Pallonetto, Fabiano and Galvani, Marta and Torti, Agostino and Vantini, Simone (2020) A Framework for Analysis and Expansion of Public Charging Infrastructure under Fast Penetration of Electric Vehicles. World Electric Vehicle, 11 (1). p. 18. ISSN 2032-6653

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Abstract

The improvement commercial competitiveness of private electric vehicles supported by the European policy for the decarbonisation of transport and with the consumers awareness-raising about CO2 emissions and climate change, are driving the increase of electric vehicles on the roads. Therefore, public charging networks are facing the challenge of supply electricity to a fast increasing number of electric cars. The objective of this paper is to establish an assessment framework for analysis and monitor of existing charging networks. The developed methodology comprises modelling the charging infrastructure electricity profile, analysing the data by using machine learning models such as functional k-means clustering and defining a novel congestion metric. The described framework has been tested against Irish public charging network historical datasets. The analyses reveal a lack of reliability of the communication network infrastructure, frequent congestion events for commercial and shopping areas in specific clusters of charge points and the presence of power peaks caused by the high number of simultaneous charging events. Several recommendations for future network expansion have been highlighted.

Item Type:	Article
Additional Information:	This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/4.0/. Cite as: Pallonetto, Fabiano, Marta Galvani, Agostino Torti, and Simone Vantini. 2020. "A Framework for Analysis and Expansion of Public Charging Infrastructure under Fast Penetration of Electric Vehicles" World Electric Vehicle Journal 11, no. 1: 18. https://doi.org/10.3390/wevj11010018
Keywords:	electric vehicles (EV); charging point; public charging network; congestion; machine learning; plug-in hybrids (PHEV); functional data analysis (FDA); functional clustering; demand side management; data analytics;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Social Sciences > Research Institutes > Innovation Value Institute, IVI Faculty of Social Sciences > School of Business
Item ID:	15007
Identification Number:	https://doi.org/10.3390/wevj11010018
Depositing User:	Fabiano Pallonetto
Date Deposited:	11 Nov 2021 17:04
Journal or Publication Title:	World Electric Vehicle
Publisher:	MDPI
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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