Outlier Suppression and Gross Measurement Tracking Methods in Power System Hybrid State Estimation
Author:
Funder
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s40313-024-01107-8.pdf
Reference30 articles.
1. Abur, A., & Exposito, A. G. (2004). Power system state estimation: Theory and implementation. Boca Raton: CRC Press.
2. Ascari, L., & Simões Costa, A. (2024). A bad data resilient multisensor fusion framework for hybrid state estimation. IEEE Transactions on Power Systems, 39(1), 132–146.
3. Bez, D., Simões Costa, A., Ascari, L., & Zanlorensi, E., Jr. (2020). A block version of orthogonal rotations for improving the accuracy of hybrid state estimators. IEEE Transactions on Power Systems, 35(6), 4432–4444.
4. Carvalho, A. C. G., & Simões Costa, A. (2020). Robustness of state estimators based on the maximum correntropy criterion to bad data in leverage points (in Portuguese). VIII Brazilian Symposium of Electrical Systems. https://doi.org/10.48011/sbse.v1i1.2154
5. Cheng, G., Lin, Y., Abur, A., Gómez-Expósito, A., & Wu, W. (2024). A survey of power system state estimation using multiple data sources: PMUs, SCADA, AMI, and beyond. IEEE Transactions on Smart Grid, 15(1), 1129–1151.
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