Computational Intelligent Approaches for Non-Technical Losses Management of Electricity

Rubén González Rodríguez, Jamer Jiménez Mares and Christian G. Quintero M.
Additional contact information
Rubén González Rodríguez: Department of Electrical and Electronics Engineering, Universidad del Norte, Barranquilla 081007, Colombia
Jamer Jiménez Mares: Department of Electrical and Electronics Engineering, Universidad del Norte, Barranquilla 081007, Colombia
Christian G. Quintero M.: Department of Electrical and Electronics Engineering, Universidad del Norte, Barranquilla 081007, Colombia

Energies, 2020, vol. 13, issue 9, 1-25

Abstract: This paper presents an intelligent system for the detection of non-technical losses of electrical energy associated with the fraudulent behaviors of system users. This proposal has three stages: a non-supervised clustering of consumption profiles based on a hybrid algorithm between self-organizing maps (SOM) and genetic algorithms (GA). A second stage for demand forecasting is based on ARIMA (autoregressive integrated moving average) models corrected intelligently through neural networks (ANN). The final stage is a classifier based on random forests for fraudulent user detection. The proposed intelligent approach was trained and tested with real data from the Colombian Caribbean region, where the utility reports energy losses of around 18% of the total energy purchased by the company during the five last years. The results show an average overall performance of 82.9% in the detection process of fraudulent users, significantly increasing the effectiveness compared to the approaches (68%) previously applied by the utility in the region.

Keywords: non-technical losses; irregular electricity consumption; fraud detection; intelligent 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: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/9/2393/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/9/2393/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:9:p:2393-:d:356591

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().