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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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