Convex quadratic relaxations for mixed-integer nonlinear programs in power systems

Hijazi, Hassan Lionel; Coffrin, Carleton James; Hentenryck, Pascal Van

doi:10.1007/s12532-016-0112-z

Convex quadratic relaxations for mixed-integer nonlinear programs in power systems

Journal Article · Sat Oct 15 00:00:00 EDT 2016 · Mathematical Programming Computation

DOI:https://doi.org/10.1007/s12532-016-0112-z· OSTI ID:1469547

^[1]; ^[2]; Hentenryck, Pascal Van ^[3]

The Australian National University, Canberra (Australia)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Univ. of Michigan, Ann Arbor, MI (United States)

Here, this paper presents a set of new convex quadratic relaxations for nonlinear and mixed-integer nonlinear programs arising in power systems. The considered models are motivated by hybrid discrete/continuous applications where existing approximations do not provide optimality guarantees. The new relaxations offer computational efficiency along with minimal optimality gaps, providing an interesting alternative to state-of-the-art semidefinite programming relaxations. Finally, three case studies in optimal power flow, optimal transmission switching and capacitor placement demonstrate the benefits of the new relaxations.

View Accepted Manuscript (DOE)

Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE; Laboratory Directed Research and Development (LDRD)

Grant/Contract Number:: AC52-06NA25396

OSTI ID:: 1469547

Report Number(s):: LA-UR--18-21065

Journal Information:: Mathematical Programming Computation, Journal Name: Mathematical Programming Computation Journal Issue: 3 Vol. 9; ISSN 1867-2949

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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42 ENGINEERING
97 MATHEMATICS AND COMPUTING
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Convex quadratic relaxations for mixed-integer nonlinear programs in power systems

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