Naslov
Support Vector Machine State Estimation

Autori
Kirinčić, Vedran ; Čeperić, Ervin ; Vlahinić, Saša ; Lerga, Jonatan

Izvornik
Applied artificial intelligence (0883-9514) 33 (2019), 6; 517-530

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Vector support machine ; state estimation

Sažetak
The power system state estimator based on the support vector machine (SVM) and the weighted least squares (WLS) method is presented in the paper. The WLS provides state estimations necessary for creating SVM model which is then used for state estimation. The developed algorithm was tested on the IEEE systems, and the performance indicators were calculated in order to compare the accuracy of estimation and the measurement error filtering. The results indicate that the proposed hybrid model outperforms the classical WLS-based state estimation in terms of accuracy and improves measurement error filtering in comparison to the classical estimator.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo

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