A robust and informative method for solving large-scale power flow problems

DOI10.1007/s10589-015-9745-5zbMath1333.90128OpenAlexW2069873885MaRDI QIDQ887172

Tomás Tinoco De Rubira, Walter Murray, Adam Wigington

Publication date: 28 October 2015

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10589-015-9745-5

zbMATH Keywords

robustpower flowNewton-Raphsonaugmented Lagrangiancomplementarity constraintsload flow

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Nonlinear programming (90C30) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33)

Uses Software

• Graphviz
• MUMPS
• CPFLOW
• PRMLT

Cites Work

• Diagonalized multiplier methods and quasi-Newton methods for constrained optimization
• Validation of an augmented Lagrangian algorithm with a Gauss-Newton Hessian approximation using a set of hard-spheres problems
• Interior-point methods for nonconvex nonlinear programming: Filter methods and merit functions
• Hessian Matrix vs. Gauss–Newton Hessian Matrix
• Complementarity constraints as nonlinear equations: Theory and numerical experience
• A note on determining an optimal target by considering the dependence of holding costs and the quality characteristics
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