EV Charging Station Placement using Nature-Inspired Optimisation Algorithms

Furkan Ahmad; Luluwah Al-Fagih; Sikandar Abdul Qadir; Mohd Khalid

doi:10.1109/PIECON56912.2023.10085885

EV Charging Station Placement using Nature-Inspired Optimisation Algorithms

Furkan Ahmad^*
, Luluwah Al-Fagih
, Sikandar Abdul Qadir
, Mohd Khalid

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

15 Scopus citations

Abstract

Electric Vehicle charging station (EVCS) infrastructure planning involves developing and implementing strategies, policies, and infrastructure in terms of optimal placement, sizing, power flow, etc., in the electric distribution network (DN) and transportation network (TN) to support the widespread adoption of EVs. Various Nature-inspired algorithms (NIOs) have offered an adaptive platform for optimal electric vehicle charging infrastructure planning. This manuscript comprehensively reviews the application of different NIOs algorithms in optimal EVCS placement.

Original language	English
Title of host publication	2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350399769
DOIs	https://doi.org/10.1109/PIECON56912.2023.10085885
State	Published - 2023
Externally published	Yes
Event	2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023 - Aligarh, India Duration: 10 Feb 2023 → 12 Feb 2023

Publication series

Name	2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023

Conference

Conference	2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023
Country/Territory	India
City	Aligarh
Period	10/02/23 → 12/02/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure
SDG 13 Climate Action

Keywords

Climate change
carbon emissions
electric vehicles
optimal placement
optimization

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Automotive Engineering
Control and Optimization
Instrumentation

Access to Document

10.1109/PIECON56912.2023.10085885

Cite this

Ahmad, F., Al-Fagih, L., Qadir, S. A., & Khalid, M. (2023). EV Charging Station Placement using Nature-Inspired Optimisation Algorithms. In 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023 Article 166 (2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PIECON56912.2023.10085885

Ahmad, Furkan ; Al-Fagih, Luluwah ; Qadir, Sikandar Abdul et al. / EV Charging Station Placement using Nature-Inspired Optimisation Algorithms. 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023).

@inproceedings{508ff2f837714deb870a262be0b33098,

title = "EV Charging Station Placement using Nature-Inspired Optimisation Algorithms",

abstract = "Electric Vehicle charging station (EVCS) infrastructure planning involves developing and implementing strategies, policies, and infrastructure in terms of optimal placement, sizing, power flow, etc., in the electric distribution network (DN) and transportation network (TN) to support the widespread adoption of EVs. Various Nature-inspired algorithms (NIOs) have offered an adaptive platform for optimal electric vehicle charging infrastructure planning. This manuscript comprehensively reviews the application of different NIOs algorithms in optimal EVCS placement.",

keywords = "Climate change, carbon emissions, electric vehicles, optimal placement, optimization",

author = "Furkan Ahmad and Luluwah Al-Fagih and Qadir, \{Sikandar Abdul\} and Mohd Khalid",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023 ; Conference date: 10-02-2023 Through 12-02-2023",

year = "2023",

doi = "10.1109/PIECON56912.2023.10085885",

language = "English",

series = "2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023",

address = "United States",

}

Ahmad, F, Al-Fagih, L, Qadir, SA & Khalid, M 2023, EV Charging Station Placement using Nature-Inspired Optimisation Algorithms. in 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023., 166, 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023, Institute of Electrical and Electronics Engineers Inc., 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023, Aligarh, India, 10/02/23. https://doi.org/10.1109/PIECON56912.2023.10085885

EV Charging Station Placement using Nature-Inspired Optimisation Algorithms. / Ahmad, Furkan; Al-Fagih, Luluwah; Qadir, Sikandar Abdul et al.
2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023. Institute of Electrical and Electronics Engineers Inc., 2023. 166 (2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - EV Charging Station Placement using Nature-Inspired Optimisation Algorithms

AU - Ahmad, Furkan

AU - Al-Fagih, Luluwah

AU - Qadir, Sikandar Abdul

AU - Khalid, Mohd

PY - 2023

Y1 - 2023

N2 - Electric Vehicle charging station (EVCS) infrastructure planning involves developing and implementing strategies, policies, and infrastructure in terms of optimal placement, sizing, power flow, etc., in the electric distribution network (DN) and transportation network (TN) to support the widespread adoption of EVs. Various Nature-inspired algorithms (NIOs) have offered an adaptive platform for optimal electric vehicle charging infrastructure planning. This manuscript comprehensively reviews the application of different NIOs algorithms in optimal EVCS placement.

AB - Electric Vehicle charging station (EVCS) infrastructure planning involves developing and implementing strategies, policies, and infrastructure in terms of optimal placement, sizing, power flow, etc., in the electric distribution network (DN) and transportation network (TN) to support the widespread adoption of EVs. Various Nature-inspired algorithms (NIOs) have offered an adaptive platform for optimal electric vehicle charging infrastructure planning. This manuscript comprehensively reviews the application of different NIOs algorithms in optimal EVCS placement.

KW - Climate change

KW - carbon emissions

KW - electric vehicles

KW - optimal placement

KW - optimization

UR - https://www.scopus.com/pages/publications/85153112884

U2 - 10.1109/PIECON56912.2023.10085885

DO - 10.1109/PIECON56912.2023.10085885

M3 - Conference contribution

AN - SCOPUS:85153112884

T3 - 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023

BT - 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023

Y2 - 10 February 2023 through 12 February 2023

ER -

Ahmad F, Al-Fagih L, Qadir SA, Khalid M. EV Charging Station Placement using Nature-Inspired Optimisation Algorithms. In 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023. Institute of Electrical and Electronics Engineers Inc. 2023. 166. (2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023). doi: 10.1109/PIECON56912.2023.10085885

EV Charging Station Placement using Nature-Inspired Optimisation Algorithms

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this