Multi criteria decision analysis to optimise siting of electric vehicle charging points— case study Winchester district, UK
Multi criteria decision analysis to optimise siting of electric vehicle charging points— case study Winchester district, UK
Achieving net-zero carbon in the UK by 2050 will necessitate the decarbonisation of the transportation systems. However, there are challenges to this, especially for vehicles in cities where the charging infrastructure is at its minimum. Overcoming these challenges will undoubtedly encourage electrical vehicle (EV) use, with commensurate reductions in emission coupled with better environmental conditions in cities, e.g., air quality. Drivers, on the whole, are reluctant to invest in an EV if they cannot access a convenient charging point within their living area. This research provides a methodology to support the planning for the optimum siting of charging infrastructure, so it is accessible to as many citizens as possible within a city. The work focuses on Winchester City and District in the UK. The multi-criteria decision approach is based on the Analytical Hierarchy Process (AHP) linked to site spatial assessment using Geographical Information System (GIS). The assessment considered key criteria such as road type, road access, on-road parking availability, road slope, proximity to fuel stations, current/planned charging points, car parks and population distributions. The process contains two suitability filters, namely, restricted road and suitability mask. In the first, all restricted roads were excluded from further analysis, which resulted in reducing the road segments from over 9000 to around 2000. When applying the second filter an overall result of 44 suitable EV charging point locations was achieved. These locations were validated using the Google Earth® imaging platform to check actual locations against those predicted by the analysis. The presented methodology is accurate and is generalisable to other cities or regions.
AHP, MCDM, Winchester District, charging points, electrical vehicles and infrastructure, spatial siting
Mahdy, Mostafa
9e2c23e6-a70e-43a0-bfda-626ba4ff4f85
Bahaj, AbuBakr S.
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Turner, Philip
772d9dd5-829d-4e40-83a2-f8ea70ee2b14
Wise, Naomi
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Alghamdi, Abdulsalam S.
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Hamwi, Hidab
8e2a7677-50b0-4955-b3be-400efcfd03a1
29 March 2022
Mahdy, Mostafa
9e2c23e6-a70e-43a0-bfda-626ba4ff4f85
Bahaj, AbuBakr S.
a64074cc-2b6e-43df-adac-a8437e7f1b37
Turner, Philip
772d9dd5-829d-4e40-83a2-f8ea70ee2b14
Wise, Naomi
f7113d9f-8048-462a-9da0-240b61722cc6
Alghamdi, Abdulsalam S.
c8473e87-8814-41ba-9352-63991e9a0dba
Hamwi, Hidab
8e2a7677-50b0-4955-b3be-400efcfd03a1
Mahdy, Mostafa, Bahaj, AbuBakr S., Turner, Philip, Wise, Naomi, Alghamdi, Abdulsalam S. and Hamwi, Hidab
(2022)
Multi criteria decision analysis to optimise siting of electric vehicle charging points— case study Winchester district, UK.
Energies, 15 (7), [2497].
(doi:10.3390/en15072497).
Abstract
Achieving net-zero carbon in the UK by 2050 will necessitate the decarbonisation of the transportation systems. However, there are challenges to this, especially for vehicles in cities where the charging infrastructure is at its minimum. Overcoming these challenges will undoubtedly encourage electrical vehicle (EV) use, with commensurate reductions in emission coupled with better environmental conditions in cities, e.g., air quality. Drivers, on the whole, are reluctant to invest in an EV if they cannot access a convenient charging point within their living area. This research provides a methodology to support the planning for the optimum siting of charging infrastructure, so it is accessible to as many citizens as possible within a city. The work focuses on Winchester City and District in the UK. The multi-criteria decision approach is based on the Analytical Hierarchy Process (AHP) linked to site spatial assessment using Geographical Information System (GIS). The assessment considered key criteria such as road type, road access, on-road parking availability, road slope, proximity to fuel stations, current/planned charging points, car parks and population distributions. The process contains two suitability filters, namely, restricted road and suitability mask. In the first, all restricted roads were excluded from further analysis, which resulted in reducing the road segments from over 9000 to around 2000. When applying the second filter an overall result of 44 suitable EV charging point locations was achieved. These locations were validated using the Google Earth® imaging platform to check actual locations against those predicted by the analysis. The presented methodology is accurate and is generalisable to other cities or regions.
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energies-15-02497
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Accepted/In Press date: 18 March 2022
Published date: 29 March 2022
Keywords:
AHP, MCDM, Winchester District, charging points, electrical vehicles and infrastructure, spatial siting
Identifiers
Local EPrints ID: 456788
URI: http://eprints.soton.ac.uk/id/eprint/456788
ISSN: 1996-1073
PURE UUID: 6b28ef2e-1160-4e06-a947-c3d101bdeaa8
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Date deposited: 11 May 2022 16:44
Last modified: 17 Mar 2024 03:55
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Contributors
Author:
Mostafa Mahdy
Author:
Philip Turner
Author:
Naomi Wise
Author:
Abdulsalam S. Alghamdi
Author:
Hidab Hamwi
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