Intelligent system for non-technical losses management in residential users of the electricity sector
The identification of irregular users is an important assignment in the recovery of energy in the distribution sector. This analysis requires low error levels to minimize non-technical electrical losses in power grid. However, the detection of fraudulent users who have billing does not present a gen...
- Autores:
-
Uparela Cantillo, Miguel
González, Ruben
Jiménez Mares, Jamer
Quintero Monroy, Christian
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2018
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/67532
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/67532
http://bdigital.unal.edu.co/68561/
- Palabra clave:
- 62 Ingeniería y operaciones afines / Engineering
non-technical losses
irregular electricity consumption
fraud detection
intelligent systems
Pérdidas no técnicas
Consumo irregular de electricidad
detección de fraudes
Sistemas inteligentes.
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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Intelligent system for non-technical losses management in residential users of the electricity sector |
| title |
Intelligent system for non-technical losses management in residential users of the electricity sector |
| spellingShingle |
Intelligent system for non-technical losses management in residential users of the electricity sector 62 Ingeniería y operaciones afines / Engineering non-technical losses irregular electricity consumption fraud detection intelligent systems Pérdidas no técnicas Consumo irregular de electricidad detección de fraudes Sistemas inteligentes. |
| title_short |
Intelligent system for non-technical losses management in residential users of the electricity sector |
| title_full |
Intelligent system for non-technical losses management in residential users of the electricity sector |
| title_fullStr |
Intelligent system for non-technical losses management in residential users of the electricity sector |
| title_full_unstemmed |
Intelligent system for non-technical losses management in residential users of the electricity sector |
| title_sort |
Intelligent system for non-technical losses management in residential users of the electricity sector |
| dc.creator.fl_str_mv |
Uparela Cantillo, Miguel González, Ruben Jiménez Mares, Jamer Quintero Monroy, Christian |
| dc.contributor.author.spa.fl_str_mv |
Uparela Cantillo, Miguel González, Ruben Jiménez Mares, Jamer Quintero Monroy, Christian |
| dc.subject.ddc.spa.fl_str_mv |
62 Ingeniería y operaciones afines / Engineering |
| topic |
62 Ingeniería y operaciones afines / Engineering non-technical losses irregular electricity consumption fraud detection intelligent systems Pérdidas no técnicas Consumo irregular de electricidad detección de fraudes Sistemas inteligentes. |
| dc.subject.proposal.spa.fl_str_mv |
non-technical losses irregular electricity consumption fraud detection intelligent systems Pérdidas no técnicas Consumo irregular de electricidad detección de fraudes Sistemas inteligentes. |
| description |
The identification of irregular users is an important assignment in the recovery of energy in the distribution sector. This analysis requires low error levels to minimize non-technical electrical losses in power grid. However, the detection of fraudulent users who have billing does not present a generalized methodology. This issue is complex and varies according to the case study. This paper presents a novel methodology to identify residential fraudulent users by using intelligent systems. The proposed intelligent system consists of three fundamental modules. The first module performs the classification of users with similar power consumption curves using self-organizing maps and genetic algorithms. The second module allows carrying out the monthly electricity demand forecasting through of recursive adjustment of ARIMA models. The third module performs the detection of fraudulent users through an artificial neural network for pattern recognition. For the design and validation of the proposed intelligent system, several tests were performed in each developed module. The database used for the design and evaluation of the modules was constructed with data supplied by the energy distribution company of the Colombian Caribbean Region. The results obtained by the proposed intelligent system show a better performance versus the detection rates obtained by the company. |
| publishDate |
2018 |
| dc.date.issued.spa.fl_str_mv |
2018-05-01 |
| dc.date.accessioned.spa.fl_str_mv |
2019-07-03T04:28:38Z |
| dc.date.available.spa.fl_str_mv |
2019-07-03T04:28:38Z |
| dc.type.spa.fl_str_mv |
Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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http://purl.org/coar/resource_type/c_6501 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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Text |
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http://purl.org/redcol/resource_type/ART |
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http://purl.org/coar/resource_type/c_6501 |
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publishedVersion |
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ISSN: 2248-8723 |
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https://repositorio.unal.edu.co/handle/unal/67532 |
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http://bdigital.unal.edu.co/68561/ |
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ISSN: 2248-8723 |
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https://repositorio.unal.edu.co/handle/unal/67532 http://bdigital.unal.edu.co/68561/ |
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spa |
| language |
spa |
| dc.relation.spa.fl_str_mv |
https://revistas.unal.edu.co/index.php/ingeinv/article/view/67331 |
| dc.relation.ispartof.spa.fl_str_mv |
Universidad Nacional de Colombia Revistas electrónicas UN Ingeniería e Investigación Ingeniería e Investigación |
