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Observability analysis and bad data processing for state estimation with equality constraints

Journal Article · · IEEE Trans. Power Syst.; (United States)
DOI:https://doi.org/10.1109/59.192905· OSTI ID:6163451
The factorization-based observability analysis and the normalized residual-based bad data processing have been derived for state estimation using normal equation approach. The observability analysis is conducted during the process of triangular factorization of the gain matrix. The normalized residuals are calculated using the sparse inverse of the gain matrix. The application of the method of Lagrange multipliers to handle state estimation with equality constraints arising from zero injections is gaining popularity because of its better numerical robustness. The method employs a different coefficient matrix in place of the gain matrix at each iteration. In this paper, the factorization-based observability analysis and the normalized residual-based data processing are extended to state estimation with equality constraints. It is shown that the observability analysis can be carried out in the triangular factorization of the coefficient matrix and the normalized residuals can be calculated using the sparse inverse of this matrix. Test results are presented.
Research Organization:
Dept. of Electrical Engineering and Computer Sciences and the Electronics Research Lab., Univ. of California, Berkeley, CA (US)
OSTI ID:
6163451
Journal Information:
IEEE Trans. Power Syst.; (United States), Journal Name: IEEE Trans. Power Syst.; (United States) Vol. 3:2; ISSN ITPSE
Country of Publication:
United States
Language:
English