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2019 1st International Conference on Industrial Artificial Intelligence (IAI) / Institute of Electrical and Electronics Engineers.

IEEE Xplore (IEEE/IET Electronic Library - IEL) Available online

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Format:
Book
Author/Creator:
Institute of Electrical and Electronics Engineers, author, issuing body.
Language:
English
Subjects (All):
Artificial intelligence--Industrial applications--Congresses.
Artificial intelligence.
Physical Description:
1 online resource (85 pages) : illustrations
Other Title:
2019 1st International Conference on Industrial Artificial Intelligence
Place of Publication:
Piscataway, New Jersey : IEEE, 2019.
Summary:
Electric Vehicles (EV) are environment-friendly with lower CO2 emissions, and financial affordability (in term of battery based refuel) benefits. Here, when and where to recharge are sensitive factors significantly impacting the environmental and financial gains, these are still challenges to be tackled. In this paper, we propose a sustainable and smart EV charging scheme enables the preemptive charging functions for heterogeneous EVs equipped with various charging capabilities and brands. Our scheme intents to address the problems when EVs are with various ownerships and priority, in related to the services agreed with charging infrastructure operators. Particularly, the anticipated EVs' charging reservations information with heterogeneity (are multiscale) including their EV type, expected arrival time and charging waiting time at the charging stations (CSs), have been considered for design, planning and optimal decision making on the selection (i.e., where to charge) among the candidature CSs. We have conducted extensive simulation studies, by taking the realistic Helsinki city geographical and traffic scenarios as an example. The numerical results have confirmed that our proposed preemptive approach is better than the First-Come-First-Serve (FCFS) based system, associated with its significant improvement on the reservation feature in EV charging.
Notes:
Description based on publisher supplied metadata and other sources.
Includes bibliographical references.
ISBN:
9781728135939
1728135931

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