| 引用本文: | 苏粟,刘紫琦,王世丹,杨恬恬,胡勇,张仁尊,李玉璟.基于用户驾驶行为特性的电动汽车有序充电策略[J].电力自动化设备,2018,(3): |
| SU Su,LIU Ziqi,WANG Shidan,YANG Tiantian,HU Yong,ZHANG Renzun,LI Yujing.Ordered charging strategy of electric vehicles based on users’ driving behavior[J].Electric Power Automation Equipment,2018,(3): |
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| 摘要: |
| 电动汽车用户重点关注充电的便利性，但用户在享受便利的同时往往会对电网产生不良的影响。因此，在充电过程中如何同时兼顾用户的便利性和电网的安全性，成为亟待解决的问题。针对上述问题，提出基于用户驾驶行为特性的电动汽车有序充电策略。采用主成分分析和模糊聚类相结合的方法研究用户的驾驶行为特性，预测电动汽车的续驶里程。据此计算车辆每次充电的充电量，同时根据局域配电网负荷曲线，对电动汽车充电进行调度。通过模拟群体电动汽车用户的出行行为，对比分析了电动汽车在无序充电和不同用户响应率下有序充电时的配电网负荷曲线，结果表明所提策略可以有效地减少配电网负荷的峰谷差，提高用户对有序充电策略的积极性。 |
| 关键词: 电动汽车 有序充电 驾驶行为特性 里程预测 主成分分析 模糊聚类 |
| DOI：10.16081/j.issn.1006-6047.2018.03.009 |
| 分类号:TM73;U469.72 |
| 基金项目:国家自然科学基金资助项目(51677004)；中央高校基本科研业务费专项资金资助项目(E16JB00140) |
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| Ordered charging strategy of electric vehicles based on users’ driving behavior |
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SU Su1, LIU Ziqi2, WANG Shidan3, YANG Tiantian1, HU Yong1, ZHANG Renzun1, LI Yujing1
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1.National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China;2.Inner Mongolia Electric Power Research Institute, Inner Mongolia 010020, China;3.State Grid Beijing Haidian Electric Power Supply Company, Beijing 100086, China
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| Abstract: |
| Electric vehicle users are focused on the convenience of charging, which may cause some problems for power grid at the same time. So how to take both users’ convenience and security of power grid into account is an urgent problem to be solved. Aiming at this problem, an ordered charging strategy of electric vehicles based on users’ driving behavior is proposed. The principal component analysis and fuzzy clustering algorithm are used to study the electric vehicle users’ driving behavior and predict the driving distance, based on which to calculate the charging power of each charging process and to dispatch the electric vehicles according to the load curves of local distribution network. By simulating electric vehicle users’ driving behavior, the load curves of distribution network when electric vehicle disordered charging and ordered charging with different user response rates are analyzed and compared, whose results show that the proposed strategy can reduce the peak valley of distribution network load effectively and can increase the electric vehicle users’ motivation to ordered charging. |
| Key words: electric vehicles ordered charging driving behavior driving distance prediction principal component analysis fuzzy clustering |
