Economic Framework for Maximising Electricity Theft Recovery in Distribution Networks

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Adebayo Adeyinka Victor
Pelumi Peter Aluko-Olokun
Ologunwa Oluyemi Philip

Electricity theft, a type of non-technical loss (NTL), reduces utility revenues, distorts feeder loadings, and hampers investments in reliability and clean energy. This study presents an integrated economic framework to maximise recoverable value from theft within distribution networks. The framework combines mechanism design to align customer incentives through pricing, amnesty programmes, and credible penalties with a portfolio approach to detection and remediation strategies. These include advanced metering, feeder/DT balancing, analytics-driven audits, and standardised legal evidence packs, all within budget, legal, and equity constraints. It models recoveries as the discounted net present value of past back-billing and legitimate future consumption, guided by key utility KPIs such as recovered NPV per cost, relapse rates, and alarm accuracy. Implementation follows a three-phase plan: initial pilots, scaling and optimisation, and institutionalisation, supported by governance structures (RACI, due process, independent audits) and measurement & verification. Examples from India and Brazil demonstrate that integrating technology, legal processes, and social measures is vital for shifting incentives away from theft and towards compliance. Ultimately, this approach provides regulators with a justifiable method to reduce NTL while upholding affordability and public trust.

Economic Framework for Maximising Electricity Theft Recovery in Distribution Networks. (2025). International Journal of Latest Technology in Engineering Management & Applied Science, 14(11), 624-632. https://doi.org/10.51583/IJLTEMAS.2025.1411000058

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Economic Framework for Maximising Electricity Theft Recovery in Distribution Networks. (2025). International Journal of Latest Technology in Engineering Management & Applied Science, 14(11), 624-632. https://doi.org/10.51583/IJLTEMAS.2025.1411000058