Optimal fast charging station placing and sizing
Payam Sadeghi-Barzani,
Abbas Rajabi-Ghahnavieh and
Hosein Kazemi-Karegar
Applied Energy, 2014, vol. 125, issue C, 289-299
Abstract:
Fast charging stations are vital components for public acceptance of electric vehicle (EV). The stations are connected to the electric grid and can recharge an electric vehicle in less than 20min. Charging station development is highly influenced by the government policy in allocating station development costs. This paper presents a Mixed-Integer Non-Linear (MINLP) optimization approach for optimal placing and sizing of the fast charging stations. The station development cost, EV energy loss, electric gird loss as well as the location of electric substations and urban roads are among the factors included in the proposed approach. Geographic information has been used to determine EV energy loss and station electrification cost. The optimization problem is solved using genetic algorithm technique. Application of the proposed approach to analyze the impact of different station development policies has been discussed. The impact of electric grid reliability on charging station place and size has been evaluated using a proposed index to evaluate loss of charging cost. Results showed the robustness and efficacy of the proposed method to determine optimal place and size of the charging stations.
Keywords: Electric vehicle; Charging; Station; Location; Reliability; Loss of charging (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (94)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261914003171
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:125:y:2014:i:c:p:289-299
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.2014.03.077
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 ().