IDEAS home Printed from https://ideas.repec.org/a/eee/juipol/v73y2021ics0957178721001387.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0957178721001387
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jup.2021.101304?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yurtseven, Çağlar, 2015. "The causes of electricity theft: An econometric analysis of the case of Turkey," Utilities Policy, Elsevier, vol. 37(C), pages 70-78.
    2. Faisal Jamil & Eatzaz Ahmad, 2014. "An Empirical Study of Electricity Theft from Electricity Distribution Companies in Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 53(3), pages 239-254.
    3. Jamil, Faisal, 2018. "Electricity theft among residential consumers in Rawalpindi and Islamabad," Energy Policy, Elsevier, vol. 123(C), pages 147-154.
    4. Zhou, Kaile & Fu, Chao & Yang, Shanlin, 2016. "Big data driven smart energy management: From big data to big insights," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 215-225.
    5. Mwaura, Francis M., 2012. "Adopting electricity prepayment billing system to reduce non-technical energy losses in Uganda: Lesson from Rwanda," Utilities Policy, Elsevier, vol. 23(C), pages 72-79.
    6. Jamil, Faisal & Ahmad, Eatzaz, 2019. "Policy considerations for limiting electricity theft in the developing countries," Energy Policy, Elsevier, vol. 129(C), pages 452-458.
    7. Kazmi, Hussain & Mehmood, Fahad & Tao, Zhenmin & Riaz, Zainab & Driesen, Johan, 2019. "Electricity load-shedding in Pakistan: Unintended consequences, opportunities and policy recommendations," Energy Policy, Elsevier, vol. 128(C), pages 411-417.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Wabukala, Benard M. & Mukisa, Nicholas & Watundu, Susan & Bergland, Olvar & Rudaheranwa, Nichodemus & Adaramola, Muyiwa S., 2023. "Impact of household electricity theft and unaffordability on electricity security: A case of Uganda," Energy Policy, Elsevier, vol. 173(C).
    3. 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).
    4. Jamil, Faisal & Ahmad, Eatzaz, 2019. "Policy considerations for limiting electricity theft in the developing countries," Energy Policy, Elsevier, vol. 129(C), pages 452-458.
    5. Hugo Brise o & Omar Rojas, 2020. "Factors Associated with Electricity Losses: A Panel Data Perspective," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 281-286.
    6. Hugo Brise o & Omar Rojas, 2020. "Factors Associated with Electricity Theft in Mexico," International Journal of Energy Economics and Policy, Econjournals, vol. 10(3), pages 250-254.
    7. Arkorful, Vincent Ekow, 2022. "Unravelling electricity theft whistleblowing antecedents using the theory of planned behavior and norm activation model," Energy Policy, Elsevier, vol. 160(C).
    8. Hugo Brise o & Jessica Rubiano & Rodolfo Garc a & Omar Rojas, 2021. "Factors Associated with Electricity Losses in Colombia," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 465-470.
    9. Daniel Leite & José Pessanha & Paulo Simões & Rodrigo Calili & Reinaldo Souza, 2020. "A Stochastic Frontier Model for Definition of Non-Technical Loss Targets," Energies, MDPI, vol. 13(12), pages 1-20, June.
    10. Gautier, Axel & Nsabimana, René & Walheer, Barnabé, 2023. "Quality performance gaps and minimal electricity losses in East Africa," Utilities Policy, Elsevier, vol. 82(C).
    11. Stracqualursi, Erika & Rosato, Antonello & Di Lorenzo, Gianfranco & Panella, Massimo & Araneo, Rodolfo, 2023. "Systematic review of energy theft practices and autonomous detection through artificial intelligence methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    12. Yakubu, Osman & Babu C., Narendra & Adjei, Osei, 2018. "Electricity theft: Analysis of the underlying contributory factors in Ghana," Energy Policy, Elsevier, vol. 123(C), pages 611-618.
    13. Jamil, Faisal & Islam, Tanweer Ul, 2023. "Outage-induced power backup choice in Pakistan," Utilities Policy, Elsevier, vol. 82(C).
    14. Sajad Ali & Min Yongzhi & Wajid Ali, 2023. "Prevention and Detection of Electricity Theft of Distribution Network," Sustainability, MDPI, vol. 15(6), pages 1-19, March.
    15. 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.
    16. Farah Mohammad & Kashif Saleem & Jalal Al-Muhtadi, 2023. "Ensemble-Learning-Based Decision Support System for Energy-Theft Detection in Smart-Grid Environment," Energies, MDPI, vol. 16(4), pages 1-16, February.
    17. Otuoze, Abdulrahaman Okino & Mustafa, Mohd Wazir & Abdulrahman, Abdulhakeem Temitope & Mohammed, Olatunji Obalowu & Salisu, Sani, 2020. "Penalization of electricity thefts in smart utility networks by a cost estimation-based forced corrective measure," Energy Policy, Elsevier, vol. 143(C).
    18. Adongo, Charles Atanga & Taale, Francis & Bukari, Shaibu & Suleman, Shafic & Amadu, Iddrisu, 2021. "Electricity theft whistleblowing feasibility in commercial accommodation facilities," Energy Policy, Elsevier, vol. 155(C).
    19. Jia, Kunqi & Guo, Ge & Xiao, Jucheng & Zhou, Huan & Wang, Zhihua & He, Guangyu, 2019. "Data compression approach for the home energy management system," Applied Energy, Elsevier, vol. 247(C), pages 643-656.
    20. Amasyali, Kadir & El-Gohary, Nora M., 2018. "A review of data-driven building energy consumption prediction studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1192-1205.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:juipol:v:73:y:2021:i:c:s0957178721001387. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.sciencedirect.com/journal/utilities-policy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.