Identificação Não-Invasiva de Cargas Elétricas Baseado em Estatísticas de Ordem Superior (Non-Intrusive Appliance Load Identification Based on Higher-Order Statistics)

Juan Diego Silva Guedes (juandiegoguedes@yahoo.com.br)2, Danton Diego Ferreira (danton@deg.ufla.br)1, Bruno Henrique Groenner Barbosa (brunohb@deg.ufla.br)1, Carlos Augusto Duque (carlos.duque@ufjf.edu.br)2, Augusto Santiago Cerqueira (augusto.santiago@ufjf.edu.br)2


1Universidade Federal de Lavras
2Universidade Federal de Juiz de Fora

This paper appears in: Revista IEEE América Latina

Publication Date: Oct. 2015
Volume: 13,   Issue: 10 
ISSN: 1548-0992


Abstract:
This paper presents a new method based on Higher-order Statistics for non-intrusive residential electrical load identification. Basically, the proposed method extracts cumulants of second and fourth order from the electric current signal of the residential electrical loads and presents these cumulants to a previously trained artificial neural network for classification. The neural network output identifies the residential electric load class of the processed signal. This study considered eleven different classes of residential electrical loads. Results were carried out from experimental electric signals and the achieved overall performance was over to 97%.

Index Terms:
Non-intrusive monitoring, electrical loads, smart grids   


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