Effective Electricity Theft Detection in Power Distribution Grids Using an Adaptive Neuro Fuzzy Inference System

Konstantinos V. Blazakis, Theodoros N. Kapetanakis and George S. Stavrakakis
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Konstantinos V. Blazakis: School of Electrical and Computer Engineering, Technical University of Crete, University Campus, GR-73100 Chania, Greece
Theodoros N. Kapetanakis: Department of Electronic Engineering, Hellenic Mediterranean University, GR-73100 Chania, Greece
George S. Stavrakakis: School of Electrical and Computer Engineering, Technical University of Crete, University Campus, GR-73100 Chania, Greece

Energies, 2020, vol. 13, issue 12, 1-13

Abstract: Electric power grids are a crucial infrastructure for the proper operation of any country and must be preserved from various threats. Detection of illegal electricity power consumption is a crucial issue for distribution system operators (DSOs). Minimizing non-technical losses is a challenging task for the smooth operation of electrical power system in order to increase electricity provider’s and nation’s revenue and to enhance the reliability of electrical power grid. The widespread popularity of smart meters enables a large volume of electricity consumption data to be collected and new artificial intelligence technologies could be applied to take advantage of these data to solve the problem of power theft more efficiently. In this study, a robust artificial intelligence algorithm adaptive neuro fuzzy inference system (ANFIS)—with many applications in many various areas—is presented in brief and applied to achieve more effective detection of electric power theft. To the best of our knowledge, there are no studies yet that involve the application of ANFIS for the detection of power theft. The proposed technique is shown that if applied properly it could achieve very high success rates in various cases of fraudulent activities originating from unauthorized energy usage.

Keywords: data mining; adaptive neuro fuzzy inference system (ANFIS); non-technical losses (NTLs); power theft detection; smart grid; smart electricity metering; power distribution grids (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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