Optimization-Based Bound Tightening Using a Strengthened QC-Relaxation of the Optimal Power Flow Problem
Optimization-Based Bound Tightening Using a Strengthened QC-Relaxation of the Optimal Power Flow Problem
复制标题
使用最佳功率流问题的强化 QC 松弛进行基于优化的边界紧缩
DOI：
10.1109/cdc49753.2023.10384116
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
R. Bent
中科院分区：
文献类型：
--
作者：
K. Sundar;Harsha Nagarajan;Sidhant Misra;Mowen Lu;Carleton Coffrin;R. Bent
本文提出了一种新的加强凸二次凸松弛的交流最优潮流（AC-OPF）问题，并提出了一种基于优化的边界收紧（OBBT）算法计算紧，可行的边界上的电压幅值变量为每个节点和每个分支在网络中的相角差变量。加强QC松弛的理论性质，这表明它的优势在文献中研究的QC松弛的其他变种，也来自。通过对基准AC-OPF测试网络的大量数值结果证实了加强QC松弛的有效性。特别是，结果表明，所提出的松弛始终提供最紧密的变量界限和最优性差距，对运行时性能的影响可以忽略不计。
This paper develops a novel strengthened convex quadratic convex (QC) relaxation of the AC Optimal Power Flow (AC-OPF) problem and presents an optimization-based bound-tightening (OBBT) algorithm to compute tight, feasible bounds on the voltage magnitude variables for each bus and the phase angle difference variables for each branch in the network. Theoretical properties of the strengthened QC relaxation, that show its dominance over the other variants of the QC relaxation studied in the literature, are also derived. The effectiveness of the strengthened QC relaxation is corroborated via extensive numerical results on benchmark AC-OPF test networks. In particular, the results demonstrate that the proposed relaxation consistently provides the tightest variable bounds and optimality gaps with negligible impacts on runtime performance.