Multiple Matrix Rank Constrained Optimization for Optimal Power Flow over Large Scale Transmission Networks

Y. Shi, H. D. Tuan, S. W. Su, A. V. Savkin

2016

Abstract

The optimal power flow (OPF) problem for power transmission networks is an NP-hard optimization problem with numerous quadratic equality and indefinite quadratic inequality constraints on bus voltages. The existing nonlinear solvers often fail in yielding a feasible solution. In this paper, we follow our previously developed nonsmooth optimization approach to address this difficult large-scale OPF problem, which is an iterative process to generate a sequence of improved solutions that converge to an optimal solution. Each iteration calls an SDP of a moderate dimension. Intensive simulations for OPF over networks with a large number of buses are provided to demonstrate the efficiency of our approach.

Paper Citation

in Harvard Style

Shi Y., Tuan H., Su S. and Savkin A. (2016). Multiple Matrix Rank Constrained Optimization for Optimal Power Flow over Large Scale Transmission Networks . In Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-184-7, pages 384-389. DOI: 10.5220/0005921303840389

in Bibtex Style

@conference{smartgreens16,
author={Y. Shi and H. D. Tuan and S. W. Su and A. V. Savkin},
title={Multiple Matrix Rank Constrained Optimization for Optimal Power Flow over Large Scale Transmission Networks},
booktitle={Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2016},
pages={384-389},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005921303840389},
isbn={978-989-758-184-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Multiple Matrix Rank Constrained Optimization for Optimal Power Flow over Large Scale Transmission Networks
SN - 978-989-758-184-7
AU - Shi Y.
AU - Tuan H.
AU - Su S.
AU - Savkin A.
PY - 2016
SP - 384
EP - 389
DO - 10.5220/0005921303840389