QoS-Aware Capacity Planning of Networked PEV Charging Infrastructure

Plug-in electric vehicle (PEV) charging infrastructure is necessary to accommodate the rapid increase in PEV penetration rate. Capacity planning of PEV charging infrastructure (EVCI) must ensure not only a satisfactory charging service for PEV users but also a reliable operation of the power grid. I...

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Main Authors: Ahmed Abdalrahman, Weihua Zhuang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Open Journal of Vehicular Technology
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9031405/
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spelling doaj-85ee0c63d19d4fb183a6597465df75672021-03-29T18:08:24ZengIEEEIEEE Open Journal of Vehicular Technology2644-13302020-01-01111612910.1109/OJVT.2020.29798209031405QoS-Aware Capacity Planning of Networked PEV Charging InfrastructureAhmed Abdalrahman0https://orcid.org/0000-0002-9142-7880Weihua Zhuang1https://orcid.org/0000-0003-0488-511XDepartment of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, CanadaDepartment of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, CanadaPlug-in electric vehicle (PEV) charging infrastructure is necessary to accommodate the rapid increase in PEV penetration rate. Capacity planning of PEV charging infrastructure (EVCI) must ensure not only a satisfactory charging service for PEV users but also a reliable operation of the power grid. In this paper, we propose a quality-of-service (QoS) aware capacity planning of EVCI. In particular, the proposed framework accounts for the link between the charging QoS and the power distribution network (PDN) capability. Towards this end, we firstly optimize charging facility sizes to achieve a targeted QoS level. Then, we minimize the integration cost for the PDN by attaining the most cost-effective allocation of the energy storage systems (ESSs) and/or upgrading the PDN substation and feeders. Additionally, we capture the correlation between the occupation levels of neighboring charging facilities and the blocked PEV user behaviors. We model the EVCI as a queuing network with finite capacity, and utilize the non-stationary queuing models to study the temporal variability of the PEV charging demand. A network of charging facilities is used to demonstrate the effectiveness of the proposed framework.https://ieeexplore.ieee.org/document/9031405/Capacity planningcharging infrastructuredistribution networkenergy storage systemnon-stationary queuesqueueing networks
collection DOAJ
language English
format Article
sources DOAJ
author Ahmed Abdalrahman
Weihua Zhuang
spellingShingle Ahmed Abdalrahman
Weihua Zhuang
QoS-Aware Capacity Planning of Networked PEV Charging Infrastructure
IEEE Open Journal of Vehicular Technology
Capacity planning
charging infrastructure
distribution network
energy storage system
non-stationary queues
queueing networks
author_facet Ahmed Abdalrahman
Weihua Zhuang
author_sort Ahmed Abdalrahman
title QoS-Aware Capacity Planning of Networked PEV Charging Infrastructure
title_short QoS-Aware Capacity Planning of Networked PEV Charging Infrastructure
title_full QoS-Aware Capacity Planning of Networked PEV Charging Infrastructure
title_fullStr QoS-Aware Capacity Planning of Networked PEV Charging Infrastructure
title_full_unstemmed QoS-Aware Capacity Planning of Networked PEV Charging Infrastructure
title_sort qos-aware capacity planning of networked pev charging infrastructure
publisher IEEE
series IEEE Open Journal of Vehicular Technology
issn 2644-1330
publishDate 2020-01-01
description Plug-in electric vehicle (PEV) charging infrastructure is necessary to accommodate the rapid increase in PEV penetration rate. Capacity planning of PEV charging infrastructure (EVCI) must ensure not only a satisfactory charging service for PEV users but also a reliable operation of the power grid. In this paper, we propose a quality-of-service (QoS) aware capacity planning of EVCI. In particular, the proposed framework accounts for the link between the charging QoS and the power distribution network (PDN) capability. Towards this end, we firstly optimize charging facility sizes to achieve a targeted QoS level. Then, we minimize the integration cost for the PDN by attaining the most cost-effective allocation of the energy storage systems (ESSs) and/or upgrading the PDN substation and feeders. Additionally, we capture the correlation between the occupation levels of neighboring charging facilities and the blocked PEV user behaviors. We model the EVCI as a queuing network with finite capacity, and utilize the non-stationary queuing models to study the temporal variability of the PEV charging demand. A network of charging facilities is used to demonstrate the effectiveness of the proposed framework.
topic Capacity planning
charging infrastructure
distribution network
energy storage system
non-stationary queues
queueing networks
url https://ieeexplore.ieee.org/document/9031405/
work_keys_str_mv AT ahmedabdalrahman qosawarecapacityplanningofnetworkedpevcharginginfrastructure
AT weihuazhuang qosawarecapacityplanningofnetworkedpevcharginginfrastructure
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