An Energy-Fraud Detection-System Capable of Distinguishing Frauds from Other Energy Flow Anomalies in an Urban Environment

Netzah Calamaro, Yuval Beck, Ran Ben Melech and Doron Shmilovitz
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Netzah Calamaro: Faculty of Electrical and Electronics Engineering, Tel-Aviv University, Tel-Aviv 6997801, Israel
Yuval Beck: Faculty of Electrical and Electronics Engineering, Tel-Aviv University, Tel-Aviv 6997801, Israel
Ran Ben Melech: Faculty of Electrical and Electronics Engineering, Tel-Aviv University, Tel-Aviv 6997801, Israel
Doron Shmilovitz: Faculty of Electrical and Electronics Engineering, Tel-Aviv University, Tel-Aviv 6997801, Israel

Sustainability, 2021, vol. 13, issue 19, 1-38

Abstract: Energy fraud detection bears significantly on urban ecology. Reduced losses and power consumption would affect carbon dioxide emissions and reduce thermal pollution. Fraud detection also provides another layer of urban socio-economic correlation heatmapping and improves city energy distribution. This paper describes a novel algorithm of energy fraud detection, utilizing energy and energy consumption specialized knowledge poured into AI front-end. The proposed algorithm improves fraud detection’s accuracy and reduces the false positive rate, as well as reducing the preliminary required training dataset. The paper also introduces a holistic algorithm, specifying the major phenomena that disguises as energy fraud or affects it. Consequently, a mathematical foundation for energy fraud detection for the proposed algorithm is presented. The results show that a unique pattern is obtained during fraud, which is independent of a reference non-fraud pattern of the same customer. The theory is implemented on real data taken from smart metering systems and validated in real life scenarios.

Keywords: AI—Artificial Intelligence; fraud detection; smart grid; smart meters (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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