Smart City Gnosys

Smart city article details

Title	Machine Learning For Solving Charging Infrastructure Planning: A Comprehensive Review
ID_Doc	35984
Authors	Deb S.
Year	2021
Published	5th International Conference on Smart Grid and Smart Cities, ICSGSC 2021
DOI	http://dx.doi.org/10.1109/ICSGSC52434.2021.9490407
Abstract	The ever-growing energy demand accompanied with environmental pollution has initiated a paradigm shift towards Electric Vehicles (EVs) from conventional vehicles. Public acceptance of EVs call for availability of charging infrastructure. Charging infrastructure planning is an intricate process involving various activities such as charging station placement, charging demand prediction, charging scheduling etc and interaction of power distribution as well as road network. In recent years, the advent of machine learning has made data driven approaches popular for solving charging infrastructure planning problem. Consequently, researchers have started using machine learning techniques for solving problems associated with charging infrastructure planning such as charging station placement, charging demand prediction, charging scheduling etc. This work aims to provide a comprehensive review of machine learning applications for solving charging infrastructure planning. © 2021 IEEE.
Author Keywords	charger; electric vehicle; machine learning; review

Similar Articles

Id	Similarity	Authors	Title	Published
35983	0.987	Deb S.	Machine Learning For Solving Charging Infrastructure Planning Problems: A Comprehensive Review	Energies, 14, 23 (2021)
35913	0.917	Shahriar S.; Al-Ali A.R.; Osman A.H.; Dhou S.; Nijim M.	Machine Learning Approaches For Ev Charging Behavior: A Review	IEEE Access, 8 (2020)
4133	0.897	Qaisar S.M.; Alyamani N.	A Review Of Charging Schemes And Machine Learning Techniques For Intelligent Management Of Electric Vehicles In Smart Grid	Managing Smart Cities: Sustainability and Resilience Through Effective Management (2022)
22524	0.895	Doda D.K.; Beemkumar N.; Awasthi A.; Gautam A.K.	Electric Vehicle Energy Management: Charging In Sustainable Urban Settings For Smart Cities	E3S Web of Conferences, 540 (2024)
36044	0.886	Neelakantam G.	Machine Learning-Based Decision Making For Charging/Discharging Cost Optimization Of Prev In Smart City	Proceedings of the 1st International Symposium on Parallel Computing and Distributed Systems, PCDS 2024 (2024)
22520	0.885	Mazhar T.; Asif R.N.; Malik M.A.; Nadeem M.A.; Haq I.; Iqbal M.; Kamran M.; Ashraf S.	Electric Vehicle Charging System In The Smart Grid Using Different Machine Learning Methods	Sustainability (Switzerland), 15, 3 (2023)
42854	0.883	Garg R.; Deogaonkar A.; Garia P.; Ahamad I.; Kharayat P.S.; Joshi T.	Prediction Of User Behaviour Of Electric Vehicles Utilizing Ensembled Machine Learning Technique	2024 IEEE International Conference on Communication, Computing and Signal Processing, IICCCS 2024 (2024)
20471	0.88	Richard R.; Cao H.; Wachowicz M.	Discovering Ev Recharging Patterns Through An Automated Analytical Workflow	2020 IEEE International Smart Cities Conference, ISC2 2020 (2020)
30935	0.878	Youness H.; Mohamed T.; Ahmed G.; Hajar A.; Benachir E.L.H.	Improving The Effectiveness Of Electric Vehicle Charging Infrastructure Within A Smart City Using Artificial Neural Networks (Ann) And The Internet Of Vehicles (Iov)	Proceedings of the International Conference on Microelectronics, ICM (2024)
40337	0.878	Alanazi F.; Alshammari T.O.; Azam A.	Optimal Charging Station Placement And Scheduling For Electric Vehicles In Smart Cities	Sustainability (Switzerland), 15, 22 (2023)