城市EV:城市电动汽车充电需求预测的开放基准数据集
Han Li1, Haohao Qu2, Xiaojun Tan1
1Sun Yat-sen University, School of Intelligent Systems Engineering, Shen Zhen, 518107, China.
Scientific data
|March 29, 2025
概括
本研究介绍了UrbanEV,这是一套用于电动汽车 (EV) 充电预测的新数据集. 它可以在电动汽车充电管理和可持续性方面取得进展.
科学领域:
- 环境科学 环境科学
- 计算机科学 计算机科学
- 运输工程 运输工程
背景情况:
- 电动汽车 (EV) 的日益普及需要改进充电基础设施和预测模型.
- 全球可持续发展目标推动了对高效电动汽车能源管理的需求.
研究的目的:
- 推出UrbanEV,一个用于预测电动汽车充电的开放数据集.
- 为研究电动汽车充电可用性和电力消耗提供一个基准资源.
主要方法:
- 在六个月内收集了中国深超过2万个车站的每小时收费数据 (占用率,持续时间,数量,价格).
- 纳入了诸如天气条件和空间接近等影响因素.
- 评估了使用UrbanEV数据集的统计,深度学习和基于变压器的预测模型.
主要成果:
- 证明了UrbanEV数据集对培训和评估各种预测模型的有用性.
- 展示了各种建模方法在现实世界电动汽车充电数据上的预测能力.
- 为先进的电动汽车充电预测和管理策略奠定了基础.
结论:
- 城市电动汽车数据集是推动电动汽车充电预测和管理的宝贵资源.
- 这一开放式数据集将加速可持续运输解决方案的研发.
- 城市电动汽车促进了更智能,更高效的电动汽车充电网络的发展.
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