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http://dx.doi.org/10.5762/KAIS.2017.18.4.34

A Study on the Analysis of Electric Energy Pattern Based on Improved Real Time NIALM  

Jeong, Han-Sang (Division of Computer Engineering, Gachon University)
Sung, Kyung-Sang (Itnade Co. ltd.)
Oh, Hae-Seok (Division of Computer Engineering, Gachon University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.18, no.4, 2017 , pp. 34-42 More about this Journal
Abstract
Since existing nonintrusive appliance load monitoring (NIALM) studies assume that voltage fluctuations are negligible for load identification, and do not affect the identification results, the power factor or harmonic signals associated with voltage are generally not considered parameters for load identification, which limits the application of NIALM in the Smart Home sector. Experiments in this paper indicate that the parameters related to voltage and the characteristics of harmonics should be used to improve the accuracy and reliability of the load monitoring system. Therefore, in this paper, we propose an improved NIALM method that can efficiently analyze the types of household appliances and electrical energy usage in a home network environment. The proposed method is able to analyze the energy usage pattern by analyzing operation characteristics inherent to household appliances using harmonic characteristics of some household appliances as recognition parameters. Through the proposed method, we expect to be able to provide services to the smart grid electric power demand management market and increase the energy efficiency of home appliances actually operating in a home network.
Keywords
energy management systems; Fourier transform; feature analysis; harmonic wave; non-intrusive load monitoring; smart grid; wavelet transform;
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