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A Non Intrusive Low Cost Kit for Electric Power Measuring and Energy Disaggregation
Author(s) -
Randy Quindai,
Bruno M. Barbosa,
Charles M. P. Almeida,
Heitor S. Ramos,
Joel J. P. C. Rodrigues,
André L. L. Aquino
Publication year - 2018
Publication title -
journal of communications software and systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.191
H-Index - 13
eISSN - 1846-6079
pISSN - 1845-6421
DOI - 10.24138/jcomss.v14i1.447
Subject(s) - computer science , measure (data warehouse) , energy (signal processing) , power (physics) , variance (accounting) , electric power , phase (matter) , calibration , simulation , real time computing , algorithm , data mining , statistics , mathematics , physics , chemistry , accounting , organic chemistry , quantum mechanics , business
This article presents a kit to collect data of electric loads of single and three phases main power supply of a house and perform the energy disaggregation. To collect the data, we use sensors based on open magnetic core to measure the electromagnetic field induced by the current in the electric conducting wire in a non intrusive way. In particular, each sensor from the three-phase device wraps/encloses each phase without alignment. In order to calibrate the three-phase device, we present a method to calculate the neutral RMS without complex numbers using (Analysis of Variance) ANOVA and post hoc Tukey’s multiple comparison test to assert the differences of measures among phases. We managed to validate the method using a measure reference. Additionally, to perform the energy disaggregation, we use the NILMTK tool. This toll was used, initially, to compare disaggregation algorithms on many public datasets. We use in our system two disaggregation algorithms Combinatorial Optimization and Factorial Hidden Markov Model algorithms. The results show that is possible to collect and perform energy disaggregation through our embedded system.

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