蔡俊鹏;陈彩泊;陈德旺;沈镛;

• 1:福州大学数学与计算机科学学院
• 2:智慧新能源研究中心

摘要(Abstract)：

随着大规模电动汽车的普及,产生一系列诸如:行驶里程限制、电网负荷过大和充电排队拥挤等问题。为了解决这些问题,大量学者对充电引导进行研究。近年来该领域所侧重的研究方向将电动汽车充电引导策略分为用户最优和系统最优两个策略进行分类阐述。通过分析对比两种引导策略可以得出,用户最优更偏向于充电行为的引导,系统最优更偏向于充电行为的调度。根据城市出行现状,认为用户最优的研究更符合现在的市场需求,系统最优的研究则更符合未来城市大规模并发充电综合调度的情形。通过探讨大量文献所提供不同角度和方法的充电引导策略,可以发现现有研究的数据利用率和协调调度的智能化程度较低。在人工智能时代,面对智慧城市和智慧出行的要求,提出一种智能化充电引导的框架,充分分析用户在充电业务逻辑中的行为,结合大数据、云计算和人工智能技术,为电动汽车充电引导的效率和智能化水平做进一步提升。

关键词(KeyWords)： 电动汽车;智能充电;人工智能;智慧城市;智慧出行;用户行为分析

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(71671044);; 教育部重点实验室项目(2018LSDMIS09);; 新能源大数据的智能分析与软件开发(01001707)

作者(Author): 蔡俊鹏;陈彩泊;陈德旺;沈镛;

Email:

DOI: 10.16652/j.issn.1004-373x.2021.01.029

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