Results 1 to 10 of about 57,754 (187)
Energy Disaggregation Using Elastic Matching Algorithms. [PDF]
Entropy (Basel), 2020 In this article an energy disaggregation architecture using elastic matching algorithms is presented. The architecture uses a database of reference energy consumption signatures and compares them with incoming energy consumption frames using template ...
Schirmer PA, Mporas I, Paraskevas M.
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Neural Fourier Energy Disaggregation. [PDF]
Sensors (Basel), 2022 Deploying energy disaggregation models in the real-world is a challenging task. These models are usually deep neural networks and can be costly when running on a server or prohibitive when the target device has limited resources. Deep learning models are
Nalmpantis C +2 more
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2D Transformations of Energy Signals for Energy Disaggregation. [PDF]
Sensors (Basel), 2022 The aim of Non-Intrusive Load Monitoring is to estimate the energy consumption of individual electrical appliances by disaggregating the overall power consumption that has been sampled from a smart meter at a house or commercial/industrial building. Last
Schirmer PA, Mporas I.
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Variational Regression for Multi-Target Energy Disaggregation. [PDF]
Sensors (Basel), 2023 Non-intrusive load monitoring systems that are based on deep learning methods produce high-accuracy end use detection; however, they are mainly designed with the one vs. one strategy.
Virtsionis Gkalinikis N +2 more
europepmc +4 more sources
Robust energy disaggregation using appliance-specific temporal contextual information [PDF]
EURASIP Journal on Advances in Signal Processing, 2020 An extension of the baseline non-intrusive load monitoring approach for energy disaggregation using temporal contextual information is presented in this paper.
Pascal Alexander Schirmer +2 more
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Capturing High-Frequency Harmonic Signatures for NILM: Building a Dataset for Load Disaggregation. [PDF]
Sensors (Basel)Advanced Non-Intrusive Load Monitoring (NILM) research is important to help reduce energy consumption. Very-low-frequency approaches have traditionally faced challenges in separating appliance uses due to low discriminative information.
Dinar F, Paris S, Busvelle É.
europepmc +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
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Real-Time Energy Disaggregation Algorithm Based on Multi-Channels DCNN and Autoregressive Model
IEEE Access, 2022 Energy disaggregation refers to the process of obtaining the energy consumption of several appliances in a house by disaggregating the aggregate power consumption measured by an electrical meter.
Lintao Deng +4 more
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Device and Time Invariant Features for Transferable Non-Intrusive Load Monitoring
IEEE Open Access Journal of Power and Energy, 2022 Non-Intrusive Load Monitoring aims to extract the energy consumption of individual electrical appliances through disaggregation of the total power consumption as measured by a single smart meter in a household.
Pascal A. Schirmer, Iosif Mporas
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Will NILM Technology Replace Multi-Meter Telemetry Systems for Monitoring Electricity Consumption?
Energies, 2023 The estimation of electric power utilization, its baseload, and its heating, light, ventilation, and air-conditioning (HVAC) power component, which represents a very large portion of electricity usage in commercial facilities, are important for energy ...
Bartłomiej Gawin +2 more
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