Electricity theft detection in smart grid using random matrix theory

• Published in: IET generation, transmission & distribution Vol. 12; no. 2; pp. 371 - 378
• Main Authors: Xiao, Fei, Ai, Qian
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 30.01.2018
• Subjects: advanced metering infrastructure; augmented matrix application; Chinese city; consumption pattern signal design; data‐driven electricity theft detector; electricity consumption; IEEE 34‐bus system; matrix algebra; numerical analysis; power consumption; power system industry; random matrix theory; random processes; Research Article; smart grid; smart meter; smart meters; smart power grids; unbalanced demand‐supply gap; smart meter; smart grid; Chinese city; augmented matrix application; random processes; smart power grids; power consumption; matrix algebra; power system industry; smart meters; electricity consumption; unbalanced demand-supply gap; IEEE 34-bus system; advanced metering infrastructure; numerical analysis; random matrix theory; consumption pattern signal design; data-driven electricity theft detector
• ISSN: 1751-8687; 1751-8695
• DOI: 10.1049/iet-gtd.2017.0898

Illegal use of electricity has been a major concern in power system industries for a long time. Fraudulent large-scale consumption of electricity may result in an unbalanced demand–supply gap. This study proposed a data-driven electricity theft detector that is based on random matrix theory with the widespread use of smart meters and advanced metering infrastructure. The application of an augmented matrix as the data source is the key step of the proposed method, indicating the correlations between power consumption and system operating states under abnormal conditions of electricity use. Moreover, the regional/individual theft detection algorithm and the abnormal consumption pattern signal are designed for shortlisting regions with a high probability of theft and selecting suspected fraudulent customers in real time. Numerical case studies using simulated case studies conducted on the IEEE 34-bus system and real data collected from the power system of a Chinese city are used to investigate the correctness and feasibility of the proposed method.