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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A NILM Dataset for Cognitive Meters Based on Conservative Power Theory and Pattern Recognition Techniques

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Author(s):
Souza, Wesley A. [1] ; Marafao, Fernando P. [2] ; Liberado, Eduardo V. [2] ; Simoes, Marcelo G. [3] ; Da Silva, Luiz C. P. [1]
Total Authors: 5
Affiliation:
[1] Univ Campinas UNICAMP, Sch Elect & Comp Engn FEEC, Dept Energy & Syst DSE, Av Albert Einstein 400, BR-13083970 Campinas, SP - Brazil
[2] Univ Estadual Paulista UNESP, Inst Sci & Technol Sorocaba ICTS, Av Tres Marco 511, BR-18087180 Sorocaba, SP - Brazil
[3] Colorado Sch Mines, Dept Elect Engn, Golden, CO 80401 - USA
Total Affiliations: 3
Document type: Journal article
Source: JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS; v. 29, n. 6, p. 742-755, DEC 2018.
Web of Science Citations: 2
Abstract

This paper presents a novel dataset capable of classifying and disaggregating residential appliances for the development of smart or cognitive power meters. This novel dataset uses power indicators (also denoted as conformity factors) from the conservative power theory (CPT), which are calculated from measured voltage and current waveforms during the operation of residential loads. The association of CPT power indicators with suitable pattern recognition algorithms (PRA) and a power signature state machine provides proper identification of each appliance. So, the paper also presents a detailed evaluation of possible PRA for this application, especially the SVMsupport vector machine, OPFoptimum-path forest, MLPmultilayer perceptron, KNNK-nearest neighbor and DTdecision tree. All these algorithms have been compared regarding accuracy and computational time. Validation results point out that KNN would be the best choice for dealing with the proposed dataset, leading to an accuracy higher than 98%. (AU)

FAPESP's process: 12/19375-1 - Study of analysis and technologies techniques for the development of energy smartmeters with a focus on residential microgrids
Grantee:Wesley Angelino de Souza
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 16/08645-9 - Interdisciplinary research activities in electric smart grids
Grantee:João Bosco Ribeiro do Val
Support Opportunities: Research Projects - Thematic Grants