Convex Relaxation of Optimal Power Flow-Part II: Exactness

被引：469

作者：

Low, Steven H. ^{[1
]}

机构：

[1] CALTECH, EAS, Pasadena, CA 91125 USA

来源：

IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS | 2014年 / 1卷 / 02期

关键词：

Convex relaxation; optimal power flow; power systems; quadratically constrained quadratic program (QCQP); second-order cone program (SOCP); semidefinite program (SDP); semidefinite relaxation;

D O I：

10.1109/TCNS.2014.2323634

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 [计算机科学与技术];

摘要：

This tutorial summarizes recent advances in the convex relaxation of the optimal power flow (OPF) problem, focusing on structural properties rather than algorithms. Part I presents two power flow models, formulates OPF and their relaxations in each model, and proves equivalence relations among them. Part II presents sufficient conditions under which the convex relaxations are exact.

引用

页码：177 / 189

页数：13

共 63 条

[1]

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