Optimization Strategies for Efficient Charging Station Deployment in Urban and Rural Networks
Authors:
Sudheer Panyaram
Addresses:
Department of Information Technology and ERP Application, Amplify Cell Technologies, Bloomington, Illinois, United States of America. sudheer5940@gmail.com
Optimized charging station deployment will enrich the electric vehicle ecosystem, especially in diversified urban and rural environments. In this research paper, an effort has been made to optimization strategies regarding the location of EV charging stations and how these can be operated effectively. The study analyzes key factors, such as population density, travel patterns, energy demand, and land availability, that provide a comprehensive framework for policymakers and planners. Urban regions are dense and thus in huge demand; thus, there must be advanced technologies to address the challenge, such as predictive analytics and dynamic pricing models. For rural regions, strategies must be developed to manage sparse populations and further travel distances. This paper attempts a hybrid approach to the station distribution optimization strategy and uses the tools of Geographic Information Systems, machine learning algorithms, and multi-criteria decision-making techniques. Methodology The method applied in the case studies gathered from different geographical regions validated the results as viable among them. Lower operational costs and improved user satisfaction seemed to be the outcomes to be perceived. The above findings, therefore, point out the integrated approach in tandem with balancing socio-economic and environmental factors such that sustainable growth can be ensured for the infrastructures of electric vehicles.
Keywords: Charging Station Optimization; Electric Vehicles (EV); Urban-Rural Infrastructure; Multi-Criteria Decision-Making (MCDM); Geographic Information Systems (GIS).
Received on: 19/09/2023, Revised on: 03/11/2023, Accepted on: 05/01/2024, Published on: 05/06/2024
DOI: 10.69888/FTSESS.2024.000245
FMDB Transactions on Sustainable Environmental Sciences, 2024 Vol. 1 No. 2, Pages: 69-80
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