Computing Critical k-Tuples in Power Networks

被引:50
|
作者
Sou, Kin Cheong [1 ,2 ]
Sandberg, Henrik [1 ,2 ]
Johansson, Karl Henrik [1 ,2 ]
机构
[1] KTH Royal Inst Technol, ACCESS Linnaeus Ctr, Sch Elect Engn, Stockholm, Sweden
[2] KTH Royal Inst Technol, Automat Control Lab, Sch Elect Engn, Stockholm, Sweden
关键词
Combinatorial optimization; critical k-tuples; minimum cut; mixed integer linear programming; state estimation; STATE ESTIMATION; OBSERVABILITY ANALYSIS; IDENTIFICATION; MATRIX;
D O I
10.1109/TPWRS.2012.2187685
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
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.
引用
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页码:1511 / 1520
页数:10
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