Strong SOCP Relaxations for the Optimal Power Flow Problem
Burak Kocuk, Santanu S. Dey, X. Andy Sun

TL;DR
This paper introduces three novel strong SOCP relaxations for the AC optimal power flow problem, achieving near-SDP solution quality, faster computation, and practical feasibility for real-time power system operations.
Contribution
The paper presents three new strong SOCP relaxations that are incomparable to each other and outperform existing convex relaxations in solution quality and computational efficiency.
Findings
Solutions are within 99.96% of SDP relaxations on average.
Relaxations can be used as warm starts for local solvers like IPOPT.
Achieved feasible solutions for large systems within seconds, close to global optimality.
Abstract
This paper proposes three strong second order cone programming (SOCP) relaxations for the AC optimal power flow (OPF) problem. These three relaxations are incomparable to each other and two of them are incomparable to the standard SDP relaxation of OPF. Extensive computational experiments show that these relaxations have numerous advantages over existing convex relaxations in the literature: (i) their solution quality is extremely close to that of the SDP relaxations (the best one is within 99.96% of the SDP relaxation on average for all the IEEE test cases) and consistently outperforms previously proposed convex quadratic relaxations of the OPF problem, (ii) the solutions from the strong SOCP relaxations can be directly used as a warm start in a local solver such as IPOPT to obtain a high quality feasible OPF solution, and (iii) in terms of computation times, the strong SOCP…
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