4.7 Article

Equivalent Relaxations of Optimal Power Flow

期刊

IEEE TRANSACTIONS ON AUTOMATIC CONTROL
卷 60, 期 3, 页码 729-742

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAC.2014.2357112

关键词

Optimal power flow (OPF); semidefinite program (SDP)

资金

  1. National Science Foundation (NSF) through NetSE [CNS 0911041, CNS-0932428, CCF-1018927, CCF-1423663, CCF-1409204]
  2. ARPA-E [DE-AR0000226]
  3. National Science Council of Taiwan [NSC 103-3113-P-008-001]
  4. Southern California Edison
  5. Los Alamos National Lab (DoE)
  6. Resnick Institute at Caltech
  7. Office of Naval Research under the MURI [N00014-08-0747]
  8. Qualcomm Inc.
  9. King Abdulaziz University

向作者/读者索取更多资源

Several convex relaxations of the optimal power flow (OPF) problem have recently been developed using both bus injection models and branch flow models. In this paper, we prove relations among three convex relaxations: a semidefinite relaxation that computes a full matrix, a chordal relaxation based on a chordal extension of the network graph, and a second-order cone relaxation that computes the smallest partial matrix. We prove a bijection between the feasible sets of the OPF in the bus injection model and the branch flow model, establishing the equivalence of these two models and their second-order cone relaxations. Our results imply that, for radial networks, all these relaxations are equivalent and one should always solve the second-order cone relaxation. For mesh networks, the semidefinite relaxation and the chordal relaxation are equally tight and both are strictly tighter than the second-order cone relaxation. Therefore, for mesh networks, one should either solve the chordal relaxation or the SOCP relaxation, trading off tightness and the required computational effort. Simulations are used to illustrate these results.

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