Emerging trends for energy monitoring as in Smart Energy Systems require intelligent solutions for appliances' identification. Non-intrusive load monitoring (NILM) systems can extract features from a single point for acquisition of aggregate consumption of the electrical network. The whole-consumption signal is contaminated with noise, which hinders successful load disambiguation of individual appliances. In this work, we propose a novel approach to denoise a signal based on the techniques of Embedding, Wavelet Shrinkage and Diagonal Averaging. The embedding stage transforms the one-dimensional signal into a sequence of lagged vectors. These vectors are denoised using wavelet decomposition, after choosing the most suitable basis function. Finally, the denoised signal is obtained by taking the diagonal averages of the resultant matrix. Our approach is compared to Wavelet Decomposition and Singular Spectrum Analysis methods for electrical signal denoising. The results are very favorable since they yield better performance as highlighted by the statistical tests performed.
Keywords
Smart Energy Systems, Signal Denoising, Wavelet Transform, Singular Spectrum Analysis
Subject
Signal Denoising, Non-Intrusive Load Monitoring Systems
Conference
Proc of Intelligent Systems Design and Applications (ISDA 2011) pp.784-789, 2011 (DOI: 10.1109/ISDA.2011.6121752), November 2011
Cited by
Year 2014 : 1 citations
Belley, C.; Gaboury, S.; Bouchard, B.; Bouzouane, A.;
"An efficient and inexpensive method for activity recognition within a smart home based on load signatures of appliances", Pervasive and Mobile Computing, Vo. 12, June 2014, Pages 58–78 (available on-line since March 2013)
Year 2013 : 3 citations
Belley, C.; Gaboury, S.; Bouchard, B.; Bouzouane, A.;
"An efficient and inexpensive method for activity recognition within a smart home based on load signatures of appliances", Pervasive and Mobile Computing, 2013 (available on-line March 2013)
http://dx.doi.org/10.1016/j.pmcj.2013.02.002
Wong, Y.F., Ahmet Sekercioglu, Y., Drummond, T., Wong, V.S., "Recent approaches to non-intrusive load monitoring techniques in residential settings", IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG), 2013, DOI: 10.1109/CIASG.2013.6611501
Wong, V.S., Wong, Y.F, Drummond, T., Ahmet Sekercioglu, Y., "A fast multiple appliance detection algorithm for non-int 10.1109/CIASG.2013.6611502rusive load monitoring", IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG), 2013, DOI:
