AC Optimal Power Flow: a Conic Programming relaxation and an iterative MILP scheme for Global Optimization
Open Journal of Mathematical Optimization, Volume 3 (2022), article no. 6, 19 p.

We address the issue of computing a global minimizer of the AC Optimal Power Flow problem. We introduce valid inequalities to strengthen the Semidefinite Programming relaxation, yielding a novel Conic Programming relaxation. Leveraging these Conic Programming constraints, we dynamically generate Mixed-Integer Linear Programming (MILP) relaxations, whose solutions asymptotically converge to global minimizers of the AC Optimal Power Flow problem. We apply this iterative MILP scheme on the IEEE PES PGLib [2] benchmark and compare the results with two recent Global Optimization approaches.

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Accepted:
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DOI: 10.5802/ojmo.17
Keywords: ACOPF, Global Optimization, Semidefinite Programming, Mixed-Integer Linear Programming
Antoine Oustry 1, 2

1 LIX CNRS, Ecole polytechnique, Institut Polytechnique de Paris, Palaiseau, France
2 Ecole des Ponts, Marne-La-Vallée, France
License: CC-BY 4.0
Copyrights: The authors retain unrestricted copyrights and publishing rights
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Antoine Oustry. AC Optimal Power Flow: a Conic Programming relaxation and an iterative MILP scheme for Global Optimization. Open Journal of Mathematical Optimization, Volume 3 (2022), article  no. 6, 19 p. doi : 10.5802/ojmo.17. https://ojmo.centre-mersenne.org/articles/10.5802/ojmo.17/

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