@inproceedings{9c66600dfbb74244ab55b663e62aeec2,
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",
}