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A data-driven approach to reduce electricity theft in developing countries

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  • Nadeem, Ahmad
  • Arshad, Naveed

Abstract

Theft of electricity is a problem in many developing countries. But AMI is paving the way for data-centric architecture to help in theft detection. However, a smart grid or even AMR is a long shot for many developing countries due to the costs involved in its large-scale deployment. This paper presents a technique to detect outliers among electricity users that further investigates electricity theft using data analytics on monthly usage data available to every utility company. Using this technique, we have reduced the search space for theft identification to as low as 3.4% of the total customer base.

Suggested Citation

  • Nadeem, Ahmad & Arshad, Naveed, 2021. "A data-driven approach to reduce electricity theft in developing countries," Utilities Policy, Elsevier, vol. 73(C).
    • Handle: RePEc:eee:juipol:v:73:y:2021:i:c:s0957178721001387
    DOI: 10.1016/j.jup.2021.101304
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    References listed on IDEAS

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    5. Razavi, Rouzbeh & Gharipour, Amin & Fleury, Martin & Akpan, Ikpe Justice, 2019. "A practical feature-engineering framework for electricity theft detection in smart grids," Applied Energy, Elsevier, vol. 238(C), pages 481-494.
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    7. Jamil, Faisal & Ahmad, Eatzaz, 2019. "Policy considerations for limiting electricity theft in the developing countries," Energy Policy, Elsevier, vol. 129(C), pages 452-458.
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    Cited by:

    1. Babar, Zainab & Jamil, Faisal & Haq, Wajiha, 2022. "Consumer's perception towards electricity theft: A case study of Islamabad and Rawalpindi using a path analysis," Energy Policy, Elsevier, vol. 169(C).

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