arXiv:1912.09232 [math.OC]AbstractReferencesReviewsResources
Improving Clique Decompositions of Semidefinite Relaxations for Optimal Power Flow Problems
Julie Sliwak, Miguel Anjos, Lucas Létocart, Jean Maeght, Emiliano Traversi
Published 2019-12-19Version 1
Semidefinite Programming (SDP) provides tight lower bounds for Optimal Power Flow problems. However, solving large-scale SDP problems requires exploiting sparsity. In this paper, we experiment several clique decomposition algorithms that lead to different reformulations and we show that the resolution is highly sensitive to the clique decomposition procedure. Our main contribution is to demonstrate that minimizing the number of additional edges in the chordal extension is not always appropriate to get a good clique decomposition.
Journal: ROADEF2020, Feb 2020, Montpellier, France
Keywords: optimal power flow problems, improving clique decompositions, semidefinite relaxations, tight lower bounds, solving large-scale sdp problems
Tags: journal article
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