EMD and Gradient Boosting Regression for NILM (Energy Disaggregation)

Main Authors: Timplalexis, Christos, Krinidis, Stelios, Ioannidis, Dimosthenis, Tzovaras, Dimitrios
Format: Proceeding poster eJournal
Terbitan: , 2019
Online Access: https://zenodo.org/record/3706433
Daftar Isi:
  • 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.