ECOSPOT - Green Charging Station Placement Strategy

Aditya Gaherwar

Title:
ECOSPOT - Green Charging Station Placement Strategy

Authors:
Aditya Gaherwar

Cite This Article :

Aditya Gaherwar "ECOSPOT - Green Charging Station Placement Strategy" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Advancements and Emerging Trends in Computer Applications - Innovations, Challenges, and Future Prospects, March 2025, pp.1312-1316, URL: https://www.ijtsrd.com/papers/ijtsrd79856.pdf

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Abstract :
The quick uptake of electric vehicles (EVs) requires an optimized and well-distributed charging infrastructure to provide convenience, reduce charging time, and maximize energy usage. This paper proposes a data-driven method for the optimal location of EV charging stations based on traffic density, energy supply, and geographical limitations. By incorporating Geographic Information Systems (GIS), Machine Learning (ML), and optimization methodologies like Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), the present research tends to improve access, enhance stability of the grid, and enable sustainable transportation. The model suggested here is empirically verified based on real datasets to ensure cost-effective deployment of charging infrastructure.

Keywords :
Electric Vehicles, Charging Stations, GIS, Machine Learning, Optimization, Sustainable Transportation.

Publication Details:

Unique Identification Number : IJTSRD79856

Published In : Special Issue | Advancements and Emerging Trends in Computer Applications - Innovations, Challenges, and Future Prospects, March 2025

Page Number(s) : 1312-1316

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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