Deep Learning Applications in non-intrusive load monitoring - Gaimes, Yousra (2022)
Within the frame of the project Non-Intrusive Load Monitoring for Intelligent Home Energy Management Systems, this work will present a deep learning application in non-intrusive load monitoring on a case study in a residential home in in Gambelas, Faro in the Algarve region south of Portugal. This work has for a goal to detect type 2 appliances in different houses. For the sake of this study, two models will be trained: - Convolutional Neural Network - Long Short-term Memory Recurrent Neural Network on three datasets: - UKDale - REDD - Data from the Portuguese private residential house from the project NILM for IHEMS.