Electricity Behavior Modeling and Anomaly Detection Services Based on a Deep Variational Autoencoder Network

Understanding electrical load profiles and detecting anomaly behaviors are important to the smart grid system. However, current load identification and anomaly analysis are based on static analysis, and less consideration is given to anomaly findings under load change conditions. This paper proposes...

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Bibliographic Details
Published in:	Energies (Basel) Vol. 17; no. 16; p. 3904
Main Authors:	Lin, Rongheng, Chen, Shuo, He, Zheyu, Wu, Budan, Zou, Hua, Zhao, Xin, Li, Qiushuang
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.08.2024
Subjects:	Algorithms anomaly detection Approximation autoencoder network Automation China Classification Clustering Customers Data analysis Data compression Data mining Electric power systems Electricity Electricity distribution Energy consumption Energy management Forecasting load pattern Methods Neural networks Parameter estimation Role models China
ISSN:	1996-1073, 1996-1073
Online Access:	Get full text
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