Research on user abnormal power consumption based on non-intrusive detection

Fang Qiu; Jia Li; Fangyu Liu

doi:10.1117/12.2685367

21 July 2023 Research on user abnormal power consumption based on non-intrusive detection

Fang Qiu, Jia Li, Fangyu Liu

Proceedings Volume 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023); 127172X (2023) https://doi.org/10.1117/12.2685367
Event: 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 2023, Wuhan, China

Abstract

With the rapid increase in the types of electrical appliances used by users, the number of electrical accidents caused by this has increased year by year. In view of this, real-time monitoring of the use and operation of electrical appliances of power users is of great significance to better protect the safety of life and property of power users. Considering the monitoring cost and the acceptability of the monitored users, this paper proposes a machine learning fusion model based on V-I trajectory characteristic curve from the perspective of non-intrusive load decomposition, which realizes the effect of remote monitoring of abnormal electrical appliances with lower cost and higher user acceptance.

Citation Download Citation

Fang Qiu, Jia Li, and Fangyu Liu "Research on user abnormal power consumption based on non-intrusive detection", Proc. SPIE 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 127172X (21 July 2023); https://doi.org/10.1117/12.2685367

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