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Non intrusive load monitoring for demand side management
Energy Informatics, 2020 In the context of a pilot project, the Lugaggia Innovation Community (LIC), we address the problem of non-intrusive load monitoring for the purpose of demand side management on low voltage grids in presence of distributed power generation (photovoltaic).
Matteo Salani +6 more
doaj +1 more source
An adaptive lightweight seq2subseq model for non‐intrusive load monitoring
IET Generation, Transmission & Distribution, 2022 Non‐intrusive load monitoring (NILM) is an important technology for deeply mining consumers' internal electricity consumption information, which can improve the level of awareness of the load and significantly improve the demand‐side management ...
Xiaomei Yang +4 more
doaj +1 more source
An Implementation Framework Overview of Non-Intrusive Load Monitoring
Journal of Sustainable Development of Energy, Water and Environment Systems, 2023 The implementation of non-intrusive load monitoring has gained significant attention as a promising solution for disaggregating and identifying individual appliances' energy consumption within households and commercial buildings. The issue at the core of
Omar Al-Khadher +4 more
doaj +1 more source
Online non-intrusive load monitoring: A review
Energy NexusSignificant progress has been achieved in managing energy consumption in the residential sector in recent years. However, the industrial sector requires better coverage due to its substantial challenges.
David Cruz-Rangel +2 more
doaj +3 more sources
ELECTRIcity: An Efficient Transformer for Non-Intrusive Load Monitoring. [PDF]
Sensors (Basel), 2022 Non-Intrusive Load Monitoring (NILM) describes the process of inferring the consumption pattern of appliances by only having access to the aggregated household signal. Sequence-to-sequence deep learning models have been firmly established as state-of-the-
Sykiotis S +3 more
europepmc +2 more sources
DRA-net: A new deep learning framwork for non-intrusive load disaggregation
Frontiers in Energy Research, 2023 The non-intrusive load decomposition method helps users understand the current situation of electricity consumption and reduce energy consumption. Traditional methods based on deep learning are difficult to identify low usage appliances, and are prone to
Fang Yu +3 more
doaj +1 more source
Non-intrusive model derivation [PDF]
Proceedings of the Seventh International Conference on Future Energy Systems, 2016 A variety of energy management and analytics techniques rely on models of the power usage of a device over time. Unfortunately, the models employed by these techniques are often highly simplistic, such as modeling devices as simply being on with a fixed power usage or off and consuming little power. As we show, even the power usage of relatively simple
Srinivasan Iyengar +2 more
openaire +1 more source
Non-intrusive load decomposition based on CNN-LSTM hybrid deep learning model [PDF]
Energy Reports, 2021 With the rapid development of science and technology, the problem of energy load monitoring and decomposition of electrical equipment has been receiving widespread attention from academia and industry.
Xinxin Zhou, Jing Feng, Yang Li
semanticscholar +1 more source
Energies, 2023 In recent years, electrical fires caused by arc faults have been increasing, seriously affecting the safety of people’s lives and property. Considering the complex arc fault characteristics of actual low-voltage users, the non-intrusive arc fault ...
Wenqian Jiang +5 more
doaj +1 more source
Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: comparison with linear subspace techniques [PDF]
Advances in Water Resources, 2021 Natural convection in porous media is a highly nonlinear multiphysical problem relevant to many engineering applications (e.g., the process of $\mathrm{CO_2}$ sequestration).
T. Kadeethum +5 more
semanticscholar +1 more source