Unsupervised Learning for Non-intrusive Load Monitoring in Smart Grid Based on Spiking Deep Neural Network

Unsupervised Learning for Non-intrusive Load Monitoring in Smart Grid Based on Spiking Deep Neural Network

This paper investigates the intelligent load monitoring problem with applications to practical energy management scenarios in smart grids. As one of the critical components for paving the way to smart grids' success, an intelligent and feasible non-intrusive load monitoring (NILM) algorit...

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Bibliographic Details
Main Authors: Zejian Zhou, Yingmeng Xiang, Hao Xu, Yishen Wang, Di Shi
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:Journal of Modern Power Systems and Clean Energy
Subjects:
Non-intrusive load monitoring (NILM)
spiking neural network (SNN)
smart grid
unsupervised machine learning
Online Access:https://ieeexplore.ieee.org/document/9447253/

Internet

https://ieeexplore.ieee.org/document/9447253/

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