Methodology based on higher‐order statistics and genetic algorithms for the classification of power quality disturbances-Reference-Cited by-同舟云学术

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

Published:2020-09-04 Issue:20 Volume:14 Page:4580-4592
ISSN:1751-8687
Container-title:IET Generation, Transmission & Distribution
language:en
Short-container-title:IET Generation, Transmission & Distribution

Author:

Romero‐Ramirez Luis Alejandro¹^ORCID,Elvira‐Ortiz David Alejandro¹^ORCID,Jaen‐Cuellar Arturo Y.¹^ORCID,Morinigo‐Sotelo Daniel²,Osornio‐Rios Roque A.¹,Romero‐Troncoso Rene de J.¹^ORCID

Affiliation:

1. HSPdigital – CA MecatronicaFacultad de Ingenieria Campus San Juan del RioUniversidad Autonoma de QueretaroRio Moctezuma 24976807San Juan del RioQueretaroMexico

2. HSPdigital – Research Group ADIREUniversity of Valladolid, UVa.Paseo del Cauce, 5947011ValladolidSpain

Funder

Consejo Nacional de Ciencia y Tecnología

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-gtd.2020.0366

Reference36 articles.

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2. Power quality assessment and event detection in hybrid power system

3. Power quality recognition in distribution system with solar energy penetration using S‐transform and fuzzy C‐means clustering;Mahela O.P.;Renew. Energy,2017

4. Emerging power quality challenges due to integration of renewable energy sources;Liang X.;IEEE Trans. Ind. Appl.,2016

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