CHARGE-MAP:一个综合框架来研究多标准的电动汽车充电基础设施扩建问题.
Kazi Ashik Islam1, Aparna Kishore1, Rounak Meyur2
1Department of Computer Science, Biocomplexity Institute, University of Virginia, Charlottesville, VA 22903.
概括
一个新的框架Charge-map通过模拟需求和规划充电站位置来优化电动汽车 (EV) 充电基础设施. 这种数据驱动的方法显著减少了充电绕道和等待时间,支持广泛采用电动汽车.
科学领域:
- 城市规划与交通科学 城市规划与交通科学
- 电气工程和电力系统.
- 计算科学和仿真计算科学和仿真
背景情况:
- 电动汽车 (EV) 的快速增长需要强大的充电基础设施.
- 扩大电动汽车充电基础设施是复杂的,涉及需求,电网容量和成本因素.
研究的目的:
- 介绍Charge-map,一个数据驱动的模拟优化框架,用于有效地规划电动汽车充电基础设施.
- 确保个人电动汽车车主获得积极的充电体验.
主要方法:
- 开发了充电地图,集成基于代理的模拟来预测需求和优化站位.
- 模拟EV采用者的移动性和充电行为,以估计时空需求.
- 优化了新的车站/充电器位置和容量,以尽量减少绕道距离和在预算限制范围内等待时间.
- 评估电网影响和变压器容量要求.
主要成果:
- 充电地图可以支持约198,600辆电动汽车,在弗吉尼亚州有1,305个新站和2,164个充电器.
- 减少了66%的平均绕道距离和72%的等待时间.
- 确定需要最小的变压器升级 (1.8%的住宅,>80%的商业支持25-50kVA).
结论:
- 充电地图为经济高效的电动汽车充电基础设施扩张提供数据驱动的见解.
- 该框架促进了针对可持续电动汽车整合的有针对性的投资.
- 为决策者和城市规划者在开发电动汽车基础设施方面提供关键数据.
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