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1.武汉理工大学自动化学院,湖北省武汉市 430070
2.葛洲坝交通投资有限公司,湖北省武汉市 430000
3.武汉理工大学经济学院,湖北省武汉市 430070
Received:04 November 2025,
Revised:2025-12-02,
Online First:20 July 2026,
Published:10 September 2026
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李俊,侯慧,姚磊等.电动汽车聚合商参与主辅电力市场协同优化[J].电力系统自动化,2026,50(17):189-200.
LI Jun,HOU Hui,YAO Lei,et al.Coordinated Optimization for Electric Vehicle Aggregators Participating in Electricity and Auxiliary Markets[J].Automation of Electric Power Systems,2026,50(17):189-200.
李俊,侯慧,姚磊等.电动汽车聚合商参与主辅电力市场协同优化[J].电力系统自动化,2026,50(17):189-200. DOI: 10.7500/AEPS20251104005.
LI Jun,HOU Hui,YAO Lei,et al.Coordinated Optimization for Electric Vehicle Aggregators Participating in Electricity and Auxiliary Markets[J].Automation of Electric Power Systems,2026,50(17):189-200. DOI: 10.7500/AEPS20251104005.
为解决电动汽车聚合商参与主辅电力市场协同出清机制问题,提出一种电动汽车聚合商参与的电能量市场为主市场、辅助服务市场为备用市场的主辅市场协同优化出清策略。首先,基于电动汽车集群出力特征、负荷弹性及用户响应特性等,构建电动汽车集群备用容量模型,量化其备用潜力;然后,设计电能量-备用市场协同优化出清模型,以安全约束机组组合及安全约束经济调度等为基础确定节点电价,通过价格传导机制与市场耦合规则实现跨市场资源高效配置;最后,基于IEEE 33节点系统进行算例分析。结果表明,所提策略通过协调电动汽车充放电行为与备用容量调用,可有效提升电动汽车聚合商收益,同时优化社会福利分配。
To address the problems of the coordinated clearing mechanism for electric vehicle aggregators (EVAs) participating in the electricity and auxiliary markets
this paper proposes a coordinated optimal clearing strategy for the electricity and auxiliary markets
in which EVAs participate in the electric energy market as the main market and the auxiliary service market as the reserve market. First
based on the output characteristics
load elasticity
and user response characteristics of electric vehicle clusters
a reserve capacity model for electric vehicle clusters is constructed to quantify their reserve potential. Secondly
an electric energy-reserve market coordinated optimal clearing model is established. On the basis of security constrained unit commitment and security constrained economic dispatch
nodal electricity prices are determined
and the efficient allocation of cross-market resources is realized through price conduction mechanisms and market coupling rules. Finally
case studies are conducted based on the IEEE 33-bus system. The results show that the proposed strategy can effectively improve the profits of EVAs and optimize the distribution of social welfare by coordinating the charging and discharging behaviors of electric vehicles and the dispatching of reserve capacity.
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