DocumentCode
3157275
Title
Cyclostationary noise modeling in narrowband powerline communication for Smart Grid applications
Author
Nassar, Marcel ; Dabak, Anand ; Kim, Il Han ; Pande, Tarkesh ; Evans, Brian L.
Author_Institution
Texas Instrum., Dallas, TX, USA
fYear
2012
fDate
25-30 March 2012
Firstpage
3089
Lastpage
3092
Abstract
A Smart Grid intelligently monitors and controls energy flows in an electric grid. Having up-to-date distributed readings of grid conditions helps utilities efficiently scale generation up or down to meet demand. Narrowband powerline communication (PLC) systems can provide these up-to-date readings from subscribers to the local utility over existing power lines. A key challenge in PLC systems is overcoming additive non-Gaussian noise. In this paper, we propose to use a cyclostationary model for the dominant component of additive non-Gaussian noise. The key contributions are (1) fitting measured data from outdoor narrowband PLC system field trials to a cyclostationary model, and (2) developing a cyclostationary noise generation model that fits measured data. We found that the period in the cyclostationary model matched half of the period of the main powerline frequency, which is consistent with previous work in indoor PLC additive noise modeling.
Keywords
carrier transmission on power lines; intelligent control; signal processing; smart power grids; PLC additive noise modeling; additive nonGaussian noise; cyclostationary noise modeling; distributed readings; electric grid conditions; measured data fitting; narrowband powerline communication; narrowband powerline communication systems; outdoor narrowband PLC system; powerline frequency; smart grid applications; smart grid intelligent energy flows control; smart grid intelligent energy flows monitoring; Data models; Narrowband; Noise; Noise measurement; OFDM; Smart grids; Spectrogram; Cyclostationarity; Linear Periodically Time-Varying (LPTV) Systems; Noise Modeling; Powerline Communications; Smart Grid;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location
Kyoto
ISSN
1520-6149
Print_ISBN
978-1-4673-0045-2
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2012.6288568
Filename
6288568
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