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Error Modeling and Anomaly Detection of Smart Electricity Meter Using TSVD+L Method
Lidan Chen1,2; Keng-Weng Lao1,2; Yongliang Ma3; Zhe Zhang3
2022-08
Source PublicationIEEE Transactions on Instrumentation & Measurement
Abstract

The trouble of lacking topology and parameter of the distribution grid and the ill-posed problem in the smart meters (SMs) error estimation are not well resolved in most energy conservation theorem-based SMs anomaly detection methods. This paper presents a sorted ‘Top-N’ anomaly detection mechanism to generate a list of suspicious anomalous SMs. The error estimation model (EEM) only using SMs electricity consumption data is investigated. The truncated singular value decomposition regularization with L-curve optimization (TSVD+L) method is proposed to address the model’s ill-posedness. Three data processing modes, namely one-pot mode, segmentation mode and sliding window technique (SWT), are suggested to obtain multiple calculation results for SMs error comprehensive evaluation. The top N% SMs in error sequence is proposed for onsite calibration instead of full inspection. The effectiveness and practicality of the proposed method are verified through both simulation case and practical distribution network application. The results show that the proposed method has higher accuracy in SMs anomaly detection, compared with the ordinary least squares (OLS) method, recursive least squares (RLS) method, and Tikhonov regularization (Tik) method.

Document TypeJournal article
CollectionFaculty of Science and Technology
DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Corresponding AuthorLidan Chen
Affiliation1.Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau
2.The State Key Laboratory of Internet of Things for Smart City, University of Macau
3.Department of Electrical Engineering, Guangzhou City University of Technology, Guangzhou
First Author AffilicationFaculty of Science and Technology;  University of Macau
Corresponding Author AffilicationFaculty of Science and Technology;  University of Macau
Recommended Citation
GB/T 7714
Lidan Chen,Keng-Weng Lao,Yongliang Ma,et al. Error Modeling and Anomaly Detection of Smart Electricity Meter Using TSVD+L Method[J]. IEEE Transactions on Instrumentation & Measurement,2022.
APA Lidan Chen,Keng-Weng Lao,Yongliang Ma,&Zhe Zhang.(2022).Error Modeling and Anomaly Detection of Smart Electricity Meter Using TSVD+L Method.IEEE Transactions on Instrumentation & Measurement.
MLA Lidan Chen,et al."Error Modeling and Anomaly Detection of Smart Electricity Meter Using TSVD+L Method".IEEE Transactions on Instrumentation & Measurement (2022).
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