Title

Wrong transition and measurement models in power system state estimation

Journal title

Archives of Electrical Engineering

Yearbook

2016

Volume

vol. 65

Issue

No 3 September

Authors

Kozierski, Piotr ; Horla, Dariusz ; Lis, Marcin

Keywords

particle filter ; estimation quality ; Population Monte Carlo

Divisions of PAS

Nauki Techniczne

Coverage

559-574

Publisher

Polish Academy of Sciences

Date

2016

Type

Artykuły / Articles

Identifier

DOI: 10.1515/aee-2016-0040 ; ISSN: 1427-4221 ; eISSN: 2300-2506

Source

Archives of Electrical Engineering; 2016; vol. 65; No 3 September; 559-574

References

Šmídl (2013), Adaptive Importance Sampling in Particle Filtering th on Information Fusion pp, Proc Int FUSION, 16. ; Huang (2007), Feasibility Studies of Applying Kalman Filter Techniques to Power System Dynamic State Estimation In Power Engineering Conference, Proc, 376. ; Kozierski (2014), Particle Filter in Power System State Estimation - Large Measurements Errors th on Advances in Applied Electrical Engineering pp, Proc Nat PES, 16, 157. ; Janiszewski (2014), Particle Filter Approach for Permanent Magnet Synchronous Motor State Estimation, Przeglad Elektrotechniczny, 90, 56. ; Cappe (null), Population Monte Carlo of Computational and Graphical Statistics, Journal, doi.org/10.1198/106186004X12803,13(4):907-929(2004) ; Schön (2011), System Identification of Nonlinear State - space Models, Automatica, 47, 39, doi.org/10.1016/j.automatica.2010.10.013