A voltage and current measurement dataset for plug load appliance identification in households [PDF]
, 2020 This paper presents the Plug-Load Appliance Identification Dataset (PLAID), a labelled dataset containing records of the electrical voltage and current of domestic electrical appliances obtained at a high sampling frequency (30 kHz). The dataset contains
Berges, Mario +8 more
core +2 more sources
Instantaneous active and reactive load signature applied in non‐intrusive load monitoring systems
IET Smart Grid, 2021 The performance of non‐intrusive load monitoring (NILM) systems heavily depends on the uniqueness of the load signature extracted from the electrical appliances. Different load signatures have been proposed.
Ricardo Brito +5 more
doaj +1 more source
Torch-NILM: An Effective Deep Learning Toolkit for Non-Intrusive Load Monitoring in Pytorch
Energies, 2022 Non-intrusive load monitoring is a blind source separation task that has been attracting significant interest from researchers working in the field of energy informatics. However, despite the considerable progress, there are a very limited number of tools and libraries dedicated to the problem of energy disaggregation. Herein, we report the development
Nikolaos Virtsionis Gkalinikis +2 more
openaire +2 more sources
Incorporating appliance usage patterns for non-intrusive load monitoring and load forecasting [PDF]
, 2017 This paper proposes a novel Non-Intrusive Load Monitoring (NILM) method which incorporates appliance usage patterns (AUPs) to improve performance of active load identi- fication and forecasting.
Dinesh, C. +4 more
core +1 more source
Optimising Parameters in Recurrence Quantification Analysis of Smart Energy Systems [PDF]
, 2018 Recurrence Quantification Analysis (RQA) can help to detect significant events and phase transitions of a dynamical system, but choosing a suitable set of parameters is crucial for the success.
Giasemidis, Georgios +1 more
core +3 more sources
Toward Robust Non-Intrusive Load Monitoring via Probability Model Framed Ensemble Method
Sensors, 2021 As a pivotal technological foundation for smart home implementation, non-intrusive load monitoring is emerging as a widely recognized and popular technology to replace the sensors or sockets networks for the detailed household appliance monitoring.
Yu Liu +5 more
doaj +1 more source
Non-Intrusive Load Monitoring Based on Swin-Transformer with Adaptive Scaling Recurrence Plot
Energies, 2022 Non-Intrusive Load Monitoring (NILM) is an effective energy consumption analysis technology, which just requires voltage and current signals on the user bus.
Yongtao Shi +3 more
doaj +1 more source
A comparative study of low sampling non intrusive load dis-aggregation [PDF]
, 2016 International audienceNon-intrusive load monitoring (NILM) deals with the identification and subsequent energy estimation of the individual appliances from the smart meter data.
Bacha, Seddik +5 more
core +2 more sources
Energies, 2012 Energy management systems strive to use energy resources efficiently, save energy, and reduce carbon output. This study proposes transient feature analyses of the transient response time and transient energy on the power signatures of non-intrusive ...
Hsueh-Hsien Chang
doaj +1 more source
MC-NILM: A Multi-Chain Disaggregation Method for NILM
Energies, 2021 Non-intrusive load monitoring (NILM) is an approach that helps residents obtain detailed information about household electricity consumption and has gradually become a research focus in recent years.
Hao Ma +4 more
doaj +1 more source