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As a major tool for reducing carbon emissions, the ownership of electric vehicles is increasing year by year. When EV numbers reach a certain level, it is equivalent to a huge load randomly connected to the network, bringing new challenges to the daily monitoring and management of EV charging stations. Accurate load prediction methods for EV charging stations with high reliability are the basis for ensuring safe operation of charging stations and supporting the planning decisions of new construction and expansion of charging infrastructure. In this paper, the charging station load prediction methods are divided into three categories: charging station angle prediction, unsupervised learning charging load prediction and supervised learning charging load prediction, and the representative studies on load prediction for EV charging stations in these categories are reviewed respectively.
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Li et al. (2022) studied this question.
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