Non-intrusive load monitoring: A review

PA Schirmer, I Mporas - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
The rapid development of technology in the electrical energy sector within the last 20 years
has led to growing electric power needs through the increased number of electrical …

Review on deep neural networks applied to low-frequency nilm

P Huber, A Calatroni, A Rumsch, A Paice - Energies, 2021 - mdpi.com
This paper reviews non-intrusive load monitoring (NILM) approaches that employ deep
neural networks to disaggregate appliances from low frequency data, ie, data with sampling …

Recent trends of smart nonintrusive load monitoring in buildings: A review, open challenges, and future directions

Y Himeur, A Alsalemi, F Bensaali… - … Journal of Intelligent …, 2022 - Wiley Online Library
Smart nonintrusive load monitoring (NILM) represents a cost‐efficient technology for
observing power usage in buildings. It tackles several challenges in transitioning into a more …

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 …

Non-intrusive load monitoring by voltage–current trajectory enabled transfer learning

Y Liu, X Wang, W You - IEEE Transactions on Smart Grid, 2018 - ieeexplore.ieee.org
Non-intrusive load monitoring (NILM) is a technique for analyzing changes in the voltage
and current flowing through the main feeder and determining the appliances in operation as …

Electricity, water, and natural gas consumption of a residential house in Canada from 2012 to 2014

S Makonin, B Ellert, IV Bajić, F Popowich - Scientific data, 2016 - nature.com
With the cost of consuming resources increasing (both economically and ecologically),
homeowners need to find ways to curb consumption. The Almanac of Minutely Power …

An event-driven convolutional neural architecture for non-intrusive load monitoring of residential appliance

D Yang, X Gao, L Kong, Y Pang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Nowadays, the advancement of non-intrusive load monitoring (NILM) is hastened by the
everincreasing requirements for smart power utilization and demand side management …

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 …

Non-intrusive load monitoring by using active and reactive power in additive Factorial Hidden Markov Models

R Bonfigli, E Principi, M Fagiani, M Severini… - Applied Energy, 2017 - Elsevier
Non-intrusive load monitoring (NILM) is the task of determining the appliances individual
contributions to the aggregate power consumption by using a set of electrical parameters …