.png){kind=icon}
.png){kind=icon}
Return
Implementation of a Large-Scale Optimal Power Flow Solver Based on Semidefinite Programming
.png){kind=icon}
PRE
AI
DOI：10.1109/TPWRS.2013.2258044.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The application of semidefinite programming to the optimal power flow (OPF) problem has recently attracted significant research interest. This paper provides advances in modeling and computation required for solving the OPF problem for large-scale, general power system models. Specifically, a semidefinite programming relaxation of the OPF problem is presented that incorporates multiple generators at the same bus and parallel lines. Recent research in matrix completion techniques that decompose a single large matrix constrained to be positive semidefinite into many smaller matrices has made solution of OPF problems using semidefinite programming computationally tractable for large system models. We provide three advances to existing decomposition techniques: a matrix combination algorithm that further decreases solver time, a modification to an existing decomposition technique that extends its applicability to general power system networks, and a method for obtaining the optimal voltage profile from the solution to a decomposed semidefinite program.
Keywords:
Optimal power flow
semidefinite optimization
Journal
IF:
7.2
Papers:
1.1W
Citations:
5.0W