| dc.relation.references.spa.fl_str_mv |
Uparela Cantillo, Miguel and González, Ruben and Jiménez Mares, Jamer and Quintero Monroy, Christian (2018) Intelligent system for non-technical losses management in residential users of the electricity sector. Ingeniería e Investigación, 38 (2). pp. 52-60. ISSN 2248-8723 |
| dc.rights.spa.fl_str_mv |
Derechos reservados - Universidad Nacional de Colombia |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
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Atribución-NoComercial 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc/4.0/ |
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info:eu-repo/semantics/openAccess |
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Atribución-NoComercial 4.0 Internacional Derechos reservados - Universidad Nacional de Colombia http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
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application/pdf |
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Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ingeniería |
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Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Uparela Cantillo, Miguelc1f5f423-fa05-4dcd-aa91-ad4e47027dad300González, Ruben17ca4a3f-ca1f-4252-9311-677b19a83fd8300Jiménez Mares, Jamer3a0c6eb8-35d6-49ff-a057-8117692e15e0300Quintero Monroy, Christian7f624839-b718-45ea-8023-6cbc16c73b013002019-07-03T04:28:38Z2019-07-03T04:28:38Z2018-05-01ISSN: 2248-8723https://repositorio.unal.edu.co/handle/unal/67532http://bdigital.unal.edu.co/68561/The identification of irregular users is an important assignment in the recovery of energy in the distribution sector. This analysis requires low error levels to minimize non-technical electrical losses in power grid. However, the detection of fraudulent users who have billing does not present a generalized methodology. This issue is complex and varies according to the case study. This paper presents a novel methodology to identify residential fraudulent users by using intelligent systems. The proposed intelligent system consists of three fundamental modules. The first module performs the classification of users with similar power consumption curves using self-organizing maps and genetic algorithms. The second module allows carrying out the monthly electricity demand forecasting through of recursive adjustment of ARIMA models. The third module performs the detection of fraudulent users through an artificial neural network for pattern recognition. For the design and validation of the proposed intelligent system, several tests were performed in each developed module. The database used for the design and evaluation of the modules was constructed with data supplied by the energy distribution company of the Colombian Caribbean Region. The results obtained by the proposed intelligent system show a better performance versus the detection rates obtained by the company.La identificación de usuarios con consumo fraudulento es una actividad importante en la recuperación de energía en el sector de la distribución. Este análisis requiere bajos niveles de error para minimizar las pérdidas eléctricas no técnicas en la red de distribución. Sin embargo, la detección de usuarios fraudulentos con facturación no tiene una metodología generalizada. Este es un problema complejo y varía de acuerdo con cada caso de estudio. Este artículo presenta una nueva metodología para la identificación inteligente de usuarios fraudulentos residenciales basada en sistemas inteligentes. El sistema inteligente propuesto consiste en tres módulos fundamentales. El primer módulo clasifica a los usuarios con curvas de consumo similares a través de mapas auto-organizativos y algoritmo genéticos. El segundo módulo realiza la predicción de consumos mensuales mediante ajustes recursivos de modelos ARIMA. El tercer módulo es el responsable de llevar a cabo la detección de usuarios irregulares por medio de una red neuronal para reconocimiento de patrones. Para el diseño y validación del sistema inteligente propuesto se realizaron pruebas en cada módulo que lo integra para diferentes tipos de clientes del mercado. La base de datos utilizada para el diseño y evaluación de los módulos fue construida a partir de los datos suministrados por la empresa de distribución de energía de la Costa Caribe Colombiana. Los resultados obtenidos por el sistema inteligente propuesto muestran un mejor desempeño frente a los índices de detección obtenidos por la empresa.application/pdfspaUniversidad Nacional de Colombia - Sede Bogotá - Facultad de Ingenieríahttps://revistas.unal.edu.co/index.php/ingeinv/article/view/67331Universidad Nacional de Colombia Revistas electrónicas UN Ingeniería e InvestigaciónIngeniería e InvestigaciónUparela Cantillo, Miguel and González, Ruben and Jiménez Mares, Jamer and Quintero Monroy, Christian (2018) Intelligent system for non-technical losses management in residential users of the electricity sector. Ingeniería e Investigación, 38 (2). pp. 52-60. ISSN 2248-872362 Ingeniería y operaciones afines / Engineeringnon-technical lossesirregular electricity consumptionfraud detectionintelligent systemsPérdidas no técnicasConsumo irregular de electricidaddetección de fraudesSistemas inteligentes.Intelligent system for non-technical losses management in residential users of the electricity sectorArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL67331-393149-1-PB.pdfapplication/pdf2606808https://repositorio.unal.edu.co/bitstream/unal/67532/1/67331-393149-1-PB.pdf4994914a6c05ec8ceee2be217f055e25MD51THUMBNAIL67331-393149-1-PB.pdf.jpg67331-393149-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg8966https://repositorio.unal.edu.co/bitstream/unal/67532/2/67331-393149-1-PB.pdf.jpgc73a2cf9273813f6938713c3ad775039MD52unal/67532oai:repositorio.unal.edu.co:unal/675322023-05-30 23:03:01.872Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |