Results 31 to 40 of about 24,815 (274)
IEEE Access, 2018 There are, in general, two methods of load monitoring which are intrusive load monitoring and non-intrusive load monitoring (NILM). The NILM method has attracted considerable research interests, since it only requires a set of voltage and current sensors
Victor Andrean +4 more
doaj +1 more source
A Scoping Review of Energy Load Disaggregation
, 2023 Energy load disaggregation can contribute to balancing power grids by enhancing the effectiveness of demand-side management and promoting electricity-saving behavior through increased consumer awareness. However, the field currently lacks a comprehensive overview. To address this gap, this paper con-ducts a scoping review of load disaggregation domains,
Balázs András Tolnai +2 more
openaire +3 more sources
Prior Day Effect in Forecasting Daily Natural Gas Flow from Monthly Data [PDF]
, 2018 Many needs exist in the energy industry where measurement is monthly yet daily values are required. The process of disaggregation of low frequency measurement to higher frequency values has been presented in this literature.
Brown, Ronald H. +2 more
core +2 more sources
Load Demand Disaggregation Based on Simple Load Signature and User's Feedback
Energy Procedia, 2015 AbstractA detailed and on-line knowledge of the electrical load demand by the users is a critical issue for an effective and responsive deployment of home/building energy management. An approach based on the application of Non Intrusive Appliance Load Monitoring (NIALM) techniques copes with the goal of disaggregating composite loads; but to get a high
Amenta V, TINA, Giuseppe Marco
openaire +3 more sources
Image-based mains signal disaggregation and load recognition [PDF]
Complex & Intelligent Systems, 2021 AbstractThe mains signal is a complex fusion of various electrical equipment load signals in a building. In the non-intrusive load monitoring recognition, our main aim is to be able to extract as much load features as possible from the complex aggregate mains signal in a simpler way through a computer vision-based approach as opposed to the powers ...
Liston Matindife +2 more
openaire +2 more sources
Energies, 2023 Nonintrusive load monitoring (NILM) is a process that disaggregates individual energy consumption based on the total energy consumption. In this study, an energy disaggregation model was developed and verified using an algorithm based on a recurrent ...
Myeung-Hun Lee, Hyeun-Jun Moon
doaj +1 more source
Municipal expected annual loss as an indicator to develop seismic risk maps in Italy [PDF]
, 2019 This work presents a risk-targeted indicator called Municipal Expected Annual Loss (MEAL) for a quantitative estimation of the seismic risk at territorial level.
Faleschini, Flora +4 more
core +1 more source
Research on lightweight non-intrusive load disaggregation model for edge computing
Diance yu yibiaoAiming at the problem that the current non-intrusive load disaggregation model based on deep learning is difficult to deploy at the edge with limited computing resources, this paper proposes a lightweight non-intrusive load disaggregation model based on ...
YE Canshen, LUO Dehan, HE Jiafeng
doaj +1 more source
Load Hiding of Household's Power Demand [PDF]
, 2014 With the development and introduction of smart metering, the energy information for costumers will change from infrequent manual meter readings to fine-grained energy consumption data.
Egarter, Dominik +2 more
core +1 more source
Neural Load Disaggregation: Meta-Analysis, Federated Learning and Beyond
Energies, 2023 Non-intrusive load monitoring (NILM) techniques are central techniques to achieve the energy sustainability goals through the identification of operating appliances in the residential and industrial sectors, potentially leading to increased rates of ...
Hafsa Bousbiat +4 more
doaj +1 more source