DocumentCode
8619
Title
Application of the Moment-SOS Approach to Global Optimization of the OPF Problem
Author
Josz, Cedric ; Maeght, Jean ; Panciatici, P. ; Gilbert, Jean Charles
Author_Institution
Dept. of Appl. Math., Univ. of Pierre & Marie Curie VI, Paris, France
Volume
30
Issue
1
fYear
2015
fDate
Jan. 2015
Firstpage
463
Lastpage
470
Abstract
Finding a global solution to the optimal power flow (OPF) problem is difficult due to its nonconvexity. A convex relaxation in the form of semidefinite programPming (SDP) has attracted much attention lately as it yields a global solution in several practical cases. However, it does not in all cases, and such cases have been documented in recent publications. This paper presents another SDP method known as the moment-sos (sum of squares) approach, which generates a sequence that converges towards a global solution to the OPF problem at the cost of higher runtime. Our finding is that in the small examples where the previously studied SDP method fails, this approach finds the global solution. The higher cost in runtime is due to an increase in the matrix size of the SDP problem, which can vary from one instance to another. Numerical experiment shows that the size is very often a quadratic function of the number of buses in the network, whereas it is a linear function of the number of buses in the case of the previously studied SDP method.
Keywords
load flow; mathematical programming; matrix algebra; OPF problem; SDP method; convex relaxation; global optimization; global solution; matrix size; moment-sos approach; optimal power flow problem; quadratic function; runtime cost; semidefinite programming; sum of squares; MATLAB; Optimization; Polynomials; Programming; Resistance; Symmetric matrices; Vectors; Global optimization; moment/sum-of-squares approach; optimal power flow; polynomial optimization; semidefinite programming;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/TPWRS.2014.2320819
Filename
6816100
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