NILM applications: Literature review of learning approaches, recent developments and challenges

GF Angelis, C Timplalexis, S Krinidis, D Ioannidis… - Energy and …, 2022 - Elsevier
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 …

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 …

An electrical load measurements dataset of United Kingdom households from a two-year longitudinal study

D Murray, L Stankovic, V Stankovic - Scientific data, 2017 - nature.com
Smart meter roll-outs provide easy access to granular meter measurements, enabling
advanced energy services, ranging from demand response measures, tailored energy …

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 …

Non-intrusive load disaggregation using graph signal processing

K He, L Stankovic, J Liao… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
With the large-scale roll-out of smart metering worldwide, there is a growing need to account
for the individual contribution of appliances to the load demand. In this paper, we design a …

[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 …

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 …

On a training-less solution for non-intrusive appliance load monitoring using graph signal processing

B Zhao, L Stankovic, V Stankovic - IEEE Access, 2016 - ieeexplore.ieee.org
With ongoing large-scale smart energy metering deployments worldwide, disaggregation of
a household's total energy consumption down to individual appliances using analytical …

Application of load monitoring in appliances' energy management–A review

I Abubakar, SN Khalid, MW Mustafa, H Shareef… - … and Sustainable Energy …, 2017 - Elsevier
Energy monitoring is one of the important aspects of the energy management, as such there
is a need to monitor the power consumption of a premises before planning some of the …

Bayesian-optimized bidirectional LSTM regression model for non-intrusive load monitoring

M Kaselimi, N Doulamis, A Doulamis… - ICASSP 2019-2019 …, 2019 - ieeexplore.ieee.org
In this paper, a Bayesian-optimized bidirectional Long Short-Term Memory (LSTM) method
for energy disaggregation, is introduced. Energy disaggregation, or Non-Intrusive Load …