Exact Convex Relaxation of Optimal Power Flow in Radial Networks
Optimization and Control
2016-11-18 v1
Abstract
The optimal power flow (OPF) problem determines power generation/demand that minimize a certain objective such as generation cost or power loss. It is nonconvex. We prove that, for radial networks, after shrinking its feasible set slightly, the global optimum of OPF can be recovered via a second-order cone programming (SOCP) relaxation under a condition that can be checked a priori. The condition holds for the IEEE 13-, 34-, 37-, 123-bus networks and two real-world networks, and has a physical interpretation.
Keywords
Cite
@article{arxiv.1311.7170,
title = {Exact Convex Relaxation of Optimal Power Flow in Radial Networks},
author = {Lingwen Gan and Na Li and Ufuk Topcu and Steven H. Low},
journal= {arXiv preprint arXiv:1311.7170},
year = {2016}
}
Comments
32 pages, 10 figures, submitted to IEEE Transaction on Automatic Control. arXiv admin note: text overlap with arXiv:1208.4076