Hierarchically coordinated optimization of power distribution systems with soft open points and electric vehicles

被引:8
|
作者
Wang, Jian [1 ]
Zhou, Niancheng [2 ]
Wang, Qianggang [2 ]
Liu, Haoming [1 ]
机构
[1] Hohai Univ, Coll Energy & Elect Engn, Nanjing 211100, Peoples R China
[2] Chongqing Univ, State Key Lab Power Transmiss Equipment & Syst Sec, Chongqing 400044, Peoples R China
关键词
Power distribution system; Soft open point; Electric vehicle; Day-ahead optimization; Real-time optimization; ACTIVE DISTRIBUTION NETWORKS; VOLTAGE REGULATION; HIGH PENETRATION;
D O I
10.1016/j.ijepes.2023.109040
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The integration of large-scale electric vehicles (EVs) into power distribution systems (PDSs) causes low voltage and line congestion problems. EV charger converters can improve the voltage profile by compensating the reactive power, whereas soft open points (SOPs) can transfer active power between branches and compensate reactive power, which can help balance the branch power. Therefore, this study proposes a coordinated dayahead (DA) and real-time (RT) optimization model for PDSs with SOPs and high penetration of EVs. In addition, directly controlling large-scale EVs is difficult for the distribution systems operator. Thus, hierarchical management of EVs is performed by using an EV aggregator (EVA) model. First, on the basis of the probability distribution of the state of EVs of each EVA, a DA optimization model with the minimum operation cost is established. A dynamic SOC boundary model is proposed to optimize active and reactive power of EVAs and EVs in RT stage. The original nonlinear problems of the DA and RT models are linearized by convex relaxation and linearization, which significantly improves the solving efficiency. Finally, the case studies demonstrate that SOPs can promote the integration of EVs, and the hierarchical coordinated optimization strategy not only can reduce the operation cost of the PDS, but also control active and reactive power of EVs in real time.
引用
收藏
页数:11
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