Wrong transition and measurement models in power system state estimation

Journal title

Archives of Electrical Engineering




vol. 65


No 3 September

Publication authors

Divisions of PAS

Nauki Techniczne


ARCHIVES OF ELECTRICAL ENGINEERING (AEE) (previously Archiwum Elektrotechniki), quarterly journal of the Polish Academy of Sciences is OpenAccess (PAN Electronic Library, publishing original scientific articles and short communiques from all branches of Electrical Power Engineering exclusively in English. The main fields of interest are related to the theory & engineering of the components of an electrical power system: switching devices, arresters, reactors, conductors, etc. together with basic questions of their insulation, ampacity, switching capability etc.; electrical machines and transformers; modelling & calculation of circuits; electrical & magnetic fields problems; electromagnetic compatibility; control problems; power electronics; electrical power engineering; nondestructive testing & nondestructive evaluation.

Scoring assigned by the Polish Ministry of Science and Higher Education: 15 points

CiteScore metrics from Scopus, CiteScore 2017: 0.86

SCImago Journal Rank (SJR) 2017: 0.233

Source Normalized Impact per Paper (SNIP) 2017: 0.661

ICI Journal Master List 2016, Index Copernicus Value: 121.43


Polish Academy of Sciences




eISSN: 2300-2506 ; ISSN: 1427-4221


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,,13(4):907-929(2004) ; Schön (2011), System Identification of Nonlinear State - space Models, Automatica, 47, 39,