Energy management using non-intrusive load monitoring techniques–State-of-the-art and future research directions
R Gopinath, M Kumar, CPC Joshua… - Sustainable Cities and …, 2020 - Elsevier
In recent years, the development of smart sustainable cities has become the primary focus
among urban planners and policy makers to make responsible use of resources, conserve …
among urban planners and policy makers to make responsible use of resources, conserve …
[HTML][HTML] Building power consumption datasets: Survey, taxonomy and future directions
In the last decade, extended efforts have been poured into energy efficiency. Several energy
consumption datasets were henceforth published, with each dataset varying in properties …
consumption datasets were henceforth published, with each dataset varying in properties …
Neural nilm: Deep neural networks applied to energy disaggregation
J Kelly, W Knottenbelt - Proceedings of the 2nd ACM international …, 2015 - dl.acm.org
Energy disaggregation estimates appliance-by-appliance electricity consumption from a
single meter that measures the whole home's electricity demand. Recently, deep neural …
single meter that measures the whole home's electricity demand. Recently, deep neural …
[HTML][HTML] Non-intrusive load monitoring approaches for disaggregated energy sensing: A survey
Appliance Load Monitoring (ALM) is essential for energy management solutions, allowing
them to obtain appliance-specific energy consumption statistics that can further be used to …
them to obtain appliance-specific energy consumption statistics that can further be used to …
Toward non-intrusive load monitoring via multi-label classification
Demand-side management technology is a key element of the proposed smart grid, which
will help utilities make more efficient use of their generation assets by reducing consumers' …
will help utilities make more efficient use of their generation assets by reducing consumers' …
Comprehensive feature selection for appliance classification in NILM
N Sadeghianpourhamami, J Ruyssinck… - Energy and …, 2017 - Elsevier
Since the inception of non-intrusive appliance load monitoring (NILM), extensive research
has focused on identifying an effective set of features that allows to form a unique appliance …
has focused on identifying an effective set of features that allows to form a unique appliance …
Leveraging smart meter data to recognize home appliances
M Weiss, A Helfenstein, F Mattern… - 2012 IEEE International …, 2012 - ieeexplore.ieee.org
The worldwide adoption of smart meters that measure and communicate residential
electricity consumption gives rise to the development of new energy efficiency services …
electricity consumption gives rise to the development of new energy efficiency services …
Transferability of neural network approaches for low-rate energy disaggregation
Energy disaggregation of appliances using non-intrusive load monitoring (NILM) represents
a set of signal and information processing methods used for appliance-level information …
a set of signal and information processing methods used for appliance-level information …
Machine learning approaches for non-intrusive load monitoring: from qualitative to quantitative comparation
C Nalmpantis, D Vrakas - Artificial Intelligence Review, 2019 - Springer
Non-intrusive load monitoring (NILM) is the prevailing method used to monitor the energy
profile of a domestic building and disaggregate the total power consumption into …
profile of a domestic building and disaggregate the total power consumption into …
Building-level and stock-level in contrast: A literature review of the energy performance of buildings during the operational stage
MS Geraldi, E Ghisi - Energy and Buildings, 2020 - Elsevier
This paper aimed to review the literature of the past ten years about the energy performance
of buildings during their operational stage. The focus of this review was empirical works that …
of buildings during their operational stage. The focus of this review was empirical works that …