Watt's up at home? Smart meter data analytics from a consumer-centric perspective
The key advantage of smart meters over traditional metering devices is their ability to
transfer consumption information to remote data processing systems. Besides enabling the …
transfer consumption information to remote data processing systems. Besides enabling the …
Improving non-intrusive load disaggregation through an attention-based deep neural network
V Piccialli, AM Sudoso - Energies, 2021 - mdpi.com
Energy disaggregation, known in the literature as Non-Intrusive Load Monitoring (NILM), is
the task of inferring the power demand of the individual appliances given the aggregate …
the task of inferring the power demand of the individual appliances given the aggregate …
Improved appliance classification in non-intrusive load monitoring using weighted recurrence graph and convolutional neural networks
A Faustine, L Pereira - Energies, 2020 - mdpi.com
Appliance recognition is one of the vital sub-tasks of NILM in which a machine learning
classier is used to detect and recognize active appliances from power measurements. The …
classier is used to detect and recognize active appliances from power measurements. The …
New design of a supervised energy disaggregation model based on the deep neural network for a smart grid
İH Çavdar, V Faryad - Energies, 2019 - mdpi.com
Energy management technology of demand-side is a key process of the smart grid that
helps achieve a more efficient use of generation assets by reducing the energy demand of …
helps achieve a more efficient use of generation assets by reducing the energy demand of …
Sequence to point learning based on an attention neural network for nonintrusive load decomposition
M Yang, X Li, Y Liu - Electronics, 2021 - mdpi.com
Nonintrusive load monitoring (NILM) analyzes only the main circuit load information with an
algorithm to decompose the load, which is an important way to help reduce energy usage …
algorithm to decompose the load, which is an important way to help reduce energy usage …
A deep recurrent neural network for non-intrusive load monitoring based on multi-feature input space and post-processing
Non-intrusive load monitoring (NILM) is a process of estimating operational states and
power consumption of individual appliances, which if implemented in real-time, can provide …
power consumption of individual appliances, which if implemented in real-time, can provide …
Non-intrusive load monitoring based on novel transient signal in household appliances with low sampling rate
TTH Le, H Kim - Energies, 2018 - mdpi.com
Nowadays climate change problems have been more and more concerns and urgent in the
real world. Especially, the energy power consumption monitoring is a considerate trend …
real world. Especially, the energy power consumption monitoring is a considerate trend …
On the use of concentrated time–frequency representations as input to a deep convolutional neural network: Application to non intrusive load monitoring
Since decades past, time–frequency (TF) analysis has demonstrated its capability to
efficiently handle non-stationary multi-component signals which are ubiquitous in a large …
efficiently handle non-stationary multi-component signals which are ubiquitous in a large …
Comparative study on load monitoring approaches
LW Tokam, SS Ouro-Djobo - Applied Sciences, 2023 - mdpi.com
Without an appropriate monitoring system, the condition/state of electrical
appliances/devices in operation in households cannot be fully assessed, resulting in …
appliances/devices in operation in households cannot be fully assessed, resulting in …
Comparative evaluation of non-intrusive load monitoring methods using relevant features and transfer learning
Non-Intrusive Load Monitoring (NILM) refers to the analysis of the aggregated current and
voltage measurements of Home Electrical Appliances (HEAs) recorded by the house …
voltage measurements of Home Electrical Appliances (HEAs) recorded by the house …