@inproceedings{b3cfdbefc5634fd0b0746e9502207d4d,
title = "Application of distributed Compressive Sensing to Power System State Estimation",
abstract = "This paper presents an application of distributed Compressive Sensing (CS) for data recovery/reconstruction in Power System State Estimation (PSSE). Transmitted measurements to power system control centers may disappear due to congestion or disconnection in communication links, sensor failures, and cyber-attacks. Consequently, the state estimator may encounter problems. In the proposed method, the identified (Phasor Measurement Unit) PMU bad/missing measurement(s) are reconstructed using CS. Data reconstruction exploits the correlation in both time and space among the PMU measurements using a random projection matrix and a wavelet dictionary. The linear state estimation is then carried out using the available and reconstructed PMU measurements. The proposed method is evaluated on the IEEE 57-Bus transmission system. The capabilities and limitations of the proposed method are also discussed.",
keywords = "Compressive sensing, data recovery, PMU data, state estimation",
author = "Hamidi, {R. Jalilzadeh} and H. Khodabandehlou and H. Livani and Fadali, {M. Sami}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; North American Power Symposium, NAPS 2015 ; Conference date: 04-10-2015 Through 06-10-2015",
year = "2015",
month = nov,
day = "20",
doi = "10.1109/NAPS.2015.7335114",
language = "English",
series = "2015 North American Power Symposium, NAPS 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 North American Power Symposium, NAPS 2015",
address = "United States",
}