Semantic Scholar Open Access 2018 26 sitasi

Optimization-Based Bound Tightening Using a Strengthened QC-Relaxation of the Optimal Power Flow Problem

K. Sundar Harsha Nagarajan Sidhant Misra Mowen Lu Carleton Coffrin +1 lainnya

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Abstrak

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.

Topik & Kata Kunci

Mathematics Computer Science

Penulis (6)

K. Sundar

Harsha Nagarajan

Sidhant Misra

Mowen Lu

Carleton Coffrin

R. Bent

Format Sitasi

APA MLA BibTeX

Sundar, K., Nagarajan, H., Misra, S., Lu, M., Coffrin, C., Bent, R. (2018). Optimization-Based Bound Tightening Using a Strengthened QC-Relaxation of the Optimal Power Flow Problem. https://doi.org/10.1109/CDC49753.2023.10384116

Akses Cepat

Lihat di Sumber doi.org/10.1109/CDC49753.2023.10384116

Informasi Jurnal

Tahun Terbit: 2018
Bahasa: en
Total Sitasi: 26×
Sumber Database: Semantic Scholar
DOI: 10.1109/CDC49753.2023.10384116
Akses: Open Access ✓