Proving global optimality of ACOPF solutions

被引：17

作者：

Gopinath, S. ^{[1
]}

Hijazi, H. L. ^{[1
]}

Weisser, T. ^{[1
]}

Nagarajan, H. ^{[1
]}

Yetkin, M. ^{[2
]}

Sundar, K. ^{[1
]}

Bent, R. W. ^{[1
]}

机构：

[1] Los Alamos Natl Lab, Los Alamos, NM 87545 USA

[2] Lehigh Univ, Dept Ind & Syst Engn, Bethlehem, PA 18015 USA

来源：

ELECTRIC POWER SYSTEMS RESEARCH | 2020年 / 189卷

关键词：

ACOPF; Convex relaxation; Global optimization; POLYNOMIAL OPTIMIZATION; RELAXATIONS; ALGORITHM; BRANCH;

D O I：

10.1016/j.epsr.2020.106688

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：

We present our latest contributions in terms of mathematical modeling and algorithm development for the global optimization of the ACOPF problem. These contributions allow us to close the optimality gap on a number of open instances in the PGLIB and NESTA benchmark libraries. This is achieved by combining valid cut generation with semidefinite programming-based bound tightening. The mathematical formulations along with the solution algorithms are implemented in the modeling framework Gravity, an open-source platform for reproducible numerical experiments.

引用

页数：7

共 28 条

[1]

[Anonymous], **DATA OBJECT**, DOI DOI 10.5281/ZENODO.1208672

[2]

ApS M., 2017, MOSEK COMM LIN TOOLS

[3] Local Solutions of the Optimal Power Flow Problem [J].