在大学校园分析电动汽车充电需求的旅行数据集
Yan Wu1, Syed Mahfuzul Aziz1, Mohammed H Haque1
1UniSA STEM, University of South Australia, Mawson Lakes, SA, Australia.
Data in brief
|April 8, 2024
概括
这项研究分析了电动汽车 (EV) 充电需求,使用来自大学校园的私人车辆旅行数据. 这些发现有助于优化电动汽车充电策略,以降低年度能源成本.
科学领域:
- 运输科学 运输科学
- 能源系统工程 能源系统工程
- 数据科学数据科学数据科学
背景情况:
- 电动汽车 (EV) 越来越多地被采用,需要了解其充电需求.
- 大学校园为分析电动汽车充电模式提供了独特的环境.
- 优化电动汽车充电可以显著降低能源成本和电网影响.
研究的目的:
- 为了确定大学校园的电动汽车 (EV) 的每日充电需求.
- 分析降低与电动汽车充电相关的年度能源成本的策略.
- 为模拟提供一种用于生成现实的电动汽车行驶数据的方法.
主要方法:
- 使用了维多利亚旅游和活动综合调查 (VISTA) 的原始数据集.
- 过和处理数据以提取每日旅行距离和工作场所到达-离开时间.
- 开发了概率分布,为单个电动汽车创建全年旅行数据.
主要成果:
- 基于模拟的个人电动汽车旅行数据生成每日电动汽车充电需求配置文件.
- 建立了测试各种电动汽车充电策略和成本优化方法的基础.
- 详细介绍了从原始数据采集到个人电动汽车旅行数据生成的实验过程.
结论:
- 该方法允许准确模拟校园内的电动汽车充电需求.
- 数据驱动的洞察力可以为开发有效的电动汽车充电管理策略提供信息.
- 这项研究有助于将电动汽车有效地整合到大学环境中.
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