基于充放电自由度的小型电动乘用车集群响应能力评估模型

殷展; 钱忠; 杨柳青; 邵银龙; 吴素我; 安硕; 杨钏

殷展,钱忠,杨柳青,邵银龙,吴素我,安硕,杨钏.基于充放电自由度的小型电动乘用车集群响应能力评估模型[J].电测与仪表,2026,63(8):84-94.
YIN Zhan,QIAN Zhong,YANG Liuqing,SHAO Yinlong,WU Suwo,AN Shuo,YANG Chuan.Assessment model for the responsive capacity of Small electric passenger car cluster based on charging and discharging freedom[J].Electrical Measurement & Instrumentation,2026,63(8):84-94.

基于充放电自由度的小型电动乘用车集群响应能力评估模型

Assessment model for the responsive capacity of Small electric passenger car cluster based on charging and discharging freedom

DOI：10.19753 / j.issn1001-1390.2026.08.009

中文关键词: 电动汽车响应能力调控策略出行链调控能力

英文关键词:Electric Vehicles, Responsive Capacity, Control Strategies, Travel Chains, Grid Regulation Capability.

基金项目:国网上海市电力公司科技项目(520931230005)

作者中文名	作者英文名	单位
殷展	YIN Zhan	国网上海市电力公司嘉定供电公司
钱忠	QIAN Zhong	国网上海市电力公司嘉定供电公司
杨柳青	YANG Liuqing	国网上海市电力公司嘉定供电公司
邵银龙	SHAO Yinlong	国网上海市电力公司嘉定供电公司
吴素我	WU Suwo	国网上海市电力公司嘉定供电公司
安硕	AN Shuo	华升科技集团有限公司
杨钏	YANG Chuan	上海电力大学

摘要点击次数: 8

中文摘要:

本文提出一种电动汽车集群(Electrical Vehicles,EVs)响应能力(Responsive Capacity, RC)评估模型,该模型着重考虑了充放电过程中的灵活性因素,并将其应用于电网互动调控的框架中。本文引入了“充放电自由度”这一核心概念,量化电动汽车在短期与中长期尺度上的响应潜力。在此基础上进一步地使用出行链规则,仿真模拟了三大典型电动汽车用户群体的差异化出行模式,从而确保了分析的现实性和准确性。仿真结果证明,通过优化调控,电动汽车集群能够展现出足够的灵活性以适应电力需求的动态变化。所提出的调控策略有效促进了SOC值的均衡分布,减少了极端高低SOC情况的发生,促使受控EV集群的SOC分布趋向集中,进而提升了整体系统的稳定性和效率。这一系列发现,从理论与实践层面共同验证了考虑充放电灵活性评估方法在提升电动汽车集群响应能力及优化调控策略方面的有效性。

英文摘要:

This paper presents an assessment model for the responsive capacity (RC) of an Electric Vehicle (EV) cluster, with a particular emphasis on the flexibility factors during charging and discharging processes, integrating it within a framework for grid interaction and control. A core concept of 'charging and discharging freedom' is introduced, which quantifies the response potential of EVs on both short-term and medium-to-long term scales. Further, utilizing travel chain rules, simulation models are developed to mimic the differentiated travel patterns of three typical EV user groups, ensuring the realism and accuracy of the analysis. Simulation outcomes demonstrate that, through optimized control, EV clusters can exhibit substantial flexibility to accommodate dynamic changes in power demand. The proposed control strategies effectively promote a balanced distribution of State-of-Charge (SOC) values, reducing instances of extreme high or low SOC, steering the controlled EV cluster's SOC distribution towards a more centralized profile, thereby enhancing the overall stability and efficiency of the system. These findings collectively validate, from both theoretical and practical perspectives, the efficacy of considering charging and discharging flexibility in assessing EV cluster response capabilities and optimizing control strategies.

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