DocumentCode :
154318
Title :
Dispersed filters for power system state estimation
Author :
Kozierski, Piotr ; Lis, Marcin ; Owczarkowski, Adam ; Horla, Dariusz
Author_Institution :
Fac. of Electr. Eng., Poznan Univ. of Technol., Poznan, Poland
fYear :
2014
fDate :
2-5 Sept. 2014
Firstpage :
129
Lastpage :
133
Abstract :
The article proposes an approach to power system state estimation allowing the division of the network into smaller parts and performing calculations for each part at the same time. The latter can be implemented in parallel, but the main aim has been to propose a method for dispersed calculations, i.e. calculations that may be performed on computing units located at various points of the whole power system. In the paper, there are 3 algorithms for which dispersed versions have been proposed: Extended Kalman Filter, Particle Filter and Extended Kalman Particle Filter. As a result of the simulations, it has been verified that the Dispersed Particle Filter works better than simple Particle Filter. In two other cases, distributed algorithms work worse, but for the Extended Kalman Filter degradation in the estimation quality is not significant.
Keywords :
Kalman filters; nonlinear filters; particle filtering (numerical methods); power system state estimation; computing units; dispersed calculations; dispersed particle filter; distributed algorithms; extended Kalman particle filter; network division; power system state estimation; Filtering algorithms; Kalman filters; Particle filters; Power measurement; Power systems; State estimation; dispersed filters; particle filter; power system; state estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Methods and Models in Automation and Robotics (MMAR), 2014 19th International Conference On
Conference_Location :
Miedzyzdroje
Print_ISBN :
978-1-4799-5082-9
Type :
conf
DOI :
10.1109/MMAR.2014.6957337
Filename :
6957337
Link To Document :
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