Convex quadratic relaxations for mixed-integer nonlinear programs in power systems
Abstract
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.
- Authors:
-
- The Australian National University, Canberra (Australia)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Univ. of Michigan, Ann Arbor, MI (United States)
- Publication Date:
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE Laboratory Directed Research and Development (LDRD) Program
- OSTI Identifier:
- 1469547
- Report Number(s):
- LA-UR-18-21065
Journal ID: ISSN 1867-2949
- Grant/Contract Number:
- AC52-06NA25396
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Mathematical Programming Computation
- Additional Journal Information:
- Journal Volume: 9; Journal Issue: 3; Journal ID: ISSN 1867-2949
- Publisher:
- Springer
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; 42 ENGINEERING; Mixed-integer nonlinear programming; Global optimization; Convex relaxation; Optimal power flow; Optimal transmission switching; Capacitor placement
Citation Formats
Hijazi, Hassan Lionel, Coffrin, Carleton James, and Hentenryck, Pascal Van. Convex quadratic relaxations for mixed-integer nonlinear programs in power systems. United States: N. p., 2016.
Web. doi:10.1007/s12532-016-0112-z.
Hijazi, Hassan Lionel, Coffrin, Carleton James, & Hentenryck, Pascal Van. Convex quadratic relaxations for mixed-integer nonlinear programs in power systems. United States. https://doi.org/10.1007/s12532-016-0112-z
Hijazi, Hassan Lionel, Coffrin, Carleton James, and Hentenryck, Pascal Van. Sat .
"Convex quadratic relaxations for mixed-integer nonlinear programs in power systems". United States. https://doi.org/10.1007/s12532-016-0112-z. https://www.osti.gov/servlets/purl/1469547.
@article{osti_1469547,
title = {Convex quadratic relaxations for mixed-integer nonlinear programs in power systems},
author = {Hijazi, Hassan Lionel and Coffrin, Carleton James and Hentenryck, Pascal Van},
abstractNote = {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.},
doi = {10.1007/s12532-016-0112-z},
journal = {Mathematical Programming Computation},
number = 3,
volume = 9,
place = {United States},
year = {Sat Oct 15 00:00:00 EDT 2016},
month = {Sat Oct 15 00:00:00 EDT 2016}
}
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