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Non-Hardware-Based Non-Technical Losses Detection Methods: A Review

Author

Listed:
  • Fernando G. K. Guarda

    (Santa Maria Technical and Industrial School, Federal University of Santa Maria, Santa Maria 97105-900, Brazil)

  • Bruno K. Hammerschmitt

    (Graduate Program in Electrical Engineering, Federal University of Santa Maria, Santa Maria 97105-900, Brazil)

  • Marcelo B. Capeletti

    (Graduate Program in Electrical Engineering, Federal University of Santa Maria, Santa Maria 97105-900, Brazil)

  • Nelson K. Neto

    (Academic Coordination, Federal University of Santa Maria, Cachoeira do Sul 96503-205, Brazil)

  • Laura L. C. dos Santos

    (Academic Coordination, Federal University of Santa Maria, Cachoeira do Sul 96503-205, Brazil)

  • Lucio R. Prade

    (Polytechnic School, University of Vale dos Sinos, São Leopoldo 93022-750, Brazil)

  • Alzenira Abaide

    (Santa Maria Technical and Industrial School, Federal University of Santa Maria, Santa Maria 97105-900, Brazil)

Abstract

Non-Technical Losses (NTL) represent a serious concern for electric companies. These losses are responsible for revenue losses, as well as reduced system reliability. Part of the revenue loss is charged to legal consumers, thus, causing social imbalance. NTL methods have been developed in order to reduce the impact in physical distribution systems and legal consumers. These methods can be classified as hardware-based and non-hardware-based. Hardware-based methods need an entirely new system infrastructure to be implemented, resulting in high investment and increased cost for energy companies, thus hampering implementation in poorer nations. With this in mind, this paper performs a review of non-hardware-based NTL detection methods. These methods use distribution systems and consumers’ data to detect abnormal energy consumption. They can be classified as network-based, which use network technical parameters to search for energy losses, data-based methods, which use data science and machine learning, and hybrid methods, which combine both. This paper focuses on reviewing non-hardware-based NTL detection methods, presenting a NTL detection methods overview and a literature search and analysis.

Suggested Citation

  • Fernando G. K. Guarda & Bruno K. Hammerschmitt & Marcelo B. Capeletti & Nelson K. Neto & Laura L. C. dos Santos & Lucio R. Prade & Alzenira Abaide, 2023. "Non-Hardware-Based Non-Technical Losses Detection Methods: A Review," Energies, MDPI, vol. 16(4), pages 1-27, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:2054-:d:1074021
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    References listed on IDEAS

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