On April 16, faculty and students from the School of Electrical Engineering at Southeast University published a research article entitled “A high-resolution electric vehicle charging transaction dataset with multidimensional features in China” inScientific Data, an authoritative journal under the Nature portfolio focusing on open data sharing.
This paper releases the first high-resolution electric vehicle charging transaction dataset in China that covers multiple cities and multidimensional features. It systematically records de-identified charging data from more than 200 high-resolution stations across 13 Chinese cities from 2020 to 2021, including information on charging transaction time, energy, price, charging status, as well as the charging termination reasons and weather data for each charging sessions. For the first time, the dataset incorporates joint modeling of user behavior and station anomaly factors, providing high-quality support for key tasks such as charging load forecasting, station siting, and power system operation and scheduling.
With the continued rapid development of electric vehicles, existing studies generally rely on small-scale, single-dimensional samples, which makes it difficult to support city-scale energy forecasting and system-level optimization decisions. This dataset fills a long-standing data gap in electric vehicle user behavior modeling and anomaly awareness, and has broad research and engineering value.
Southeast University is the first-affiliated institution of the paper. Professor Yuanshi Zhang and Professor Tao Chen from the School of Electrical Engineering are the first and third authors, respectively; senior undergraduate student Tongxin Xu is the second author; and Professor Qinran Hu is the corresponding author.
Paper link:https://www.nature.com/articles/s41597-025-04982-1
Text/Photos: Tao Chen Reviewers: Wei Gu
