Evaluation of automatic power quality classification in microgrids operating in islanded mode

Igual, Raúl; Medrano, Carlos; Schubert, Franz

doi:10.1109/ptc.2019.8810911

Cited by 4 publications

(1 citation statement)

References 23 publications

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“…These elements are sources of power quality distortions [2]. This problem has been aggravated with the development of distributed technologies, which mainly include renewable sources [3].…”

Section: Introductionmentioning

confidence: 99%

Analysis of public datasets of power quality distortions

Dominguez-Gimeno¹,

Igual²,

Medrano³

2020

REPQJ

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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.

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“…These elements are sources of power quality distortions [2]. This problem has been aggravated with the development of distributed technologies, which mainly include renewable sources [3].…”

Section: Introductionmentioning

confidence: 99%