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Analysis of Electric Vehicle Charging Behavior under Differential Privacy Protection

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DOI: 10.23977/isspj.2020.51003 | Downloads: 38 | Views: 2924


Baoyi Wang 1, Ziyi Liu 1, Shaomin Zhang 1


1 School of Control and Computer Engineering, North China Electric Power University, HuaDian Road, Baoding, China

Corresponding Author

Baoyi Wang


In order to reduce the impact of electric vehicles on the power grid, the charging behavior of electric vehicles is analyzed, which can improve the reliability of power grid operation. Understanding the charging behavior of electric vehicle users is helpful to improve charging service and guide charging behavior. Aiming at the problem of privacy disclosure in the process of data analysis, this paper proposes an electric vehicle charging data clustering algorithm under differential privacy protection. This method enhances the availability of clustering result by improving the selection of initial cluster center points and detecting outliers. The classification of electric vehicle users is realized through experiment, and the characteristics of charging mode corresponding to each user are analyzed.


Electric Vehicles, Differential Privacy Protection, K-means Algorithm


Baoyi Wang, Ziyi Liu and Shaomin Zhang. Analysis of Electric Vehicle Charging Behavior under Differential Privacy Protection. Information Systems and Signal Processing Journal (2020) 5: 11-17. DOI:


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