Secure And Adaptive State Estimation For A Pmu-Equipped Smart Grid
Keywords
bad data processing; data security; Phasor Measurement Units (PMU); Power system state estimation
Abstract
Modern power systems are constantly subjected to various disturbances, device failures, as well as data attacks. To improve the quality of monitoring and control in smart grid, researchers have conducted extensive studies in exploring the advantages of real-time digital meters such as the Phasor Measurement Units, combining with dynamic estimation methods such as Kalman filters. Standard Kalman filter assumes we have statistical knowledge regarding the uncertainty of the system under study. The reality is, the accurate system model is almost impossible to obtain, especially with the existence of malicious data attack. A lightweight and efficient adaptive Kalman filter algorithm is presented in this paper for its ability to alleviate the impact of incorrect system models and/or measurement data. Simulations demonstrate that it is resilient to suboptimal system modeling, sudden system dynamic changes and bad data injection.
Publication Date
7-22-2015
Publication Title
2015 IEEE 15th International Conference on Environment and Electrical Engineering, EEEIC 2015 - Conference Proceedings
Number of Pages
1431-1436
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/EEEIC.2015.7165380
Copyright Status
Unknown
Socpus ID
84943170101 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84943170101
STARS Citation
Zhang, Jinghe; Momtazpour, Marjan; Ramakrishnan, Naren; Welch, Greg; and Rahman, Saifur, "Secure And Adaptive State Estimation For A Pmu-Equipped Smart Grid" (2015). Scopus Export 2015-2019. 1789.
https://stars.library.ucf.edu/scopus2015/1789