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1.新能源电力系统国家重点实验室(华北电力大学),北京市 102206
2.南瑞集团有限公司(国网电力科学研究院有限公司),江苏省南京市 211106
Received:17 March 2022,
Revised:2022-05-24,
Published Online:10 August 2022,
Published:25 September 2022
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胡俊杰,马文帅,薛禹胜等.基于CPSSE框架的电动汽车聚合商备用容量量化[J].电力系统自动化,2022,46(18):46-54.
HU Junjie,MA Wenshuai,XUE Yusheng,et al.Quantification of Reserve Capacity Provided by Electric Vehicle Aggregator Based on Framework of Cyber-Physical-Social System in Energy[J].Automation of Electric Power Systems,2022,46(18):46-54.
胡俊杰,马文帅,薛禹胜等.基于CPSSE框架的电动汽车聚合商备用容量量化[J].电力系统自动化,2022,46(18):46-54. DOI: 10.7500/AEPS20220317007.
HU Junjie,MA Wenshuai,XUE Yusheng,et al.Quantification of Reserve Capacity Provided by Electric Vehicle Aggregator Based on Framework of Cyber-Physical-Social System in Energy[J].Automation of Electric Power Systems,2022,46(18):46-54. DOI: 10.7500/AEPS20220317007.
近年来电动汽车(EV)保有量持续增长,EV作为一种灵活性资源,与电网互动已成为目前的研究热点。针对EV备用容量量化存在的用户参与意愿不确定性强、功率能量时域耦合等问题,开展了电动汽车聚合商(EVA)备用容量量化研究。首先,提出以EVA为主体参与电力系统能量市场与辅助服务市场的能源领域信息物理社会系统框架(CPSSE);其次,基于心理学原理与社会行为建立了用户意愿模型,刻画社会系统中EV用户参与调控行为的不确定性;然后,考虑用户意愿与备用容量调控信号对备用容量量化的影响,建立了以EVA收益最大为目标的计划功率与备用容量的联合优化模型;再次,提出了一种基于麻雀搜索算法与线性规划的联合求解算法;最后,通过算例验证了模型的有效性与算法的收敛效果。
In recent years
the number of electric vehicles (EVs) keeps growing. It has become a hot research topic that EV interacts with the power grid as a flexible resource. Aiming at the problems of the strong uncertainty of user participation willingness and time-domain coupling of power and energy in EV reserve capacity quantification
a quantification research of reserve capacity provided by electric vehicle aggregator (EVA) is carried out. Firstly
the framework of cyber-physical-social system in energy (CPSSE) is proposed
which takes EVA as the main subject to participate in the power system energy market and auxiliary service market. Secondly
based on psychological principles and social behaviors
a user willingness model is established to describe the uncertainty of the participation in regulation behaviors of EV users in the social system. Thirdly
considering the influence of user willingness and reserve capacity regulation signals on the quantification of reserve capacity
a joint optimization model of planned power and reserve capacity is established with the objective of maximizing EVA income. Fourthly
a joint solution algorithm based on the sparrow search algorithm and linear programming is proposed. Finally
the effectiveness of the model and the convergence effect of the algorithm are verified by the numerical example.
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