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Nonlinear loads model for harmonics flow prediction, using multivariate regression

Author
Lamich, M.; Balcells, J.; Corbalan, M.; Griful, E.
Type of activity
Journal article
Journal
IEEE transactions on industrial electronics
Date of publication
2017-06
Volume
64
Number
6
First page
4820
Last page
4827
DOI
https://doi.org/10.1109/TIE.2017.2674596 Open in new window
Repository
http://hdl.handle.net/2117/108748 Open in new window
http://ieeexplore.ieee.org/document/7862787/?arnumber=7862787&source=authoralert Open in new window
Abstract
This paper describes a method for obtaining a model of a single or a set of nonlinear loads (NLL) connected to a certain point of an electrical network. The basic assumption is that the network supplying the NLL has significant series impedances and is disturbed by other parallel, random, and unknown neighbor loads, sharing part of the supply system with the NLL. The main interest for obtaining the model is its further use to predict the amount and flow of harmonic currents generated by the NLL,...
Citation
Lamich, M., Balcells, J., Corbalan, M., Griful, E. Nonlinear loads model for harmonics flow prediction, using multivariate regression. "IEEE transactions on industrial electronics", Juny 2017, vol. 64, núm. 6, p. 4820-4827.
Keywords
Harmonics, modeling, multivariate regression, nonlinear loads (NLL), power quality
Group of research
DISEN - Distributed Sensor Networks
Electromagnetic Compatibility (EMC); Widebandgap (WBG); Internal Activity; Feature Selective Validation (FSV); Spread Spectrum modulation; Reliability; Multilevel Converters; Fault detection;
L'AIRE - Laboratory of Aeronautical and Industrial Research and Studies
PERC-UPC - Power Electronics Research Centre

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