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Federated learning-enhanced generative models for non-intrusive load monitoring in smart homes. [PDF]
Sci RepLu Y, Xu S, Liu Y, Jiang X.
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Proceedings of the 5th International Workshop on Non-Intrusive Load Monitoring, 2020
Over the years, an enormous amount of research has been exploring Deep Neural Networks (DNN), particularly Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) for estimating the energy consumption of appliances from a single point source such as smart meters - Non-Intrusive Load Monitoring (NILM).
Anthony Faustine +3 more
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Over the years, an enormous amount of research has been exploring Deep Neural Networks (DNN), particularly Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) for estimating the energy consumption of appliances from a single point source such as smart meters - Non-Intrusive Load Monitoring (NILM).
Anthony Faustine +3 more
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Proceedings of the 5th International Workshop on Non-Intrusive Load Monitoring, 2020
In the context of residential Non-intrusive load monitoring (NILM), the usual service deployment process consists of collecting data from a metering device to the cloud, run algorithms on the cloud and then display results in a Web front or in an App. This approach comes with two major problems: on the one hand, important resources are allocated to the
Shamim Ahmed, Marc Bons
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In the context of residential Non-intrusive load monitoring (NILM), the usual service deployment process consists of collecting data from a metering device to the cloud, run algorithms on the cloud and then display results in a Web front or in an App. This approach comes with two major problems: on the one hand, important resources are allocated to the
Shamim Ahmed, Marc Bons
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eeRIS-NILM: An Open Source, Unsupervised Baseline for Real-Time Feedback Through NILM
2020 55th International Universities Power Engineering Conference (UPEC), 2020Awareness of residential consumers about the impact of their behavior on electricity consumption is an important determinant for energy efficiency and for their participation in electricity markets. Non-intrusive load monitoring (NILM) has been proposed as a cost-effective approach for providing detailed information about the consumption of individual ...
Christos Diou, Georgios Andreou
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MO-NILM: A multi-objective evolutionary algorithm for NILM classification
Energy and Buildings, 2019Abstract Non-intrusive load monitoring (NILM) techniques estimate the consumption of individual appliances in a household or facility, based on readings of a centralized meter. In this work a new method for multi-dimensional NILM signals is proposed—the Multi-objective NILM (MO-NILM).
Ram Machlev +3 more
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2023
This chapter introduces the technology Non-Intrusive Load Monitoring, a method for detecting individual devices from an overall signal. Non-Intrusive Load Monitoring is the research area and technology behind the third word in Smart Meter Inclusive. Using a smart meter as a basis and recognizing devices from the power profile is not a new idea but is ...
Weißhaar, Daniel +5 more
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This chapter introduces the technology Non-Intrusive Load Monitoring, a method for detecting individual devices from an overall signal. Non-Intrusive Load Monitoring is the research area and technology behind the third word in Smart Meter Inclusive. Using a smart meter as a basis and recognizing devices from the power profile is not a new idea but is ...
Weißhaar, Daniel +5 more
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Unsupervised learning procedure for NILM applications
2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON), 2020In a domestic context, NILM applications (NonIntrusive Load Monitoring) allow users to know their electric consumption per appliance without having to install sensors for each appliance in their house. The aim of this paper is to present a new generic method allowing to discover the different appliances present in a house.
Gilles Jacobs, Pierre Henneaux
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IEEE Sensors Journal, 2022
In the subsequent decades, the increasing energy will demand renewable resources and intelligent solutions for managing consumption. In this sense, Non-Intrusive Load Monitoring (NILM) techniques detail consumption information for users, allowing better electric power management and avoiding energy losses.
Lucas da Silva Nolasco +2 more
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In the subsequent decades, the increasing energy will demand renewable resources and intelligent solutions for managing consumption. In this sense, Non-Intrusive Load Monitoring (NILM) techniques detail consumption information for users, allowing better electric power management and avoiding energy losses.
Lucas da Silva Nolasco +2 more
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Unsupervised NILM Implementation Using Odd Harmonic Currents
2021 56th International Universities Power Engineering Conference (UPEC), 2021In this paper, an unsupervised non-intrusive load monitoring approach is proposed in order to encounter the disaggregation problem for Non-Intrusive Load Monitoring (NILM) methodologies, using odd harmonic current amplitudes. The problem has been contemplated as a multi-class multi-label one and for the combinations examined the number of appliances ...
Petros G. Papageorgiou +3 more
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