PB-NILM: Pinball Guided Deep Non-Intrusive Load Monitoring [PDF]
IEEE Access, 2020 The work in this paper proposes the application of the pinball quantile loss function to guide a deep neural network for Non-Intrusive Load Monitoring. The proposed architecture leverages concepts such as Convolution Neural Networks and Recurrent Neural ...
Eduardo Gomes, Lucas Pereira
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Non-Intrusive Load Monitoring (NILM), Interests and Applications
Journal of Nigerian Society of Physical Sciences, 2023 In developing effective energy management mechanisms, new concepts have been developed to provide new approaches. Non-intrusive load monitoring (NILM) is an approach that was originally developed to allow the occupants of a room to identify the ...
Leonce Wehnelt TOKAM +1 more
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Towards Feasible Solutions for Load Monitoring in Quebec Residences. [PDF]
Sensors (Basel), 2023 For many years, energy monitoring at the most disaggregate level has been mainly sought through the idea of Non-Intrusive Load Monitoring (NILM). Developing a practical application of this concept in the residential sector can be impeded by the technical
Hosseini SS +4 more
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Rule-Based Non-Intrusive Load Monitoring Using Steady-State Current Waveform Features. [PDF]
Sensors (Basel), 2023 Monitoring electricity energy usage can help to reduce power consumption considerably. Among load monitoring techniques, non-intrusive load monitoring (NILM) provides a cost-efficient solution to identify individual load consumption details from the ...
Shareef H +3 more
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Non-Intrusive Load Monitoring. [PDF]
Sensors (Basel), 2022 Non-Intrusive load monitoring (NILM) represents an emerging strategy based on the application of sevaral multidisciplinary topics [...]
Fortuna L, Buscarino A.
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Smart Distribution Boards (Smart DB), Non-Intrusive Load Monitoring (NILM) for Load Device Appliance Signature Identification and Smart Sockets for Grid Demand Management. [PDF]
Sensors (Basel), 2020 Traditionally, the choices to balance the grid and meet its peaking power needs are by installing more spinning reserves or perform load shedding when it becomes too much. This problem becomes worse as more intermittent renewable energy resources are installed, forming a substantial amount of total capacity.
Kerk SG, Hassan NU, Yuen C.
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Fed‐NILM: A federated learning‐based non‐intrusive load monitoring method for privacy‐protection
Energy Conversion and Economics, 2022 Non‐intrusive load monitoring (NILM) is essential for understanding consumer power consumption patterns and may have wide applications such as in carbon emission reduction and energy conservation.
Haijin Wang +5 more
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Non-Intrusive Load Monitoring (NILM) for Energy Disaggregation Using Soft Computing Techniques [PDF]
Energies, 2020 Non-intrusive load monitoring (NILM) has become an important subject of study, since it provides benefits to both consumers and utility companies. The analysis of smart meter signals is useful for identifying consumption patterns and user behaviors, in ...
Cristina Puente +3 more
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Steady State Modification Method Based On Backpropagation Neural Network For Non-Intrusive Load Monitoring (NILM) [PDF]
MATEC Web of Conferences, 2018 Household electric power sector is highlighted as one of significant contributors to national energy consumption. To reduce electric energy usage in this sector, a technique called Non-Intrusive Load Monitoring (NILM) has been developed recently. NILM is
Tri Atmaja Sigit, Halim Abdul
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Privacy-preserving household load forecasting based on non-intrusive load monitoring: A federated deep learning approach. [PDF]
PeerJ Comput Sci, 2022 Load forecasting is very essential in the analysis and grid planning of power systems. For this reason, we first propose a household load forecasting method based on federated deep learning and non-intrusive load monitoring (NILM).
Zhou X, Feng J, Wang J, Pan J.
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