2022
DOI: 10.1109/tim.2022.3189748
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A Novel Unsupervised Data-Driven Method for Electricity Theft Detection in AMI Using Observer Meters

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Cited by 45 publications
(7 citation statements)
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“…The proposed model achieved outstanding performance, on the Irish dataset, with 0.29 of FPR and 99.42 of AUC [23]. Hasan et al in reference [24] proposed a CNN-LSTM-based ETD model using historical power consumption data for 10,000. The author addresses the missing value in the dataset.…”
Section: Literature Reviewmentioning
confidence: 99%
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“…The proposed model achieved outstanding performance, on the Irish dataset, with 0.29 of FPR and 99.42 of AUC [23]. Hasan et al in reference [24] proposed a CNN-LSTM-based ETD model using historical power consumption data for 10,000. The author addresses the missing value in the dataset.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Equation (22) shows the data with values x i with class c. Average and standard deviation are found using Equations ( 23) and (24).…”
Section: Gaussian Naive Bayesmentioning
confidence: 99%
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“…Reference [8] defined user's short-lived consumption pattern and detected ongoing electricity consumption theft. Reference [9] incorporated wavelet-based feature extraction and fuzzy c-means clustering. State estimation aims at looking for the anomaly measures among all measures of whole region.…”
Section: Introductionmentioning
confidence: 99%
“…However, while supporting the economic and social development, there is also a series of frequent electricity theft, which not only destroys the social order of electricity supply and consumption, but also further has a serious impact on the safe and stable operation of the power system, bringing very serious economic losses to China's power system [1,2] . If power theft cannot be stopped in time, it will not only damage the safety of the national power grid, but also the interests of the whole society [3][4][5] . At present, foreign research on anti-theft technology and systems has developed in the direction of intelligence [6] , building up a complete network system to collect, store and analyse information about customers' electricity consumption.…”
Section: Introductionmentioning
confidence: 99%