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Machine learning for solving charging infrastructure planning problems : a comprehensive review
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Deb, Sanchari (2021) Machine learning for solving charging infrastructure planning problems : a comprehensive review. Energies, 14 (23). 7833. doi:10.3390/en14237833
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Official URL: https://doi.org/10.3390/en14237833
Abstract
As a result of environmental pollution and the ever-growing demand for energy, there has been a shift from conventional vehicles towards electric vehicles (EVs). Public acceptance of EVs and their large-scale deployment raises requires a fully operational charging infrastructure. Charging infrastructure planning is an intricate process involving various activities, such as charging station placement, charging demand prediction, and charging scheduling. This planning process involves interactions between power distribution and the road network. The advent of machine learning has made data-driven approaches a viable means for solving charging infrastructure planning problems. Consequently, researchers have started using machine learning techniques to solve the aforementioned problems associated with charging infrastructure planning. This work aims to provide a comprehensive review of the machine learning applications used to solve charging infrastructure planning problems. Furthermore, three case studies on charging station placement and charging demand prediction are presented. This paper is an extension of: Deb, S. (2021, June). Machine Learning for Solving Charging Infrastructure Planning: A Comprehensive Review. In the 2021 5th International Conference on Smart Grid and Smart Cities (ICSGSC) (pp. 16–22). IEEE. I would like to confirm that the paper has been extended by more than 50%. View Full-Text
| Item Type: | Journal Article | ||||||
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| Subjects: | Q Science > Q Science (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TL Motor vehicles. Aeronautics. Astronautics |
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| Divisions: | Other > Institute of Advanced Study | ||||||
| Library of Congress Subject Headings (LCSH): | Electric vehicles , Battery charging stations (Electric vehicles) , Battery charging stations (Electric vehicles) -- Design and construction , Battery charging stations (Electric vehicles) -- Installation, Battery charging stations (Electric vehicles) -- Installation -- Data processing , Electric vehicles -- Power supply, Machine learning | ||||||
| Journal or Publication Title: | Energies | ||||||
| Publisher: | M.D.P.I.A.G. | ||||||
| ISSN: | 1996-1073 | ||||||
| Official Date: | 23 November 2021 | ||||||
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| Volume: | 14 | ||||||
| Number: | 23 | ||||||
| Article Number: | 7833 | ||||||
| DOI: | 10.3390/en14237833 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Open Access | ||||||
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