Causes of Non -Technical Losses and Reduction Measures in Power Distribution Utilities: A Review
DOI:
https://doi.org/10.54536/ajenr.v5i1.5440Keywords:
Causes, Developing Countries, Non-Technical Losses, Power Distribution Utilities, Reduction MeasuresAbstract
Non-technical also called commercial losses present a significant challenge for electric power distribution utilities, especially in developing countries. These losses are due to fraud and energy theft, such as illegal meter tampering and unauthorized connections, as well as billing errors and defective meters. Addressing non-technical losses requires targeted actions, not just general network upgrades like those used for technical losses. Reducing non-technical losses is crucial for the financial sustainability of utilities. High loss levels result in inefficient systems, poor power quality, and unreliable supply, leading to consumer dissatisfaction and adversely affecting the financial health of power distribution utilities. This paper provides a detailed resource for determining the causes and measures to reduce non-technical losses, supported by practical case studies, with a focus on developing countries.
Downloads
References
Baloch, M. H., Tahir Chauhdary, S., Ishak, D., Kaloi, G. S., Nadeem, M. H., Wattoo, W. A., Younas, T., & Hamid, H. T. (2019). Hybrid energy sources status of Pakistan: An optimal technical proposal to solve the power crises issues. Energy Strategy Reviews, 24(January), 132–153. https://doi.org/10.1016/j.esr.2019.02.001
Berha, A., & Khemani, S. (2026). Unreliable Electricity in Developing Countries The Role of Weak Institutions. http://reproducibility.worldbank.org,
Carr, D., & Thomson, M. (2022). Non-Technical Electricity Losses. Energies 2022, Vol. 15, Page 2218, 15(6), 2218. https://doi.org/10.3390/EN15062218
Coma-Puig, B., Calvo, A., Carmona, J., & Gavaldà, R. (2024). A case study of improving a non-technical losses detection system through explainability. Data Mining and Knowledge Discovery, 38(5), 2704–2732. https://doi.org/10.1007/s10618-023-00927-7
Cui, L., Qu, Y., Gao, L., Xie, G., & Yu, S. (2020). Detecting false data attacks using machine learning techniques in smart grid: A survey. Journal of Network and Computer Applications, 170(February), 102808. https://doi.org/10.1016/j.jnca.2020.102808
De Cassai, A., Dost, B., Tulgar, S., & Boscolo, A. (2025a). Methodological Standards for Conducting High-Quality Systematic Reviews. Biology, 14(8), 973. https://doi.org/10.3390/BIOLOGY14080973
de Oliveira Ventura, L., Melo, J. D., Padilha-Feltrin, A., Fernández-Gutiérrez, J. P., Sánchez Zuleta, C. C., & Piedrahita Escobar, C. C. (2020). A new way for comparing solutions to non-technical electricity losses in South America. Utilities Policy, 67(September). https://doi.org/10.1016/j.jup.2020.101113
Depuru, S. S. S. R., Wang, L., & Devabhaktuni, V. (2011a). Electricity theft: Overview, issues, prevention and a smart meter based approach to control theft. Energy Policy, 39(2), 1007–1015. https://doi.org/10.1016/J.ENPOL.2010.11.037
Dodo, U. A., Nwohu, M. N., Abubakar, I. N., & Dodo, M. A. (2020). Appraisal of Aggregate Technical, Commercial and Collection Losses in Nigerian Electricity Distribution System. Nigerian Journal of Technological Development, 17(4), 286–294. https://doi.org/10.63746/NJTD.V17I4.555
Esgalhado et al. (2019). Utilities collections: Practical steps for utilities to get a grip on bad debt | McKinsey. https://www.mckinsey.com/industries/electric-power-and-natural-gas/our-insights/getting-a-grip-on-bad-debt-practical-steps-to-help-utilities-boost-their-resilience?utm_source=chatgpt.com#/
Ghasemi, A. A., & Gitizadeh, M. (2018). Detection of illegal consumers using pattern classification approach combined with Levenberg-Marquardt method in smart grid. International Journal of Electrical Power and Energy Systems, 99(January), 363–375. https://doi.org/10.1016/j.ijepes.2018.01.036
Glauner, P., Meira, J. A., Valtchev, P., State, R., & Bettinger, F. (2017). The challenge of non-technical loss detection using artificial intelligence: A survey. International Journal of Computational Intelligence Systems, 10(1), 760–775. https://doi.org/10.2991/ijcis.2017.10.1.51
Guarav, S., Pal, S., Jain, S., & Katna, R. (2018). Transmission and Distribution Losses and Aggregate Technical and Commercial Losses. Global Journal of Enterprise Information System. https://doi.org/10.18311/gjeis/2018/19938
Hartoyo, M. H. and H. (2010). Guidelines for Minimizing Losses in Energy Delivery.
