Dissertação

Rede neural convolucional aplicada à identificação de equipamentos residenciais para sistemas de monitoramento não-intrusivo de carga

This research presents the proposal of a new methodology for the identification of residential equipment in non-intrusive load monitoring systems. The system is based on a Convolutional Neural Network to classify residential equipment, which uses directly as inputs to the system, the transient power...

ver descrição completa

Autor principal: PENHA, Deyvison de Paiva
Grau: Dissertação
Idioma: por
Publicado em: Universidade Federal do Pará 2018
Assuntos:
Acesso em linha: http://repositorio.ufpa.br/jspui/handle/2011/10063
Resumo:
This research presents the proposal of a new methodology for the identification of residential equipment in non-intrusive load monitoring systems. The system is based on a Convolutional Neural Network to classify residential equipment, which uses directly as inputs to the system, the transient power signal data of 7 equipment obtained at the moment they are connected in a residence. The methodology was developed using data from a public database (REED) that presents data collected at a low frequency (1 Hz). The results obtained in the test database show an accuracy of more than 90%, indicating that the proposed system is capable of performing the task of identification. In addition, the results presented are considered satisfactory when compared with the results already presented in the literature for the problem in question.