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] Next-generation energy systems for sustainable smart cities: Roles of transfer learning
Smart cities attempt to reach net-zero emissions goals by reducing wasted energy while
improving grid stability and meeting service demand. This is possible by adopting next …
improving grid stability and meeting service demand. This is possible by adopting next …
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 …
has led to growing electric power needs through the increased number of electrical …
Transfer learning for non-intrusive load monitoring
M D'Incecco, S Squartini… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Non-intrusive load monitoring (NILM) is a technique to recover source appliances from only
the recorded mains in a household. NILM is unidentifiable and thus a challenge problem …
the recorded mains in a household. NILM is unidentifiable and thus a challenge problem …
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 …
neural networks to disaggregate appliances from low frequency data, ie, data with sampling …
Towards trustworthy energy disaggregation: A review of challenges, methods, and perspectives for non-intrusive load monitoring
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 …
consumption into its individual sub-components. Over the years, signal processing and …
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 …
observing power usage in buildings. It tackles several challenges in transitioning into a more …
[HTML][HTML] An active learning framework for the low-frequency Non-Intrusive Load Monitoring problem
T Todic, V Stankovic, L Stankovic - Applied Energy, 2023 - Elsevier
With the widespread deployment of smart meters worldwide, quantification of energy used
by individual appliances via Non-Intrusive Load Monitoring (NILM), ie, virtual submetering, is …
by individual appliances via Non-Intrusive Load Monitoring (NILM), ie, virtual submetering, is …
Context aware energy disaggregation using adaptive bidirectional LSTM models
Energy disaggregation, or Non-Intrusive Load Monitoring (NILM), describes various
processes aiming to identify the individual contribution of appliances, given the aggregate …
processes aiming to identify the individual contribution of appliances, given the aggregate …
Adaptive weighted recurrence graphs for appliance recognition in non-intrusive load monitoring
A Faustine, L Pereira… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
To this day, hyperparameter tuning remains a cumbersome task in Non-Intrusive Load
Monitoring (NILM) research, as researchers and practitioners are forced to invest a …
Monitoring (NILM) research, as researchers and practitioners are forced to invest a …