@inproceedings{b2bb8e1bd25242e68f73521a4c2ae996,
title = "Hybrid state estimation using distributed Compressive Sensing",
abstract = "In this paper, a hybrid state estimation (HSE) method is proposed for the integration of Phasor Measurement Unit (PMU) data into conventional weighted least square state estimators. PMU measurements are not easily compatible with conventional state estimators because PMUs provide different measurement types at a much faster rate than SCADA measurements. However, the vast majority of state estimators are SCADA-based and they cannot utilize PMU data. In the proposed method, PMU data are converted into the SCADA form based on their statistical properties, and the difference between the refreshing rates is compensated using the distributed Compressive Sensing (CS) which exploits the spatial-temporal correlation of PMU data. Simulations are carried out on the IEEE 14- and 57-bus systems to evaluate the proposed hybrid SE. The simulation results are used to discuss the pros and cons of the proposed method.",
keywords = "Compressive sensing, Hybrid state estimation, PMU, SCADA, WLS",
author = "Hamidi, {Reza J.} and H. Khodabandelou and H. Livani and M. Sami-Fadali",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Power and Energy Society General Meeting, PESGM 2016 ; Conference date: 17-07-2016 Through 21-07-2016",
year = "2016",
month = nov,
day = "10",
doi = "10.1109/PESGM.2016.7742038",
language = "English",
series = "IEEE Power and Energy Society General Meeting",
publisher = "IEEE Computer Society",
booktitle = "2016 IEEE Power and Energy Society General Meeting, PESGM 2016",
address = "United States",
}
