Polytope-Based Aggregation of Electric Vehicles for Day-Ahead Bi-Level Scheduling of Active Distribution Network Considering Uncertainties

被引：0

作者：

Lu, Jiangang ^{[1
]}

Zhu, Jie ^{[2
]}

Zhao, Ruifeng ^{[1
]}

Guo, Wenxin ^{[1
]}

Xu, Yinliang ^{[2
]}

Lin, Chenhui ^{[3
]}

机构：

[1] Guangdong Power Grid Corp, Elect Power Dispatch Ctr, Guangzhou, Peoples R China

[2] Tsinghua Univ, Tsinghua Shenzhen Int Grad Sch, Shenzhen, Peoples R China

[3] Tsinghua Univ, Dept Elect Engn, Beijing, Peoples R China

来源：

2024 THE 7TH INTERNATIONAL CONFERENCE ON ENERGY, ELECTRICAL AND POWER ENGINEERING, CEEPE 2024 | 2024年

关键词：

electric vehicles; aggregation; distribution network; distributionally robust optimization; scheduling; bi-level model;

D O I：

10.1109/CEEPE62022.2024.10586570

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The integration of large-scale electric vehicles (EVs) into the distribution network can significantly increase the complexity of system management. In this paper, a polytope-based inner approximate aggregation model is developed to effectively describe the feasible region of large-scale EVs. A bi-level model is then developed for the participation of EV aggregators in the optimal scheduling of the distribution network, where the uncertainty in the bi-level model is modeled by chance constraints. The bi-level model is solved using distributionally robust optimization, Strong Duality Theorem, and KKT conditions. A numerical case study of the IEEE 33 bus distribution network is conducted and the results show the effectiveness of the proposed method.

引用

页码：808 / 812

页数：5

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