Achieving SDP Tightness Through SOCP Relaxation with Cycle-Based SDP Feasibility Constraints for AC OPF
Lingling Fan, Hossein Ghassempour Aghamolki, Zhixin Miao, Bo Zeng

TL;DR
This paper introduces a novel SOCP relaxation approach for AC optimal power flow that guarantees SDP tightness by enforcing PSD constraints on cycles and cliques, significantly reducing computation time.
Contribution
It reformulates SDP relaxation as SOCP with cycle-based constraints, enabling efficient handling of large power systems and ensuring SDP tightness through graph decomposition.
Findings
Reduces SDP computation time for large power systems
Guarantees SDP tightness via cycle and clique constraints
Handles systems with thousands of buses efficiently
Abstract
In this paper, we show that the standard semidefinite programming (SDP) relaxation of altering current optimal power flow (AC OPF) can be equivalently reformulated as second-order cone programming (SOCP) relaxation with maximal clique- and cycle-based SDP feasibility constraints. The formulation is based on the positive semi-definite (PSD) matrix completion theorem, which states that if all sub-matrices corresponding to maximal cliques in a chordal graph are PSD, then the partial matrix related to the chordal graph can be completed as a full PSD matrix. Existing methods in [1] first construct a chordal graph through Cholesky factorization. In this paper, we identify maximal cliques and minimal chordless cycles first. Enforcing the submatrices related to the maximal cliques and cycles PSD will guarantee a PSD full matrix. Further, we conduct chordal relaxation for the minimal chordless…
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Taxonomy
TopicsFault Detection and Control Systems · Analytical Chemistry and Sensors
