Journal
ENERGIES
Volume 15, Issue 7, Pages -Publisher
MDPI
DOI: 10.3390/en15072497
Keywords
AHP; electrical vehicles and infrastructure; MCDM; spatial siting; charging points; Winchester District
Categories
Funding
- Winchester City Council
- Ministry of Education in Saudi Arabia [714]
- UKRI EPSRC [EP/G06394X/1, EP/T023074/1, EP/R030391/1]
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This research presents a methodology for planning the optimal siting of charging infrastructure for electric vehicles (EVs) in cities. The methodology uses the Analytical Hierarchy Process (AHP) and Geographical Information System (GIS) to assess various criteria and identify suitable locations. The study focuses on Winchester City and District in the UK but can be applied to other cities or regions. The methodology is accurate and generalisable.
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(R) 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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