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Multi Criteria Decision Analysis to Optimise Siting of Electric Vehicle Charging Points—Case Study Winchester District, UK

Author

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  • Mostafa Mahdy

    (Energy & Climate Change Division, Sustainable Energy Research Group, Faculty of Engineering & Physical Science, University of Southampton, Southampton SO16 7QF, UK)

  • AbuBakr S. Bahaj

    (Energy & Climate Change Division, Sustainable Energy Research Group, Faculty of Engineering & Physical Science, University of Southampton, Southampton SO16 7QF, UK)

  • Philip Turner

    (Energy & Climate Change Division, Sustainable Energy Research Group, Faculty of Engineering & Physical Science, University of Southampton, Southampton SO16 7QF, UK)

  • Naomi Wise

    (Winchester City Council, Winchester SO23 9LJ, UK)

  • Abdulsalam S. Alghamdi

    (Electrical and Computer Engineering Department, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Hidab Hamwi

    (Kuwait Institute for Scientific Research (KISR), Safat 13109, Kuwait)

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.

Suggested Citation

  • Mostafa Mahdy & AbuBakr S. Bahaj & Philip Turner & Naomi Wise & Abdulsalam S. Alghamdi & Hidab Hamwi, 2022. "Multi Criteria Decision Analysis to Optimise Siting of Electric Vehicle Charging Points—Case Study Winchester District, UK," Energies, MDPI, vol. 15(7), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2497-:d:781941
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    References listed on IDEAS

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    Cited by:

    1. Torkey, Alaa & Abdelgawad, Hossam, 2022. "Framework for planning of EV charging infrastructure: Where should cities start?," Transport Policy, Elsevier, vol. 128(C), pages 193-208.
    2. Panagiotis Skaloumpakas & Evangelos Spiliotis & Elissaios Sarmas & Alexios Lekidis & George Stravodimos & Dimitris Sarigiannis & Ioanna Makarouni & Vangelis Marinakis & John Psarras, 2022. "A Multi-Criteria Approach for Optimizing the Placement of Electric Vehicle Charging Stations in Highways," Energies, MDPI, vol. 15(24), pages 1-13, December.
    3. Oluwasola O. Ademulegun & Paul MacArtain & Bukola Oni & Neil J. Hewitt, 2022. "Multi-Stage Multi-Criteria Decision Analysis for Siting Electric Vehicle Charging Stations within and across Border Regions," Energies, MDPI, vol. 15(24), pages 1-28, December.
    4. Hidab Hamwi & Tom Rushby & Mostafa Mahdy & AbuBakr S. Bahaj, 2022. "Effects of High Ambient Temperature on Electric Vehicle Efficiency and Range: Case Study of Kuwait," Energies, MDPI, vol. 15(9), pages 1-12, April.

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