考虑用户充电行为的充电站多级充电建议

Xun Li, Yantao Sun, Mengge Shi, Youwei Jia
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引用次数: 0

摘要

随着电动汽车数量的快速增长,如何对各类电动汽车的充电进行有序管理,对电力系统的稳定运行起着至关重要的作用。为此,本文提出了一种基于不同类型电动汽车用户充电行为的充电站多阶段充电规划策略。首先,针对典型CSs的电动汽车用户制定核心用户信息标签,构建电动汽车用户行为数据分析模型,并根据用户反应对标签进行修改。其次,以满足日前计划充电负荷曲线为目标,向核心电动汽车用户发送日前邀请信息。此外,在日内推荐阶段调整充电负荷,减少与日前购电计划的偏差。通过一系列仿真实验,验证了所提出的云存储系统日前邀请和当日推荐框架的可行性,有效降低了云存储系统的运行成本。
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Multi-stage Charging Recommendation of Charging Station Considering User's Charging Behavior
With the rapid growth of the number of electric vehicles (EVs), how to manage the charging of various types of EVs in an orderly manner plays a crucial role in the stable operation of the power system. Therefore, this paper proposes a multi-stage charging planning strategy for charging stations (CSs) based on the various types of EV user’s charging behavior. First, formulate core user information labels for EV users of typical CSs, build EV users’ behavior data analysis models, and revise labels according to EV users’ responses. Secondly, to meet the day-ahead planned charging load curve as the goal, send the day-ahead invitation information to the core EV users. In addition, the charging load is adjusted in the intra-day recommendation stage to reduce the deviation from the day-ahead power purchase plan. Through a series of simulation experiments, the feasibility of the proposed framework of day-ahead invitation and intra-day recommendation of CSs is verified, and the operating costs of CSs can be effectively reduced.
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