DocumentCode :
790297
Title :
Incorporating nonlinearities of measurement function in power system dynamic state estimation
Author :
Mandal, J.K. ; Sinha, A.K. ; Roy, L.
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol., Kharagpur, India
Volume :
142
Issue :
3
fYear :
1995
fDate :
5/1/1995 12:00:00 AM
Firstpage :
289
Lastpage :
296
Abstract :
Dynamic state estimation in power systems is based on the extended Kalman filter (EKF) scheme. The EKF system uses a linearised measurement equation, neglecting the nonlinearities of the measurement function. Under certain circumstances (e.g. large load changes) this leads to degradation in the filter performance. Two algorithms are proposed for dynamic state estimation which incorporate the measurement function nonlinearities in the EKF scheme. The performance of the schemes are compared with the standard linear EKF scheme under various conditions and comparative results are presented
Keywords :
Kalman filters; power system analysis computing; power system state estimation; CPU time; algorithms; computer simulation; extended Kalman filter; load changes; measurement function nonlinearities; performance; power system dynamic state estimation;
fLanguage :
English
Journal_Title :
Generation, Transmission and Distribution, IEE Proceedings-
Publisher :
iet
ISSN :
1350-2360
Type :
jour
DOI :
10.1049/ip-gtd:19951715
Filename :
388364
Link To Document :
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