Published October 29, 2019
| Version v1
Poster
Open
EMD and Gradient Boosting Regression for NILM (Energy Disaggregation)
- 1. Information Technologies Institute/ The Centre for Research and Technology Hellas
Description
Abstract: In this study a novel appliance load estimation in a non-intrusive way is presented. The proposed algorithm includes signal processing techniques such as filtering and Empirical Mode Decomposition (EMD) which is used to decompose random noise from the power consumption data collected from the smart meter. Lag features that capture the variance of the data across time are utilized. Experimental results which showcase the effectiveness of the suggested method are also presented.
Files
AI_CON_poster_presentation_CERTH.pdf
Files
(1.4 MB)
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