- Tytuł:
- Wrong transition and measurement models in power system state estimation
- Autorzy:
-
Kozierski, P.
Lis, M.
Horla, D. - Powiązania:
- https://bibliotekanauki.pl/articles/141129.pdf
- Data publikacji:
- 2016
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
particle filter
estimation quality
Population Monte Carlo - Opis:
- The influence of wrong information about transition and measurement models on estimation quality has been presented in the paper. Two methods of a particle filter, with and without the Population Monte Carlo modification, and also the extended and unscented Kalman filters methods have been compared. A small 5-bus power system has been used in simulations, which have been performed based on one data set, and this data set has been chosen from among 100 different – to draw the most general conclusions. Based on the obtained results it has been found that for the particle filter methods the implementation of the slightly higher standard deviation than the true value, usually increases the estimation quality. For the Kalman filters methods it has been concluded that optimal values of variances are equal to the true values.
- Źródło:
-
Archives of Electrical Engineering; 2016, 65, 3; 559-574
1427-4221
2300-2506 - Pojawia się w:
- Archives of Electrical Engineering
- Dostawca treści:
- Biblioteka Nauki
Artykuł