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Appl. Sci. 2018, 8(4), 554; https://doi.org/10.3390/app8040554

Low-Rate Non-Intrusive Load Disaggregation with Graph Shift Quadratic Form Constraint

School of Electric and Electronic Engineering, North China Electric Power University, Changping District, Beijing 102206, China
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Received: 16 March 2018 / Revised: 26 March 2018 / Accepted: 26 March 2018 / Published: 4 April 2018
(This article belongs to the Section Energy)
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Abstract

Non-intrusive load monitoring (NILM) is a cost-effective technique for extracting device-level energy consumption information by monitoring the aggregated signal at the entrance of the electric power. With the large-scale deployment of smart metering, NILM should ideally be designed to operate purely on the low-rate data from smart meters. In this paper, an approach based on Graph Shift Quadratic Form constrained Active Power Disaggregation (GSQF-APD) is proposed, which is built upon matrix factorization and introduces graph shift quadratic form constraint according to piecewise smoothness of the power signal. In addition, a two-step iterative optimization method is designed to solve this problem. The first step minimizes the regularization term to find the signal with minimum variation, and then the second step uses the simulated annealing (SA) algorithm to iteratively minimize the objective function and constraint based on the total graph variation minimizer. Using one open-access dataset, the strength of GSQF-APD is demonstrated through three sets of experiments. The numerical results show the superior performance of GSQF-APD, with Graph Laplacian Quadratic Form constrained Active Power Disaggregation (GLQF-APD) and the state-of-the-art NILM methods as benchmarks. View Full-Text
Keywords: non-intrusive load monitoring; load disaggregation; matrix factorization; graph shift quadratic form constrained non-intrusive load monitoring; load disaggregation; matrix factorization; graph shift quadratic form constrained
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Qi, B.; Liu, L.; Wu, X. Low-Rate Non-Intrusive Load Disaggregation with Graph Shift Quadratic Form Constraint. Appl. Sci. 2018, 8, 554.

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