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Optimal supercharge scheduling of electric vehicles

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dc.contributor.author Atallah, Ribal F.
dc.contributor.author Assi, Chadi M.
dc.contributor.author Fawaz, Wissam
dc.contributor.author Tushar, Mosaddek Hossain Kamal
dc.contributor.author Khabbaz, Maurice Jose
dc.date.accessioned 2019-10-03T07:18:43Z
dc.date.available 2019-10-03T07:18:43Z
dc.date.copyright 2018 en_US
dc.identifier.issn 0018-9545 en_US
dc.identifier.uri http://hdl.handle.net/10725/11364
dc.description.abstract The contemporary problem of scheduling the recharge operations of electric vehicles (EVs) has gained a lot of research attention. This is particularly true given the governmental and industrial confidence in a bright future for EVs accompanied with the widespread installation of an enormous number of charging stations across the world. As such, this paper addresses the delay-optimal scheduling of charging EVs at several charging stations (CSs) each with multiple charging outlets. At first, a centralized optimization framework is formulated using an integer linear problem (ILP) that accounts for the delayed arrival of EVs to CSs and the randomness in the requested recharge time interval. Simulation results showed the efficacy of the ILP model when compared to naive as well as sophisticated scheduling heuristics. Next, motivated by the scalability issues of the ILP model, this paper then proposes a distributed game-theoretical approach where each EV communicates with its selected CS and iterates on modifying its strategy until all EVs converge to selecting an appropriate CS that minimizes their waiting times for receiving services. The distributed game-theoretical approach recorded promising results especially when compared to the well-known shortest job first scheduling algorithm. Further, unlike the other approaches, which normally are centralized and suited for offline scheduling, the game-based method is suited for online scheduling since it played at anytime a batch of EVs requests charging services. The running time of the game is remarkably small and outperforms all other heuristics and its convergence to Nash equilibrium is guaranteed after only small number of iterations. en_US
dc.language.iso en en_US
dc.title Optimal supercharge scheduling of electric vehicles en_US
dc.type Article en_US
dc.description.version Published en_US
dc.title.subtitle centralized versus decentralized nethods en_US
dc.author.school SOE en_US
dc.author.department Electrical And Computer Engineering en_US
dc.description.embargo N/A en_US
dc.relation.journal IEEE Transactions on Vehicular Technology en_US
dc.journal.volume 67 en_US
dc.journal.issue 9 en_US
dc.article.pages 7896-7909 en_US
dc.keywords Linear optimization en_US
dc.keywords Electric vehicles en_US
dc.keywords Scheduling en_US
dc.keywords Game theory en_US
dc.identifier.doi https://doi.org/10.1109/TVT.2018.2842128 en_US
dc.identifier.ctation Atallah, R. F., Assi, C. M., Fawaz, W., Tushar, M. H. K., & Khabbaz, M. J. (2018). Optimal Supercharge Scheduling of Electric Vehicles: Centralized Versus Decentralized Methods. IEEE Transactions on Vehicular Technology, 67(9), 7896-7909. en_US
dc.author.email wissam.fawaz@lau.edu.lb en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://ieeexplore.ieee.org/abstract/document/8369097 en_US
dc.orcid.id https://orcid.org/0000-0002-3161-1846 en_US
dc.author.affiliation Lebanese American University en_US


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