Optimizing placement of new EV charging stations in India using machine learning methodology

Singh, Abhijit (2024) Optimizing placement of new EV charging stations in India using machine learning methodology. Masters thesis, Dublin, National College of Ireland.

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Abstract

Automobiles have always been a crucial part of daily life of individuals. There is exponential increase in the daily commuters majorly in populated countries like India which has highlighted the limitations of conventional fuel-based vehicles in the future due to depleting resources. These fuel based vehicles are also harmful to the environment. The Government of India aims for 30% EV adoption by 2030 through initiatives like FAME-1 and FAME-2 but there is a poor adoption rate of EVs due to high costs and insufficient charging infrastructure that present challenges in adoption. This research proposes a machine learning framework using K-means clustering and HDBSCAN to optimize the placement of new EV charging stations across India by considering the existing infrastructure and socio-economic factors like per capita income, population density, and national highway density. The goal is to minimize waiting times and enhance user convenience, to support the government’s EV adoption targets.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Basilio, Jorge UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	26 Aug 2025 10:42
Last Modified:	26 Aug 2025 10:42
URI:	https://norma.ncirl.ie/id/eprint/8633

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