Abstract
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.
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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Tang, Q., Xie, Mz., Wang, L., Luo, Ys., Yang, K. (2017). A Load Balanced Charging Strategy for Electric Vehicle in Smart Grid. In: Hu, J., Leung, V., Yang, K., Zhang, Y., Gao, J., Yang, S. (eds) Smart Grid Inspired Future Technologies. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 175. Springer, Cham. https://doi.org/10.1007/978-3-319-47729-9_16
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DOI: https://doi.org/10.1007/978-3-319-47729-9_16
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