Comparative Evaluation of Non-Intrusive Load Monitoring Methods Using Relevant Features and Transfer Learning

Non-Intrusive Load Monitoring (NILM) refers to the analysis of the aggregated current and voltage measurements of Home Electrical Appliances (HEAs) recorded by the house electrical panel. Such methods aim to identify each HEA for a better control of the energy consumption and for future smart grid a...

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書誌詳細

主要な著者:	Sarra Houidi, Dominique Fourer, François Auger, Houda Ben Attia Sethom, Laurence Miègeville
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2021-05-01
シリーズ:	Energies
主題:	Non-Intrusive Load Monitoring (NILM) Home Electrical Appliances (HEAs) identification feature selection transfer learning deep learning
オンライン･アクセス:	https://www.mdpi.com/1996-1073/14/9/2726
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