Non-intrusive residential load identification based on load feature matrix and CBAM-BiLSTM algorithm

Non-intrusive residential load identification based on load feature matrix and CBAM-BiLSTM algorithm

With the increasing demand for the refined management of residential loads, the study of the non-invasive load monitoring (NILM) technologies has attracted much attention in recent years. This paper proposes a novel method of residential load identification based on load feature matrix and improved...

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Bibliographic Details
Main Authors: Shunfu Lin, Bing Zhao, Yinfeng Zhan, Junsu Yu, Xiaoyan Bian, Dongdong Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-08-01
Series:Frontiers in Energy Research
Subjects:
non-intrusive load monitoring
load feature
convolutional block attention module
bi-directional long short-term memory
dynamic time warping
Online Access:https://www.frontiersin.org/articles/10.3389/fenrg.2024.1443700/full

Internet

https://www.frontiersin.org/articles/10.3389/fenrg.2024.1443700/full

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