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基于收费数据建模电动汽车的充电配置文件
Natascia Andrenacci1, Federico Karagulian1, Antonino Genovese1
1Ente per le Nuove Tecnologie, l'Energia e l'Ambiente (ENEA), Rome, 00193, Italy.
分析巴塞罗那和图尔库的电动汽车 (EV) 充电数据,揭示了快速充电与慢速充电的不同用户习惯. 不同的合成负载配置方法对充电基础设施的可再生能源系统尺寸产生重大影响.
科学领域:
- 电气工程 电气工程
- 可持续能源系统 可持续能源系统
- 交通基础设施 交通基础设施
背景情况:
- 有效的电动汽车 (EV) 充电基础设施设计对于用户和经理的好处至关重要.
- 分析电动汽车充电数据有助于规划和管理充电基础设施,包括与可再生能源和储能系统的集成.
- 了解充电行为和模式是优化基础设施开发的关键.
研究的目的:
- 分析电动汽车充电时间和能源消耗的每小时,每天和季节性模式.
- 模拟充电站 (CS) 的电力需求,并确定一个综合可再生能源系统 (RES) 的最佳尺寸.
- 评估不同合成负载配置生成方法对可再生能源尺寸的影响.
主要方法:
- 分析了来自西班牙巴塞罗那和芬兰图尔库的两个电动汽车充电数据集.
- 调查充电模式,包括充电时间和输送的能量.
- 蒙特卡洛模拟使用统计和非参数分布来建模用户流入,并确定最佳的RES大小.
主要成果:
- 在快速和缓慢的电动汽车充电之间发现了不同的用户习惯,快速充电的持续时间更短.
- 每小时的请求分布因收费类型 (快速或缓慢) 和数据集位置而有很大差异.
- 选择合成负载配置生成方法对可再生能源系统 (RES) 的投资结果产生了重大影响.
结论:
- 该研究强调了不同合成配置设计方法对确定电动汽车充电基础设施光伏 (PV) 系统最佳尺寸的关键影响.
- 使用净当前价值 (NPV) 评估的经济可行性对所选择的负载配置模型方法敏感.
- 结果为优化设计和在电动汽车充电基础设施中整合可再生能源提供了宝贵的见解.
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