Feature Characterization of Power Quality Events According to Their Underlying Causes
Paper in proceeding, 2010

In this paper are discussed features resulting from the analysis of each underlying cause of power quality (PQ) disturbances. A feature set for each underlying cause is analyzed; likewise, another feature set able to distinguish between the different underlying causes is also analyzed. The proposed feature sets are useful for building suitable frameworks for automatic identification of the underlying cause of events stored in PQ databases. The features are analyzed using real-world and synthetic voltage a current waveforms. A rule-based framework is also proposed and tested. The rules are based on the analyzed features. The framework has obtained a good classification rate of 95.9% demonstrating a high accuracy distinguishing between the different underlying causes in PQ events.

distribution of electric power

power distribution faults

power quality

Diagnosis (fault)

power system monitoring.


Víctor Núñez

University of Girona

Irene Yu-Hua Gu

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

M. H. J. Bollen

Luleå University of Technology

Joaquim Melendez

University of Girona

The 14th IEEE Inte'l Conf. on Harmonics and Quality of Power (ICHQP'10)

978-142447244-4 (ISBN)

Subject Categories

Signal Processing

Other Electrical Engineering, Electronic Engineering, Information Engineering





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