Classification of Power Quality Considering Voltage Sags occurred in Feeders

Anderson Roges Teixeira Góes, Maria Teresinha Arns Steiner, Pedro José Steiner Neto


In this paper we propose a methodology to classify Power Quality for feeders, based on sags and by the use of KDD technique, establishing a quality level printed in labels. To support the methodology, it was applied to feeders on a substation located in Curitiba, Paraná, Brazil, based on attributes such as sag length, duration and frequency (number of occurrences on a given period of time). In the search for feeders quality classification, on the Data Mining stage, the main stage on KDD process, three different techniques were used in a comparatively way for pattern recognition: Artificial Neural Networks, Support Vector Machines an Genetic Algorithms. Those techniques presented acceptable results in classification feeders with no possible classification using a simplified method based on maximum number of sags. Thus, by printing the label with information and Quality level, utilities companies can get better organized for mitigation procedures, by establishing clear targets.


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Paper Citation

in Harvard Style

Teixeira Góes A., Arns Steiner M. and Steiner Neto P. (2013). Classification of Power Quality Considering Voltage Sags occurred in Feeders . In Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2013) ISBN 978-989-8565-77-8, pages 433-442. DOI: 10.5220/0004511104330442

in Bibtex Style

author={Anderson Roges Teixeira Góes and Maria Teresinha Arns Steiner and Pedro José Steiner Neto},
title={Classification of Power Quality Considering Voltage Sags occurred in Feeders},
booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2013)},

in EndNote Style

JO - Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2013)
TI - Classification of Power Quality Considering Voltage Sags occurred in Feeders
SN - 978-989-8565-77-8
AU - Teixeira Góes A.
AU - Arns Steiner M.
AU - Steiner Neto P.
PY - 2013
SP - 433
EP - 442
DO - 10.5220/0004511104330442