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作 者:郑虎虎 叶剑华[1] 罗凤章[2] Zheng Huhu;Ye Jianhua;Luo Fengzhang(Tianjin Key Laboratory of Information Sensing&Intelligent Control,Tianjin University ofTechnology and Education,Tianjin 300222,China;Key Laboratory of Smart Grid of Ministry of Education,Tianjin University,Tianjin 300072,China)
机构地区:[1]天津职业技术师范大学天津市信息传感与智能控制重点实验室,天津300222 [2]天津大学智能电网教育部重点实验室,天津300072
出 处:《太阳能学报》2025年第4期200-209,共10页Acta Energiae Solaris Sinica
基 金:国家自然科学基金(51977140)。
摘 要:大规模电动汽车充电站接入配电网形成电力-交通耦合系统(PTN),针对PTN中存在的多种不确定性,提出一种综合考虑交通流量、风光出力及负荷不确定性的两阶段分布鲁棒规划模型。首先,建立含交通流量最优分配的充电站选址定容模型,根据电动汽车充电站运行约束将交通流量不确定性转化为PTN充电负荷的不确定性。然后,将交通网最优流量分配和充电站选址结果与主动配电网(ADN)耦合,以ADN投资运行成本和交通网投资成本最小为目标建立PTN协调规划模型。使用分布鲁棒优化方法处理模型中的多种不确定性,并采用列与约束生成(C&CG)算法进行求解。最后,以一个33节点ADN和12节点交通网耦合系统进行算例分析,分析结果验证所提模型及求解方法的有效性。This paper proposes a two-stage robust planning model that comprehensively considers uncertainties in traffic flow,renewable energy generation,and load in the power-traffic networks(PTN)formed by the integration of large-scale electric vehicle charging stations into the power distribution grid.Firstly,an optimal allocation model for charging station siting is established considering traffic flow,converting traffic flow uncertainties into uncertainties in PTN charging load based on operational constraints.Then,integrating the optimal traffic flow allocation and charging station siting results with the active distribution network(ADN),a coordinated PTN planning model is formulated aiming to minimize ADN investment and operational costs along with traffic network investment costs.Various uncertainties in the model are dealt with by using a distributionally robust optimization approach and the column and constraint generation(C&CG)algorithm is used to solve them.Finally,a case study on a coupled system of a 33-node distribution grid and a 12-node traffic network validates the effectiveness of the proposed model and solution methodology.
关 键 词:配电网 交通网 电动汽车充电站 分布鲁棒优化 规划
分 类 号:TM715[电气工程—电力系统及自动化]
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