在韩国代表电动汽车充电配置的数据驱动集群分析
Kangsan Kim1, Geumbee Kim1, Jiwon Yoo1
1Department of Data Algorithm, LG Energy Solution, Gwacheon 13818, Republic of Korea.
Sensors (Basel, Switzerland)
|November 9, 2024
概括
了解电动汽车 (EV) 的充电模式是电网稳定的关键. 这项研究使用充电状态数据模拟了电动汽车充电行为,从现实数据中识别了七个不同的用户配置文件.
科学领域:
- 电动汽车技术 电动汽车技术
- 能源系统分析 能源系统分析
- 数据科学是数据科学.
背景情况:
- 越来越多的电动汽车 (EV) 需要了解它们的运行,以确保电网稳定性和电池健康.
- 用户充电习惯的变化使电动汽车运行数据的统一分析变得复杂.
研究的目的:
- 通过实际现场数据提出分析电动汽车充电特征的框架.
- 在统一的格式中建模单个EV操作配置文件.
- 为了确定代表性的电动汽车充电模式.
主要方法:
- 使用充电开始和充电结束状态 (SoCs) 的概率分布建模单个EV操作配置文件.
- 采用层次聚类分析来得出代表性的充电配置文件.
- 利用来自韩国的大型,车辆特定的电动汽车数据.
主要成果:
- 开发了一个框架,以捕捉基于充电-放电区域的电动汽车充电特征.
- 使用SoC概率分布建模了EV操作配置文件.
- 层次聚类确定了七个不同的代表性电动汽车充电配置文件.
结论:
- 拟议的框架有效地统一了各种各样的电动汽车充电数据.
- 确定了七个代表性的充电配置文件,简化了对电动汽车电池充放电行为的分析.
- 这种分类有助于理解和管理电动汽车与电网的整合.
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