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Article

New Time-Frequency Transient Features for Nonintrusive Load Monitoring

IRIMAS, Université de Haute-Alsace, 61 rue Albert Camus, 68093 Mulhouse, France
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Tek Tjing Lie
Energies 2021, 14(5), 1437; https://doi.org/10.3390/en14051437
Received: 10 February 2021 / Revised: 27 February 2021 / Accepted: 2 March 2021 / Published: 5 March 2021
(This article belongs to the Special Issue Advanced Techniques for Power Quality Improvement)
A crucial step in nonintrusive load monitoring (NILM) is feature extraction, which consists of signal processing techniques to extract features from voltage and current signals. This paper presents a new time-frequency feature based on Stockwell transform. The extracted features aim to describe the shape of the current transient signal by applying an energy measure on the fundamental and the harmonic frequency voices. In order to validate the proposed methodology, classical machine learning tools are applied (k-NN and decision tree classifiers) on two existing datasets (Controlled On/Off Loads Library (COOLL) and Home Equipment Laboratory Dataset (HELD1)). The classification rates achieved are clearly higher than that for other related studies in the literature, with 99.52% and 96.92% classification rates for the COOLL and HELD1 datasets, respectively. View Full-Text
Keywords: nonintrusive load monitoring (NILM); time-frequency transform; Stockwell transform; harmonics; feature extraction nonintrusive load monitoring (NILM); time-frequency transform; Stockwell transform; harmonics; feature extraction
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MDPI and ACS Style

Drouaz, M.; Colicchio, B.; Moukadem, A.; Dieterlen, A.; Ould-Abdeslam, D. New Time-Frequency Transient Features for Nonintrusive Load Monitoring. Energies 2021, 14, 1437. https://doi.org/10.3390/en14051437

AMA Style

Drouaz M, Colicchio B, Moukadem A, Dieterlen A, Ould-Abdeslam D. New Time-Frequency Transient Features for Nonintrusive Load Monitoring. Energies. 2021; 14(5):1437. https://doi.org/10.3390/en14051437

Chicago/Turabian Style

Drouaz, Mahfoud; Colicchio, Bruno; Moukadem, Ali; Dieterlen, Alain; Ould-Abdeslam, Djafar. 2021. "New Time-Frequency Transient Features for Nonintrusive Load Monitoring" Energies 14, no. 5: 1437. https://doi.org/10.3390/en14051437

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