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Augmenting EV charging infrastructure towards transformative sustainable cities: An equity-based approach

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posted on 2025-08-02, 10:38 authored by SK Sikder, M Nagarajan, N Mustafee
An increasing number of studies have reported on the need to augment public electric vehicle (EV) charging points (E-CPs) in areas with growing demand for parking. However, the focus on E-CP infrastructure equity has largely been ignored. For increased uptake of EVs, we argue that future E-CP infrastructure augmentation (EIA) will necessitate the identification of the optimal locations based on a need-focused strategic approach. Our work utilises open datasets and presents a generic multicriteria-based modelling framework for EIA framework. The E-CP Infrastructure Framework a two-stage framework. The first stage assesses the existing infrastructure gap and spatial disparity of E-CP allocation at the city scale. Next, guided by the information from stage one, stage two identifies the optimal E-CP candidate locations for future EIA expansion. The locations are determined using a parametric scoring approach that includes ease of access, available bays for parked vehicles, and potential congestion risk. We take the example of Dresden city to demonstrate the applicability of the EIA framework. Our findings show the wide prevalence of spatial disparities in E-CPs across nine of the ten wards in the city. Our proposed city-scale approach for identifying candidate locations could help policymakers decide on the augmentation strategies of E-CP infrastructure in a spatially equitable and cost-effective manner.

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© 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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This is the final version. Available on open access from Elsevier via the DOI in this record Data availability: We maintain all dataset, code and interactive visualizaiton for this paper in an open repository. This can be accessed at: https://doi.org/10.5281/zenodo.8335314

Journal

Technological Forecasting and Social Change

Pagination

122829-122829

Publisher

Elsevier

Version

  • Version of Record

Language

en

FCD date

2023-09-25T07:38:34Z

FOA date

2023-09-25T07:43:51Z

Citation

Vol. 196, article 122829

Department

  • Management

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