Review on Data-driven Based Electricity Theft Detection Method and Research Prospect for Low False Positive Rate

Electricity theft in the power distribution system is the main cause of non-technical loss of power grids, and it is a chronic problem in operation and management of power utilities. The electricity information acquisition system collects massive user data, which makes it possible to carry out data-driven abnormal electricity detection and accurately pinpoint electricity theft consumers. Affected by the diversity of electricity consumption behaviors of users, the false positive rate of data-driven based electricity theft detection method is still difficult to meet the practical demands in some scenarios, which seriously restricts the engineering application of this method. Firstly, this paper describes the implementation measures of electricity theft, and then sorts out the basic ideas and limitations of the electricity theft detection methods applied in engineering practice and the data-driven based electricity theft detection methods. On this basis, combining with different requirements of engineering application for the evaluation index of electricity theft detection, it is pointed out that the lack of useful extracted information, the low sensitivity and reliability of the characteristic index items are the major reasons that hinder the data-driven based electricity theft detection methods from being practical in engineering. Finally, the electricity theft detection with low false positive rate is prospected from different levels such as algorithm design, state space subdivision, and design and selection of characteristic index items. © 2022 Automation of Electric Power Systems Press.