NDLI: Methodology based on higher-order statistics and genetic algorithms for the classification of power quality disturbances

Content Provider	IET Digital Library
Author	Ramirez, Luis Alejandro Romero Ortiz, David Alejandro Elvira Cuellar, Arturo Y. Jaen Sotelo, Daniel Morinigo Rios, Roque A. Osornio Troncoso, Rene de J. Romero
Abstract	The present work proposes a methodology for the detection and classification of some transient power quality disturbances. It uses a genetic algorithm for estimating the amplitude, frequency, and phase of the fundamental component in an optimum way to suppress it from an electric signal. By using this pre-processing strategy, it is possible to remove a single frequency component instead of removing a whole frequency band as other methodologies do. Once the fundamental component is suppressed, it is possible to perform a better identification of an anomalous condition in a signal because its high energy does not hide the presence of a disturbance. After the suppression, the proposed methodology computes three higher-order statistics (variance, kurtosis, and sixth-order cumulant) from the resulting signal and uses them as inputs for a fuzzy-based classifier. Higher-order statistics are selected because they are insensible to the presence of Gaussian noise adding robustness to the proposed methodology. Experimentation is performed using both synthetic and real signals. Real signals come from a photovoltaic generation plant and a hospital facility, both located in Spain. Results prove that the proposed methodology allows enhancing the results delivered by other methodologies up to 30%.
Starting Page	4580
Ending Page	4592
Page Count	13
ISSN	17518687
Volume Number	14
e-ISSN	17518695
Issue Number	Issue 20, Oct (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/14/20
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2020.0366
Journal	IET Generation, Transmission & Distribution
Publisher Date	2020-08-13
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Combinatorial Mathematics Electric Signal Fuzzy Set Theory Fuzzy-based Classifier Gaussian Noise Genetic Algorithm Harmonics Higher Order Statistics Higher-order Statistics Hospital Facility Optimisation Technique Photovoltaic Generation Plant Power Supply Quality Real Signal Signal Classification Signal Denoising Signal Processing And Detection Single Frequency Component Spain Statistics Synthetic Signal Transient Power Quality Disturbance Classification
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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