Tightening McCormick Relaxations Toward Global Solution of the ACOPF Problem

被引:35
作者
Bynum, Michael [1 ,2 ]
Castillo, Anya [2 ]
Watson, Jean-Paul [3 ]
Laird, Carl D. [1 ,2 ]
机构
[1] Purdue Univ, Davidson Sch Chem Engn, W Lafayette, IN 47907 USA
[2] Sandia Natl Labs, POB 5800, Albuquerque, NM 87185 USA
[3] Sandia Natl Labs, Livermore, CA 94550 USA
关键词
ACOPF; bounds tightening; convex relaxation;
D O I
10.1109/TPWRS.2018.2877099
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We demonstrate that a strong upper bound on the objective of the alternating current optimal power flow (ACOPF) problem can significantly improve the effectiveness of optimization-based bounds tightening (OBBT) on a number of relaxations. We additionally compare the performance of relaxations of the ACOPF problem, including the rectangular form without reference bus constraints, the rectangular form with reference bus constraints, and the polar form. We find that relaxations of the rectangular form significantly strengthen existing relaxations if reference bus constraints are included. Overall, relaxations of the polar form perform the best. However, neither the rectangular nor the polar form dominates the other. Ultimately, with these strategies, we are able to reduce the optimality gap to less than 0.1% on all but 5 NESTA test cases with up to 300 buses by performing OBBT alone.
引用
收藏
页码:814 / 817
页数:4
相关论文
共 15 条
[1]  
[Anonymous], NESTA NICTA EN UNPUB
[2]  
Bienstock D., 2014, LINEAR RELAXAT UNPUB
[3]  
Bynum M., 2018, Computer Aided Chemical Engineering, V44, P1555, DOI DOI 10.1016/B978-0-444-64241-7.50254-8
[4]   Global optimization problems and domain reduction strategies [J].
Caprara, Alberto ;
Locatelli, Marco .
MATHEMATICAL PROGRAMMING, 2010, 125 (01) :123-137
[5]   Strengthening Convex Relaxations with Bound Tightening for Power Network Optimization [J].
Coffrin, Carleton ;
Hijazi, Hassan L. ;
Van Hentenryck, Pascal .
PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING, CP 2015, 2015, 9255 :39-57
[6]  
Hart W.E., 2012, Pyomo - optimization modeling in Python (Springer optimization and its applications), V67
[7]   Convex quadratic relaxations for mixed-integer nonlinear programs in power systems [J].
Hijazi H. ;
Coffrin C. ;
Hentenryck P.V. .
Mathematical Programming Computation, 2017, 9 (03) :321-367
[8]  
HSL, 2007, COLL FORTR COD LARG
[9]   A conic quadratic format for the load flow equations of meshed networks [J].
Jabr, Rabih A. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2007, 22 (04) :2285-2286
[10]   Matrix minor reformulation and SOCP-based spatial branch-and-cut method for the AC optimal power flow problem [J].
Kocuk B. ;
Dey S.S. ;
Sun X.A. .
Mathematical Programming Computation, 2018, 10 (04) :557-596