ADMM-based Coordinated Control of Electric Vehicles in an Unbalanced Distribution Grid: Assessing Tolerance to Communication Failures

In this paper, we propose an Alternating Direction Method of Multipliers (ADMM) approach combined with consensus optimization to coordinate electric vehicle (EV) charging and discharging in an unbalanced distribution grid. The underlying optimization problem has an objective function to minimize the customer energy costs, subject to a globally coupled network constraint in the form of a linear inequality (representing grid voltage and transformer core temperature limits) and local polyhedron constraints (representing customer charging requirements and limitations in charging infrastructure capacity). EV coordination is achieved by means of an iterative routine, wherein EVs (agents) exchange limited information with their neighboring EVs through a connected peer-to-peer communication network. Our proposed approach is also designed to accommodate time-varying communication networks arising from communication link faults and random disconnection of agents from communication channels. Numerical simulations verify the performance of our network-aware EV coordination approach to communication-based failures.

Authors

Institutions

Publication Details

Published
2024-11-20
DOI
https://doi.org/10.1109/aupec62273.2024.10807540
Citations
1
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.21

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ADMM-based Coordinated Control of Electric Vehicles in an Unbalanced Distribution Grid: Assessing Tolerance to Communication Failures

Elizabeth L. Ratnam, Nanduni Nimalsiri
1 citations
Smart Grid Energy Management
0.21
article

ADMM-based Coordinated Control of Electric Vehicles in an Unbalanced Distribution Grid: Assessing Tolerance to Communication Failures

Elizabeth L. Ratnam, Nanduni Nimalsiri
article en
1 citations

Abstract

In this paper, we propose an Alternating Direction Method of Multipliers (ADMM) approach combined with consensus optimization to coordinate electric vehicle (EV) charging and discharging in an unbalanced distribution grid. The underlying optimization problem has an objective function to minimize the customer energy costs, subject to a globally coupled network constraint in the form of a linear inequality (representing grid voltage and transformer core temperature limits) and local polyhedron constraints (representing customer charging requirements and limitations in charging infrastructure capacity). EV coordination is achieved by means of an iterative routine, wherein EVs (agents) exchange limited information with their neighboring EVs through a connected peer-to-peer communication network. Our proposed approach is also designed to accommodate time-varying communication networks arising from communication link faults and random disconnection of agents from communication channels. Numerical simulations verify the performance of our network-aware EV coordination approach to communication-based failures.

Australian National University (AU), Commonwealth Scientific and Industrial Research Organisation (AU)
Australian Research Council
Affordable and clean energy
Openalex Percentile: Top 45%
Smart Grid Energy Management
0.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.