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

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

Content Provider	Springer Nature Link
Author	Hijazi, Hassan Coffrin, Carleton Hentenryck, Pascal Van
Copyright Year	2016
Abstract	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. Three case studies in optimal power flow, optimal transmission switching and capacitor placement demonstrate the benefits of the new relaxations.
Starting Page	321
Ending Page	367
Page Count	47
File Format	PDF
ISSN	18672949
Journal	Mathematical Programming Computation
Volume Number	9
Issue Number	3
e-ISSN	18672957
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-10-15
Publisher Institution	Mathematical Optimization Society
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Mixed-integer nonlinear programming Global optimization Convex relaxation Optimal power flow Optimal transmission switching Capacitor placement Mixed integer programming Nonconvex programming, global optimization Convex programming Nonlinear programming Applications of mathematical programming Optimization Operation Research/Decision Theory Theory of Computation Mathematics of Computing
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Software

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