Anomaly Detection Method of Electrical Power Consumption Based on Deep Autoencoder

Authors

Ningke Sun, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;Follow
Yan Wang, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;Follow
Zhicheng Ji, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;

Abstract

Abstract: Aiming at the nonlinear and non-stationary characteristics of electrical power consumption data, an abnormal electrical power consumption detection model based on deep autoencoder is proposed. Gated recurrent unit (GRU) network of the deep learning is combined with autoencoder structure, and the encoder and decoder parts of traditional autoencoder are realized by gated recurrent unit network, which gives full play to the data feature extraction capability of gated recurrent unit and the data reconstruction function of autoencoder structure. Based on the reconstruction error between original data and reconstructed data, abnormal data points of the electrical power consumption are detected. By applying the proposed method to actual workshop electrical power consumption data set, it is shown that the proposed method can detect the abnormal points of power consumption data, and the detection effect is better.

Recommended Citation

Sun, Ningke; Wang, Yan; and Ji, Zhicheng (2022) "Anomaly Detection Method of Electrical Power Consumption Based on Deep Autoencoder," Journal of System Simulation: Vol. 34: Iss. 12, Article 5.
DOI: 10.16182/j.issn1004731x.joss.22-FZ0931
Available at: https://dc-china-simulation.researchcommons.org/journal/vol34/iss12/5

First Page

2557

Revised Date

2022-09-26

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.22-FZ0931

Last Page

2565

CLC

TP391.9

Recommended Citation

Ningke Sun, Yan Wang, Zhicheng Ji. Anomaly Detection Method of Electrical Power Consumption Based on Deep Autoencoder[J]. Journal of System Simulation, 2022, 34(12): 2557-2565.

Corresponding Author

Yan Wang,wangyan@jiangnan.edu.cn

DOI

10.16182/j.issn1004731x.joss.22-FZ0931