It is difficult to find the characteristics of electric vehicle users through charging transaction data. However, these characteristics are very important for charging station operators to improve the service quality of their operation and maintenance. This paper uses the K-means clustering model to study the transaction data of the charging stations in northern Hebei from October 2016 to September 2017. It finds three types of users: high-speed primary users, high-speed secondary users, and urban users; Based on this, four types of users are further drilled out: play users, cross-city office users, pass users, and urban residents users. Based on these user characteristics, corresponding operational strategies, charging station planning and construction suggestions are proposed.
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