Optimal Placement of Electric Vehicle Charging Stations to Maximize Coverage and Utilization in Dublin

Jadhav, Shubham Ramrao (2023) Optimal Placement of Electric Vehicle Charging Stations to Maximize Coverage and Utilization in Dublin. Masters thesis, Dublin, National College of Ireland.

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Abstract

Globally, electric vehicles (EVs) are spearheading the sustainable transportation movement. To encourage more people to buy electric vehicles, charging stations must be easily accessible and strategically placed (Zero Emission Vehicles Ireland: Policy documents; 2023). In order to maximise coverage and usage, this comprehensive analysis optimises the placement of electric vehicle charging stations (EVCS) in Dublin, Ireland. With the use of urban and demographic data, the binary particle swarm optimisation (BPSO) and Greedy algorithms are employed to locate possible EVCS hotspots. This study makes use of spatial analysis, and demographic research. Although the Greedy strategy may perform better in scenarios with constrained resources or phased development, the findings show that the BPSO technique achieves 85.14% station coverage optimization. The knowledge gained from this research is valuable for sustainable development and city planning. Specifically in light of the expansion of EV infrastructure, the research’s conclusions are crucial for informing initiatives related to sustainable development and urban planning.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Jain, Mayank UNSPECIFIED
Uncontrolled Keywords:	Electric vehicle (EV); electric vehicle charging station (EVCS); binary particle swarm optimisation (BPSO)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > TE Highway engineering. Roads and pavements D History General and Old World > DA Great Britain > Ireland > Dublin T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electricity Supply H Social Sciences > HT Communities. Classes. Races > Urban Sociology > Urban Renewal
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	09 May 2025 08:28
Last Modified:	09 May 2025 08:28
URI:	https://norma.ncirl.ie/id/eprint/7530

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