Iterative bad-data suppression applied to state estimators based on the augmented matrix method

Electric Power Systems Research

Volumn 20, Issue 3, 1991, Pages 205-213

  Simoes Costa A ^a   Rolim, J G ^a   Aitchison, P W ^b  

^a FEDERAL UNIVERSITY OF SANTA CATARINA   (Brazil)

^b UNIVERSITY OF MANITOBA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 44949272799     PISSN: 03787796     EISSN: None     Source Type: Journal    
DOI: 10.1016/0378-7796(91)90065-U     Document Type: Article

References (20)

1. A robust numerical technique for power system state estimation
2. An orthogonal row processing algorithm for power system state estimation
3. Hachtel's augmented matrix method—a rapid method improving numerical stability in power system static state estimation
4. A comparison of some methods for the solution of sparse overdetermined systems of lienar equations
5. Observability analysis and bad data processing for state estimation using Hachtel's augmented matrix method
6. State estimation based on the augmented matrix method: numerical aspects and bad data processing
7. Computational issues in the Hachtel's augmented matrix method for power system state estimation
8. Comparison of different methods for state estimation
9. State estimation in power systems: detecting bad data through the sparse inverse matrix method
10. Bad data suppression in power system state estimation with a variable quadratic-constant criterion
11. Multiple bad data identification techniques for orthogonal row-processing state estimators
12. Direct solution of sets of linear equations whose matrix is sparse, symmetric and indefinite
13. A survey of sparse matrix research
14. Bad data analysis for power system state estimation
15. Hypothesis testing identification: a new method for bad data analysis in power system state estimation
16. Power system state estimation by the augmented matrix method: numerical aspects and bad data processing (in Portuguese)
17. Diakoptics as a general approach in engineering
18. On deriving the inverse of a sum of matrices