distribution feeders.