Non-Intrusive Load Monitoring via Deep Learning Based User Model and Appliance Group Model

Non-Intrusive Load Monitoring via Deep Learning Based User Model and Appliance Group Model

Non-Intrusive Load Monitoring (NILM) increases awareness on user energy usage patterns. In this paper, an efficient and highly accurate NILM method is proposed featuring condensed representation, super-state and fusion of two deep learning based models. Condensed representation helps the two models...

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Bibliographic Details
Main Authors: Ce Peng, Guoying Lin, Shaopeng Zhai, Yi Ding, Guangyu He
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Energies
Subjects:
NILM
deep learning
deep user model
deep appliance group model
user behavior
Online Access:https://www.mdpi.com/1996-1073/13/21/5629

Internet

https://www.mdpi.com/1996-1073/13/21/5629

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