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Updated: May 29, 2025

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一个空间时间分布预测模型,用于电动汽车在运输电力联网络中充电负载
Xiaolong Yang1,2, Jingwen Yun3, Shuai Zhou4
1School of Economics and Management, Northeast Electric Power University, Jilin, 132012, China. yangxiaolong@neepu.edu.cn.
Scientific reports
|February 1, 2025
概括
准确预测电动汽车 (EV) 充电负载对于城市基础设施规划至关重要. 本研究介绍了一个模型来预测电动汽车充电需求,支持高效的充电站发展.
科学领域:
- 运输工程 运输工程
- 电力系统工程 电力系统工程
- 城市规划 城市规划
背景情况:
- 电动汽车 (EV) 普及的增加给城市充电基础设施带来了挑战,包括充电点不足和站点位置不足.
- 电动汽车充电基础设施的有效规划需要准确预测充电负载.
研究的目的:
- 为电动汽车 (EV) 充电负载在运输电力联网 (TPCN) 中提出一个时空分布预测模型.
- 为预测区域电动汽车充电需求提供可靠的方法,并支持电动汽车充电站的合理规划.
主要方法:
- 使用迪克斯特拉算法和基于车辆行驶特征的精细起源-目的地 (OD) 概率矩阵进行路径规划.
- 制定充电选择模型,包括运输条件,环境温度和休息日等因素.
- 通过使用图形理论分析和通过蒙特卡洛模拟预测空间时间充电负载分布来建立TPCN.
主要成果:
- 电动汽车充电负载在不同的功能领域,时间段和场景中表现出显著的变化.
- 拟议的模型准确地预测了电动汽车充电负载的空间和时间分布.
- 该研究通过城市地区的案例研究来验证该模型.
结论:
- 开发的模型提供了一种可靠的方法来预测特定城市地区的电动汽车充电需求.
- 这项研究为城市电动汽车充电站网络的战略规划和优化提供了必要的支持.
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