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2024 | OriginalPaper | Buchkapitel

Machine Learning-Based DC Microgrid Control for Electric Vehicle Charging Stations

verfasst von : Anirudh Pratap, D. K. Palwalia, Mohit Tepan, Nikhil Jain, Anjali Kumari, Anil Mina

Erschienen in: Flexible Electronics for Electric Vehicles

Verlag: Springer Nature Singapore

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Abstract

The use of Renewable energy sources to construct modern-day DC microgrids which have various implementations, one such implementation is an Electric vehicle charging station. The demand for EV is increasing throughout the world and the seamless transition of this kind in the automobile industry requires the construction of EV charging stations, maybe more in numbers than the conventional fuel stations. Therefore, a wide network of EV charging points needs to be created even in remote locations, the use of DC microgrids with grid integration seems to be a proper solution for this problem. This paper presents a machine learning-based energy distribution system for the DC microgrid to be implemented for EV charging station. The designed system is tested in MATLAB/Simulink environment and is compared with conventional control systems.

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Titel: Machine Learning-Based DC Microgrid Control for Electric Vehicle Charging Stations
verfasst von: Anirudh Pratap
D. K. Palwalia
Mohit Tepan
Nikhil Jain
Anjali Kumari
Anil Mina
Verlag: Springer Nature Singapore
Buch: Flexible Electronics for Electric Vehicles
Print ISBN: 978-981-9947-94-2

Electronic ISBN: 978-981-9947-95-9

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-981-99-4795-9_37