电动汽车充电基础设施的时空空间规划:在不确定性条件下对需求进行估计和对电网进行优化
Jingbo Wang1, Harshal D Kaushik1, Roshni Anna Jacob1,2
1Department of Mechanical Engineering, The University of Texas at Dallas, Richardson, TX 75080, USA.
iScience
|October 7, 2025
概括
本研究引入了一个三阶段框架,通过预测需求,确定最佳位置和评估电网影响来优化电动汽车 (EV) 充电器部署. 该方法确保了具有成本效益的,可访问的收费,同时保持了电网可靠性.
科学领域:
- 交通运输电气化的电气化
- 城市基础设施规划城市基础设施规划
- 智能电网技术是一项智能电网技术.
背景情况:
- 电动汽车 (EV) 采用的快速增长需要对充电基础设施进行战略规划.
- 目前的部署策略往往缺乏与实时需求数据和电网容量考虑的整合.
- 优化充电器放置对于可访问性,成本效益和电网稳定性至关重要.
研究的目的:
- 为规划和部署电动汽车充电基础设施提出一个全面的三阶段框架.
- 整合各种数据源,包括交通,兴趣点活动和电网模型.
- 为了平衡服务覆盖,安装成本和电网影响的竞争目标.
主要方法:
- 使用实时时空数据 (流量,POI活动) 预测电动汽车充电需求.
- 采用双阶段的随机最大覆盖率模型,以最佳地点和容量选择.
- 进行电流模拟,以评估电网性能和托管能力.
主要成果:
- 该框架在德克萨斯州奥斯的一个案例研究中成功确定了最佳的充电地点和容量.
- 模拟结果表明,不同部署策略之间在电网负载和服务覆盖方面存在权衡.
- 该研究验证了该框架能够在电网托管能力限制范围内确保安全集成的能力.
结论:
- 拟议的综合框架为战略电动汽车充电基础设施规划提供了一个强大的方法.
- 这种方法促进了明智的决策,以平衡城市环境中的成本,可访问性和电网可靠性.
- 该研究通过解决关键基础设施和电网整合挑战,支持电动汽车网络的可持续扩张.
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