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


Autoria(s): Liu, Mingming; McLoone, Seán
Data(s)

01/09/2013

Resumo

<p>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. © Springer-Verlag Berlin Heidelberg 2013.</p>

Identificador

http://pure.qub.ac.uk/portal/en/publications/investigation-of-aimd-based-charging-strategies-for-evs-connected-to-a-lowvoltage-distribution-network(0615dc41-9dfd-4a9b-8bd3-f2dca4ee1fb8).html

http://dx.doi.org/10.1007/978-3-642-37105-9_48

http://www.scopus.com/inward/record.url?scp=84883762488&partnerID=8YFLogxK

Idioma(s)

eng

Direitos

info:eu-repo/semantics/restrictedAccess

Fonte

Liu , M & McLoone , S 2013 , ' Investigation of AIMD based charging strategies for EVs connected to a low-voltage distribution network ' Communications in Computer and Information Science , vol 355 , pp. 433-441 . DOI: 10.1007/978-3-642-37105-9_48

Palavras-Chave #AIMD #Distributed algorithm #EV charging #Smart Grid #/dk/atira/pure/subjectarea/asjc/1700 #Computer Science(all)
Tipo

article