Energy disaggregation of appliances consumptions using ham approach

H Liu, Q Zou, Z Zhang - IEEE Access, 2019 - ieeexplore.ieee.org
Non-intrusive load monitoring (NILM) makes it possible for users to track the energy
consumption of a household. In this paper, we present a new hybrid energy disaggregation …

[HTML][HTML] Building plug load mode detection, forecasting and scheduling

L Botman, J Lago, X Fu, K Chia, J Wolf, J Kleissl… - Applied Energy, 2024 - Elsevier
In an era of increasing energy demands and environmental concerns, optimizing energy
consumption within buildings is crucial. Despite the vast improvements in HVAC and lighting …

An IoT-based gamified approach for reducing occupants' energy wastage in public buildings

TG Papaioannou, N Dimitriou, K Vasilakis, A Schoofs… - Sensors, 2018 - mdpi.com
Conserving energy amenable to the activities of occupants in public buildings is a
particularly challenging objective that includes associating energy consumption to particular …

Device-level plug load disaggregation in a zero energy office building and opportunities for energy savings

B Doherty, K Trenbath - Energy and Buildings, 2019 - Elsevier
Along with heating, cooling, ventilation, and lighting, plug loads are one of the principal
consumers of energy in commercial buildings. Managing ever-changing plug loads is a …

An improved non-intrusive load disaggregation algorithm and its application

H Liu, C Yu, H Wu, C Chen, Z Wang - Sustainable cities and society, 2020 - Elsevier
The non-intrusive load monitoring (NILM) method is proposed to acquire the energy
consumption of appliances in a building. Steady-state current decomposition is one of the …

Applicability of using time series subsequences to study office plug load appliances

B Kalluri, A Kamilaris, S Kondepudi, HW Kua… - Energy and …, 2016 - Elsevier
Energy management in offices requires efficient methods (eg non-intrusive load monitoring
techniques, NILM) to monitor the large number of workstations and office appliances. The …

Low-power appliance recognition using recurrent neural networks

AR Pratama, FJ Simanjuntak, A Lazovik… - … of Intelligent Systems, 2018 - ebooks.iospress.nl
Indoor energy consumption can be understood by breaking overall power consumption
down into individual components and appliance activations. The classification of …

Power-based device recognition for occupancy detection

AR Pratama, Widyawan, A Lazovik, M Aiello - Service-Oriented Computing …, 2018 - Springer
Each person using electrical devices leaves electricity fingerprints in the form of power
consumption. These can be very useful for understanding the context of that person in, for …

Non-Intrusive Load Monitoring in Smart Grids: A Comprehensive Review

Y Liu, Y Wang, J Ma - arXiv preprint arXiv:2403.06474, 2024 - arxiv.org
Non-Intrusive Load Monitoring (NILM) is pivotal in today's energy landscape, offering vital
solutions for energy conservation and efficient management. Its growing importance in …

[PDF][PDF] Classifying office plug load appliance events in the context of NILM using time-series data mining

B Kalluri, A Kamilaris, S Kondepudi… - Proceedings of the …, 2016 - superworld.cyens.org.cy
Smart building energy management requires knowledge of individual appliance operation
from reduced metering points. The key purpose of this study is to present a classification …