Multifunctional applications of batteries within fast-charging stations based on EV demand-prediction of the users’ behaviour

This study presents a methodology to improve the operation of the power system and to deal with technical issues caused by electric vehicles (EVs) fast charging load. Fast charging stations (FCSs) are indispensable for widespread use of EVs since they can fully charge EVs in a short period of time....

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Main Authors: Marjan Gjelaj, Nataly Bañol Arias, Chresten Traeholt, Seyedmostafa Hashemi
Format: Article
Language:English
Published: Wiley 2019-06-01
Series:The Journal of Engineering
Subjects:
bes
fcs
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9280
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spelling doaj-37ddf1ad6d534864bafe48e8aee8f1b32021-04-02T06:09:45ZengWileyThe Journal of Engineering2051-33052019-06-0110.1049/joe.2018.9280JOE.2018.9280Multifunctional applications of batteries within fast-charging stations based on EV demand-prediction of the users’ behaviourMarjan Gjelaj0Nataly Bañol Arias1Nataly Bañol Arias2Chresten Traeholt3Seyedmostafa Hashemi4CEE-Department of Electrical Engineering, DTU-Technical University of DenmarkDepartment of Electrical Engineering, UNESP – Sao Paulo State UniversityDepartment of Electrical Engineering, UNESP – Sao Paulo State UniversityCEE-Department of Electrical Engineering, DTU-Technical University of DenmarkCEE-Department of Electrical Engineering, DTU-Technical University of DenmarkThis study presents a methodology to improve the operation of the power system and to deal with technical issues caused by electric vehicles (EVs) fast charging load. Fast charging stations (FCSs) are indispensable for widespread use of EVs since they can fully charge EVs in a short period of time. The integration of battery energy storage (BES) within the FCSs is considered a smart option to avoid the power congestion during the peak hours as well as the grid reinforcement costs due to FCSs. In addition, the BES can be used as multifunctional equipment, which is able to provide services such as peak shaving and frequency regulation. This study proposes a method to determine an optimal size of BES considering a stochastic modelling approach of the EVs load demand based on the users’ behaviour and their probabilistic driving patterns. Finally, a case study is carried out using a real DC fast-charging infrastructure in Copenhagen.https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9280battery storage plantsbattery powered vehicleselectric vehicle chargingvehicle-to-gridstochastic processesfrequency regulationbesdc fast-charging infrastructurepower systemelectric vehicles fast charging loadfast charging stationsbattery energy storagepower congestiongrid reinforcement costsmultifunctional equipmentpeak shavingfcsev load demand predictionstochastic modelling approachcopenhagen
collection DOAJ
language English
format Article
sources DOAJ
author Marjan Gjelaj
Nataly Bañol Arias
Nataly Bañol Arias
Chresten Traeholt
Seyedmostafa Hashemi
spellingShingle Marjan Gjelaj
Nataly Bañol Arias
Nataly Bañol Arias
Chresten Traeholt
Seyedmostafa Hashemi
Multifunctional applications of batteries within fast-charging stations based on EV demand-prediction of the users’ behaviour
The Journal of Engineering
battery storage plants
battery powered vehicles
electric vehicle charging
vehicle-to-grid
stochastic processes
frequency regulation
bes
dc fast-charging infrastructure
power system
electric vehicles fast charging load
fast charging stations
battery energy storage
power congestion
grid reinforcement costs
multifunctional equipment
peak shaving
fcs
ev load demand prediction
stochastic modelling approach
copenhagen
author_facet Marjan Gjelaj
Nataly Bañol Arias
Nataly Bañol Arias
Chresten Traeholt
Seyedmostafa Hashemi
author_sort Marjan Gjelaj
title Multifunctional applications of batteries within fast-charging stations based on EV demand-prediction of the users’ behaviour
title_short Multifunctional applications of batteries within fast-charging stations based on EV demand-prediction of the users’ behaviour
title_full Multifunctional applications of batteries within fast-charging stations based on EV demand-prediction of the users’ behaviour
title_fullStr Multifunctional applications of batteries within fast-charging stations based on EV demand-prediction of the users’ behaviour
title_full_unstemmed Multifunctional applications of batteries within fast-charging stations based on EV demand-prediction of the users’ behaviour
title_sort multifunctional applications of batteries within fast-charging stations based on ev demand-prediction of the users’ behaviour
publisher Wiley
series The Journal of Engineering
issn 2051-3305
publishDate 2019-06-01
description This study presents a methodology to improve the operation of the power system and to deal with technical issues caused by electric vehicles (EVs) fast charging load. Fast charging stations (FCSs) are indispensable for widespread use of EVs since they can fully charge EVs in a short period of time. The integration of battery energy storage (BES) within the FCSs is considered a smart option to avoid the power congestion during the peak hours as well as the grid reinforcement costs due to FCSs. In addition, the BES can be used as multifunctional equipment, which is able to provide services such as peak shaving and frequency regulation. This study proposes a method to determine an optimal size of BES considering a stochastic modelling approach of the EVs load demand based on the users’ behaviour and their probabilistic driving patterns. Finally, a case study is carried out using a real DC fast-charging infrastructure in Copenhagen.
topic battery storage plants
battery powered vehicles
electric vehicle charging
vehicle-to-grid
stochastic processes
frequency regulation
bes
dc fast-charging infrastructure
power system
electric vehicles fast charging load
fast charging stations
battery energy storage
power congestion
grid reinforcement costs
multifunctional equipment
peak shaving
fcs
ev load demand prediction
stochastic modelling approach
copenhagen
url https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9280
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