Towards trustworthy energy disaggregation: A review of challenges, methods, and perspectives for non-intrusive load monitoring

M Kaselimi, E Protopapadakis, A Voulodimos… - Sensors, 2022 - mdpi.com
Non-intrusive load monitoring (NILM) is the task of disaggregating the total power
consumption into its individual sub-components. Over the years, signal processing and …

Electric energy disaggregation via non-intrusive load monitoring: A state-of-the-art systematic review

S Dash, NC Sahoo - Electric Power Systems Research, 2022 - Elsevier
Appliance energy consumption tracking in a building is one of the vital enablers of energy
and cost saving. An economical and viable solution would be to estimate individual …

Context aware energy disaggregation using adaptive bidirectional LSTM models

M Kaselimi, N Doulamis, A Voulodimos… - … on Smart Grid, 2020 - ieeexplore.ieee.org
Energy disaggregation, or Non-Intrusive Load Monitoring (NILM), describes various
processes aiming to identify the individual contribution of appliances, given the aggregate …

Wavenilm: A causal neural network for power disaggregation from the complex power signal

A Harell, S Makonin, IV Bajić - ICASSP 2019-2019 IEEE …, 2019 - ieeexplore.ieee.org
Non-intrusive load monitoring (NILM) helps meet energy conservation goals by estimating
individual appliance power usage from a single aggregate measurement. Deep neural …

[HTML][HTML] Effective non-intrusive load monitoring of buildings based on a novel multi-descriptor fusion with dimensionality reduction

Y Himeur, A Alsalemi, F Bensaali, A Amira - Applied Energy, 2020 - Elsevier
Recently, a growing interest has been dedicated towards develo** and implementing low-
cost energy efficiency solutions in buildings. Accordingly, non-intrusive load monitoring has …

Sequence-to-sequence load disaggregation using multiscale residual neural network

G Zhou, Z Li, M Fu, Y Feng, X Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
With the increased demand on economy and efficiency of measurement technology,
nonintrusive load monitoring (NILM) has received more and more attention as a cost …

Multi-channel recurrent convolutional neural networks for energy disaggregation

M Kaselimi, E Protopapadakis, A Voulodimos… - IEEE …, 2019 - ieeexplore.ieee.org
Power consumption signals of household appliances are characterized by randomly
occurring events (eg switch-on events), making timeseries modeling a demanding process …

Nonintrusive load monitoring using an LSTM with feedback structure

H Hwang, S Kang - IEEE Transactions on Instrumentation and …, 2022 - ieeexplore.ieee.org
Many non-intrusive load monitoring (NILM) studies use high-frequency data to classify the
device's ON/OFF state. However, these approaches cannot be applied in real-world …

Artificial bee colony optimization based non-intrusive appliances load monitoring technique in a smart home

S Ghosh, D Chatterjee - IEEE Transactions on Consumer …, 2021 - ieeexplore.ieee.org
Recent advances of energy management system in a smart home can lead to load
monitoring of electrical appliances for energy saving and reduction of electricity bill. Thus …

Improving residential load disaggregation for sustainable development of energy via principal component analysis

A Moradzadeh, O Sadeghian, K Pourhossein… - Sustainability, 2020 - mdpi.com
The useful planning and operation of the energy system requires a sustainability
assessment of the system, in which the load model adopted is the most important factor in …