A review of computer tools for modeling electric vehicle energy requirements and their impact on power distribution networks

Khizir Mahmud and Graham E. Town

Applied Energy, 2016, vol. 172, issue C, 337-359

Abstract: This paper presents a review of the many simulation tools that have been reported for modeling and managing the impact of electric vehicles on power distribution networks, and associated applications. One hundred and twenty-five simulation tools have been identified and among them sixty-seven tools have been summarized to facilitate selection of the most appropriate tools for specific tasks. Typical applications of the tools include vehicle system analysis and control, renewable energy and vehicle-to-grid integration and impact analysis, energy market behavior and charge scheduling, vehicle energy management, and traffic system simulation. No single tool covers all areas of these applications, however sufficient information is provided to enable researchers to select the most appropriate combination of tools to meet specific research objectives.

Keywords: Electric vehicle; EV tools; Grid tools; Smart grid; V2G tools; Vehicle traffic systems (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (28)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261916304275
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:172:y:2016:i:c:p:337-359

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2016.03.100

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().