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Increasing the efficiency in non-technical losses detection in utility companies

Opened Access Increasing the efficiency in non-technical losses detection in utility companies
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Autor: Guerrero Alonso, Juan Ignacio
León de Mora, Carlos
Biscarri Triviño, Félix
Monedero Goicoechea, Iñigo Luis
Biscarri Triviño, Jesús
Millán Navarro, María del Rocío
Departamento: Universidad de Sevilla. Departamento de Tecnología Electrónica
Fecha: 2010
Publicado en: 15th IEEE Mediterranian Electromechanical Conference: Valletta (Malta), 25-28 de Abril, 2010, 136-141
Tipo de documento: Ponencia
Resumen: Usually, the fraud detection method in utility companies uses the consumption information, the economic activity, the geographic location, the active/reactive ration and the contracted power. This paper proposes a combined text mining and neural networks to increase the efficiency in NonTechnical Losses (NTLs) detection methods which was previously applied. This proposed framework proposes to collect all the information that normally cannot be treated with traditional methods. This framework is part of a research project. This project is done in collaboration with Endesa, one of the most important power distribution companies of Europe. Currently, the proposed framework is in the test stage and it uses real cases.
Tamaño: 819.9Kb
Formato: PDF

URI: http://hdl.handle.net/11441/23494

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