Hashmi, M. U., & Priolkar, J. G. (2015). Anti-theft energy metering for smart electrical distribution system. 2015 International Conference on Industrial Instrumentation and Control, ICIC 2015, 1424–1428. https://doi.org/10.1109/IIC.2015.7150972
Jamasb, T., Thakur, T., & Bag, B. (2018). Smart electricity distribution networks, business models, and application for developing countries. Energy Policy, 114(June 2017), 22–29. https://doi.org/10.1016/j.enpol.2017.11.068
Jeff Shepard. (2014, December 11). World Loses $89.3 Billion Annually to Electricity Theft - News. New Article. https://eepower.com/news/world-loses-89-3-billion-annually-to-electricity-theft/#
Kaushik, A., & Singh, J. (2017). Study on Technical & Commercial Losses in Power Distribution System. Journal of Engineering Research and Application Www.Ijera.Com, 7(7), 32–37. https://doi.org/10.9790/9622-0709073237
Kessides, Ioannis. (2003). Infrastructure regulation : promises, perils and principles. 200.
Kgaphola, P. M., Marebane, S. M., & Hans, R. T. (2024). Electricity Theft Detection and Prevention Using Technology-Based Models: A Systematic Literature Review. In Electricity (Vol. 5, Issue 2, pp. 334–350). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/electricity5020017
Khonjelwayo, B., & Nthakheni, T. (2021). Determining the causes of electricity losses and the role of management in curbing them: A case study of City of Tshwane Metropolitan Municipality, South Africa. Journal of Energy in Southern Africa, 32(4), 45–57. https://doi.org/10.17159/2413-3051/2021/v32i4a8704
Knayer, T., & Kryvinska, N. (2022). An analysis of smart meter technologies for efficient energy management in households and organizations. Energy Reports, 8(November 2022), 4022–4040. https://doi.org/10.1016/j.egyr.2022.03.041
Leite, J. B., & Mantovani, J. R. S. (2018). Detecting and locating non-technical losses in modern distribution networks. IEEE Transactions on Smart Grid, 9(2), 1023–1032. https://doi.org/10.1109/TSG.2016.2574714
Messinis, G. M., & Hatziargyriou, N. D. (2018). Review of non-technical loss detection methods. Electric Power Systems Research, 158, 250–266. https://doi.org/10.1016/J.EPSR.2018.01.005
Mohammed, O. O., Otuoze, A. O., Salisu, S., Abioye, A. E., Usman, A. M., & Alao, R. A. (2020). THE CHALLENGES AND PANACEAS TO POWER DISTRIBUTION LOSSES IN NIGERIA. 16(1), 120–136. www.azojete.com.ng
Mohapatra, S., & Mohanty, S. (2017). Improving operational efficiency in utility sector through technology intervention. In Int. J. Enterprise Network Management (Vol. 8, Issue 4).
National Electricity Act. (2011). the National Electricity Act, 2011. Government of Sierra Leone, 1–18. http://www.sierra-leone.org/Laws/2011-16.pdf
Ngamchuen, S., & Pirak, C. (2013). Smart anti-tampering algorithm design for single phase smart meter applied to AMI systems. 2013 10th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2013. https://doi.org/10.1109/ECTICON.2013.6559617
Nwohu et al. (2017). Methodology for Evaluation of Aggregate Technical, Commercial and Collection (ATC & C) Losses in a Typical Radial Distribution System. International Journal of Research Studies in Electrical and Electronics Engineering, 3(2). https://doi.org/10.20431/2454-9436.0302001
Obiora, G. N., Igbinosa, G. O., & Fiemobebefa, C. B. (2025). Technical Losses across Distribution Networks in Nigeria and Mitigative Measures: A Review. ABUAD Journal of Engineering Research and Development (AJERD), 8(1), 43–49. https://doi.org/10.53982/ajerd.2025.0801.05-j
Odje, M., Uhunmwangho, R., & Okedu, K. E. (2021). Aggregated Technical Commercial and Collection Loss Mitigation Through a Smart Metering Application Strategy. Frontiers in Energy Research, 9(November), 1–12. https://doi.org/10.3389/fenrg.2021.703265
OhioLINK ETD: Suriyamongkol, Dan. (n.d.). Retrieved January 13, 2026, from https://etd.ohiolink.edu/acprod/odb_etd/etd/r/1501/10?clear=10&p10_accession_num=ohiou1175007802
Oliveira, C. C. B., Kagan, N., Méffe, A., Jonathan, S., Caparroz, S., & Cavaretti, J. L. (2001). A new method for the computation of technical losses in electrical power distribution systems. IEE Conference Publication, 5(482). https://doi.org/10.1049/CP:20010889
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Systematic Reviews 2021 10:1, 10(1), 89-. https://doi.org/10.1186/S13643-021-01626-4
Romero Aguero, J. (2012). Improving the efficiency of power distribution systems through technical and non-technical losses reduction. Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference. https://doi.org/10.1109/TDC.2012.6281652
Saeed, M. S., Mustafa, M. W., Hamadneh, N. N., Alshammari, N. A., Sheikh, U. U., Jumani, T. A., Khalid, S. B. A., & Khan, I. (2020a). Detection of Non-Technical Losses in Power Utilities-A Comprehensive Systematic Review. Energies 2020, Vol. 13, Page 4727, 13(18), 4727. https://doi.org/10.3390/EN13184727
Savian, F. de S., Siluk, J. C. M., Garlet, T. B., do Nascimento, F. M., Pinheiro, J. R., & Vale, Z. (2021). Non-technical losses: A systematic contemporary article review. Renewable and Sustainable Energy Reviews, 147(July 2020). https://doi.org/10.1016/j.rser.2021.111205
Sharma, D., & Pradhan, S. (2017). The Effect of Burden on the Accuracy of Instrument Transformers – A Case Analysis. ISAET - International Scientific Academy of Engineering & Technology, July.
Sinha, P. N., & Choudhury, S. (2018). Aggregate Technical and Commercial Loss Analysis in the areas of Kamrup District under GEC- II, Assam : A case study. 6(2), 715–719.
Smith, T. B. (2004). Electricity theft: A comparative analysis. Energy Policy, 32(18), 2067–2076. https://doi.org/10.1016/S0301-4215(03)00182-4
Srivastava, I. K. A. and V. B. V. S. (2023). The Role of Advanced Meter Infrastructure (AMI) for Electricity Theft Detection in Smart City. https://smartcities.ieee.org/newsletter/march-2023/the-role-of-advanced-meter-infrastructure-ami-for-electricity-theft-detection-in-smart-city?utm_source=chatgpt.com
Srucp. (2017). Reducing Non-Technical Electricity Loss through Employee Incentive Schemes. November, 1–54.
Stevenson, E. S., & Bihl, T. (n.d.). Understanding Electricity Theft: Causes, Consequences, and AI-Based Detection.
Tan, B. (2025, December). Current Transformer (CT) Guide: Accuracy & Selection. https://transformer4u.com/current-transformer-ct-complete-guide/?utm_source=chatgpt.com
The Indian Electricity Act. (2003). The Electricity Act, 2003 -1 MINISTRY OF LAW AND JUSTICE (Legislative Department).
Trimble, C., Kojima, M., Perez Arroyo, I., & Mohammadzadeh, F. (2016). Financial Viability of Electricity Sectors in Sub-Saharan Africa: Quasi-Fiscal Deficits and Hidden Costs. Financial Viability of Electricity Sectors in Sub-Saharan Africa: Quasi-Fiscal Deficits and Hidden Costs, August. https://doi.org/10.1596/1813-9450-7788
Wakodikar, P., Bedi, R., Nandevalia, B., Deb, P., Rathod, J. M., & ... (2014). Smart Energy Meter With Tamper Detection And Communication Feature. Researchgate.Net, March 2016.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Steven Foday Sesay, Engidaw Abel Hailu, Elyas Smaida

This work is licensed under a Creative Commons Attribution 4.0 International License.