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

Author

Listed:
  • Alireza Vahabzadeh

    (Faculty of New Sciences and Technologies, University of Tehran, Tehran 1439957131, Iran)

  • Alibakhsh Kasaeian

    (Faculty of New Sciences and Technologies, University of Tehran, Tehran 1439957131, Iran)

  • Hasan Monsef

    (School of Electrical and Computer Engineering, University of Tehran, Tehran 1417414418, Iran)

  • Alireza Aslani

    (Faculty of New Sciences and Technologies, University of Tehran, Tehran 1439957131, Iran)

Abstract

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.

Suggested Citation

  • Alireza Vahabzadeh & Alibakhsh Kasaeian & Hasan Monsef & Alireza Aslani, 2020. "A Fuzzy-SOM Method for Fraud Detection in Power Distribution Networks with High Penetration of Roof-Top Grid-Connected PV," Energies, MDPI, vol. 13(5), pages 1-24, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1287-:d:330864
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    References listed on IDEAS

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    Cited by:

    1. Savian, Fernando de Souza & Siluk, Julio Cezar Mairesse & Garlet, Taís Bisognin & do Nascimento, Felipe Moraes & Pinheiro, José Renes & Vale, Zita, 2021. "Non-technical losses: A systematic contemporary article review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    2. Muhammad Salman Saeed & Mohd Wazir Mustafa & Nawaf N. Hamadneh & Nawa A. Alshammari & Usman Ullah Sheikh & Touqeer Ahmed Jumani & Saifulnizam Bin Abd Khalid & Ilyas Khan, 2020. "Detection of Non-Technical Losses in Power Utilities—A Comprehensive Systematic Review," Energies, MDPI, vol. 13(18), pages 1-25, September.

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