Chargym: An EV Charging Station Model for Controller Benchmarking-Reference-Cited by-同舟云学术

Chargym: An EV Charging Station Model for Controller Benchmarking

Published:2022 Issue: Volume: Page:241-252
ISSN:1868-4238
Container-title:IFIP Advances in Information and Communication Technology
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Author:

Karatzinis Georgios^ORCID,Korkas Christos^ORCID,Terzopoulos Michalis,Tsaknakis Christos,Stefanopoulou Aliki^ORCID,Michailidis Iakovos^ORCID,Kosmatopoulos Elias^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-08341-9_20

Reference22 articles.

1. Ma, Z., Callaway, D.S., Hiskens, I.A.: Decentralized charging control of large populations of plug-in electric vehicles. IEEE Trans. Control Syst. Technol. 21(1), 67–78 (2011)

2. Han, S., Han, S.H., Sezaki, K.: Design of an optimal aggregator for vehicle-to-grid regulation service. In: 2010 Innovative Smart Grid Technologies (ISGT). IEEE (2010)

3. Korkas, C.D., Baldi, S., Michailidis, P., Kosmatopoulos, E.B.: A cognitive stochastic approximation approach to optimal charging schedule in electric vehicle stations. In: 2017 25th Mediterranean Conference on Control and Automation (MED), pp. 484–489. IEEE, July 2017

4. Korkas, C.D., Baldi, S., Yuan, S., Kosmatopoulos, E.B.: An adaptive learning-based approach for nearly optimal dynamic charging of electric vehicle fleets. IEEE Trans. Intell. Transp. Syst. 19(7), 2066–2075 (2017)

5. Qian, T., Shao, C., Wang, X., Shahidehpour, M.: Deep reinforcement learning for EV charging navigation by coordinating smart grid and intelligent transportation system. IEEE Trans. Smart Grid 11(2), 1714–1723 (2019)

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