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Polynomial SDP cuts for Optimal Power Flow
2016
2016 Power Systems Computation Conference (PSCC)
The use of convex relaxations has lately gained considerable interest in Power Systems. These relaxations play a major role in providing quality guarantees for non-convex optimization problems. For the Optimal Power Flow (OPF) problem, the semidefinite programming (SDP) relaxation is known to produce tight lower bounds. Unfortunately, SDP solvers still suffer from a lack of scalability. In this work, we introduce an exact reformulation of the SDP relaxation, formed by a set of polynomial
doi:10.1109/pscc.2016.7540908
dblp:conf/pscc/HijaziCH16
fatcat:tikylatj6rccbdxd3pmtlwr2yq