Convex Relaxation for Optimal Power Flow Problem: A Recent Review

被引：0
|
作者：
Lin Z. [1 ]
Hu Z. [1 ]
Song Y. [2 ]
机构：
[1] Smart Grid Operation and Optimization Lab, Dept. of Electrical Engineering, Tsinghua University, Haidian District, Beijing
[2] Dept. of Electrical and Computer Engineering, University of Macau, Macau
来源：
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | 2019年 / 39卷 / 13期
基金：
中国国家自然科学基金;
关键词：
Convex relaxation; Optimal power flow; Power system optimization; Second-order cone programming; Semidefinite programming;
D O I：
10.13334/j.0258-8013.pcsee.182217
中图分类号：
学科分类号：
摘要：
Convex relaxation for the optimal power flow (OPF) problem can transform the non-convex OPF problem into a convex one, and thereafter the global optimal solution of the original problem can be obtained when the relaxation is exact. Over the past decade, it has been a research hotspot in the field of power system optimization. In this paper, the state-of-the-art researches on convex relaxations for OPF problems were firstly reviewed. The basic concepts and mathematical forms of the semi-definite programming (SDP), second-order cone programming (SOCP) and quadratic convex (QC) relaxations were then introduced. As for the exactness of the convex relaxation, the sufficient conditions for ensuring exact relaxations and the approaches for generating tighter relaxations were summarized. Finally, the potential research topics on the technique and application of convex relaxations were proposed. © 2019 Chin. Soc. for Elec. Eng.
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页码：3717 / 3727
页数：10
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