Bridging the Gap between Energy Consumption and Distribution through Non-Technical Loss Detection

Bernat Coma-Puig and Josep Carmona
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Bernat Coma-Puig: Department of Computer Science, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain
Josep Carmona: Department of Computer Science, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain

Energies, 2019, vol. 12, issue 9, 1-17

Abstract: The application of Artificial Intelligence techniques in industry equips companies with new essential tools to improve their principal processes. This is especially true for energy companies, as they have the opportunity, thanks to the modernization of their installations, to exploit a large amount of data with smart algorithms. In this work we explore the possibilities that exist in the implementation of Machine-Learning techniques for the detection of Non-Technical Losses in customers. The analysis is based on the work done in collaboration with an international energy distribution company. We report on how the success in detecting Non-Technical Losses can help the company to better control the energy provided to their customers, avoiding a misuse and hence improving the sustainability of the service that the company provides.

Keywords: fraud detection; machine learning; supervised systems (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: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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