NILM applications: Literature review of learning approaches, recent developments and challenges
This paper presents a critical approach to the non-intrusive load monitoring (NILM) problem,
by thoroughly reviewing the experimental framework of both legacy and state-of-the-art …
by thoroughly reviewing the experimental framework of both legacy and state-of-the-art …
[HTML][HTML] A non-intrusive load monitoring algorithm based on multiple features and decision fusion
With the large-scale deployment of smart meters and wide application of various machine
learning algorithms, non-intrusive load monitoring (NILM) has attracted the attention of …
learning algorithms, non-intrusive load monitoring (NILM) has attracted the attention of …
An image based approach of energy signal disaggregation using artificial intelligence
M Senarathna, M Herath… - 2021 IEEE 16th …, 2021 - ieeexplore.ieee.org
Non-Intrusive Load Monitoring (NILM) is the real-time monitoring of energy consumption
data of individual appliances through the decomposition of composite energy signal …
data of individual appliances through the decomposition of composite energy signal …
Non-intrusive load disaggregation based on deep learning and multi-feature fusion
Non-intrusive load monitoring (NILM) is an important part of smart grid. In recent years, the
deep learning method has been widely used in non-intrusive load dis-aggregation, but most …
deep learning method has been widely used in non-intrusive load dis-aggregation, but most …
An Image-Based Disaggregation Study of Time Series Energy Data Using Gramian Angular Field
Non-intrusive Load Monitoring (NILM) proves effective in disaggregating energy
consumption data for individual household appliances. Traditional NILM techniques rely on …
consumption data for individual household appliances. Traditional NILM techniques rely on …
Appliance Anomaly Detection as NILM Extention
M Herath, T Thilakanayake… - 2023 IEEE PES 15th …, 2023 - ieeexplore.ieee.org
The demand for and use of residential electrical appliances has increased rapidly in recent
years, as people seek a more comfortable life. Consequently, the number of faults and …
years, as people seek a more comfortable life. Consequently, the number of faults and …
Novel Image Based Method Using VI Curves with Aggregate Energy Data for Non-Intrusive Load Monitoring Applications
PML Liyanage, GM Herath… - … on Advancements in …, 2022 - ieeexplore.ieee.org
The emerging energy crises allow consumers to be concerned with the energy consumption
of their appliances. Consumption data of individual appliances as opposed to the entire …
of their appliances. Consumption data of individual appliances as opposed to the entire …
[DOC][DOC] 1 Sri Lanka Institute of Information Technology, Malabe, Sri Lanka 2 University of Waterloo, Waterloo, ON, Canada
I Dhanawansa, GM Herath, TD Thilakanayake… - researchgate.net
Abstract The use of Convolutional Neural Networks (CNN) in the field of Non-Instructive
Load Monitoring (NILM) for the disaggregation of energy signals is a relatively new field in …
Load Monitoring (NILM) for the disaggregation of energy signals is a relatively new field in …