University of Oulu

Moreira, A.C., Paredes, H.K.M., de Souza, W.A. et al. J Control Autom Electr Syst (2018) 29: 75.

Evaluation of pattern recognition algorithms for applications on power factor compensation

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Author: Moreira, Alexandre C.1; Paredes, Helmo K. M.2; de Souza, Wesley A.1;
Organizations: 1Department of Energy & Systems (DSE), School of Electrical and Computer Engineering (FEEC), University of Campinas (UNICAMP), Av. Albert Einstein, 400, Campinas, SP, Brazil, 13083-970
2Group of Automation and Integrated Systems (GASI), Univ. Estadual Paulista (UNESP), Campus of Sorocaba, Av. Três de Março, 511, SP, Brazil,13083-970
3Centre for Wireless Communications (CWC), University of Oulu, Erkki Koiso-Kanttilan katu 3, 90570 Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 2.5 MB)
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Language: English
Published: Springer Nature, 2018
Publish Date: 2018-12-05


This paper assesses different applied pattern recognition algorithms to decide the most appropriate power factor compensator for a particular point of common coupling. Power factor, current unbalance factor, total demand distortion, voltage harmonic distortion and reactive power daily variation, as well as human expertise, are the key parameters used to set each recognition algorithm. These algorithms are then trained with a series of both simulation and experimental data. Numerical results consistently indicate the decision-tree algorithm with depth 20 as the best classifier for power factor improvement in terms of all metrics considered in this work.

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Series: Journal of control, automation & electrical systems
ISSN: 2195-3880
ISSN-E: 2195-3899
ISSN-L: 2195-3880
Volume: 29
Issue: 1
Pages: 75 - 90
DOI: 10.1007/s40313-017-0352-9
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
Funding: The authors gratefully acknowledge the contributions of São Paulo Research Foundation (FAPESP) under Grant 2016/08645-9 and by Finnish Academy and CNPq/Brazil (n.490235/2012-3) as part of the joint project SUSTAIN, by Strategic Research Council/Aka BC-DC project (n.292854) for their financial support toward the development of this research.
Academy of Finland Grant Number: 292854
Detailed Information: 292854 (Academy of Finland Funding decision)
Copyright information: © Brazilian Society for Automatics--SBA 2017. This is a post-peer-review, pre-copyedit version of an article published in J Control Autom Electr Syst. The final authenticated version is available online at: