| Charging Behavior Analysis Based on BIRCH Clustering | |
Yan, Dong1; Luo, Chong-Yang1; Li, Yulan2 ; Zhu, Bin3; Yan, Miao-Long4; Yao, Shu-Li4
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| 2022 | |
| 会议录名称 | 2022 12th International Conference on Power and Energy Systems, ICPES 2022
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| 页码 | 450-454 |
| 会议名称 | 12th International Conference on Power and Energy Systems, ICPES 2022 |
| 会议日期 | December 23, 2022 - December 25, 2022 |
| 会议地点 | Guangzhou, China |
| 出版地 | NEW YORK |
| 出版者 | Institute of Electrical and Electronics Engineers Inc. |
| 摘要 | Many charging pile statistics have been produced as a result of the increased popularity of electric vehicles and the ongoing growth in the number of charging stations. In order to obtain a typical charging user profile, this paper collects and cleans the charging data from 2021 to 2022 in Banan District, Chongqing. It then uses the BIRCH clustering method to group the charging power, SOC, and RFM data into one-dimensional, two-dimensional, and three-dimensional cluster groups. According to the clustering results, 75% of users in the Banan District charge at low and medium power levels. Some users exhibit overt signs of anxiety about their mileage or refuse to wait for charging. RFM clustering categorizes the level of user demand for charging in the Banan District into three types, demonstrating how frequently users charge there. Finally, this research offers several recommendations based on the three clustering traits. The user profile and recommendations can successfully aid distribution networks and operators in better understanding users, and they can serve as useful resources for creating better charge configuration plans and marketing campaigns. © 2022 IEEE. |
| 关键词 | Charging (batteries) Clustering algorithms Electric power distribution Marketing Piles User profile Behavior analysis BIRCH Charging data Charging station Chongqing Cluster Clustering methods Clusterings RFM User's profiles |
| DOI | 10.1109/ICPES56491.2022.10072610 |
| 收录类别 | CPCI-S |
| 语种 | 英语 |
| WOS研究方向 | Construction & Building Technology ; Energy & Fuels |
| WOS类目 | Construction & Building Technology ; Energy & Fuels |
| WOS记录号 | WOS:001031346600080 |
| EI入藏号 | 20231513885450 |
| 原始文献类型 | Conference article (CA) |
| 引用统计 | |
| 文献类型 | 会议论文 |
| 条目标识符 | https://ir.cqcet.edu.cn/handle/39TD4454/17797 |
| 专题 | 建筑与材料学院 |
| 作者单位 | 1.College of Automation, Chongqing University of Posts and Telecommunications, Chongqing, China; 2.Chongqing College of Electronic Engineering, Chongqing, China; 3.State Grid Chongqing Electric Power Company, Marketing Service Center, Metrology Center State Grid, State Grid, Yu Bei District, Chongqing, China; 4.Xinli Smart Science Technology Chonging Ltd., Chongqing, China |
| 推荐引用方式 GB/T 7714 | Yan, Dong,Luo, Chong-Yang,Li, Yulan,et al. Charging Behavior Analysis Based on BIRCH Clustering[C]. NEW YORK:Institute of Electrical and Electronics Engineers Inc.,2022:450-454. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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