Publication | Open Access
Application of the Moment-SOS Approach to Global Optimization of the OPF Problem
105
Citations
27
References
2014
Year
Numerical AnalysisMathematical ProgrammingLarge-scale Global OptimizationEngineeringOpf ProblemSdp MethodSemidefinite ProgrammingNonlinear OptimizationStructural OptimizationOperations ResearchNonlinear ProgrammingSdp ProblemCombinatorial OptimizationApproximation TheoryContinuous OptimizationConvex RelaxationComputer EngineeringPower System OptimizationInverse ProblemsComputer ScienceEnergy ManagementOptimization ProblemConvex OptimizationSemi-definite OptimizationLinear ProgrammingMoment-sos Approach
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.
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