EconPapers    
Economics at your fingertips  
 

Two-stage stochastic sizing and packetized energy scheduling of BEV charging stations with quality of service constraints

Giuseppe Graber, Vito Calderaro, Pierluigi Mancarella and Vincenzo Galdi

Applied Energy, 2020, vol. 260, issue C, No S030626191931949X

Abstract: The expected deployment of battery electric vehicles (BEVs) strongly depends on the development of an adequate charging station (CS) infrastructure that guarantees a certain level of quality of service (QoS) to the BEV users. This paper proposes a two-stage method to select the number and type of CSs in parking areas (PAs) and schedule the charging sessions of the incoming BEVs ensuring a predetermined QoS level while minimizing the cost for the CS manager. In particular, stage one solves the CS sizing problem while stage two involves a probabilistic simulation procedure able to solve the charging scheduling problem by using a packetized energy approach. We also take into account the typical charging current and voltage characteristic of a BEV battery pack, and the real statistical distribution of BEV arriving times and expected parking times. A case study based on the PA at the University of Salerno Campus is used to demonstrate the effectiveness of the proposed method.

Keywords: Charging stations; Economic analysis; Electric vehicles; Optimization; Quality of service (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S030626191931949X
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:260:y:2020:i:c:s030626191931949x

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.2019.114262

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 ().

 
Page updated 2025-03-19
Handle: RePEc:eee:appene:v:260:y:2020:i:c:s030626191931949x