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A load balanced charging strategy for electric vehicle in smart grid

Tang, Q and Xie, MZ and Wang, L and Luo, YS and Yang, K (2017) A load balanced charging strategy for electric vehicle in smart grid. In: UNSPECIFIED, ? - ?.

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Abstract

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017. As the number of Electric Vehicle (EV) increases, the uncoordinated charging behaviors may cause the charging demand fluctuations and the charging load unbalanced. Besides, the users’ charging behaviors are affected by many factors. For example, the residual energy of battery decides the travel distance of EV and if an EV has more residual energy, the charging willing is lower. Because EV users don’t have much willing to change their charging time and place just as in the past, the charging habit may also affect the charging decision. In this paper, we propose a smart charging startegy CDF (Charging Decision Function), where three sub-functions related to the residual energy of battery, EV’s charging habit, and the charging efficiency of charging station are all weighted and involved, for improving the balance of charging load and reducing the charging demand fluctuations. The charging decision is resulted from the CDF’s value, and if an EV decides to charge, the charging time as well as charging place is also calculated. Compared with other two related strategies, CDF has the best performance in terms of reducing the charging demand fluctuations. The load balance among different charging stations is also improved.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: Published proceedings: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 14 Feb 2017 09:40
Last Modified: 17 Aug 2017 17:19
URI: http://repository.essex.ac.uk/id/eprint/19020

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