AC Optimal Power Flow: a Conic Programming relaxation and an iterative MILP scheme for Global Optimization

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 Mix...

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Bibliographic Details
Main Author: Oustry, Antoine
Format: Article
Language:English
Published: Université de Montpellier 2022-11-01
Series:Open Journal of Mathematical Optimization
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Online Access:https://ojmo.centre-mersenne.org/articles/10.5802/ojmo.17/
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Summary: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.
ISSN:2777-5860