@inproceedings{b4c56683bb6141e6a60cc71dd6ec5c02,
title = "Applications of compressed sensing and sparse representations for state estimation in power systems",
abstract = "Compressed sensing is an emerging signal processing method that finds applications in diverse estimation problems. This paper shows that power systems events may be analyzed in terms of sparse structures, especially if the probability of their occurrence within a power network is low. The paper presents several examples for such events, and suggests methods for locating them within large power systems using few measurements. Several types of sparse events are analyzed: faults, lightning strikes, polluting loads, and electricity thefts.",
keywords = "compressed sensing, electricity thefts, fault location, harmonic distortion, sparse estimation, sparse representations, state estimation, wide-area sensing",
author = "Igal Rozenberg and Yoash Levron",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems, COMCAS 2015 ; Conference date: 02-11-2015 Through 04-11-2015",
year = "2015",
month = dec,
day = "17",
doi = "10.1109/COMCAS.2015.7360397",
language = "אנגלית",
series = "2015 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems, COMCAS 2015",
booktitle = "2015 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems, COMCAS 2015",
}