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Τίτλος: Exploiting data acquisition approaches in an electric vehicle charging scheduling module
Συγγραφείς: Chen, Henry 
Lambrinos, Lambros 
Grammenos, Ryan 
Karagiannis, Konstantinos 
Kfoury, Elie 
Major Field of Science: Natural Sciences
Field Category: Computer and Information Sciences
Λέξεις-κλειδιά: Accuracy;Roads;Data acquisition;Power system stability;Electric vehicle charging;Stability analysis;State of charge;Information technology;Stress
Ημερομηνία Έκδοσης: 4-Ιου-2024
Πηγή: 10th International Conference on Control, Decision and Information Technologies (CoDIT), 1-4 July, 2024
Conference: 10th International Conference on Control, Decision and Information Technologies 
Περίληψη: In the last few years there is a significant increase in the use of electric vehicles and this highly welcomed development obviously contributes towards the reduction of emissions. On the other hand, as electric vehicles require considerable power during charging, the electric grid infrastructure is put under stress during periods of high overall demand from households. As such, a smart electric vehicle charging scheduling system is a necessity satisfying the needs of the vehicle owners while ensuring the stability of the grid. One of the most significant inputs to such a system, that should be inherently available, is vehicle and user drive cycle data. To this end, this paper examines three different yet practical electric vehicle data acquisition techniques, which were tested in the real world. Consequently, data acquisition constitutes a primary building block in a newly proposed electric vehicle charging scheduling recommendation module.
URI: https://hdl.handle.net/20.500.14279/33631
ISBN: 9798350373974
DOI: 10.1109/CoDIT62066.2024.10708327
Rights: Copyright IEEE
Type: Conference Papers
Affiliation: Cyprus University of Technology 
University College London 
General Technology Ltd 
IntelliCasa Ltd 
Εμφανίζεται στις συλλογές:Άρθρα/Articles

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