
1.智能配用电装备与系统全国重点实验室(河北工业大学),天津市 300130
2.国网江苏省电力有限公司电力科学研究院,江苏省南京市 211103
3.智能配用电装备与系统全国重点实验室(天津大学),天津市 300072
Received:22 June 2025,
Revised:2025-12-23,
Online First:26 May 2026,
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董晓红,李心真,王明深等.基于用户充电行为画像的电动汽车可调度潜力概率评估方法[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250622002.
DONG Xiaohong,LI Xinzhen,WANG Mingshen,et al.Probabilistic Assessment Method for Dispatchable Potential of Electric Vehicles Based on User Charging Behavior Profiles[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250622002.
董晓红,李心真,王明深等.基于用户充电行为画像的电动汽车可调度潜力概率评估方法[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250622002. DOI:
DONG Xiaohong,LI Xinzhen,WANG Mingshen,et al.Probabilistic Assessment Method for Dispatchable Potential of Electric Vehicles Based on User Charging Behavior Profiles[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250622002. DOI:
随着电动汽车(EV)接入电网,规模化EV在参与电网调度中展现出巨大潜力。为准确评估EV参与电网调度的潜力,提出了一种基于用户充电行为画像的EV可调度潜力概率评估方法。首先,根据充电行为、车辆属性以及用户主观心理效应构建多维用户画像标签,并基于分类决策模型将各用户划分为不同集群,形成个体差异化行为画像;然后,针对单个用户构建不同置信度下的EV能量概率可行域与可调度功率模型,并提出考虑不同时段时间与能量价值的改进奇诺多面体近似方法,对EV能量概率可行域进行内近似;最后,基于用户画像结果所生成的不同EV集群,采用闵可夫斯基和方法对近似后的EV能量概率可行域进行聚合,并对集群内各EV不同置信度下的可调度功率进行聚合,生成对应的集群可调度功率,从而概率化评估不同集群的可调度潜力。
With the integration of electric vehicles (EVs) into the power grid
large-scale EVs exhibit great potential for participating in grid dispatch. To accurately assess the potential of EVs in grid dispatch
a probabilistic assessment method for dispatchable potential of EVs based on user charging behavior profiles is proposed. First
multi-dimensional user profile labels are constructed according to charging behaviors
vehicle attributes and users' subjective psychological effects. A classification decision model is adopted to categorize users into different clusters to establish individually differentiated behavior profiles. Second
for each individual user
EV energy probability feasible regions and dispatchable power models under different confidence levels are constructed. An improved zonotope approximation method considering time and energy values in different time periods is put forward to conduct inner approximation of the EV energy probability feasible region. Finally
for different EV clusters generated from user profile results
the Minkowski sum method is used to aggregate the approximated EV energy probability feasible regions. The dispatchable power of each EV within the cluster under different confidence levels is aggregated to yield the corresponding cluster dispatchable power
so as to probabilistically assess the dispatchable potential of different clusters.
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