Power Quality Analysis in an Industrial Electrical System by Probability Density Function

G. B. Gibelli, M. Oleskovicz, J. C. M. Vieira



This research aimed to analyze the Power Quality (PQ) in an Industrial Electrical System (IES) through event classification by applying the Probability Density Function (PDF). The aim is to obtain PQ indicators that enable an informative action (warning sign) for the protection devices associated through the classification of disturbances conducted by PDF. The methodology and results are based on the modeling and simulation of a real IES containing Three Phase Induction Motors (TPIM), using the DIgSILENT PowerFactory software. The modeling was performed to generate representative situations of IES operation featuring short duration voltage variations. The classification of the situations by the proposed methodology could be initially checked by observing this disturbance. Satisfactory results attest to the potential of the approach developed until now.

Published in: Renewable Energy & Power Quality Journal (RE&PQJ, Nº. 14)
Pages: 145-150 Date of Publication: 2016/5/20
ISSN: 2172-038X Date of Current Version:2016/05/04
REF: 250-16 Issue Date: May 2016
DOI:10.24084/repqj14.250 Publisher: EA4EPQ

Authors and affiliations

G. B. Gibelli(1), M. Oleskovicz(2), J. C. M. Vieira(2)
1. Department of Engineering of Energy. FAEN. Federal University of Grande Dourados. UFGD. Brazil
2. Department of Electrical and Computer Engineering. University of São Paulo. USP/EESC. Brazil

Key words

Power Quality, Industrial Electrical System, Probability Density Function, Three Phase Induction Motor.


[1] R. C. Dugan, M. F. McGranaghan, S. Santoso and H. W. Beaty, Electrical Power Systems Quality, McGraw-Hill,
[2] D. G. Lieberman, R. J. T. Troncoso, R. A. O. Rios, A. G. Perez, and E. C. Yepez, “Techniques and methodologies for power quality analysis and disturbances classification in power systems: a review,” IET Generation, Transmission
and Distribution 5(4), 519-529, 2011.
[3] W. Fan, Y. Liao, T. Laughner, B. Rogers, G. Pitts, et al., “Intelligent data analysis for power systems,” In IEEE PES
General Meeting, 2012.
[4] R. Bernardes and F. Ayello, “PQMS – Power quality monitoring system: improve power systems through ieds ,”
in 20th Internacional Conference on Electricity Distribution, IEEE, 2009.
[5] S. Haykin and M. Moher, Comunication Systems, Wiley, 2009.
[6] D. C. Montgomery and G. C. Runger, Applied Statistics and Probability for Motorers, LTC, 2012.
[7] J. L. Devore, Probability and Statistics for Motorering and the Sciences, Cengage Learning, 2015.
[8] Z. Gang, A. Duffy, H. Sasse and W. Lixin, “The use of Probability Density Funtions to improve the interpretation
of FSV results,” in IEEE International Symposium on Electromagnetic Compability (EMC), pp. 685-689, 2012.
[9] DIgSILENT PowerFactory, “Power System Analysis Software,” Available:, 2010.
[10] IEEE 1159, “Recommended Practice for Monitoring Electric Power Quality,” 1995.