Classification of Voltage Sags Based on MPCA Models

Authors:
Abbas Khosravi;Joaquim Melendez;Joan Colomer
Affiliations:
eXit Group, Dept. of Electronics, Informatics & Automatics, Institute of Informatics and Applications, University of Girona,;eXit Group, Dept. of Electronics, Informatics & Automatics, Institute of Informatics and Applications, University of Girona,;eXit Group, Dept. of Electronics, Informatics & Automatics, Institute of Informatics and Applications, University of Girona,
Venue:
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Year:
2007

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Classification of Disturbances in Electrical Signals Using Neural Networks

IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Bio-inspired Applications of Connectionism-Part II

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Abstract

In this paper, we introduce a new framework for classification of short duration voltage reductions in the area of Power Quality Monitoring using Multiway Principal Component Analysis (MPCA). Firstly, we recast the sags occurred in High Voltage (HV) and Medium Voltage (MV) lines in a format which is suitable for MPCA. Then, MPCA technique is employed for building statistical models for classification of sags originated in HV and MV networks and recorded in the same substation. Projecting sags registered in different substations to MPCA models of other substations has been also explored to deduce similarities and dissimilarities between different substations according to the sags registered in them.