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Open AccessArticle

A Fuzzy-SOM Method for Fraud Detection in Power Distribution Networks with High Penetration of Roof-Top Grid-Connected PV

1
Faculty of New Sciences and Technologies, University of Tehran, Tehran 1439957131, Iran
2
School of Electrical and Computer Engineering, University of Tehran, Tehran 1417414418, Iran
*
Author to whom correspondence should be addressed.
Energies 2020, 13(5), 1287; https://doi.org/10.3390/en13051287
Received: 2 February 2020 / Revised: 3 March 2020 / Accepted: 4 March 2020 / Published: 10 March 2020
This study proposes a fuzzy self-organized neural networks (SOM) model for detecting fraud by domestic customers, the major cause of non-technical losses in power distribution networks. Using a bottom-up approach, normal behavior patterns of household loads with and without photovoltaic (PV) sources are determined as normal behavior. Customers suspected of energy theft are distinguished by calculating the anomaly index of each subscriber. The bottom-up method used is validated using measurement data of a real network. The performance of the algorithm in detecting fraud in old electromagnetic meters is evaluated and verified. Types of energy theft methods are introduced in smart meters. The proposed algorithm is tested and evaluated to detect fraud in smart meters also. View Full-Text
Keywords: fraud-detection; non-technical loss; power distribution; load profile modeling; data mining; fuzzy-SOM fraud-detection; non-technical loss; power distribution; load profile modeling; data mining; fuzzy-SOM
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Vahabzadeh, A.; Kasaeian, A.; Monsef, H.; Aslani, A. A Fuzzy-SOM Method for Fraud Detection in Power Distribution Networks with High Penetration of Roof-Top Grid-Connected PV. Energies 2020, 13, 1287.

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