A critical review of technical case studies for electricity theft detection in smart grids: A new paradigm based transformative approach

Electricity theft detection (ETD) is a vital global concern that affects utility providers (UPs), and non-technical losses (NTLs) are a major issue. While smart metering has helped to reduce conventional technical losses (TLs), NTLs caused by theft are still difficult to identify and have serious effects. Consumers frequently underreport their power consumption, which complicates detection attempts. This paper provides a comprehensive review of various ETD approaches, categorizing them into five areas: (i) Theft Detection with synthetic data, (ii) sequential data-based schemes, (iii) non-sequential data analysis, (iv) neighborhood area-based networks (NANs), and (v) IoT and hardware-based solutions. Each area is presented using case examples that have been statistically, mathematically, and visually analyzed. The article also includes a summary table of known problems and possible solutions, making it a useful resource for academics and developers. A comparison analysis utilizing F1 scores is presented to assess the efficacy of different detection strategies. This is the first review of its type to convert technical articles into real-world case studies, offering useful insights for selecting the best theft detection technologies in smart grids.