A demand-side approach to the optimal deployment of electric vehicle charging stations in metropolitan areas

N. Andrenacci, R. Ragona and G. Valenti

Applied Energy, 2016, vol. 182, issue C, 39-46

Abstract: Despite all the acknowledged advantages in terms of environmental impact reduction, energy efficiency and noise reduction, the electric mobility market is below expectations. In fact, electric vehicles have limitations that pose several important challenges for achieving a sustainable mobility system: among them, the availability of an adequate charging infrastructure is recognized as a fundamental requirement and appropriate approaches to optimize public and private investments in this field are to be delineated. In this paper we consider actual data on conventional private vehicle usage in the urban area of Rome to carry out a strategy for the optimal allocation of charging infrastructures into portions (subareas) of the urban area, based on an analysis of a driver sample under the assumption of a complete switch to an equivalent fleet of electric vehicles. Moreover, the energy requirement for each one of the subareas is estimated in terms of the electric energy used by the equivalent fleet of electric vehicles to reach their destination. The model can be easily generalized to other problems regarding facility allocation based on user demand.

Keywords: Electric mobility; Electric charging station deployment; Big data analysis; Electric vehicle energy requirement; Cluster analysis; Electric vehicle simulation (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (46)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S030626191631087X
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:182:y:2016:i:c:p:39-46

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.2016.07.137

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 ().