Investigation of AIMD based charging strategies for EVs connected to a low-voltage distribution network

Mingming Liu, Seán McLoone

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

In this paper we consider charging strategies that mitigate the impact of domestic charging of EVs on low-voltage distribution networks and which seek to reduce peak power by responding to time-ofday pricing. The strategies are based on the distributed Additive Increase and Multiplicative Decrease (AIMD) charging algorithms proposed in [5]. The strategies are evaluated using simulations conducted on a custom OpenDSS-Matlab platform for a typical low voltage residential feeder network. Results show that by using AIMD based smart charging 50% EV penetration can be accommodated on our test network, compared to only 10% with uncontrolled charging, without needing to reinforce existing network infrastructure.

Original languageEnglish
Pages (from-to)433-441
Number of pages9
JournalCommunications in Computer and Information Science
Volume355
DOIs
Publication statusPublished - 01 Sep 2013

Keywords

  • AIMD
  • Distributed algorithm
  • EV charging
  • Smart Grid

ASJC Scopus subject areas

  • Computer Science(all)

Fingerprint

Dive into the research topics of 'Investigation of AIMD based charging strategies for EVs connected to a low-voltage distribution network'. Together they form a unique fingerprint.

Cite this