• DocumentCode
    1467831
  • Title

    Computing Critical k -Tuples in Power Networks

  • Author

    Kin Cheong Sou ; Sandberg, Henrik ; Johansson, Karl H.

  • Author_Institution
    ACCESS Linnaeus Center & the Autom. Control Lab., KTH R. Inst. of Technol., Stockholm, Sweden
  • Volume
    27
  • Issue
    3
  • fYear
    2012
  • Firstpage
    1511
  • Lastpage
    1520
  • Abstract
    In this paper the problem of finding the sparsest (i.e., minimum cardinality) critical k-tuple including one arbitrarily specified measurement is considered. The solution to this problem can be used to identify weak points in the measurement set, or aid the placement of new meters. The critical k-tuple problem is a combinatorial generalization of the critical measurement calculation problem. Using topological network observability results, this paper proposes an efficient and accurate approximate solution procedure for the considered problem based on solving a minimum-cut (Min-Cut) problem and enumerating all its optimal solutions. It is also shown that the sparsest critical k -tuple problem can be formulated as a mixed integer linear programming (MILP) problem. This MILP problem can be solved exactly using available solvers such as CPLEX and Gurobi. A detailed numerical study is presented to evaluate the efficiency and the accuracy of the proposed Min-Cut and MILP calculations.
  • Keywords
    distribution networks; integer programming; linear programming; measurement systems; numerical analysis; transmission networks; CPLEX; Gurobi; MILP problem; approximate solution procedure; combinatorial generalization; critical k-tuples; critical measurement calculation problem; measurement set; min-cut problem; minimum cardinality; minimum-cut problem; mixed integer linear programming problem; numerical study; power networks; topological network observability; weak points; Approximation algorithms; Indexes; Observability; Optimization; Power measurement; Power transmission lines; Transmission line measurements; Combinatorial optimization; critical $k$ -tuples; minimum cut; mixed integer linear programming; state estimation;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2012.2187685
  • Filename
    6168238