96073 20250605081002.0 doi 10.24084/repqj18.317 sideral 120417 ART-2020-120417 eng Domínguez Gimeno, Sergio (orcid)0000-0002-1229-8591 Analysis of public datasets of power quality distortions 2020 Access copy available to the general public Unrestricted Automatic classification of power quality distortions has gained interest in research due to the proliferation of distributed power systems with renewable sources. To train and test a classification system, data with power quality distortions are required. Most studies generate synthetic data from mathematical equations, since real distortions are difficult to record. A possible alternative is to use public datasets of real disturbances. However, there are strong differences among public datasets. In this paper, existing datasets of power quality distortions were compiled and their main features were analysed and compared. To the best of our knowledge, this is the first work reviewing these datasets. To identify the datasets, the most cited papers on this topic were surveyed. In addition, systematic searches were conducted in four popular scientific repositories. As a result, four available datasets were identified. They included a limited number of samples (20- 44) and types of distortions. Sampling frequencies and recording conditions were appropriate and the two main fundamental grid frequencies (50 and 60 Hz) were also considered. Although these datasets are appropriate for partially testing automatic classifiers, a remaining research effort is to provide comprehensive datasets with hundreds of samples and several types of distortions. info:eu-repo/grantAgreement/ES/DGA-FEDER/T49-17R info:eu-repo/grantAgreement/ES/MECD/CAS18/218 info:eu-repo/grantAgreement/ES/UZ/IT1-19 info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 0.136 2020 Electrical and Electronic Engineering 2020 Q4 Renewable Energy, Sustainability and the Environment 2020 Q4 Energy Engineering and Power Technology 2020 Q4 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Igual Catalán, Raúl Universidad de Zaragoza (orcid)0000-0002-1561-0536 Medrano Sánchez, Carlos Universidad de Zaragoza (orcid)0000-0001-7671-7540 5008 785 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Tecnología Electrónica 5009 535 Universidad de Zaragoza Dpto. Ingeniería Eléctrica Área Ingeniería Eléctrica 18, 3 (2020), 321-326 Renewable energy power qual. j. Renewable Energy and Power Quality Journal 2172-038X 1321585 http://zaguan.unizar.es/record/96073/files/texto_completo.pdf Versión publicada 622729 http://zaguan.unizar.es/record/96073/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:96073 articulos driver 2025-06-05-08:03:15 ARTICLE